Lynne Jones: Alright, good morning, everybody.
Lynne Jones: We'll wait a few more minutes, it looks like. There's still people coming in.
Lynne Jones: I hope yesterday was… was useful to people. I know that there was some overlap with what we talked about in the science assemblies, but,
Lynne Jones: I didn't…
Lynne Jones: Not everybody made it to the Science Assembly, and I did try to make it a little bit different.
Lynne Jones: Good morning to those of you just joining us. I'm just gonna…
Lynne Jones: We had a few minutes for people to finish trickling in.
Lynne Jones: Well, I don't want to wait too long, because actually, this first part of today is kind of super packed, so, unfortunately.
Lynne Jones: The content and the time span for that.
Lynne Jones: It turned out weren't as great a match as I thought.
Lynne Jones: So, let's get going. Good morning, and welcome again to the SELC Workshop page, Day 2.
Lynne Jones: This is your SEOC and all of the members, and I… we… on the…
Lynne Jones: from LSST, we really appreciate all of the work the SEOC do.
Lynne Jones: Today, we're going to talk about, more details of some of the things we talked about yesterday.
Lynne Jones: Code of conduct reminder, please be kind. We're here to help make Rubin the most awesome thing it can be together, so let's, be kind, be honest, be inclusive. If you do have a problem, please reach out to me, or Federica Bianco, or your science collaboration point of contact.
Lynne Jones: Okay, quick review of what we did yesterday. We went through the current, options, and we talked about metrics, primarily in sort of a high level, over the whole survey kind of point of view.
Lynne Jones: And today we'll talk about some particular aspects of those
Lynne Jones: Simulations and what we're… what we're actually seeing.
Lynne Jones: From data management, from, various aspects.
Lynne Jones: And at the end of today, we have the…
Lynne Jones: the, a time to talk more specifically about DESI. So…
Lynne Jones: that we'll… we will cover that today, and David, I see you're here. I wasn't able to… to make sure we had the right time, but I think you're up for… for doing…
Lynne Jones: If we're talking about Desi in that last section a little bit, right?
David Schlegel: I'm here all day.
Lynne Jones: Perfect, thank you.
Lynne Jones: Alright.
Lynne Jones: Right, and on Monday, we have this, session to get feedback from the science collaborations.
Lynne Jones: So we can adjust these times as needed for what people's feedback wants to be.
Lynne Jones: Alright, so today.
Lynne Jones: The first thing up is details of the, FBS configuration.
Lynne Jones: and what we're starting the survey with. So this is the chunk of today that is quite dense, and
Lynne Jones: it's hard to talk about the FBS and how it's doing what it's doing in a way that makes sense to people without actually telling you a little bit about what's going on inside the FBS. So that's what I'm going to do.
Lynne Jones: And,
Lynne Jones: If you have absolutely no interest in the inner workings of the FBS, this might not be for you, but I actually think it's pretty fascinating, so hopefully it'll be interesting to you, too. Some of this might be a little bit,
Lynne Jones: fast going through, because, like I said, we…
Lynne Jones: We made the time… the agenda before we made the… before we figured out exactly what had to go in this pot, and but I'm gonna… I'm gonna try for that.
Lynne Jones: Anyway, here we go. Light introduction to the inside of the FBS, and what that means for the start of the survey with V5.3.
Lynne Jones: So… Inside the FBS.
Lynne Jones: how… what we have is the whole scheduler configuration, and inside the FES, there is a list of lists of surveys. The list is what we call tiers, so it's like, this is… you can think of it as prioritizing.
Lynne Jones: A higher tier always has priority over a lower tier.
Lynne Jones: So if we put deep drilling over, a tier with lots of pairs, if the deep drilling survey can request an observation, it will.
Lynne Jones: Within a tier, those surveys compete. So if you have multiple surveys inside a tier, they can compete with each other to say, oh, I really want this observation, or, somebody else may say, I kind of want this one, but they'll go side to side-to-head to see which survey is going to choose the observation for the…
Lynne Jones: Upcoming observations be taken.
Lynne Jones: So…
Lynne Jones: So this is important to keep in mind. We have this concept of tiers, which are priority. If a higher tier survey can take an observation, even if it's a lower priority for that survey than one in a lower tier, the higher tier survey will win.
Lynne Jones: So, tiers prioritize, and then within a tier, the surveys compete.
Lynne Jones: That's the basics. The next thing is, what are surveys?
Lynne Jones: So not every survey makes decisions in the same way, and this is not just true of, like, what goes into the decision in a particular survey, but that they also have different decision-making methods. And so, Peter says, you know, it's a modular decision tree, so we have some of those modules are the tiers
Lynne Jones: And then, within the tiers, the decisions from the surveys. But also, it's because there's a modular range of surveys. So we have things like scripted surveys, which take a list of desired observations, along with some constraints, like, the time window, the hour angle, what the sun altitude is.
Lynne Jones: And then it will try to acquire the observations in that list when the constraints for those… that particular observation is matched.
Lynne Jones: So we use this for the deep drilling fields, you could also use it for engineering tests, and there's lots of use for this, but it's a very, sort of, prescriptive survey.
Lynne Jones: If something can be done, it will, basically.
Lynne Jones: And then we have,
Lynne Jones: Markov, which is our… we actually have many subclasses of this kind of survey. It's basically saying this is a survey that uses a lot of basis functions, potentially a lot of basis functions, to make decisions about which observation to take, and we use these for a wide area survey, for the most part.
Lynne Jones: Sometimes we use them for more like a single pointing, and those are field surveys. They are…
Lynne Jones: They're related, they're… it's just they only have one.
Lynne Jones: Position on the sky.
Lynne Jones: For field surveys, you can put in a sequence to be… to be obtained every time you… that survey would request an observation. For the Markov surveys, it's more like you choose one observation, but you can choose it based on anywhere on the sky.
Lynne Jones: Now, really, to fully define a survey, you also… and to know, like, this survey is this survey, and not a slightly different survey. You do have to dig into all of the basis functions to say, like, how is this survey making its decisions?
Lynne Jones: I am not going to go through all of the basis functions for every survey.
Lynne Jones: Here, because that would not be interesting to people, and it would be very long.
Lynne Jones: But for now, let's just say that for most of the Markov-based surveys, the typical balance we look for is between the footprint, the,
Lynne Jones: what we call M5 difference, which is the 5-sigma point source limiting magnitude that we estimate you would have now over the sky versus the dark sky depth. So it's an estimate, not just of where it's, where it's,
Lynne Jones: Where you have the most limiting magnitude right now, but also just compared to what that would be under dark sky conditions.
Lynne Jones: And then we have, a slew time basis function.
Lynne Jones: And these are sort of our big three. You can think of as, like, if you have a wide area survey, these are the big three.
Lynne Jones: basis functions that you'll be trying to balance. And it goes so that you have in… you can balance even coverage, efficient observations with the slew time, and
Lynne Jones: Photon collection with the depth.
Lynne Jones: And there's… there's numbers that you can use to change how these balance against each other, for example.
Lynne Jones: These are all some of the things that go into making a full survey configuration, but this is the basic, basic.
Lynne Jones: And then another thing we do for the use at the summit, is we have
Lynne Jones: some standard masks, which we apply to every survey. And these are basically that we're… we're putting in the administrative constraints, or the just general con…
Lynne Jones: A little bit more than that because of Venus and Jupiter, but these are constraints that every survey will follow.
Lynne Jones: So we have, avoiding the moon, by about 30 degrees. Every survey will respect the altitude limits for the telescope.
Lynne Jones: So we don't… so this will mask off the sky below our lower limit and around zenith. And every survey, in the FES avoids Venus, Mars, and Jupiter, merely because they're so bright and they move fast, so it's just not worth, us looking at them.
Lynne Jones: And we can also add temporary masks, so for example, if we need to avoid a given azimuth range on a particular night, we can… we can add this in.
Lynne Jones: So that's the basics of what goes into
Lynne Jones: our FPS configurations on the sky. And, like, this is the specifics for what we have now in V5.3.
Lynne Jones: So, you can see there's a lot of things on this list. We have 8 tiers.
Lynne Jones: And then within those tiers, we have 40 surveys, but all those are not necessarily in the same tier, so those 40 surveys aren't all competing against each other, they're only competing within their same tier.
Lynne Jones: Okay, so when we say this is what the FES is doing, what we mean is at a particular time, the FES gets updated with the conditions, so the… where the telescope is, what the seeing is like, what the weather's like, what the sky brightness is.
Lynne Jones: And then it goes through this list of tiers until it comes to a tier that says, yes, this is perfect, I can take an observation now, and then that tier will choose an observation.
Lynne Jones: For the survey.
Lynne Jones: For the whole survey. This is where it gets a little tricky. So we have our survey objects, and then we have the survey we're doing, but here, I mean, I'll try to make sure I'm saying survey by the survey objects.
Lynne Jones: So…
Lynne Jones: These are our tiers. I'm going to go through each tier and just say this is the kind of observations this would take and what they look like in our 5.3 simulation.
Lynne Jones: So we have the target of opportunity tier, the TO tier.
Lynne Jones: This, is a set of… basically a set of scripted observations that are waiting for information that says, oh, this event happened. If the event matches the type of object it's supposed to follow up, then it follows the scripted,
Lynne Jones: the predefined observation plan, which comes from the 2024 TO Workshop Report.
Lynne Jones: So…
Lynne Jones: this is a top-tier survey, the very top tier, so if a TO event comes in, and a survey… one of these, TOO surveys.
Lynne Jones: matches the event, and the observations are possible, like, the list of observations from a scripted survey says, yes, this matches the conditions, then this will be the next thing that's observed.
Lynne Jones: I'm gonna introduce here, not just our sky plot on the left, but on the right. This is an LTAS distribution of where those observations were in V5.3. So you see, these are… these are being picked up over
Lynne Jones: On the left, you can see over it pretty much all over the sky, and that's, by chance, of course, because…
Lynne Jones: We don't know where the real TOs are going to be.
Lynne Jones: And on the right is, like, telling you where, from the telescope's point of view, it was observing in order to
Lynne Jones: to see these duos.
Lynne Jones: Our next tier is, a survey that's trying to coordinate with the Roman Galactic playing field. So, this results in… it's set up to obtain about,
Lynne Jones: just over 2,000 visits, spanning 5 years. This is frequent monitoring while the field is available, so… and it goes through GRIZ bands.
Lynne Jones: And the idea is to coordinate with Roman.
Lynne Jones: This does not request any observations within year one, and it is a survey that we need to update and make sure we're actually coordinating, because we don't have this full information yet. So…
Lynne Jones: These observations in the full 5.3 simulation are a little bit of a placeholder, but it's about what we want to do.
Lynne Jones: Our next year is… The deep drilling fields.
Lynne Jones: So, this is a single scripted survey containing all of the predefined DDF
Lynne Jones: desired observations. So this survey is configured a little bit differently than a lot of our other things.
Lynne Jones: For a scripted survey, you basically can give it a list to say ahead of time, to say, here, these are the observations I want to take. Please try to take these observations if you can.
Lynne Jones: And obviously, each of those observations come with
Lynne Jones: Some constraints, the most important of which is usually the time window that that observation could be acquired in.
Lynne Jones: So, to set up our desired DDF observations, we optimize those independently ahead of time. And this is so that
Lynne Jones: because these are a very limited set of pointings, we can do this. We can say, when would be the best time to observe this field when we have this particular number of observations we want to get in the season.
Lynne Jones: With some cadence constraints, perhaps, and then pick the best time in the night based on the sky brightness, to obtain that observation. And also, that way we can skip times when the moon is bright, and so on.
Lynne Jones: So, the DDFs are handled a little bit differently than most of the other things. We're going ahead, before we even get to the survey to say, this is when we should take these observations over the season. Obviously, we don't know when the weather's going to be good or bad, but that's where the scripted survey can handle that.
Lynne Jones: Because you can give it each of those observations, a time window of when to… to actually run.
Lynne Jones: So when we set up our list, we take into account the time window and flexibility, for example.
Lynne Jones: So, the… we have, again, on the bottom here, the…
Lynne Jones: RADEX, distribution on the sky for the deep drilling fields. I think this is fairly familiar to most people. In the middle, the distribution of those visits over altitude and azimuth.
Lynne Jones: And this is kind of interesting because you can see that there's this little hole in the middle. You probably can't see my mouse cursor, but there.
Lynne Jones: I mean, that's the zenith exclusion region, because we can't track the telescope through zenith.
Lynne Jones: So we can observe on either side of Zenith, but not right at Zenith.
Lynne Jones: And then on the right, here is now, another new plot. So what this one shows is…
Lynne Jones: On the y-axis, it's time away from local midnight, and on the x-axis, it's just,
Lynne Jones: Basically, the night of the survey.
Lynne Jones: So, you can see the length of the night changing over… this is just the first two years of the survey. So, you can see the length of the night changing with those red lines getting narrower and then wider. And then the times of the deep drilling fields and their filters are shown by the little lines on the inside.
Lynne Jones: And it is a little bit hard to,
Lynne Jones: There's a problem with, like, scale and how much data you're trying to show, so some of these points in the plot are not super easy to see, but hopefully you were able to pick up the link to my slides.
Lynne Jones: But you can… what you can see here is that
Lynne Jones: As the field becomes available, we observe the field.
Lynne Jones: At the best time of the night for,
Lynne Jones: for the time where the field is visible. And then you can see the similar thing happening for, like, the other fields, because this is all the deep join fields together. They're not quite at the same RA, but they're very clustered.
Lynne Jones: And then began the same.
Lynne Jones: So that, that is all of the deep drilling fields, so they have slightly different
Lynne Jones: RA ranges and times, but you can see how we're observing,
Lynne Jones: At the best… hopefully at the best time of the night for all of those that we've chosen the time when the sky brightness is the best.
Lynne Jones: Alright, so…
Lynne Jones: Right, I need to say a little bit more about the deep drilling fields. For each deep drilling visit, we have, rotational and translational dithers applied. It's a 3-degree rotational dither between visits, so until we change the filter, we just…
Lynne Jones: Click along by 3 degrees. And then the translational offset is a radial dither around the field center of 0.2 degrees.
Lynne Jones: For, the Euclid deep drilling field, it's a little bit different, because we don't do a radial dither, we do dither towards the other field, but
Lynne Jones: It's… it's easier to just describe these for the rest of the deep drilling fields.
Lynne Jones: The sequences,
Lynne Jones: For these… the sequences we set up in the pre-calculated requests, so this is what we're trying to obtain, are in deep seasons, those are the shallow seasons or deep seasons,
Lynne Jones: It alternates. So on even days, we would get two visits in G and 2 visits in I, and on odd days, we'd get two visits in R and 2 visits in C.
Lynne Jones: And then every few days, so that it lines up with these, but it's not quite every day, we have 3 visits in U and 2 visits in Y.
Lynne Jones: So, as I said, we have time windows for each of these, so you can think of them as expiring. So, the even and odd don't build up over multiple days. They expire very quickly. The U and Y, expire a little bit more slowly, so they can occasionally double up, and so we would get 6 in U.
Lynne Jones: Or foreign and Y.
Lynne Jones: For the EDFS field, the sequences are the same, but the cadence, the frequency, is slower to accommodate the double pointing.
Lynne Jones: And then in ultra-deep seasons, we still have the same even-odd day sequences, but then we also add, frequent, but not everyday, sequences of
Lynne Jones: 8 in U, 4 in G, 18 in R,
Lynne Jones: 55 in I, 52 in Z, and 20 in Y band.
Lynne Jones: So this is very, very red-heavy.
Lynne Jones: And the idea is that this is looking for a high redshift supernova.
Lynne Jones: Now we move along to the template tier.
Lynne Jones: Please do go ahead and raise your hand if you have questions while we're going through here.
Lynne Jones: Okay, so let's talk about tier. This is our new tier.
Lynne Jones: In B5.3.
Lynne Jones: We're acquiring visits separated by about 25 minutes, and good image quality for the template here.
Lynne Jones: And you can see the names of the filters that are paired together for these pairs in the list up at the top. So we have U paired with U, G with G, G also with R, R with A, R,
Lynne Jones: R&I. So, in general, for our standard pairs, we don't pair the same filter with itself, except for Y-band, but for the template tier, because they're, we're trying to get the U-band images under
Lynne Jones: tighter constraints for the image quality, we do pair U with itself and G with itself.
Lynne Jones: So…
Lynne Jones: The template tier will only request observations when the atmospheric seeing, as we're getting the measurement from the DIMM currently, implies that the predicted seeing, full width half max, sorry, for the next visit would be better than the equivalent of, 1.2 arcseconds at zenith.
Lynne Jones: And this is a little bit, tiny bit tricky to explain, because when I say 1.2 arcseconds at zenith, we do let that vary with declination, so I have a plot on the right of what a 1.2 full-width half max at zenith translates to over the declination range of our footprint.
Lynne Jones: Because obviously a higher deck, you don't get as good seeing.
Lynne Jones: And so… That the… the template tier is looking for the declination appropriate,
Lynne Jones: predicted full-width half wax at its location. And it will also only track observations which meet those, those, full-width half-max requirements.
Lynne Jones: There are also some hour angle limits to make sure we're pushing towards Zenith, and there are some additional constraints. Otherwise, many aspects are similar to the standard pair survey.
Lynne Jones: The template tier is important to note, shuts off when 6 visits with the desired full-width half max are acquired.
Lynne Jones: Or at the end of year one, whichever is soonest.
Lynne Jones: And this is in our 5.3 configuration. This is the kind of thing, like, the details of what are… is the cutoff, at Zenith, and how many visits we need, and when should it cut off. Those are things that we'll… we'll go back and adjust as we see
Lynne Jones: As we sync up better with, data management pipeline and requirements.
Lynne Jones: And we see what they, what they can use.
Lynne Jones: The template tier, so this is the…
Lynne Jones: footprint, again, on the sky in our NDAC, and the footprint in altitude and azimuth. So what you're seeing here, that wedge shape, is the hour angle constraints.
Lynne Jones: And then, on the right is that same plot of, like, when the observations are happening. And notice this one's much shorter in time because it only runs for the first year.
Lynne Jones: You can also, now that there's more observations on this plot, you can see,
Lynne Jones: A blank period here, just shortly after the start of the simulation, and that's because we have a downtime period there.
Lynne Jones: In the simulation.
Lynne Jones: Your Casol can notice that This is taking up most of the time of the survey.
Lynne Jones: Not all of it, but a lot of it. And actually, now I think about it, see, if you notice this stripe going through here… oops…
Lynne Jones: That would be because that matches up with our deep drilling fields in the previous pot.
Lynne Jones: And when the deep drilling fields are intensely taking observations.
Lynne Jones: Okay.
Lynne Jones: Our next tier down is triplets, because we have a desire to get a few hour timescale follow-up.
Lynne Jones: So, what happens here is we have a pair taken near the start of the night, which then triggers a follow-up visit two to seven hours later in one of the same filters. So the first pair is GR, RI, or IZ.
Lynne Jones: And the, follow-up visit is in one of those same filters. The pairs come from a standard pair survey, but only runs once a night, only once every four days, so there's more time constraints. And the third visit comes from one of these scripted surveys, which says, oh, you took an observation, let me put that on my list to follow up.
Lynne Jones: There are some hour angle constraints on the first pair, so we push it into parts of the sky which are rising, so we don't accidentally, like, make sure that we couldn't opposite reserve later.
Lynne Jones: And then here you can see what happens. So we have the first pair.
Lynne Jones: being pushed into the parts of the sky that are rising, and then you have the second visit of the pair, or sorry, the triplet after the pair, occurring at a wider range of positions on the sky. Because of that, it could be anywhere from 2 to 7 hours later.
Lynne Jones: And then these are the same plots here, but this is the first part, first pair.
Lynne Jones: So you can see it's stacked up near the start of the night.
Lynne Jones: And only happening once per night.
Lynne Jones: And then, the second… the triplet, sorry.
Lynne Jones: Second survey, triplet of the pair, happening at various other times during the night.
Lynne Jones: Okay, and now we come to our parent survey, which is fairly far down in the tiers, but this is actually the workhorse of our survey. More than 60% of the visits actually come from this tier. This is the…
Lynne Jones: the standard pairs all over the sky, survey that we have. So this is where we're, again, we're balancing the M5 difference, the footprint, the slew times, make generally balanced choices, and then
Lynne Jones: We add some extra basis functions to do things like make sure we get, at least 4 visits per pointing in each band per year,
Lynne Jones: So that we don't try to take more than two visits per night at any point in the sky. The pairs are,
Lynne Jones: The first visit of… of…
Lynne Jones: The pair is followed by a second in a different filter, and you can see the filter combinations up at the top.
Lynne Jones: But…
Lynne Jones: And we… the goal revisit time for the second visit in the pair is 33 minutes, and you can see on this plot here, which is, over the whole sky, what is the typical time to coming back to the field, that we do have this good, strong peak at,
Lynne Jones: 33 minutes. You also see this peak here, and this is just because of how this metric works, and this is from field overlaps. So when we take a visit, we're most likely to take the next visit right next to it, and then that gives us a little bit of overlap, so that has a very short
Lynne Jones: Interval between visits in there.
Lynne Jones: So, at 5.3, one of the new things we've done is that the visits in the pair
Lynne Jones: The interval is trying to make 33 minutes, but it will scale that slightly depending on, the best visit time available.
Lynne Jones: Sorry, how to best fill the time of the night. So the goal is 33 minutes, that's the most common time, but it can range, coming from the same survey, anywhere from, like, 40, 20,
Lynne Jones: to,
Lynne Jones: It's 40 or 45 minutes, or something like that. So we… it could be a little bit longer, depending on how much time you have in the night.
Lynne Jones: This replaces, in our… if you were more familiar with our old survey configuration, we had this 15-minute pair and a 33-minute pair. We've consolidated them with this, dynamic time scaling. We only have this one pair survey now. So, this is good, simplifies by…
Lynne Jones: How are these observing over the whole sky?
Lynne Jones: Pretty much everywhere.
Lynne Jones: And then on the right, you see this same plot of visits over time from 5.3, and notice there's very few visits in pairs in the first year, and that's because most of the time we're taking templates. And then after the template tier shuts off, we start taking, pairs.
Lynne Jones: the standard pairs. Remember, the templates are in pairs as well.
Lynne Jones: Alright, now we have one of our microsurvey,
Lynne Jones: tiers, our only microsurvey tier, and this is the Twilight Near Sun microsurvey. It takes observations in RI and Z. It's trying to get low, solar elongation, nearly ecliptic, observations during twilight, so it…
Lynne Jones: runs, it will only start if the sun altitude is,
Lynne Jones: above minus 15 during this time period, and it does short exposures, 15 seconds. So…
Lynne Jones: It runs in the target area. It defines a target area.
Lynne Jones: One of these RIZ will win in that tier, and then it will try to get four images for pointing in the target area. And the area means that the total time we need to complete the whole microsurvey in, like, the morning or night of when it's triggered is about 20 minutes.
Lynne Jones: So… These do successfully get low solar elongation visits, you can see that on the right.
Lynne Jones: And you can also see that these are being pushed to the,
Lynne Jones: The far edges of the, of the,
Lynne Jones: Of the sky, and this triggers in the morning and the evening, but not every day, it's every, 4 days.
Lynne Jones: I think.
Lynne Jones: Yes.
Lynne Jones: All right, and then the very last tier we have is the greedy tier. So, this tier serves as a filler. When no other survey can schedule visits, the greedy survey is there for you. It just schedules one visit at a time, and it doesn't,
Lynne Jones: have a lot of other time constraints. It sort of is discouraged from revisiting the same part of the sky more than once in a night, but other than that, it just is going to balance what's the depth, what's the footprint, what's the sleeve time, so that it can make generally balanced choices. But there are no pairs required, there's no,
Lynne Jones: You must finish,
Lynne Jones: because it's only one visit, it doesn't have to consider too far into the future. And so, a lot of those other basis functions from all of the other surveys have dropped. It's simple,
Lynne Jones: You wouldn't want to take most of your survey visits like this, because it also does things like get trapped in particular areas of the sky, but
Lynne Jones: Yeah, this is our… this is our…
Lynne Jones: our single visits over the sky.
Lynne Jones: Backing up everything else. This runs in RIZNY.
Lynne Jones: Look at that, I made it through all of the tiers. I'm actually going to talk a little bit about, like, what else went into our simulations and what we didn't know next, so if there are questions about, like, the survey configuration itself, the scheduler configuration.
Lynne Jones: Could, take just a quick moment.
Lynne Jones: David?
David Schlegel: Yeah, for the wide, fast, deep survey, then, is that… that's the combination of the template survey and then the para-survey?
Lynne Jones: So, this… this is a great question, actually. I didn't… really,
Lynne Jones: So the… so the wide, fast, deep is more of, like, an area and goal number, of visits over the sky. So, when we define the footprint that goes into the greedy survey, or the pairs survey, or the temp…
Lynne Jones: Not so much the template, but a little bit the template. But when we define the footprint that goes in here.
Lynne Jones: and the greedy survey. We use our footprint over the whole sky, and so the whitefast deep footprint is encoded into…
Lynne Jones: That information that we pass to each of these surveys.
Lynne Jones: So…
Lynne Jones: The Wide Fast Deep… there is not really a survey that is charged with acquiring Wide Fast Deep from the scheduler point of view.
Lynne Jones: The… where this comes in is that we, as the survey strategy team, know what our coverage should be, and so we say, yes, that's what the footprint should look like, so that we do have a wide, fast, deep area.
Lynne Jones: And then we put… place that into the footprint. And because we know we want pairs in the YFSD, most… we arrange things so that the pair survey gets most of those visits.
Lynne Jones: So… From within the scheduler configuration, there really is no Wide Fast Deep versus North Ecliptic spur.
Lynne Jones: But that all goes in as part of the information we feed into the survey.
David Schlegel: So, sorry, just a quick follow-up. So, but it must be that things like the twilight observations wouldn't count towards that coverage?
Lynne Jones: Yeah, so, so…
Lynne Jones: Also a good question. This is true, because every one of these surveys that I talked about, you not only have the option to mask off parts of the sky, but you can also tell it to ignore certain kinds of observations. So there is a piece of metadata that actually gets into all of the
Lynne Jones: information from the visits that is later available to everybody, called the scheduler note. And this is our piece of metadata that sort of tracks which of these surveys it came from, and sometimes extra information as well.
Lynne Jones: And so, when this visit comes from the Twilight Near Sun Survey, it carries a piece of information that says, this came from the Twilight Near Sun Survey.
Lynne Jones: And so…
Lynne Jones: The pair survey is told, ignore those. Those are not relevant for you, you don't use that to build up the footprint.
Lynne Jones: So…
Lynne Jones: that's how… that's how this works. And we also tell the the par survey, for example, to ignore the TOO's observations, because they were putting dents in our footprint.
Lynne Jones: And so there's… There's a lot of…
Lynne Jones: Room to go in and think about, like, how can you…
Lynne Jones: change how the survey is behaving, and this is one of the challenges, but also one of the strengths about the FBS configuration. There's usually more than one way to do a thing.
Lynne Jones: Bye.
Lynne Jones: So, I will…
Lynne Jones: Unless there's other questions. I'm gonna go and talk a little bit about, like, so yesterday we talked about the V5.3 simulation, we talked about, oh, there's 10% lost visits in the 5.3, yeah, sorry, Sarah pointed out the trip list here also contributes to YFAST. There's a lot of things that contribute to WideFastD.
Lynne Jones: And even the greedy survey does.
Lynne Jones: So, yesterday we said there's 10% fewer visits in V5.3.
Lynne Jones: And, I just want to take a moment to acknowledge that this… as Jocko did as well, right, we don't know what the weather is going to be. We also don't know some other things. So, the visit gap, the time between visits we talked about yesterday,
Lynne Jones: I said it has some overhead that's for every slew that is kind of variable.
Lynne Jones: And… at the moment, I think that variability might be,
Lynne Jones: at least might lead to a variation in the total number of visits, that it may be that we get the number wrong by about 10%.
Lynne Jones: That might be… not be too high right now.
Lynne Jones: But after 6 months, I think that we should not be, like.
Lynne Jones: incorrect by this much, and not just because we will know better, like, how the slew time is, but because the slew time itself will improve and match our model. But we don't know exactly how fast that's going to improve.
Lynne Jones: And so, we didn't put it into the simulation.
Lynne Jones: So, in the first… in the first period of time, our rate of acquiring visits in the simulation, V5.3, is probably a little bit too high.
Lynne Jones: The actual engineering time needs. So, we put in 2 half-nights for the first 6 months.
Lynne Jones: But that could be 2 full nights for the first 6 months. And so that kind of gives you that we might be as much as, 15% too high in the total number of visits in the first 6 months.
Lynne Jones: But, after a full year, when… if we're not doing that engineering time anymore, which we… is not the
Lynne Jones: current estimate.
Lynne Jones: Then we might… we wouldn't be that
Lynne Jones: incorrect. That number reduces over time, right?
Lynne Jones: Also, it doesn't take into account that we might get science images from those engineering tests.
Lynne Jones: Because sometimes they do run the FES during their engineering night, sometimes they run the very specific kinds of observations that are still valid observations for engineering.
Lynne Jones: So there's… there's sort of uncertainty here about what is… what will happen with that engineering time, and
Lynne Jones: What use it might be able to be used for.
Lynne Jones: there's the fault downtime and timescale of improvement. So, we do have a model for faults in B5.3, which is an improvement over our earlier sims. I do think it's
Lynne Jones: more accurate and relatively accurate, but there is a lot of variability on this, and so this, I think, is a little hard to say.
Lynne Jones: I'm hoping we have guessed fairly right, but this is… it's hard to put a number on how accurate or not accurate,
Lynne Jones: The values we've come up with are.
Lynne Jones: Then we have the system contribution to seeing, and the timescale for improvement. So we're just not modeling this at present. We can look at doing that, especially during the first year, but also we don't know the timescale for that improvement, or,
Lynne Jones: Or… or… what will happen there? Most likely, as we get more louvers, we'll see changes, and…
Lynne Jones: That will be, will be something we track, for sure.
Lynne Jones: But then we have the effects of cloud transparency, which we don't model at present, and dodging clouds, which we haven't… we're working on, and we actually have a couple of things in active development, but,
Lynne Jones: There certainly is room for future improvement here, so…
Lynne Jones: And then the last thing is the weather downtime. So, we don't have any clear indication of issues, but obviously we'll be monitoring this.
Lynne Jones: So, As you look at smaller and smaller chunks of time out of V5.3.1, I think your uncertainty,
Lynne Jones: is higher, right? As you look at the full 10 years, that's probably not as uncertain as if you're looking only at the first 6 months. So I think this is the main thing I wanted to say here, is just to make sure we… you understand, like.
Lynne Jones: If you're looking at a small timescale, The uncertainty is definitely higher.
Lynne Jones: Right.
Lynne Jones: We took a couple questions along the way.
Lynne Jones: But let's… if there's any questions here… and then I have…
Lynne Jones: Taken up most of the, most of the question time.
Lynne Jones: With the presentation up to this point, but…
Lynne Jones: We'll move on to TOs a little bit late, maybe.
Lynne Jones: Okay, so if there's any questions… Or comments?
Lynne Jones: About this part, we can take them here.
Lynne Jones: R&I, okay.
Lynne Jones: Well, in which case… I'm on time.
Lynne Jones: So, targets of opportunity. We have the… I talked about the target of opportunity tier, and…
Lynne Jones: What it,
Lynne Jones: just briefly, like, how it works. Like, we have these… this list of scripted surveys that are all in the TOO tier,
Lynne Jones: They would compete against each other, but it's just that we don't…
Lynne Jones: expect to get, multiple TOs at the same time.
Lynne Jones: If we did, they would just queue up behind each other.
Lynne Jones: Up to 3% of the survey time may be directed to TOL follow-up.
Lynne Jones: The general plans for TO follow-up at present are well described in this, 2024 TO Workshop report.
Lynne Jones: There…
Lynne Jones: There is another follow-up report, so Sean McBride has been doing a lot of work with the observatory,
Lynne Jones: To, to sort of…
Lynne Jones: pull in the different TOL workshop report, and the very few cases that we didn't simulate, because they were over large amounts of area.
Lynne Jones: And so…
Lynne Jones: there is an update for this somewhere, and I have heard that there was a workshop this year that will probably be,
Lynne Jones: Talking… looking into updating these follow-up plans as well.
Lynne Jones: But what we have now, does match the TOL workshop, and also some… I'll find the link for the other documentation.
Lynne Jones: We have a Rubin TO Advisory Board,
Lynne Jones: This is a link to their documentation, their charge, and they provide guidance regarding specific TO events.
Lynne Jones: Much of the TO process is intended to be automated, so we get an alert from an external program.
Lynne Jones: It's evaluated by, the Rubin TOL Producer, which is a separate, not, not, not FBS scheduler, but it's a, Summit piece of software and framework.
Lynne Jones: It evaluates the… the TOL producer evaluates the alert, and if it meets criteria, then it passes the alert information into
Lynne Jones: the FBS, eventually. It goes through some systems, like the engineering facilities database, the EFD at the summit, and then it gets to the FBS.
Lynne Jones: And so one of the FBS2O surveys, upon receiving that alert.
Lynne Jones: We'll create the list of desired observations that match the predefined plan for that kind of table.
Lynne Jones: And then… off we go. So…
Lynne Jones: This… if the criteria are defined appropriately, this can all happen automatically and quickly without needing a human in the loop.
Lynne Jones: The external events that are currently received by the TWOL producer include gravitational wave events, of the LVK alerts.
Lynne Jones: It can obtain observations of potentially hazardous asteroids from JPL Scout.
Lynne Jones: high-energy neutrinos from IceCube, and
Lynne Jones: the galactic supernova from Super Kami Okande.
Lynne Jones: The… there's another event producer that they're working on adding. It should be within the next year or so, but is not available yet.
Lynne Jones: No.
Lynne Jones: that's the automated route, but if the… if there is an alert or some kind of event that Ruben should follow, but is not one of these automated,
Lynne Jones: sets of events. Then, the TO Advisory Board, whose members are listed here.
Lynne Jones: will activate, and they will sort of activate that to you all, and they can provide guidance, on what to do here.
Lynne Jones: So…
Lynne Jones: The TO Advisory Board is intended to provide general guidance on the TO program on short timescales, like less than 24 hours for these things that don't fit into our current criteria and wouldn't match the
Lynne Jones: automated response. You can do medium time scale response for
Lynne Jones: Perhaps following up a multi-day, TO.
Lynne Jones: And then they also do feedback on longer timescales, like weeks and months. And so one of the things, obviously, that we will have to do is keep track of how the TO events are…
Lynne Jones: performing and how they're matching up with the rest of the survey, so that if we need to go and change the criteria for the automated triggering, then we can do that.
Lynne Jones: The general TOL workflow looks like this, so we have our event… external event producers, LVK, IceCube.
Lynne Jones: Super K JPL.
Lynne Jones: And then that goes into SIMA. So Sima Hopscotch is where we receive the alerts from.
Lynne Jones: Then this is part of the TOL producer, so it parses the alert for quality. Does it meet criteria, or does it meet criteria? Does it fail? If it's failed, it's just rejected. If it passes the quality criteria.
Lynne Jones: Then it goes to the Rubin EFD. Then it goes to the Scheduler CSE, which is the framework that the FBS runs within at the summit.
Lynne Jones: And then this scheduler creates an observing strategy. This is the FBS, creates this observing strategy, and then
Lynne Jones: passes that back to the scheduler CSC, so Ruben executes the observation.
Lynne Jones: And then afterwards, we have all of our processing to understand what the alert is. I pulled this, image from, Sean McBride's SBIE paper for this year, so…
Lynne Jones: This is hot off the press.
Lynne Jones: And of course, the TO Advisory Committee can decide to observe a non-standard TO
Lynne Jones: Yeah. During commissioning, we did get a chance to test this workflow. It was, not as automated as some of the previous
Lynne Jones: as the previous steps may have implied. But that was kind of on purpose, because we were in commissioning, and we didn't want to just be passing through alerts unexpectedly, so…
Lynne Jones: every, alert that was actually passed to the FBS was done by hand, so we didn't get more than we expected.
Lynne Jones: We tested the TWO workflow, of…
Lynne Jones: passing the alerts through the EFD and into the FBS, on two…
Lynne Jones: two, well, actually three, but let's… let's focus on these two, which got, more observations. So there was, 3i Atlas, and this was a very successful TOL program, and, resulted in, I think, probably the first paper coming out of,
Lynne Jones: ribbon commissioning.
Lynne Jones: in the SV survey over the summer.
Lynne Jones: This was… this would definitely have been a non-standard TO, no matter what,
Lynne Jones: But we did… we did observe it several times. You can see the, observation footprint here. This little spot here was,
Lynne Jones: We were testing this by hand, remember? And this was not a mistake, it was just that, we obs…
Lynne Jones: On one night, we tried to observe this field, and our masks in the FBS did their job and said, you cannot observe that field right now because it's too close to the moon.
Lynne Jones: And so they said, okay, we still want to test the TOO procedure, so we're just going to put a different pointing center into the information we pass to the FBS.
Lynne Jones: So we have this thing here, which we should have updated the labeling for, but we didn't, and so the commissioning, right? But I thought it was really great, because it also illustrated the FBS is doing its job with the masks, and it's making sure that we're not,
Lynne Jones: We're not doing things that this… that the telescope is not supposed to do.
Lynne Jones: On the right was our bigger follow-up, TO, so this was…
Lynne Jones: Gravitational wave candidate, S251112.
Lynne Jones: CM.
Lynne Jones: we do have some work to do on our metadata, because it came through looking at, like, one. But we actually… we fixed that already, we just haven't had another chance to test it.
Lynne Jones: So this TO was a gravitational wave that had a very large footprint, and it covered the whole sky, almost through… through here. This is the… what we deemed at the time to be the high priority area of the footprint.
Lynne Jones: with some over here. So this, in this case, this was not a mistake, it was just a very far part of the footprint.
Lynne Jones: And we observed this TO for a couple of nights.
Lynne Jones: In G&I band.
Lynne Jones: And so we followed this area, we did it again, we did it again. And so this was following the planned observations. One of the things about the…
Lynne Jones: 3i Atlas being a non-standard TOO is that we had to actually put in the observations we wanted, because it didn't really,
Lynne Jones: We had to make it look like one of the cases we expected.
Lynne Jones: Okay, and over here, this one did, so we followed it. What we found was that there are…
Lynne Jones: there were some details about how the FBS runs at the summit that are a little bit different than how it runs when we run it in a simulation. And so there were some things… there were definitely things we learned from this experience. It was also really good to see us follow this large area.
Lynne Jones: I think it has proved difficult to process this without, like, production-grade templates.
Lynne Jones: Yeah, and so we're… we'll see how that… Gentles.
Lynne Jones: Okay.
Lynne Jones: So, we have,
Lynne Jones: Excuse me. We have… Children
Lynne Jones: So, we did the gravitational wave case, and we learned things, and we're implementing updates for this in the FPS.
Lynne Jones: And then we have questions for any of this so far.
Lynne Jones: Roberta?
Roberto Assef: Yes, thank you very much. Just a couple of very quick questions. So, is there, thinking… I'm thinking mostly of gravitational waves
Roberto Assef: follow-up, is there a ramp-up, considering the number of requests towards the later years? Because I will assume that, sort of, this will keep increasing and increasing.
Lynne Jones: It kind of goes, with the…
Lynne Jones: With the observing seasons for,
Lynne Jones: For LIGO, Virgo, for… so they're not actually spread evenly throughout the whole survey, and they are concentrated in… I think it's year 2. Peter might have a better answer on when exactly it is.
Lynne Jones: They are concentrated in time. This is also something we'll have to consider, because obviously.
Lynne Jones: we've said, okay, this is when we think that the alerts will be coming in, and we've based that time span and the rates on what came out of the TOO workshop.
Lynne Jones: But… We don't know, for sure.
Roberto Assef: Okay, and… and can I ask one more question? The… so, right, a lot of what we… what happened by the change to 5.3 was this… the last 10% lower on Sky time. So I'm wondering, is it too difficult to, sort of.
Roberto Assef: after the fact, see if the images obtained for TO could fit within the strategies of the WFD and the DDFs. It could add to zero, because we don't know where the TOOs will be and when they will be, but if they add, that will help recover some of that.
Lynne Jones: So… Potentially. The… I mean, and the…
Lynne Jones: It's difficult because, when we're observing, like, with the PARS survey, or, all the other
Lynne Jones: tiers that go into making our normal observing mode. We don't really have, a way to force it to say, okay, on tonight, actually really go do this part of the sky. So, you would still be activating a TOO, essentially.
Lynne Jones: And…
Lynne Jones: we… what it would be is maybe what we would… could do is make the TO gentler, but that's kind of the opposite of what you want for the TOO, right?
Lynne Jones: So… so there… yes, there is this tension between, like, following up the TOO as it… as it ideally would be, and as quick as it would be, versus, like, doing it in a way that might just look like the normal survey.
Lynne Jones: And… the… looking like the normal survey is… I'm not…
Lynne Jones: Yeah. We did have… we… the reason we… so, originally, when we made TOs, we counted them towards the… the footprint for the pairs survey, but, what we found was that disturbs the cadence we're trying to get with the pairs as well. So, it's kind of like they…
Lynne Jones: Don't go together super well, but certainly, you know, if this turns out to be a really big
Lynne Jones: problem that we really have many more TOs than we… that we need to follow up than we can accommodate. This would be something we could go and revisit, but it… it is difficult.
Lynne Jones: And I'm not sure it'd be successful.
Roberto Assef: Thank you.
Lynne Jones: Bindu?
Bindu Rani: Yeah, hi, Lynn. Really quick, is there a fixed amount of time assigned for the TO observations? And, if it is, is there a plan, like, you know, in case if that time has not been used,
Bindu Rani: How that time will be used.
Bindu Rani: Otherwise.
Lynne Jones: Yeah, good question. It's not… there is a fixed cap… well.
Lynne Jones: in theory, a fixed cap is… we don't enforce it in the FBS. To enforce the cap on the TOs, it would have to come into, like, the criteria for triggering on the TOs.
Lynne Jones: So… The TUL program is expected to use up to 3% of the total survey time.
Lynne Jones: there's nothing that, like, if they… there are no TOOs, it's not like we're not observing. We just don't observe a TOO, and we do observe all the normal stuff we would observe, so all of the other tiers lower in the scheduler just would activate.
Lynne Jones: And, like I was saying yesterday, our footprint is just a ratio, so if we have more time, we just get more observations distributed over the footprint, and if we have less time, we just get less observations distributed over the footprint.
Bindu Rani: I still think.
Lynne Jones: So, it just… if we… if we didn't have any TOs, we would have a little bit more time
Lynne Jones: That would go into everything else in the survey, and if we had more TOOs.
Lynne Jones: Then it takes the time.
Bindu Rani: Thanks.
Lynne Jones: Rachel?
Rachel Mandelbaum: Yeah, hi, Lynn. Just to… to add to that and make sure I've understood properly, especially given an answer you gave to another question.
Rachel Mandelbaum: Is it correct that, like, you know, since We do anticipate that The number of gravitational wave…
Rachel Mandelbaum: Events will depend on, like, weather.
Rachel Mandelbaum: whether there's, like, a LIGO ROGO CAGRA observing run on or not.
Lynne Jones: They're.
Rachel Mandelbaum: There might be some years where the TOO time could exceed the 3%, and the 3% is more across the whole survey.
Lynne Jones: Yeah.
Lynne Jones: Yeah, the… I mean, we do expect it to be variable, because most of the time in the TOs is for these very large events, which are not as frequent, so they will be bunched up. Sorry, not bunched up, but the TO time overall will be bunchy.
Lynne Jones: I don't think we have a…
Lynne Jones: cap on how much TOL time can be used within a particular time frame.
Lynne Jones: And that… that is something that I think the SEOC have…
Lynne Jones: decided to think about, but it is hard to make progress on that without understanding what the actual,
Lynne Jones: event rate is going to be, because there's… there's uncertainty on it, so…
Lynne Jones: And it's also hard, because it is hard then also to say, okay, what effect will that have on the rest of the observations? So…
Lynne Jones: Yeah, I do think this is a thing that we need to think about, because it would go back to the,
Lynne Jones: to the TO Advisory Board, and they would say, hey, this… this time is being used too… too quickly, and we should… we should change the criteria. Igor, and you are on the, TO Advisory Board, so hopefully you can say a few words.
Igor Andreoni: Yeah, maybe just complimenting a little bit, all you've said was in response to Rachel.
Igor Andreoni: the…
Igor Andreoni: We have tried to rally up the community, bringing it together to discuss and develop strategies and come up with realistic budgets.
Igor Andreoni: for TU observation requests. So this was done in 2024.
Igor Andreoni: And we are doing it again right now. Hopefully, we will have the new documents published by the end of July.
Igor Andreoni: So, I would suggest…
Igor Andreoni: If you want to have, like, a preview, you can check on the archive. We have put the report from 2024.
Igor Andreoni: I think if you search the Rubin TO program on ADS, should be the first thing that comes up.
Igor Andreoni: Otherwise, waiting a month, you will have more solid numbers.
Igor Andreoni: These numbers that we've come up with, try to be more or less within 3% over the course of the whole survey.
Igor Andreoni: We are trying to be very, mindful of,
Igor Andreoni: minimizing disruption, of course, and when I say we, I really mean everyone who is interested in TOs, from gravitational waves to other types of messengers, to, potentially hazardous asteroids.
Igor Andreoni: In addition.
Igor Andreoni: at the moment, the go-to policy is whenever a counterpart we're searching for is found, we stop observations, so that the other telescope with a smaller field of view can perform the follow-up if they're available. So there are…
Igor Andreoni: I think…
Igor Andreoni: There are ways we're actually perform… gonna perform the observations that are maybe not fully encapsulated in the simulations, because again, they're so… honestly, so difficult to predict.
Igor Andreoni: But my hope is that the…
Igor Andreoni: We will use the time well in a very efficient manner.
Igor Andreoni: Possibly all the… what's available, and if not, observation will go towards
Igor Andreoni: The minimum… all the meaningful science that can be achieved with the regular survey.
Igor Andreoni: And all of this keeps changing. The rates, for example, for gravitational wave sources keep changing as more and more light runs are performed. And at the same time, new ideas for interesting science cases are brought up by the community. So we…
Igor Andreoni: Every couple of years, we'll try to rethink a little bit how to structure the program and try to make it as effective and efficient as possible.
Lynne Jones: Thanks, Igor.
Lynne Jones: I'm glad you… I'm glad you, got a…
Lynne Jones: Though we got to hear from somebody from the TO Advisory Board.
Lynne Jones: Yay.
Lynne Jones: Alright.
Lynne Jones: And now we can move… oh, sorry, go ahead, Rob. We can take one more question here.
Saurabh Jha: Yeah, I just wanted to follow up on, a little bit on Roberta's question. One of the things about the TOs, and I just checked in with Peter about this, was, some of the observations are using non-standard visits, so the exposure times might go up to 120 seconds in the TOOs.
Saurabh Jha: And so, you know, whether those could be included in what becomes Wide Fast Deep, yeah, I mean, maybe, probably, but, you know, they are a little bit different than the other observations in the survey, or can be.
Lynne Jones: Alright, excellent. And, let's move on to talking about the templates and the templates here. Eric…
Lynne Jones: Are you… Were you,
Lynne Jones: Oh, great. Okay. I… I… I didn't… I wasn't quite sure where to put in your slides. I was just going to say a little bit about our new option for the template tier, and then, hand… hand over to you for that.
Eric C Bellm: That's fine, how much time do you want me to spend?
Lynne Jones: You… you said you didn't want very long, so… I'm thinking you can… somewhere between 5 and 10 minutes.
Eric C Bellm: Okay, that sounds fine.
Lynne Jones: And some of that might be questions, if that works better.
Lynne Jones: Okay.
Lynne Jones: So, some of this I… Eric is gonna just say yes or no about, but basically.
Lynne Jones: One of the issues we have is good template creation requires at least 5 to 6 visits, with the full-width half mics and transparency, required for the template co-add, and that's…
Lynne Jones: Awesome. So they… so they… these are declination-dependent and band-dependent values.
Lynne Jones: Now, the other thing is, why can't we just create bad templates and keep going? Well, bad templates are bad, because, replacing templates is bad for the… it adds offsets in the magnitudes of the alerts, so the template continuity over time is strongly preferred.
Lynne Jones: And then the other thing is bad templates make more alerts, which then make even more alerts because of how, alert… the alert, prompt processing pipeline works, and this basically just loads up the prompt processing database with noise.
Lynne Jones: And…
Lynne Jones: So, we don't want to just make bad templates and keep going, so we want to make good templates, and then the problem is, if we don't
Lynne Jones: set up the FBS to sort of have a specific push to acquire the 5 to 6 visits with good image quality and good transparency.
Lynne Jones: at each point on the sky per band, there is a high likelihood that we would not acquire those necessary visits within year one. And this is not just a high likelihood, but almost certain in UNG with our… without the template here.
Lynne Jones: So, this is why we added the template tier to the baseline surveys, so that we meet this need.
Lynne Jones: Now, the… the thing we immediately did was we just put in templates… a template tier which… which acquired visits and singles, but because there's so many visits in this
Lynne Jones: Tier in year one.
Lynne Jones: Singles were not a good choice, so I keep saying we acquire the templates in pairs, because that actually was an important consideration.
Lynne Jones: The next question is, can we improve on the template acquisition? Because there is still a risk that we would not complete the templates over the whole… the template inputs, we don't make the templates, that we would not get enough template inputs over the whole sky at the end of year one.
Lynne Jones: So we have, a simulation called Faster Templates. This is in our V5.3 set of simulations. And the idea here is we need epics with dithering for the pixel coverage.
Lynne Jones: Individually, they could be shallower, potentially, although they shouldn't be worse quality full-width half max, but because they are good quality full-width half max, perhaps they can just be a little bit shorter exposures, and it doesn't make them that much, shallower in depth.
Lynne Jones: So… This simulation poses a question, what if we take the template image, the template visits.
Lynne Jones: As 20-second images, increasing the number of epics,
Lynne Jones: As… versus what we would have if we just took them as 30-second visits. Now, so, U-band is special, as always, because U-band is 38 seconds in a standard visit, and it would go down to 25 seconds in these shorter visits.
Lynne Jones: Now, this is not just for us to say, because there's lots of impacts to everybody else, so we have an RFC, a request for comment, in progress within Ribbon to evaluate the possibility and impacts of making this change.
Lynne Jones: And I will just note that 70% of the first-year images in the simulation are acquired with the template tier. So, when we say, oh, you can just take some 20-second images, we actually mean the majority of the images in year one would be these shorter images.
Lynne Jones: the impacts on our metrics. So, if you remember this grid from yesterday, we have the high-level, metrics across a bunch of different science areas. So, these are, at the bottom, are the, SRD metrics, and we have things that go into,
Lynne Jones: Cosmology, and then time domain.
Lynne Jones: static science of galaxies and solar system objects. And this is all normalized to, be 5.3.
Lynne Jones: And at the… here we have what happens if we go to these 20-second templates, so the 20-second fast template simulation.
Lynne Jones: some things get better, some things get worse. It's not obvious we've completely captured the effect in our metrics, but one thing that is for sure is that
Lynne Jones: On the right here, what we have is the night that you have captured a given amount of area.
Lynne Jones: while getting, at least 4 visits per band onto, silicon. So… This is math.
Lynne Jones: Evaluating the camera footprint on our visit bore sites.
Lynne Jones: Which is not quite the same as how, as I mentioned yesterday, as how data management would count
Lynne Jones: whether the… detector was usable to go into the co-add, because they have,
Lynne Jones: probably different constraints on the edges and things like that. So, this is our estimate, but it's not the final answer.
Lynne Jones: So this is… if we have this deck-dependent seeing limit, and we chose… we said it's a limit of 1.2 arcseconds at zenith, and how many, how much area would you have where you got 4 visits onto silicon and… per band?
Lynne Jones: And so what you see is this is the total area of the survey, and if… with, with the Comp Survey V5.3, that's the one where we used the old downtime, so we don't have our extra downtime. It's blue.
Lynne Jones: The green line here that's lower is our baseline 5.3. So this is the effect of not having as many visits in year one.
Lynne Jones: And then the red line is what happens if we, take those visits and make them shorter. So we… with a shorter visit, we do have a little bit less duty cycle on the sky, but we still end up with more visits, and so…
Lynne Jones: If we were to do that, and all of the things, like the visit gaps remain the same, then we would push back up to, the same number of visits as we would have had without the extra downtime.
Lynne Jones: And, so this is… this is close to you. This is…
Lynne Jones: Essentially getting templates over the sky by the end of year one.
Lynne Jones: Now, like I said, this is uncertain. You know, you can't say, oh, if we don't do this, we won't close the sky for the templates, and if we do, then we will, but that's…
Lynne Jones: And if you said instead of 4 per year, you said 5… sorry, 4 per band, you said 5 per band, the difference between these would scale similarly, but,
Lynne Jones: It's true that the overall Area would be slightly different.
Lynne Jones: Right, so from the… that's our… from the point of view of metrics. Now, is this…
Lynne Jones: So now I'm going to hand it over to Eric to talk about actual templates, and did you have slides of your own that you wanted to talk about?
Eric C Bellm: Yeah, I can share.
Lynne Jones: I put this one in because I wasn't quite sure.
Eric C Bellm: Yeah, I'll… I'll put them into the shared slide deck after I talk. I just didn't have the link in time.
Lynne Jones: Perfect, yeah, sorry about that.
Lynne Jones: I'm gonna stop sharing a hand to you.
Eric C Bellm: Alright, so I'm just gonna spend a few minutes talking about,
Eric C Bellm: templates from the data management perspective. So I, I think it's worth,
Eric C Bellm: saying up front, you know, kind of distinguishing in our minds two separate questions. One is thinking about what we're aiming for at the end of year one, as the… for the inputs into DR1.
Eric C Bellm: which has been kind of targeted as our source of, you know, good all-Sky templates, and so that's, I think, especially driving some of the questions around the template tier that Lynn is describing. You know, how do we get to an endpoint where we have enough inputs of good quality over the whole footprint that we can co-add. Separately, you know, of course.
Eric C Bellm: I, like all of you, am extremely excited to get alert science going, early in the survey, in this first year, and so for that, we need to be even more, sort of, aggressive in getting templates deployed.
Eric C Bellm: how do we manage… how do we maximize that sort of science ahead of DR1? And so there, I think it's clear, as you're gonna see in a minute, you know, we have to… we have to accept some compromises of some kind, and it's just a question of
Eric C Bellm: It's kind of an engineering and science trade-off of where do we cut the corners, because it's… we don't have as many images as we'd like, and we have to kind of figure out what to do about that.
Eric C Bellm: All right, there are kind of two technical constraints that really, influence what we do on template generation. The one is for alert production. There's a database we call the APDB, the Alert Production Database, which serves as sort of the core of the association and light curve generation, sort of.
Eric C Bellm: For alerts, and it's very sensitive to, false positive rate. If we… if we pump it full of junk sources, it will… it will break down. It will… it will reach capacity and not function. We have approached that on a few occasions and, learned from the process, but, you know, we have to be thoughtful about it. And I would say, probably as science users, you also don't want just
Eric C Bellm: cascades of bad detections either. There's lots of knobs we're learning to tune here, you know, both in things like Real Bogus and how we configure image subtraction, but I just want to put out front that this is something that we really do care about a lot, and as you'll see in a minute, templates are a major source of false positives. So, the other challenge is that it is not as easy
Eric C Bellm: as either it sounds, or we'd like it to be to change the templates frequently. The processing takes a while, frankly, and so it's not easy to do a big template run and just update things. I also think, scientifically, most users don't actually want that, because when you change the templates, all the…
Eric C Bellm: All the different slight curves are gonna shift. You get different amounts of contamination from
Eric C Bellm: transients in the… in the template for supernovae and things like that, and for variables. So, all of that just says that, like, you know, we will change templates over time, but we're not gonna thrash them, especially in the first year. So, we're trying to do the best job we can, you know, put templates on and keep them there for, you know, of order a year.
Eric C Bellm: All right, so since we can't update the templates a lot, we want to try to minimize gaps where we can, because if you have a hole in the template, you can't fill it for a while, you get no alerts from there at all. The fill factor of the camera, in terms of, when you project it into the template space, it's about 88%, and so if you just use single images, then you're gonna just have
Eric C Bellm: 12% holes. So…
Eric C Bellm: So we want multiple inputs, and what is the very minimum? If you think of these as just uncorrelated and ask, you know, how many, how many, what area doesn't have any pixels on it, you only need sort of 2 or 3, and you get real close to 100% fill factor. So that's, like, kind of the minimum.
Eric C Bellm: like, baseline to if you want to avoid holes. There are some other image quality and image subtraction issues, which we'll discuss there, but in terms of, like.
Eric C Bellm: What's… what is the bare minimum for year one if… if we accept that we don't want to just leave giant holes in the survey, then… then there's a few images to input?
Eric C Bellm: And again, those should be good quality images, they shouldn't have clouds in them, things like that.
Eric C Bellm: As we add images, we do better.
Eric C Bellm: with 3 or more images, we can do something, we can do artifact rejection. We have some algorithms that, especially work nicely when you get lots of images, where we… it's, able to reject, footprint… detection footprints that only show up in a configurable fraction of the inputs.
Eric C Bellm: As you can see, on the right here, the difference between
Eric C Bellm: sort of, you know, mean and sigma clip coads and this, what we call compare warp rejection, which is great for getting rid of things like satellite trails and glints and so on. So, this is, what we, you know, why we push for more inputs when we have them.
Eric C Bellm: So again, we're trying to get to that sort of greater than 3 images, and that's where we sort of talked to Lynn about, can we get to 5, 6 sort of images to, to get inputs.
Eric C Bellm: All right, what have we done so far? We have DP2 coming, later this year, and that is, based on commissioning images from last year, which got, especially this wide trance that you see here in the ecliptic plane and crossing through, sort of, the galactic center region.
Eric C Bellm: We… this is the, a view of the HIPS maps from the Deepco ad. The template selections are very slightly different and a little smaller, but it's useful for illustration.
Eric C Bellm: And when you zoom down at this level, it looks great, and you're like, okay, we got templates on all that area. It's not quite that simple. When you zoom in in the middle somewhere, you see that, yes, indeed, it is pretty well covered. But at the edges, you can see, that, you know, these are sort of single epochs that have big chip gaps in them. Don't pay too much attention to the interpolation here, but you can see the…
Eric C Bellm: The chip structure of the camera.
Eric C Bellm: This is U-band for comparison, and in U-band, for instance, there's even larger holes, even in the middle of this… of this footprint.
Eric C Bellm: So as Lynn, showed, we have deployed these DP2 templates in addition to the existing drilling templates. There's a dashboard that's been circulated, and we're keeping updated as we add new ones. We added a few more, from,
Eric C Bellm: From a few weeks ago, and are continuing to do so.
Eric C Bellm: And so our alert volumes have accordingly increased.
Eric C Bellm: What I do want to say, and this, again, impacts the… sorry, darn it. Let me…
Eric C Bellm: Rapidly edit this.
Eric C Bellm: Meant to make that a…
Eric C Bellm: animation. We do see that even the DP2 templates have some challenges. So this is a pattern of alerts that we've sent out in the last few days, and you can see there's a pretty strong grid structure in some regions of this, of the sky. And this is, we have tracked down due to,
Eric C Bellm: when we have co-added even, you know, a relatively small number of images in this wide area, there's a wide enough range of PSF sizes that when you have chip gaps.
Eric C Bellm: Sometimes the PSF that results in the COAD is printing through has some pretty strong spatial variations, which you can see on the right for a patch here. I apologize, the full width half max here is in pixel units.
Eric C Bellm: Which is, you know, multiplied by 0.2, but you can kind of see how these structures, you know, have the imprint of the focal plane in full width, half max space. And so image differencing has a fair bit of trouble right now. It's sort of managing, you can't…
Eric C Bellm: The kernel is not able to handle such rapid changes, and so you get
Eric C Bellm: an excess of false positives. We have a number of ideas about how to deal with this, both at the vetting side and in template construction, image differencing, and so on.
Eric C Bellm: But I guess I would just, you know, highlight the point that, you know, it's not quite as simple as, you know, just take, take in image, you know, take two images and add them and everything will be fine. It really does… we do see problems.
Eric C Bellm: I mean, the good news is these are not such large, bogus volumes that it's overwhelming the APDB, but it is something where we feel like we need to take some corrective action.
Eric C Bellm: All right, so we're looking ahead to incremental templates with,
Eric C Bellm: with pre-LSST images, as well as the previous input inputs. Lynn hasn't seen these, because I just got them done this morning. So these are plots of basically all of the Rubin science images subject to some cuts.
Eric C Bellm: And… and sort of looking where we… where we could start building incremental templates now, and so this is band by band. I'll call your attention mainly to the green boxes, which are tracks that have complete coverage of at least 3 input images, and so that would be kind of a good place to start.
Eric C Bellm: So this is U-band, there's some, you know, maybe, I guess it's labeled here. 42 tracks are maybe plausible.
Eric C Bellm: G, a little wider. The white areas already have templates deployed, either from the DDFs or from DP2. R-band, a little bit of coverage, sort of, in the south. It remains patchy. This… there's a region, here that maybe we could explore.
Eric C Bellm: Iban, there's these big stripes that were taken during OES commissioning, which we can build templates in, so those are a natural place for us to start.
Eric C Bellm: Zband, I think, is in some ways the best. There are some really large areas here that have quite a bit of coverage.
Eric C Bellm: And then Y band a little less. So, I think we do have a bit of a head start building templates over a reasonable but not overwhelming area, but we need to sort of understand, some of the issues we're seeing with the DP2 templates.
Eric C Bellm: In order to make sure that we're making the right choices there as we deploy them. So, happy to… I don't know if we're going to questions here, Lynn, but that's all I have for the moment.
Lynne Jones: Yep, it was, just questions, and then we… we back up to the break next. So, actually, that was awesome, Eric, thank you so much. And all of that new stuff, very fascinating.
Lynne Jones: I wanted to make the comment that when we know that we can build a template in a particular area of the sky, we will be able to load that into the template tier survey, so that they know that, like, okay, yeah, we…
Lynne Jones: You may not know about those observations, because we're going to wipe its memory clean when we start the survey, but we can tell that, yes, there are already templates available for this part of the SCA.
Lynne Jones: Alright, David.
David Schlegel: Yeah, these DP2 template observations, are that all the range of rotation angles?
Eric C Bellm: Yeah, that's right. It's getting the… maybe Lynn can speak better to it, but my understanding is those are widefast, deep-style dithers in rotation and translation.
Lynne Jones: Yeah, the… so the… the stripe across the sky in the ecliptic area was mostly wide-fast-y, style. It was mostly coming from, our Paris survey.
Lynne Jones: tier, but… The… because of the fact that, it's a smaller area on the sky.
Lynne Jones: We… the repeat rate was a little bit higher, and
Lynne Jones: Yeah, but other than that, it would be like our normal survey observations.
Lynne Jones: Alright, wow.
Lynne Jones: I really thought everybody would have questions for you, Eric, because of the…
Lynne Jones: I'm really fascinated to see the, you know, where we can go with incremental templates, and what we might be able to do even before we start the survey, because these are really
Lynne Jones: big questions, like, what are we going to try to do in the first year regarding templates?
Lynne Jones: I… nobody has asked, but I'm gonna ask, because…
Lynne Jones: I get asked, how soon can you have templates for a particular area of the sky?
Lynne Jones: And I know from watching that there's a… can be a significant lag, because as you said, it's quite labor-intensive.
Lynne Jones: Do you… do you want to say a few words on, like, the rate of, like, once we cover the sky, or, like…
Eric C Bellm: Yeah, I had this in a slide and kind of brushed past it. My estimate right now is that the delta between, we know we have enough images here, and we could get this into production, is about a month.
Eric C Bellm: And a lot of that is human steps, you know, either shepherding data through, or looking… vetting the data before we deploy it, or getting it deployed. I hope that can come down over time as we streamline
Eric C Bellm: You know, our metrics and learn to trust, you know, what we're looking at.
Eric C Bellm: you know, again, we sort of started with the DDFs, which have a very different sort of…
Eric C Bellm: behavior when you co-add them, versus some of these wider areas. So, you know, that's… that's my estimate right now, is it takes a month, and I hope that it improves over time. It kind of needs to, but, I don't… I don't think that's… that's happening quickly, so…
Lynne Jones: John?
John Gizis: So I guess I… I guess I don't quite follow the big picture case for, sort of, taking a major part of the first
John Gizis: year and turning it into a 20-second survey, right? I mean, if there's one-month delays anyway on templates.
John Gizis: The alert, you know, volume is so large.
John Gizis: you know, in the long run, of course, you can… you will have templates and can go backwards in time, so it's just about alert production. Doesn't it seem like there'll be enough alerts that maybe you should just stick with the 30-second? Like, what's the big picture? Like.
John Gizis: Like, you really won't be able to generate alerts even after one year.
Lynne Jones: So…
John Gizis: Over the whole sky? In every filter? Is that the problem? Like…
Lynne Jones: Oh.
John Gizis: Understand what drives such a big change.
Lynne Jones: Yeah, I don't… I don't… okay, so Eric, I saw Eric…
Lynne Jones: You put up your hand, so I'm gonna say maybe you… if you have something to say about this, go ahead.
Eric C Bellm: Okay, sure, we can take two turns. I think the advantage to 20-second exposures is that it gives you more images
Eric C Bellm: you know, more… a larger number of images at any given position and filter in the sky at the end of year one. And…
Eric C Bellm: If those are… especially if those are preferentially taken in better conditions, that increases the odds that you have a good set of inputs that you can, reject artifacts, you know.
Eric C Bellm: you know, dither out chip caps, etc. So, you're sort of sacrificing a little bit of depth in exchange for kind of an absolute image quality improvement. It's less about, in my mind, it's less about
Eric C Bellm: Getting alerts out in year one, and more about, do you have enough, you know, what is the quality and aerial coverage of templates at the end of, at the end of year one?
Eric C Bellm: I will say, you know, Lynn didn't say, but, you know, we have been discussing in data management, like, can we support 20-second images? Are there concerns we need to worry about? Largely, the answer is no, with one exception. There is some concern that the active optics system
Eric C Bellm: instead of being able to correct, sort of, every, you know, 2 images later would be then at 3 images later correction because of the shorter, sort of, cycle time. And that is a significant concern that they worry that the image quality will suffer, and that may be, you know, maybe a showstopper. And there's some discussion, I don't know if Bob or others want to comment, you know, we should just test this.
Eric C Bellm: But I think that's maybe the biggest concern that I'm aware of with the 20-second exposures outside of the survey strategy question.
John Gizis: And could I ask a related question? My metric actually seemed to survive, because the, you know, the extra images probably makes up for anything you lose, so it's, it's, you know, it's all fine.
John Gizis: But I heard a lot, I think, in previous workshops of the need for really high-quality, G-band and R-band images, that it was important to get, you know, sort of deep, good-seeing images there.
John Gizis: And it sort of seems like that might…
John Gizis: be a real problem to what I heard, you know, repeatedly in a lot of documents, that that was sort of really a priority for the 10-year static case. Maybe it's all in the wash, since it's only 1 tenth.
John Gizis: But, has that… is there any comments about that?
Lynne Jones: This is… this is a good point, because I think that this is one of the things that's not necessarily well captured in the metrics that we have, like, how… and… and what it goes into is, how well can you de-blend things like stars and galaxies, is my understanding.
Lynne Jones: Yeah, so…
Lynne Jones: That might be an issue. I think it certainly is one of the things we would have to go and consider.
Lynne Jones: It also, after 10 years, it does kind of probably come out in the wash, but the question is, do you need that at the end of year one? Which I think was actually their request, that you have those at the end of year one. That said, they also didn't have a large number of these
Lynne Jones: you can sort of think of them as Pathfinder, like, they're the, like, that's pin to blending based on these, like, really deep, good-seeing images.
Lynne Jones: And…
Lynne Jones: it's not obvious you wouldn't have that anyway, even with the slightly shallower depths, because they are in good conditions, so that you naturally get a slightly deeper depth. So I think that's something to also look at, for sure.
Lynne Jones: It's also true that it may be a showstopper based on the AOS,
Lynne Jones: So, we'll see. There's, there's… there's…
Lynne Jones: This is still very much in the, we're going to…
Lynne Jones: Have to think about this a little bit more, maybe test some data on the sky.
Lynne Jones: The other… there wasn't another…
Lynne Jones: there's maybe some concern about U-band, and maybe we would have to leave U-band at 38 seconds, just because,
Lynne Jones: getting even further… getting back into the read noise, which is what would start to happen with the 25-second exposure, might be bad. Alright, here's… this is the other thing I was gonna say, though.
Lynne Jones: it may not be that we have… then… if I didn't say, oh, it's so that we can get templates over the whole sky and we can close the sky, but if instead I said, and this might hold up DR1,
Lynne Jones: Does that change your opinion?
Lynne Jones: Because that… not having… not being able to make templates over the whole sky might actually mean, like, oh, we're gonna wait a little bit longer until we get those images so we can make them as part of DR1.
Lynne Jones: That is not my decision to make, obviously, and it's… it's not a for-sure thing, but, like, that would be a possibility.
Lynne Jones: So… Damn.
Dan Taranu: Yeah, so you showed this plot that had the number of… or the area covered versus the number of nights, or the various scenarios, and it kind of looked like
Dan Taranu: The slope from the baseline after you reach around 15,000 square degrees was just about the same.
Dan Taranu: I was wondering, are those the same 15,000 square degrees? Are you envisioning a scenario where you do 20 seconds for, like, 200 days and then switch over, or…
Lynne Jones: This one… this one here, you mean?
Dan Taranu: Yeah.
Lynne Jones: Yes, sorry, after… so this would only be 20-second visits coming from the template tier. Any other tier would just do normal 30-second visits. However, like I said, in the first year, and the template tier switches off after the first year, right? So in the first year,
Lynne Jones: On the order of 70% of the visits would be the shorter visits coming from the template tier.
Lynne Jones: So yeah, after this point, it looks…
Lynne Jones: It will become fairly similar, but that's also… the template here isn't trying to acquire any visits after that point.
Dan Taranu: Right. Well, what I meant was after about
Dan Taranu: Knight 300, the slope of the green line looks basically the same as red, right?
Dan Taranu: So, if you were to switch over from 20 seconds to 30 seconds after, like.
Dan Taranu: I don't know, 250 nights?
Lynne Jones: I'm…
Lynne Jones: So, okay, Peter can say something more about this if he wants, because he made this plot, but I'm gonna guess that that's…
Lynne Jones: Not just because of,
Lynne Jones: A lot of that has to do with how much area is new and appearing on the sky, maybe rather than quite so much as,
Lynne Jones: the rate of acquiring just enough. I'm not sure, yeah. Peter, do you have anything to say about that?
Peter Yoachim: I bet that rapid rise is that we observed some area at the start of the survey, but didn't get enough to get templates, and so it's come back around, and so now we're able to rapidly, you know.
Peter Yoachim: One image gets us to the threshold, and so that's why there's that rapid rise.
Lynne Jones: Yeah.
Peter Yoachim: Yeah, it's… it's area that's coming back around that… that now we can complete.
Lynne Jones: Yeah, that makes sense. So, it's… it's because we did… we did part of the sky that we're observing here, we did it back here, but we didn't reach 4.
Peter Yoachim: Yeah.
Lynne Jones: Okay.
Lynne Jones: I'll pause for a minute if there's any more questions. We are into our break, so… But also I think that…
Lynne Jones: these are all really good questions, and I really appreciate hearing about the templates and the current plans. So thank you, Eric.
Lynne Jones: Alright.
Lynne Jones: I don't see any more questions. Remember, you can ask questions on Slack, or on Community if you have a more general question. That's great, a great place as well.
Lynne Jones: Alright.
Lynne Jones: Actually, this is the time for our break, so we'll come back at, in 20 minutes at 10 o'clock.
Lynne Jones: All right.
Lynne Jones: Here we are, 10 o'clock,
Lynne Jones: Hopefully everybody comes back from the break now. Okay, so…
Lynne Jones: Next, we have, two more specific areas to cover, rolling cadence and options around rolling cadence, and Leanne Guy's gonna talk a little bit, with us about
Lynne Jones: uniformity in coads and data management processing for DRP.
Lynne Jones: As well, to go with that. And then we're going to talk about the DESE survey options. And then we have some time for general discussion.
Lynne Jones: As, as we need it.
Lynne Jones: Okay.
Lynne Jones: So…
Lynne Jones: rolling cadence. So, if you remember, this is what we do so that we can boost the cadence, for time domain in certain areas of the sky, at the expense of in other seasons that has slightly lower cadence. So.
Lynne Jones: When a part of the sky is in active rolling cadence, the… the gap between, nights of visits is… is sort of 2.
Lynne Jones: On average. And in a low cadence season, the gap between coming back to the same, part of the sky, the same pointing on the sky, is about 7 nights.
Lynne Jones: So it does vary, and then…
Lynne Jones: In between, in our seasons, which are just, like, normal, uniform cadence, like in the first year, the gap between revisits is actually,
Lynne Jones: Medium value of 3, you know, obviously there's a little bit more scatter in there, so…
Lynne Jones: So, if you look at the whole survey, and don't look at individual seasons of rolling, you mostly… and you're just measuring something like the
Lynne Jones: the gap between visits. You mostly see the uniform seasons, and it sort of washes out that increase from rolling and the decrease from the, low activity rolling errors. But.
Lynne Jones: If you are looking at something like how much… how well you're recovering particular light curves.
Lynne Jones: That will be influenced by the details of the observations in a particular season or year, and so you'll notice that a little bit more.
Lynne Jones: So that's one of the things that, depending on how you're…
Lynne Jones: Looking at what you're looking at when you're trying to evaluate impacts of
Lynne Jones: just the visit spacing on time domain.
Lynne Jones: metrics. You do have to consider whether you're
Lynne Jones: Sensitive to the changes in a given year of rolling, or if you're sort of washing out over the whole survey.
Lynne Jones: So, that said…
Lynne Jones: That makes some of the metrics a little tough to interpret when you're looking at 10-year metrics.
Lynne Jones: And rip.
Lynne Jones: what we have is, in baseline V5.3, we start rolling after year one. This is the standard. We don't want to roll inside of year one, because we want fairly uniform coverage at the end of year one, so that we can do
Lynne Jones: Calibration and photometric and astrometric catalogs over the whole sky with something that's,
Lynne Jones: That has the number of visits and is fairly uniform.
Lynne Jones: Now, if we're still acquiring visits.
Lynne Jones: needed for the input templates, instead of starting rolling right after year 2, or right at the start of year two, at the end of year one, we could delay the start of rolling until after year two, because there is, a reasonable argument to be made that you should not start rolling when you don't have templates yet.
Lynne Jones: Because, the templates are needed to fully leverage the time domain, and the time domain is the reason for going into the rolling cadence.
Lynne Jones: Now, it is also too early yet to know if this is a problem.
Lynne Jones: And the decision can wait while we're investigating options on whether we should start rolling at the end of year one, or whether we should start rolling at the end of year two. So, some of the things we're talking about here in the various simulations that we have are questions of
Lynne Jones: things to think about, we don't… we won't be making the decision today.
Lynne Jones: Or… or immediately, anyway.
Lynne Jones: This series of plots over here on the right is the number of visits in IBAND, so I chose just a single band, after year one. So, year one is a time…
Lynne Jones: deadline, not a season. So remember, this is just the… the end of year one. We would have this many visits in IBAN.
Lynne Jones: At the end of year two, our coverage would look like this, because we've started rolling during year two.
Lynne Jones: At the end of year three, it looks like this, because we've started rolling, but also we've started the opposite rolling, but you still see all of this signature rolling.
Lynne Jones: And then we have a season for the rolling cadence, where instead of doing a high activity or low activity, it has an average, so the medium.
Lynne Jones: Or normal uniform activity. And so that lets the sky catch up and, equalize, and so at the end of year four.
Lynne Jones: we have what looks like a fairly uniform coverage on the sky. Now, I did make these plots, removing any of the special surveys.
Lynne Jones: Because that… then this lets us see exactly how uniform,
Lynne Jones: Things like the… the pair survey, and our normal wide, fast, deep kind of observations would look.
Lynne Jones: If we delay the start of rolling until after year two, what this basically means is we're shuffling the high and low activity and uniform seasons so that the end of year two is uniform, so instead of being here at the end of year four, year 2 would be uniform.
Lynne Jones: And then 3 and 4 would be non-uniform, because we've just shuffled that order.
Lynne Jones: Okay.
Lynne Jones: So, we have some simulations.
Lynne Jones: That illustrate
Lynne Jones: different options. So if we go with the baseline, normally at the end of year four, we have a uniform data release.
Lynne Jones: And I'm gonna keep saying uniform with quotes because, this is part of the things that
Lynne Jones: that Leon is going to talk about.
Lynne Jones: Well, we'll talk about a little bit more in a minute.
Lynne Jones: So at the end of year four, normally we would have a uniform data release, but if we reshuffle and delay the start of rolling, that year 4 uniform data release disappears, and it moves into year 2. So these are…
Lynne Jones: Two other options. This is if we just delay the start of rolling, or we don't change anything else. So you can see year four, so across in this plot is all year four, for different simulations. Down in these series of images is different years, so it's 4, 5, and 7, not 6. I skipped a year, but…
Lynne Jones: There.
Lynne Jones: So this is… on the left is the baseline, year 4, 5, and 7. And the second row is just a simple… we'll delay the start of rolling for one year.
Lynne Jones: So this is what we… the simulation we're calling Roll Mash, 5.3. So it goes… this is, again, your 4, 5, and 7, and you can see your 7…
Lynne Jones: Because we only shuffled some of these rolling seasons early in the survey, year 7 looks very similar. So you have year 7 in the baseline, year 7 in Roll Mash.
Lynne Jones: That's our uniform data release year.
Lynne Jones: And then, if we not only reshuffle the, seasons of uniform rolling,
Lynne Jones: in the first year… sorry, in year 2 and 3 and 4, if we also shuffle them in later years, we can move that uniform data release that was in year 7
Lynne Jones: into your 5. And so this is roll U5, V5.3.
Lynne Jones: So this one… in this U5 simulation, we also delayed the start of rolling for a year.
Lynne Jones: But instead of taking the uniform season, right before the year 7 data release, we've moved it up in time, and so we have a uniform data release at year 5 instead.
Lynne Jones: So in both of these simulations, because we wait, we have a uniform data release in year 1, year 2, and then this would be year 7, and year 10, and this would be year 5, and year 10.
Lynne Jones: So, if we delay… This started rolling.
Lynne Jones: We inevitably lose uniform data release at year 4, but then we can have a choice about if it's year 7 or year 5.
Lynne Jones: And of course, year 10 in all of these simulations is the same.
Lynne Jones: So… Because at the end of 10 years, you've done the same…
Lynne Jones: number of visits, and the simulation is generally the same. Just reshuffling the seasons when you're doing rolling cadence and when you're not should be…
Lynne Jones: really have a minimal impact on those Year 10 metrics.
Lynne Jones: And so this is our metric grid again. It's, here's V5.1, the baseline, and so this is what everything is normalized to, and these are these high-level summary metrics.
Lynne Jones: Now… Role…
Lynne Jones: Year 2, U7 is, like, we have… wait until year 2, this is the roll mash, sorry, it's renamed. This is one reason why, in general, we discourage people from renaming, but I did it anyway.
Lynne Jones: And this is the one where it was… the uniform data release was shuffled into year 5 instead of year 7.
Lynne Jones: And you can see it's not exactly the same.
Lynne Jones: The changes are pretty minimal, so this… note the scaling here, this is,
Lynne Jones: 10% into the… into the red, or 10% into the… into the blue.
Lynne Jones: And these are all generally a few percent, except for some. There's… there are some of these time domain metrics which seem a little bit more sensitive.
Lynne Jones: And it may be that what we're actually seeing here is noise, rather than actually something, real in the changes of the metrics, because really, these impacts should be minimal, but it is possible that as we change things around.
Lynne Jones: There's some unintended effects.
Lynne Jones: So it's worth looking at, but it is also possible that… Not that significant.
Lynne Jones: So this is the thing we should think about, like, what do we do about, if we did delay the start of rolling, which we don't know we would do yet, but it is a possibility, especially if we can't.
Lynne Jones: Complete templates around the sky at the end of year one.
Lynne Jones: Then what do we do about later years, and down the road, do we shift some of these uniform data releases around?
Lynne Jones: Now, I also wanted to talk a little bit about uniformity and what that means, because we talk a lot about, hey, let's have a uniform data release.
Lynne Jones: But, that's not really very well defined.
Lynne Jones: And… It's not obvious, what's the best way to support that?
Lynne Jones: There's some uniformity we can enforce, we can try to gain from survey strategy.
Lynne Jones: By not letting our… our number of epochs or depths get too uneven across the sky.
Lynne Jones: And an example of trying to manage that uniformity is with this uniform season in the rolling cadence.
Lynne Jones: There's also an aspect, like, you could enforce uniformity later in the processing chain at data management, although if we do that there, it necessarily means dropping visits to gain uniformity, so you're not dropping visits completely, but not including them in the coads.
Lynne Jones: So… This raises questions, how could or should we achieve
Lynne Jones: uniformity in the coads and the catalogs that come from the coads.
Lynne Jones: What does that mean? There is some natural variation due to weather, that will lead to variations in the coated depth across the low dust, wide, fast, deep region, but is it that we want less than the magnitude of variation in the estimated coated depth, the number of epochs?
Lynne Jones: Is it a different number on the… on the RMS of the coated depth?
Lynne Jones: And what does it mean for visits which are not included in the co-ads?
Lynne Jones: So these are all good questions, that I had, and then the plots here show us the co-ed depth and I-band, if you do include all of the special surveys, versus if you don't. So even if we don't have a question about, like, what do we do with rolling cadence, what do we do with DESI,
Lynne Jones: anything, we already have non-uniformity due to things like the TOs, and other special surveys.
Lynne Jones: So… Leanne, are you there?
Leanne Guy (Rubin): I am here.
Lynne Jones: Excellent, excellent. I was going to hand this over to you to talk a little bit about, some of the things we chatted about the other day, like, what happens to visits that don't get included in co-ads and things like that?
Leanne Guy (Rubin): Yeah, okay, thanks, Lynn, thanks for introducing us. So, I've sort of just come along at the last minute at Lynn's request to support this meeting. I have nothing prepared, I have no answers for you, but I am here to take a lot of questions and to think about how we can address some of the open topics and questions.
Leanne Guy (Rubin): What happens to visits that are not included in COADs? They will still be perfectly valid single visit images, and there will be catalogues of detections in those single visit images, and they will be included in a data release. They just won't have gone into a COAD.
Leanne Guy (Rubin): You'll already see this, in fact, with Data Preview 2, which is coming up sometime in the July to September timeframe. We have a region of DP2 which has co-ads.
Leanne Guy (Rubin): And then we have a lot of other visits scattered across a very large area of the sky. So the co-added region is roughly 3,000 square degrees, although there's variation of co-added depth within that 3,000 square degrees. And then you can get out to another sort of, I think it's about 12,000 or so
Leanne Guy (Rubin): degrees, with just single visit images taken at various positions on the sky. So, some of the positions on the sky will only actually have one visit, maybe some will have two, but none of these were co-added.
Leanne Guy (Rubin): So, you'll already see how that looks in the Data Preview 2 release.
Leanne Guy (Rubin): So the term throw out is a bit strong, maybe. We will throw them out of the co-add, but we will not throw them out of the release, provided they meet other quality criteria.
Lynne Jones: Sorry for my thrashing there as I tried to unmute myself.
Lynne Jones: Yeah, and those… the catalogs from the single visit images are calibrated in the same way, like, against, the full astrometric and photometric calibration, etc.
Leanne Guy (Rubin): In a data release, yes. Like, single visit images in the prompt, nightly processing, no, have a, I think, more fast approximate calibration, but in data release, yes, they are fully calibrated, single-visit images. It's… they're processed in exactly the same way as every other single visit image, irrespective of whether it goes into a co-add or not.
Lynne Jones: So if we were able to make a goal on the uniformity of the co-edit depth, so that when we make catalogs from the co-edit images.
Lynne Jones: that the…
Lynne Jones: Depth in those catalogs is fairly uniform across the sky, and obviously there's a limit to how much you can do there.
Lynne Jones: But if we were to do that, you would still have all of the single visit measurements well-calibrated, so you could do light curve analysis,
Lynne Jones: On all of the visits, and it would just be that your, co-edited visit
Lynne Jones: Co-edited catalog would be more uniform and more shallow.
Leanne Guy (Rubin): Yeah, I mean, the co-added images that are created would be shallower, they would be missing some images, and that would, of course, have an impact on detection in co-ads, which is what goes into the object catalogue, so…
Leanne Guy (Rubin): let's say, quite simply, they wouldn't have the same depth. Let's… if we… if we remove some, you'd lose some depth, so then you might not have, you might have fewer objects detected in those coads, or their parameters might not be measured with the same sort of accuracy or characterization. There might be more uncertainty around them.
Leanne Guy (Rubin): Yep, I think that answers the question.
Lynne Jones: Let's see if, there are questions from…
Lynne Jones: the people listening. Or comments on, like, what the… the impact of this uniformity or not is.
Lynne Jones: Roberta?
Roberto Assef: Yeah, one question, is it…
Roberto Assef: Would it be feasible in any way to sort of think of doing the full code, and then produce a good enough error model, so that at the catalog space, you could add those sort of additional uncertainties to homogenize your catalog at whatever level you want to.
Roberto Assef: To do that.
Leanne Guy (Rubin): I think so, yes, but as Dan's on there, and Dan's more deeply embedded in the pipelines than me, he might have a response to that, but I don't think, in principle, that would be a problem. I'm not sure if it's part of our current processing
Leanne Guy (Rubin): Pipelines.
Roberto Assef: Okay.
Leanne Guy (Rubin): Dan, do you want to throw something in?
Dan Taranu: Well, I was gonna say that…
Dan Taranu: the image we do detection on doesn't necessarily have to be the same as the coeds we do measurement on, and
Dan Taranu: The simplest example is we could do detection on a multivand image, and that has been tested, but not
Dan Taranu: Fully implemented and… The impact hasn't really been measured yet, but it is a possibility.
Leanne Guy (Rubin): Can I throw… can I add something just quickly to that? If we were to do this, though, consistently across the entire widefasted for a data release, that would involve producing two coads, essentially, for every position on the sky, right? To do detection on…
Leanne Guy (Rubin): The deepest, and then measurement on the uniform.
Dan Taranu: Yeah, but I mean, we are already making template coads, for DP2. We have also added the pretty co-ads that we're making images out of, so…
Dan Taranu: I mean, yeah, there is a storage question. If this is… the thing we do detection on is something we persist as a product separately from the other coads, but I don't think it's out of the question.
Leanne Guy (Rubin): So, so technically it's not out of the question, but there is a non-zero question of storage cost plus processing time plus
Leanne Guy (Rubin): etc.
Leanne Guy (Rubin): The short of it is, I can't tell you we can do that right now, because it's got budget involved, and I'd have to go back and talk to other people as well, but it's good to understand that the scientific and technical side doesn't necessarily pose any problems.
Lynne Jones: And my understanding from previous questions about this was that it was… it probably did… was out of scope, especially once you included all the catalogs that you would generate from that, as well as the co-ed itself.
Lynne Jones: But yeah, that, I mean…
Lynne Jones: Those are really good questions, like.
Leanne Guy (Rubin): I mean, there's also going to be provenance questions as well, and keeping track of all this, and what was done on what, so there's all sorts of, you know, data wrangling that has to go in as well.
Leanne Guy (Rubin): Yeah.
Leanne Guy (Rubin): Like, it's not just a flip-the-switch thing.
Roberto Assef: Good.
Leanne Guy (Rubin): There is work involved, but it's not,
Leanne Guy (Rubin): It's… it's not, what's the word?
Leanne Guy (Rubin): Well, we would know how to do it, like, yeah.
Lynne Jones: But this does raise the point that somebody else could do it, too.
Leanne Guy (Rubin): Indeed. But then it… that also raises the point of, you know, how do we define our data releases as our, sort of, flagship product?
Leanne Guy (Rubin): That's… yeah, sorry, we're interrupting Rachel.
Rachel Mandelbaum: You can't interrupt someone who hasn't started talking.
Rachel Mandelbaum: so, I just…
Rachel Mandelbaum: I… it could be that I… that I… that I missed something, but the way this slide and some of the discussion was framed.
Rachel Mandelbaum: It seems like there may be a lack of awareness that there's been a lot of work on desk in, you know, defining metrics of sufficient uniformity in COAGs, and, quite a few people, you know, Boris Leistat, Renee Losec, me, a few others, put a lot of time and effort into getting metrics into MAF.
Rachel Mandelbaum: So that they could be
Rachel Mandelbaum: you know, run on the simulations and use to assess them. They cover, a subset of the questions one cares about with uniformity, so if there's a strategy that, for example, the metrics currently assume that if
Rachel Mandelbaum: you know, RI and Z band are uniform-ish than the others are, so if there's a simulation for which that assumption is false, they won't catch that. But, you know, a lot of work went into that, and I wanted to advocate for those being included by default.
Rachel Mandelbaum: and used, at least in part, to address this. I also want to say that I recognize that, you know, there are other science cases besides the Cosmology ones and desk for which uniformity matters, and it could be that
Rachel Mandelbaum: for example, for galaxies, maybe the criteria are a bit different, but… but I do think that having some metrics is better than having no metrics, so I wanted to flag that, and I'll put a link in the, in the Slack
Rachel Mandelbaum: Channel for this workshop, as well, to the, to the paper.
Lynne Jones: Yeah, thank you, Rachel. I mean, you have a very good point, and I will apologize, because we did not run these metrics on the current set of simulations. We had missed including this in the automatic processing, and it turns out
Lynne Jones: when we went back to look at it, there… we… we actually… there's a, NumPy upgrade-related issue with… with…
Lynne Jones: Running it.
Lynne Jones: So, we'll… we will look at that, we will work with you guys to make sure we're fixing it in a way that is consistent with your, outputs. I think what I'm missing, and maybe this is already in the metric, and I'm just missing it, is…
Lynne Jones: I thought that the metrics indicated which simulations were better than others, and not necessarily gave the guidance that would be, if data management was setting out.
Lynne Jones: to make a uniform co-add, what is their specific goal? And maybe I just missed it, and that's, like, on my part for not understanding what the metric is telling me.
Lynne Jones: But I didn't know if there was a number on, like, this is the uniformity requirement at the end.
Rachel Mandelbaum: So, we might want to talk offline about that. I think the short answer is that
Rachel Mandelbaum: For one of the metrics, there is essentially a criterion one can apply, and, you know, we used it that way in the paper. But I do want to say that, you know, the reason that people have found it kind of slippery is, you know, is this uniform enough?
Rachel Mandelbaum: Because the answer is that when it's not uniform.
Rachel Mandelbaum: one has to try to mitigate that with, you know, like, how you do the analysis. So, you know, in principle, if it's really non-uniform, but maybe, you know, people spend, like, years putting together new analysis methods, technically, yes, they… maybe they could do cosmology, but, like.
Rachel Mandelbaum: I'm not sure that's what we should be aiming for.
Rachel Mandelbaum: So, the metrics generally are about, you know, with existing analysis methods.
Rachel Mandelbaum: you know, which still take quite a while, lots of work and validation to apply to, you know, a large imaging survey, you know, is this, is this, uniform enough? And we can talk details offline, maybe, but, I wanted to just share the…
Rachel Mandelbaum: the… the basic thought process behind, those metrics.
Lynne Jones: Sora?
Saurabh Jha: Yeah, I think, you know, I second everything Rachel just said. Just one part of it, which, and I'm really glad to hear from Leanne and Dan that, you know.
Saurabh Jha: possibilities are, you know, not really off the table. It's not exactly the message that we'd sort of internalized a while ago, and so I think that's a very positive development. I think part of it was this philosophical idea, right? If you have, you know, quote-unquote, good visits in some part of the sky.
Saurabh Jha: in time for a data release, are you going to deliberately not include them in a co-add? And I think the… there was at least a philosophical bent, at least coming from, you know, some portions of the community that said, no, you would have to include them in a data release. And so then, you know, we'd be talking about two separate coads, a uniform one and a full one.
Saurabh Jha: But, you know, I think from DESC, I think also Galaxies, as I recall, had this as their highest, priority scientifically, is that for the coads and the catalogs that are made from those coads to be as uniform as possible. And of course, you know, those first two questions, you know, what does it actually mean? What does uniformity mean? I think that's a totally valid question.
Saurabh Jha: But if it is possible to do something like that, where we know that those visits, you know, even if they're there.
Saurabh Jha: They've been sitting on disk for a few months, and now is the time for the new data release, and they're gonna be treated just as single
Saurabh Jha: visits, and they will show up in the COAD in the next data release, or in the final data release. I think that would be a huge scientific win if we could have some sort of, you know, definition of what a uniform co-ad and catalog means. That's up to the scientific community. But as that, as the main product of a data release, is something closer to uniform, I think that would be a huge scientific win. So I'm all in support
Saurabh Jha: of trying to make that, you know, technically feasible and have the science drive the, you know, technical and budgetary requirements.
Lynne Jones: Yeah, and, and…
Lynne Jones: I know Desk did do this analysis of, like, how much depth you would lose if you were just correcting for rolling cadence all the time. And it was a significant amount of depth, so it is also possible that what we end up looking at is, some kind of…
Lynne Jones: hybrid, where we do decide, okay, these will be uniform data releases, these may not, just based on the rolling cadence, but then there is this aspect of, like, we will have non-uniformity from the TOs, from the special surveys, from other things, like, if we include those stripes that Eric showed earlier.
Lynne Jones: Right, that were the engineering data.
Lynne Jones: That is very non-uniform. So, what do we do with all of this, and when do we want to,
Lynne Jones: ensure we have uniform data releases. So I think these are all really good questions, and it's…
Lynne Jones: there's… there's things we can do at Survey Strategy to make it,
Lynne Jones: make it a good place to start from, but I do think that we can't make it all uniform from survey strategy at the end of the day.
Saurabh Jha: Yeah, I agree, and I was focusing specifically on the uniform checkpoints that are, you know, in either one, you know, 14710 or 12510, you know, whatever it ends up being, those four checkpoints where we think it's going to be roughly uniform.
Lynne Jones: Yeah, I think that's a great approach. Leanne?
Leanne Guy (Rubin): Yeah, so I put my hand up to say something, and I'm going to respond, though, to a few of the points that came up. So, Saurabh, yes, you're right. In the past, there was sort of more of a… I wouldn't say it was a message, but it was maybe a bit of a reluctance for us to pivot our strategy to make uniform coeds during the construction period.
Leanne Guy (Rubin): We had, the DM Science team, had a lot of discussions with Rachel and other people on the desk about this.
Leanne Guy (Rubin): At the time, though, it wasn't so much that
Leanne Guy (Rubin): we'd rejected the idea, but just that there were other… there were other avenues to explore, with the survey, and with trying to, you know, with trying to work this into the survey and not having to make duplicate sets of data products, and not having to make two sets of data products. So we wanted to explore all those avenues first, before we actually got to the point of doing work, which would, you know, have to go into our system to make these extra data products, to curate them, to have provenance, to search
Leanne Guy (Rubin): of them, etc. And to pay the, you know, it is a non-zero cost increase to serve up an extra set of coads and do this work, so…
Leanne Guy (Rubin): it wasn't off the table, it's just we wanted to explore all the other easier options first about, about, you know, getting this into the baseline survey cadence. So that's more what that was about.
Leanne Guy (Rubin): let's see, what did you… you said it was… it would be a scientific win if we could have something like this, but it… doesn't that really depend on what science people are doing? Because uniform coads does sacrifice depth.
Leanne Guy (Rubin): And my recollection from… I forget who did the paper, someone on the desk, was it was something like 10% over 10 years, was it? Or maybe it was a bit less than that on that sort of order, I can't remember, but… I mean, you do sacrifice depth, and it is, like, not including data, so…
Leanne Guy (Rubin): I guess it doesn't… it just doesn't it depend on what science people are trying to do as to whether it's a scientific gain or not?
Saurabh Jha: Yeah, yeah, for sure. I mean, I was sort of, maybe responding maybe too eagerly to the idea that there would be two sets. One would be a full, and one would be a uniform, and so you wouldn't have… it wouldn't be such a trade-off. I think, you know, for a lot of time domain, that's going to be a lot of single-visit science anyway. We have this separate issue about nightly co-ads or monthly co-ads, and you know, like, there are all these other time scales you could consider for other science cases.
Saurabh Jha: So I didn't want to open that discussion.
Leanne Guy (Rubin): Yeah, I…
Saurabh Jha: I fully agree, yeah, different science cases will have different requirements, but, you know, for Desk and Galaxy, certainly having catalogs as uniform as possible across the sky is a big scientific…
Leanne Guy (Rubin): So if we could set up the two sets of data products, the depth-optimized COAD and the, uniform-optimized COAD.
Leanne Guy (Rubin): together. Yes, that would be a science game for everyone.
Leanne Guy (Rubin): I guess I should probably go back and try to cost that now, given that we've gotten to this point. Cost in terms of actual dollars and cost in terms of people, time, effort, you know, all the rest of it.
Leanne Guy (Rubin): Okay, so what I did put my hand up to ask about, unless, Rachel, you want to say something about what I just mentioned?
Leanne Guy (Rubin): I have a different question.
Rachel Mandelbaum: It is… it is kind of about what you… you just mentioned.
Leanne Guy (Rubin): Go ahead.
Rachel Mandelbaum: kind of the costs and the trade-offs in these different things you were just talking about. So,
Rachel Mandelbaum: It could be this isn't quite what you meant, but…
Rachel Mandelbaum: like.
Rachel Mandelbaum: when we see, some of the depth maps where, for example, the TO observations are included together with everything else, and leading to some splotchiness, you know, at year 10,
Rachel Mandelbaum: I had thought that that…
Rachel Mandelbaum: could actually be more effort than a typical co-add, because, like, some of the exposures might have different exposure times. Like, it might actually be harder to throw the TOOs in than it is to, like, exclude them, and so it's felt like an…
Rachel Mandelbaum: like, the cost trade-off isn't just that the uniform co-add is, you know.
Leanne Guy (Rubin): Yeah.
Rachel Mandelbaum: extra effort, but it could be I'm not totally…
Lynne Jones: Yeah.
Leanne Guy (Rubin): Lynn wants to say something.
Lynne Jones: A little hard to find all the things and not hit my slides, sorry.
Lynne Jones: Yes, and then there's also the question that, like, the TO observations may be at higher air mass, and they could be under, like, non-optimal conditions because the timing is the constraint. There will be visits that are not included in the coads because they don't meet quality.
Lynne Jones: constraints. So we're already going to be not including some visits into the co-ads, and so this is maybe, like, adding an extra level of intentionally excluding visits, which could otherwise have been included, I think is one way to look at it.
Lynne Jones: I am gonna say, we should move along to Desi, but we do have extra discussion time after DESI to cover any questions that have come up, throughout…
Lynne Jones: all of this area. And I also do think this is very good preparation for when we talk about the DESI stuff, because that does also introduce some non-uniformity.
Lynne Jones: But I'm gonna… if you have something to wrap up here real quick, Leanne.
Leanne Guy (Rubin): Yeah, very, very quickly, but we can come back to this discussion. You've got a good starting set of questions there. A couple of others that I'd throw into it are.
Leanne Guy (Rubin): And very importantly, how do we select which images to not include in the co-ad? And there's a whole lot of criteria. You know, we already have quality cuts on images to include in coads like seeing, for example. But, you know, does, for example, the time distribution of images throughout a co-add have any impact on the science people want to do? So that's also a really important one that I think data management cannot decide.
Leanne Guy (Rubin): And we need some sort of algorithm, we need some sort of selection process agreed by the community across all sciences as to how
Leanne Guy (Rubin): Optimally, to decide.
Leanne Guy (Rubin): you know, what are the criteria that you want to cut on, and how do you combine those criteria to satisfy all the different sciences? That's just another important question I want to throw in there.
Lynne Jones: Yeah, that…
Lynne Jones: I didn't… I didn't write that, but that is definitely a good one. How do you pick the visits?
Lynne Jones: Okay.
Lynne Jones: So,
Lynne Jones: I'm going to give a really brief overview on, what we did for the DESI simulations and how that contrasts to how we would be acquiring visits, otherwise. And then I'm going to hand this over to David, who will tell you all about the great, synergies that come out of,
Lynne Jones: What could be enabled by the… this change in the survey strategy?
Lynne Jones: So the basic idea in the request is,
Lynne Jones: to take this about 5,000 square degree area that is shown here in the yellow and purple areas, and sort of accelerate the coverage of that area to get to a depth of 30 to 40 visits in each of you, GRIZY, by the end of year 4.
Lynne Jones: And the initial, like, sort of question was, could we get to the yellow portion of that footprint by the end of year two?
Lynne Jones: On the left, what I have is the median number of visits over the sky in the baseline survey. So this is a median, and it's over…
Lynne Jones: Just without any, any, influence, and as you've seen before, rolling cadence does start to influence things after
Lynne Jones: After you… when you get to year two.
Lynne Jones: But this is… this is sort of median number of visits that we would have over the sky, and you can see
Lynne Jones: in RISY in the redder bands, we would get to that, or close to that depth at the end of year 3.
Lynne Jones: And then UNG are where we have the problem with this goal, because at year 3, we're still very far back at, like, 10 and 16 visits.
Lynne Jones: Note that our template tier has already accelerated U and G in year one, to get to the number of visits we need for the templates.
Lynne Jones: And we don't actually reach 30 visits in these bands until year 6 or year 8, if we go with a natural cadence.
Lynne Jones: So that's the primary problem. What you see, if you look at, like, our band, is that year 4, so after the… year four would be the end of the, the request, can you cover this footprint to your
Lynne Jones: to this number of visits by year 4. At year 4 in G-Band, the dizzy footprint is very obvious, because it's ahead of the rest of the sky, and at year four, in our band, it's not really very obvious.
Lynne Jones: Which just matches what we see from the number of visits per year.
Lynne Jones: The other thing to consider with this is that… within the DESE footprint.
Lynne Jones: So this is the number of… the night, and the number of visits we've acquired to that… to… up to that night. And so, in year one, we really… because we have this template tier, because we're pushing hard to get all the visits for the template, there isn't really that much of a change. Whether you're in the DESI footprint or outside the DESE footprint, we're doing the same thing in year one.
Lynne Jones: But… After… after year one,
Lynne Jones: if in the DESE simulations, we sort of switch over to, like, okay, let's try and get the, the visits for this
Lynne Jones: footprint. You can see that it, accelerates.
Lynne Jones: And so we get up to, this is a part in the year 2 footprint, so the yellow area. So you can see we get up to,
Lynne Jones: Maybe not. Okay, sorry, it's not vibe.
Lynne Jones: So we get, we get a lot of visits in, UGRIZ,
Lynne Jones: because of the being in the Desi footprint, but then after you get that number of visits, because now you're very far ahead in this part of the sky, you get very few visits for a very long time, and then eventually the rest of the sky catches up to you, and so you say… so the scheduler
Lynne Jones: Says, okay, great, now we're… we're balanced in the footprint, and we can… we should start taking visits here again.
Lynne Jones: And so you see this…
Lynne Jones: acceleration, and then a weight until you take more visits. And that's not as strong in the rider bands, because those are more on par with the rest of the sky.
Lynne Jones: And then outside of the DESI footprint.
Lynne Jones: So this is a much lower declination that's outside of that footprint. You see that you get a little bit of suppression in that period where it's… the scheduler is concentrating on DESI, and then you… you start
Lynne Jones: Recovering visits after that.
Lynne Jones: And of course, we can look at our metrics. The metrics here… so this is DESI, and we have two simulations for the DESI footprint. We…
Lynne Jones: oops, sorry, we have two simulations to date for the DESI footprint. DESI yearly does that yellow band and blue band completing by year 2 and Year 4, and the DESI 3040, actually tries to complete the whole thing by year 2, which I'm sure Desi loves.
Lynne Jones: But this does have more of an impact on,
Lynne Jones: When you'll see that delay in the footprint.
Lynne Jones: It's kind of a much stronger effect than we actually intended. So, the DESI yearly completes the request by year 2 and Year 4 on the relevant parts of that footprint.
Lynne Jones: And…
Lynne Jones: It's not clear to me that our current metrics, especially when we evaluate at the end of year 10, that they really capture, any…
Lynne Jones: potential benefits, or the, you know, full impact for this. So, I think you need, you know, we take this with a grain of salt. There certainly are some metrics which don't seem to be impacted by the end of year 10, which, as you would expect, the co-added depth
Lynne Jones: If… if you have static science that only cares about co-added depth, at the end of year 10, the co-added depths are very similar.
Lynne Jones: You didn't gain or lose by having
Lynne Jones: This reshuffling of the observation cadence.
Lynne Jones: And for some time domain, this will be an impact, and it's not obvious that when we look at the impact at the end of year 10, that we've… we've captured this properly or not.
Lynne Jones: And then I was gonna say, we do have one simulation that we've not made yet, but that we will look at, which… it's not clear it will make a huge difference, but, the idea is instead of covering
Lynne Jones: the whole footprint by year 4. Instead, we split it up into smaller chunks and let the last chunk sort of hang off the end, so it's at the end of year 5. And so.
Lynne Jones: this is not necessarily the order you would do this, but I made a little plot to give the idea. So the different colors on the right are, like, doing 1,000… about 1,000 square degrees at the end of year two, another by the end of year 3, and so then you end up with…
Lynne Jones: the final… 1,000 square degrees being completed at the end of year 10.
Lynne Jones: Five.
Lynne Jones: And… It's… it's worth noting, like, this… one thing that would happen here is that after year 3,
Lynne Jones: And maybe even during year 3, you wouldn't be accelerating any of the redder bands. So…
Lynne Jones: the redder band cadence would only be disturbed in two of these bands, but the bluer visits, like U and G, would still be disturbed in all of the band passes, and it's just…
Lynne Jones: It might not be quite as strong of an effect, but it would still be there, and you would still…
Lynne Jones: if you completed to 30 visits here, you're 5. You… oop, sorry.
Lynne Jones: You would still be sort of waiting until about,
Lynne Jones: your 7 or 8 until you started picking up more visits in this area. Unless we do something else again, like, add more visits in UNG to this part of the sky.
Lynne Jones: Which is yet another variation on the survey strategy, and it's not…
Lynne Jones: super clear, given that we've lost 10% of… lost. Since we… since we've updated our forecasts to be slightly fewer visits overall, what exactly the impact of that is?
Lynne Jones: So now I'm going to turn it over to David to tell you about all of the good things that come out of this. Oh, sorry, Kathy, you have a quick question?
Kathy Vivas: Yeah, my question, Lynn, is, how do you see…
Kathy Vivas: This strategy will combine with running cadence.
Lynne Jones: Yeah, so… so the original request was actually quite smart, because in… it doesn't…
Lynne Jones: quite line up, now we've changed the start of the survey, but in the original version of the survey strategy, which… where we had started this simulation on November, this year 2 and Year 4 did align with the rolling cadence, so it was kind of like.
Lynne Jones: Building on the rolling cadence.
Lynne Jones: When we changed the start of the survey, we changed which part, like, the part of the sky, and so there's some changes about whether we're in a…
Lynne Jones: up deck band or a down deck band, and so it doesn't quite align anymore, but that's something we could reinstate, and certainly, when you look at something like this, we could arrange these to be more smartly aligned with the rolling cadence.
Lynne Jones: All right, I do want to make sure that David gets to tell you about the good aspects here. So, I'm actually going to cut off questions, and we can come back and discuss this more afterwards.
Lynne Jones: David, is that okay? Are you…
David Schlegel: Yeah, no, that's good, yeah. If I could share also.
Lynne Jones: Oh, sorry.
David Schlegel: Yeah, let me start with Lynn. It's… yeah, it's been wonderful working with this SCOC group, very responsive, and we are trying to, you know, approach this in a way that we're making minimal impact on, group and observing.
David Schlegel: Okay,
David Schlegel: This is my one slide about what is DESI. Hopefully you've heard of DESI before. It's really the most wonderful multi-object spectrograph on the planet right now. Over the past 5 years, it's mapped 47 million galaxies, 20 million stars.
David Schlegel: This is a fully, 100% DOE-funded, operation, so we're making use of the Noir Lab, telescope at Kit Peak.
David Schlegel: And then here's just the, the basic stats on this, where it's, it's 5,000, robotic fibers.
David Schlegel: Broad wavelength range, and the, data quality is just wonderful.
David Schlegel: Partly because every observation, we get simultaneously 100 standard stars, 600 skies, so we can really produce, excellent Poisson Limited spectra.
David Schlegel: Okay, these are just, representative spectrum. These are truly representative of what the DESI main survey has been doing, because we do these dynamic exposures where we adjust
David Schlegel: the open shutter time according to seeing, sky brightness, transparency. And I do want to know what you're talking about, uniformity. We're now operating DeckCam in exactly this mode.
David Schlegel: It's not too late for Ruben, and here's some quotes here, like, what do people say about dynamic exposures? All good things. From my perspective, one of the best things is we actually get a faster survey, because on good nights, we collect about twice as much data as you might expect.
David Schlegel: So we really do a lot of catching up on the Prime nights.
David Schlegel: So, you know, you're talking about, you want to get 10% back? You could easily get 10% back.
David Schlegel: Okay, starting… actually, I think it's tonight, Desi begins mapping
David Schlegel: Further south, so we've expanded the, DESI Run 1 footprint,
David Schlegel: this is the expanded footprint for DESE, that we'll be doing over the next couple years, and I just want to note this because this new area fully overlaps, the Rubin
David Schlegel: footprint.
David Schlegel: Okay, what we're interested in enabling here, though, is what we're calling DESI Run 2.
David Schlegel: So this will be the next phase of the DESI project starting in January 2029. Most of the dark time is focused on a cosmology
David Schlegel: experiment at redshifts 2 to 3.5 over this, 5,000 square degree equatorial footprint that Lynn was just showing you, and we chose this footprint,
David Schlegel: Not because this is necessarily our best footprint, it's a little too far south for us, but again, we're trying to minimize our impact on Rubin, so we're fitting this in on the northernmost good sky that Ruben was already planning on observing.
David Schlegel: Okay, so we have a proposed data exchange between Desi and Ruben, so this is following the policies of both collaborations.
David Schlegel: Where what we're asking from Ruben is, this, early imaging when necessary over this equatorial footprint, and that's what we'll be using for target selection, for DESIRUN2. So, you know, obviously we need this
David Schlegel: before Desi run 2, just so we can select the targets. And then…
David Schlegel: In return on this data exchange, what we've put on the table is, what we call 250 effective dark hours. What that corresponds to is four and a half months
David Schlegel: of DESI time? And, you know, what can be done with four and a half months of DESI time? Well, if you're talking about the kind of data we've been collecting typically for the last five years, that would be 4 million spectra.
David Schlegel: Or one can do deeper observations, so, you know, hundreds of thousands of spectra deeper, or some combination of all of these.
David Schlegel: Another point here is that the data are fully reduced, typically by the time I'm having coffee in the morning, and I get up early, so these data, they're spooled over to NERSC during the night, and
David Schlegel: you know, we'd say typically available within 12 hours. If you're impatient, they're actually available faster than that.
David Schlegel: Okay, these observations would be coordinated, between the two projects so that we make, you know, best use of this time. Examples of what could be done that,
David Schlegel: you know, this, DESI Rubin Working Group has been looking at so far are primarily based on observations in the two deep drilling fields that are available to both telescopes.
David Schlegel: So we could go quite deep in these deep drilling fields for, PhotoZee catalogs in these footprints.
David Schlegel: And also, we could be observing transients, within a day of discovery.
David Schlegel: And in practice, we can do these in such a way that we do observations where you're doing both simultaneously. So you're observing these deep fields, you're picking up new transients, and then you accumulate signal-to-noise on fainter objects at the same time.
David Schlegel: Desi's already measured about a quarter million redshifts in these two deep drilling fields already. These footprints, they're essentially the same size as the Rubin footprints. The field of view of both instruments is about the same.
David Schlegel: This just shows you the density of targets that we've already published, and just, you know, you can see the scale here, 50 arcseconds. So very high density of targets that we've already observed.
David Schlegel: So it's kind of a down payment of what's available in these deep drilling fields.
David Schlegel: We've also demonstrated, that we can go,
David Schlegel: quite a bit deeper, so we've taken data up to about 5 hours and demonstrated that we can get Poisson-level spectroscopy. So these are objects where we've observed
David Schlegel: Well, 3 or 4 hours, 24th, 25th magnitude, spectra.
David Schlegel: So this is all published.
David Schlegel: We also have a pretty good understanding of, redshift success rate as a function of integration time, so this is also something that was just published a couple months back, so this is looking at that success rate versus exposure time. It's actually very dependent on the
David Schlegel: you know, magnitude and colors of objects. So there are parts of color space where, you know, we're already doing this right now. We're observing, for example, luminous red galaxies at redshift of 1 in 15 minutes.
David Schlegel: Just because it's a color space where we know we can very quickly get a successful redshift.
David Schlegel: Okay, timeline, so we really need the first bit of, the Rubin imaging.
David Schlegel: available prior to the start of this Desi Run 2 in January 2029. And we could…
David Schlegel: you know, it'd be great if we could have all of this prior to 2029, but we're, you know, we're willing to work with Rubin and space this out over a few years, just so that the Rubin imaging is…
David Schlegel: You know, still prior to each footprint that we're observing with DESE.
David Schlegel: And then for this, data trade, so the DESI spectroscopy, this could be provided early.
David Schlegel: And or it could be cadence throughout the DESI Run 2 going through 2034. So, in other words, what we're imagining is, early in DESI Run 2, we would do
David Schlegel: Some deep observations in these deep drilling fields, and then over the course of, you know, maybe the next 4 or 5 years.
David Schlegel: You know, do, transient follow-up in those, in those fields.
David Schlegel: Okay, and then let me just end with DESI has no plans to coordinate with any other surveys, so it really is just…
David Schlegel: The Ruben that we're trying to coordinate with us on this.
David Schlegel: Okay, so that's… That's actually all I had to show.
David Schlegel: And I should note, there are some other DESE folks on as well. We tried to not overwhelm your call, but, but who could answer questions here?
Lynne Jones: Alright.
Lynne Jones: Thank you, David. That's,
Lynne Jones: That's a… that's a great demonstration of what… what we gain from the… from… from doing this.
Lynne Jones: Yeah, let's go with questions now. Dan?
Dan Taranu: When you say you don't have plans to coordinate with other surveys, do you mean imaging surveys, or also…
Dan Taranu: upcoming spectroscopics, I'm thinking of… Subaru PFS is definitely gonna target deep fields.
Dan Taranu: Foremost, I guess, is not really overlapping, but,
Dan Taranu: And I don't think they've asked for anything specific, but could you not also make the argument, well, we should also prioritize covering, like, the waves?
Dan Taranu: foremost.
Dan Taranu: Fields in a similar fashion.
David Schlegel: Sorry, that Desi should be coordinating with Waves, or what…
Dan Taranu: No, so, for the first part.
Dan Taranu: Are you coordinating at all with Subaru PFS?
Dan Taranu: In the deep drilling fields, for example.
David Schlegel: Yeah, so we don't have any coordination. So the only other coordination we have is we are obtaining other imaging that we need for DESI Run 2 from several different telescopes. We're running those imaging surveys within DESE. These are medium-band imaging surveys.
David Schlegel: So that is our other coordination. That's just internal, as For other spectroscopic projects.
David Schlegel: we're really far ahead on DESI, and it's… it's kind of…
David Schlegel: the question gets turned on its head of, you know, these other projects shouldn't repeat what DESI has already done.
Lynne Jones: Rachel?
Rachel Mandelbaum: Yeah, I have a comment and a question, if that's okay?
Rachel Mandelbaum: So the, the comment,
Rachel Mandelbaum: is more on the earlier part of the presentation. There was a statement that the metrics… you know.
Rachel Mandelbaum: For impact of… of…
Rachel Mandelbaum: these strategies on the science, may not capture, you know, the full impact. They may not be designed for that. I want to actually strengthen that to say that several of the desk metrics definitely
Rachel Mandelbaum: Do not capture the impact of this change in strategy, because they make assumptions about
Rachel Mandelbaum: the coverage in each band tracking each other in a way that these simulations violate, so I think it's a stronger statement that
Rachel Mandelbaum: you know, we'll likely need to update the metrics. But then, to ask my actual question,
Rachel Mandelbaum: One other timeline question that I wanted to understand is, when would a decision have to be made about doing this? Like, at what point would the Rubin strategy need to start to deviate from what it would otherwise be? Because that feels like a pretty important and relevant factor to understand.
Lynne Jones: Yeah, that is a great question.
Lynne Jones: I don't actually have a super good answer for you, except for the fact that I would say.
Lynne Jones: when we did run these simulations with the DESI survey, like, the DESI 3040 and the DESI yearly.
Lynne Jones: There was no change inside of year one, because the template tier, was put in at a higher priority.
Lynne Jones: I'm assuming, that's right. Is that right, Peter?
Peter Yoachim: Yep, that's right.
Lynne Jones: Yeah, so the templates being a higher priority meant that the templates were trying to get their visits, and because the templates take up most of year one, it just basically means there's no…
Lynne Jones: actual impact. So yes, we should decide as soon as possible, in practice, if our priority is actually first getting templates, which I think it should be.
Lynne Jones: But that's my opinion, of course. But then, then… then we have, then we have some time in practice.
Lynne Jones: we should definitely decide before… I mean, ideally, we decide as soon as possible, because it makes a difference for funding, for various things, right? But,
Lynne Jones: In practice, if we…
Lynne Jones: had a strategy in place, like, a decision in place 6 months from now, I think that that would… it would not really impact what we're actually doing on Sky.
Rachel Mandelbaum: Yeah, and to be clear, it's not like I wanted to push to wait until the latest possible moment. It was more trying to understand, is this, like, a right now decision, or, you know, we should do this within a couple of months, and the time will fly, so,
Rachel Mandelbaum: Thank you for clarifying.
David Schlegel: Yeah, I mean, let me just say, from the DESI side, though, we're eager to get to a decision point
David Schlegel: quickly, even if this isn't perturbing Rubin observations for another year. And that's just, you know, you can imagine that this could blow up the DESE Run 2
David Schlegel: Planning.
Lynne Jones: Yeah, definitely. That's good.
Lynne Jones: Roberto?
Roberto Assef: Yeah, so, there were… we discussed this a little bit on the impact on the AGN science collaboration in the latest telecom, and there were a couple of questions that, so I…
Roberto Assef: that I think were very interesting that came up. So, one was, is the DESE2 footprint fixed?
Roberto Assef: And if so, do you know how much does it overlap with Euro Cedar, at least the German part of Eurosida?
David Schlegel: Oh, that's a good question. I don't have that right in front of me, but maybe…
David Schlegel: Maybe one of my collaborators can figure this out quickly, but it's, I mean, you can look at it, it must be a fair amount of overlap, because we're…
David Schlegel: you know, we're overlapping LSST, which has a fair amount of overlap.
David Schlegel: So sorry, I don't pull that offhand.
Roberto Assef: That's fine. And the other question was,
Roberto Assef: So, right, currently the offer, right, is for the exchange to 250 dark time hours. One of the questions was, would it be instead, or, you know, with some partition, access to all the DES spectra taking over the…
Roberto Assef: LSSD footprint.
David Schlegel: So all of the DESI spectra, they are made public on some timescale, and in fact, the DESI DR1 release, which goes back a year now, most of that is actually over the Rubin footprint, in fact, just because we started
David Schlegel: Or it must be more than half, because we started kind of equatorial with, DESI. So we… we've… we've not discussed that. I… I…
David Schlegel: The DESE director's on, maybe he would like to respond to that.
David Schlegel: Michael?
Michael Levi: I'm sorry, what was the question?
David Schlegel: Oh.
Michael Levi: No, sorry.
David Schlegel: Do you want to just repeat your question?
Roberto Assef: Sure, sure. So, the question that came up was, would it be, would…
Roberto Assef: could there be access to the private DESE data, DESE2 data, on the regions that overlap the LSST footprint?
Michael Levi: Well, the 250 hours that we're talking about, I think the answer is yes, because you would be defining what those are.
Roberto Assef: Oh, right, but not… okay.
Roberto Assef: Okay, so I think the question was, instead of the 250 hours, access to all the spectra.
Roberto Assef: But, I mean, I see what you mean, right? So we could coordinate to make sure that it's reconciled.
Michael Levi: So, no, this is not an offer to open up the…
Michael Levi: proprietary, all of the proprietary, DESI data, I mean, that would be…
Michael Levi: It's possible for, you know, you as an individual
Michael Levi: to come in to DESE as an external collaborator with a particular scientific project to work with one of our other collaborators within DESE, to work with us on a topic where then you would have access to some of that information.
Michael Levi: So that's technically possible. You know, a broader… if you're asking a question, well, what about a collaboration between
Michael Levi: Desi and E. Rosita, you know, that's probably out of context for this meeting, but…
Roberto Assef: Yeah, absolutely.
Michael Levi: So, I think that's, you know, it would be a different format than what we're talking about here.
Roberto Assef: Okay. Thank you.
Lynne Jones: Toronto?
Saurabh Jha: Yeah, David, I just wanted to understand a little better, the DESI Run 2 needs, and maybe this is probably in some document, and I apologize if I have not read the appropriate document. But the example spectra you showed, like, even the long exposure ones, were getting down to, you know, 23rd, 24th magnitude, and I guess I understand that the DESI Run 2 is targeting somewhat higher redshift, so maybe, maybe slightly fainter is the goal, but…
Saurabh Jha: That was a surprising number a little bit to me, because if you're requesting 4-year-ish Rubin depth, that seems a lot deeper. So, you know, even in one visit, you're getting to close to 24th magnitude in U, 24.5 in G, so it feels like in a few visits, I know maybe you need signal and noise of 10 or 50 in the images, so maybe you just need very high,
Saurabh Jha: fidelity photometry, but it seems like in 4 years of Rubin, you get down to, like, 26th magnitude, and so is it possible that you can do the target selection with less data from Rubin?
David Schlegel: Yeah, we started with a request that was even deeper, and then dialed that back after some studies. The, the reason is, you know, these are the high-rich
David Schlegel: galaxies for which we can most efficiently and quickly, get a redshift. So they're not typical redshift 3 galaxies, they're the ones that we can
David Schlegel: get a redshift up. So the, primarily, you should think of these as the U-dropout galaxies, where if you want an efficient selection of… it's just the brightest U-dropout galaxies, you need about these 30 visit depths.
David Schlegel: The other objects that we're looking at, it's,
David Schlegel: It's these Lyman Alpha emitters, where their broadband photometry is really quite faint, because they're objects where we've picked them up as a 25th magnitude object.
David Schlegel: In medium band imaging, and then the broadband depth is deeper than that, but we still want the broadband color to distinguish those from interlopers.
David Schlegel: So, you know, we've looked pretty carefully at these depth requirements.
Julien Guy: Maybe to complement that, we, we have run target selection with random forest, assuming different depths of LSST.
Julien Guy: And, for four-year depths, which is equivalent to what we're discussing here.
Julien Guy: we get a purity of only, 55%. So, we really need that depth to,
Julien Guy: To get an efficient survey afterwards.
Saurabh Jha: Thanks.
Lynne Jones: John?
John Gizis: Oh, sorry, I didn't realize my camera was off.
John Gizis: So I guess, so my science case, it doesn't make any difference in the long run, you know, when you move the filters around, particularly the blue filters. But I do want to ask, because I've spent a lot of time lately hearing about Roman, it seems like this preferentially moves U and G observations out of Roman overlap.
John Gizis: In the upcoming years, and since we now believe it will really launch in August.
John Gizis: It seems like this is a very high impact on the American astronomical community, to lose
John Gizis: that potential science case, where presumably Roman can't observe U and G, so it was really adding something to the…
John Gizis: How will the SCOC, I don't think it's a question for David, address, you know, those sorts of concerns? What the views of other, communities that aren't necessarily LSST-centric?
John Gizis: dude.
John Gizis: So it's a question to raise a big issue, I guess.
Lynne Jones: So…
Lynne Jones: I don't think this is a question for me to answer, as I'm a ex-officio member of the SEOC. However, Fed is not actually, with us today, unfortunately, due to personal information.
Zeljko: in Ubers, so there may be too much background noise, I apologize.
Lynne Jones: There we go.
Zeljko: But, as Lynn said, we want SEOC to focus on scientific impact and cadence change.
Zeljko: And other aspects of this proposal will be considered elsewhere. There are, of course, many other aspects to it.
Zeljko: SCOC is in the best position to assess what would be impacts on MSSD science cases if we followed the strategy that we already simulated in response to this.
Zeljko: That is the main goal for this committee.
Zeljko: Those other aspects that are valid and that we need to consider, they will be addressed elsewhere.
John Gizis: Yeah, so overlap with external,
John Gizis: surveys is out of bounds, but a purely LSST consideration of the impact.
John Gizis: Is… Right.
John Gizis: That's very helpful for us to understand. Thank you so much.
Zeljko: Okay, sorry for the noise.
Lynne Jones: I think it is… it is certainly a goal in general of the SELC to consider as many aspects as possible of
Lynne Jones: of survey strategy changes as they come up. There is always, of course, the limitation that,
Lynne Jones: our knowledge within the project and our knowledge from… coming from the science collaborations will be imperfect. And so, if this comes up through the science collaborations, that they say, oh, you know, one of the…
Lynne Jones: things that I'm now concerned about is, like, how LSST survey coverage is… is going to impact my other science. It's true, that's a little bit,
Lynne Jones: It's a bit of a question that's, like, out of bounds for what the LSSD is, because the priority of the SEOC has to remain, the LSSD science, but it certainly is something that they can… can think about.
Lynne Jones: Nobody's going to say that you… they couldn't consider something.
Lynne Jones: But yeah, it… there are always…
Lynne Jones: There are always, unfortunately, things that we're gonna miss, of course, but…
Lynne Jones: at the end of the day, we are here to try to make the best LSST.
Lynne Jones: And, let's see.
Lynne Jones: We have… we do have some more time here for questions. We can talk about, Desi, and we can talk about other questions from other… other parts of the… the session. I do want to make sure, if we have things we didn't want to circle back to from the rest of the…
Lynne Jones: the workshop, that we… that we cover those as well. But… so damn.
Dan Taranu: Yeah, sorry, I had a lingering question from before, and I…
Dan Taranu: Missed the discussion about the DDFs earlier, but looked at… looked at the slides.
Dan Taranu: Do you have a lot of metrics for specifically optimizing the radial dithering in the… or translational dithers in the DDFs? Is it basically trading off the area that gets full coverage versus the larger area that might get less coverage on the outer skirts, and…
Dan Taranu: Does that one failed detector that's very near the edge of the focal plane, but not quite, does that change things at all, or…
Lynne Jones: Okay, so this is… This is a good question that touches along a lot of,
Lynne Jones: On a particular math aspect as well.
Lynne Jones: With math, what we do is,
Lynne Jones: We do imprint the camera footprint when we're calculating our metrics.
Lynne Jones: We don't necessarily have the resolution to really say this is the…
Lynne Jones: We don't usually run our metrics at super high resolution, so we don't… we represent the chip gap statistically, but not necessarily exactly, for example.
Lynne Jones: That said, we should take our camera footprint and take out the… because we do have the chip gaps in our camera footprint. We haven't taken out the missing detector, and we should do that, and that's a very good point.
Lynne Jones: So I don't know if the missing detector makes a difference or not.
Lynne Jones: The metrics we have for the deep drilling fields and the dithering really do just, as you say, look at the trades between as you get wider.
Lynne Jones: bigger dithers, you decrease the cadence, so we do have things that are looking at, like, what is the… essentially, what is the cadence within the deep drilling fields, and you do, decrease the coated depth.
Lynne Jones: Because you're spreading that over more area. I don't know specifically we look at, like, what happens with the roll-off, but as you… towards the edges of the dinner, but we,
Lynne Jones: We definitely… that is the primary driver for having smaller jitters, is you get a better cadence, and you get deeper depths.
Lynne Jones: That's a problem.
Saurabh Jha: Yeah, just to follow up on that, so yeah, it's true that the metrics don't always capture that for the DDFs, but this is something we put in the DDF task force of the SCOC we posed to the science collaborations, and basically, you know, you can imagine you have this umbra of the DDF, and then you have this penumbra, which gets bigger the more you dither, and you could imagine some science cases would like, you know, basically you're making your effective area of a deep drilling field just bigger.
Saurabh Jha: But it turns out, in terms of, like, external synergies for the DDFs and, like, you know, space-based imaging and stuff, that the Rubin footprint is already big.
Saurabh Jha: Right? Compared to the size of these fields. And so, increasing that area was not generally a science win across the board for the science collaborations. And so, from the science collaborations point of view, keeping that as small as possible, like maybe just dithering over chip gaps, that would be the ideal. And then that would improve the cadence, just as Lynn said, and get the highest co-added depth.
Saurabh Jha: So basically, the dithering we would want to do with EDFs is as little as possible that DM says is okay.
Lynne Jones: And it does seem like we've, moved on to other questions, so I'm gonna make sure we thank all of the DESI people for joining us. Of course, like, please stay on so that in case we come back to more DESI questions, but thank you for…
Lynne Jones: For your presentation and joining us.
Lynne Jones: Neal?
William Nielsen Brandt: Yeah, sorry, I just did want to ask one other just point of clarification, just to be sure I didn't miss something along the way. So, if the DESE plan were implemented, what would you anticipate the effects upon the deep drilling fields, if anything, material, to be?
William Nielsen Brandt: I presume, we would still maintain truly excellent time domain coverage in any of the deep drilling fields that are also in that footprint.
William Nielsen Brandt: That would… that's obviously very important, and it's key to the nature of the deep drilling field, you know, in terms of the U and G bands.
William Nielsen Brandt: But are there other effects you could anticipate there that we should be thinking about?
Lynne Jones: I have.
David Schlegel: Let me jump in for a sec. I mean, I don't see why this would affect Ruben at all, but we do have the opportunity on the DESI side. We don't have any other cadencing requirements or anything like that, so if, you know, if the request
David Schlegel: for this data exchange from DESE said, hey, you know, we really want to do the DESI follow-up on the following days, or, you know, just
David Schlegel: you know, more of a triggered response, you know, we could do that, so that… I think we'd certainly see that on the DESE side.
William Nielsen Brandt: Thanks. Yes, I'm mostly interested in the Rubin side here.
William Nielsen Brandt: So, Lynn, did you have any insights there? I mean.
Lynne Jones: So it's true, I haven't specifically looked to see in the Desi Sims, did we change the deep drilling coverage? However, I would guess we did not, and so Rob is shaking his head.
Lynne Jones: Because of the fact that, the deep drilling fields are programmed separately, and they're in a higher tier, so they should…
Lynne Jones: continue as, as previously planned, and we didn't, like, decrease the DDF coverage because we were getting this other coverage as well.
Lynne Jones: That's wrong?
William Nielsen Brandt: Okay.
Saurabh Jha: Yeah, I was gonna say the same thing, that the DFs are not affected. It's really the WFD visits in that northern part of the sky that get shipped.
William Nielsen Brandt: Very good. I just wanted to be sure there wasn't some second-order effect that I wasn't appreciating, but thank you. Okay.
Lynne Jones: No, in fact, it's usually the other way around, that the DDFs affect the coverage of the rest of the sky, because they are in this higher priority tier.
Lynne Jones: And this was, for example, one of the reasons we had to move the ultra-deep season of EDFS out of year one, because we were already a little stretched thin in that part of the sky.
Lynne Jones: And so… and with, like, assuming a higher fault rate and lower efficiency at the start of the survey, it made things a little bit too tight.
Lynne Jones: So… Yeah, the deep drilling fields are… Or… Very strongly,
Lynne Jones: defined, I guess, is one way to put it.
Lynne Jones: All right, do we have other questions? We have about… 10 more minutes.
Lynne Jones: Yeah, Rachel.
Rachel Mandelbaum: Yeah, so this is a question for…
Rachel Mandelbaum: Rubin Leadership, so looking at who's on the call, maybe Phil or Jelco? So… For the,
Rachel Mandelbaum: Does the observing time that would come out of this exchange? Like, does Rubin leadership have an idea for a model for how to allocate that to maximize the benefit to the Rubin community?
Phil Marshall (SLAC/Rubin): I would say… Not yet, but we have some…
Phil Marshall (SLAC/Rubin): I've already done some thinking about,
Phil Marshall (SLAC/Rubin): other in-kind contributions of telescope time and so on. So…
Phil Marshall (SLAC/Rubin): we would look at what we've done there with the, you know, contributions from Subaru and other places, and think about whether we could
Phil Marshall (SLAC/Rubin): treat this, you know, the DESI time or the DESI data in a similar way. I mean, we're trying to be…
Phil Marshall (SLAC/Rubin): even-handed in our support of the RSST science community, and YLAB has, you know, open skies policies that we're trying to observe as well. So, we would try and make sure that the…
Phil Marshall (SLAC/Rubin): that the benefits of any data exchange with DESI were… were shared around.
Phil Marshall (SLAC/Rubin): it may well be that some parts of the RSSD science community would benefit more from this than others.
Phil Marshall (SLAC/Rubin): and… You know, we would…
Phil Marshall (SLAC/Rubin): we would try and take that into account as well, but, I mean, there would… there would be something significant to work out here in terms of how best to use these data. I mean, the…
Phil Marshall (SLAC/Rubin): I think… I suppose there's some hope that,
Phil Marshall (SLAC/Rubin): that there could be simple ways, and I think David was highlighting these in his slides, simple ways for… for using DESI spectra, kind of synoptically, similar to the LSST survey itself, so looking for applications that already serve multiple science cases, and PhotoZ training is one of those, for example.
Nathalie Palanque-Delabrouille: Yeah, so I'm just reiterating what David showed, but with just a one-slight summary of topics that we've discussed for collaboration between DESI, Spectra, and LSST, and in the deep billing fields in particular, we can really contribute to the DSST science, the Rubin science.
Nathalie Palanque-Delabrouille: By providing the spectra of live transients, or a supernovae host.
Nathalie Palanque-Delabrouille: And for the weak lensing science, we can also significantly support that science by providing the very deep spectra for, photocalibration. We've, tested, up to a few hours, but we've shown that with the instrumentation upgrade that we're planning for this second phase of DESI, we could actually, stack up to 80
Nathalie Palanque-Delabrouille: hours of Spectra, and so that would really provide very deep,
Nathalie Palanque-Delabrouille: spectra for calibration of photos Zs, and so this is an example of what we've been discussing so far, but of course, this is not set in stone, and we can definitely continue to identify what would be the best, outcome of this data exchange.
Phil Marshall (SLAC/Rubin): Thanks, Natalie.
Lynne Jones: Wow.
Lynne Jones: I think we've, we've… Covered a lot, and we've had a lot to think about.
Lynne Jones: I don't see any more questions or hands coming up.
Lynne Jones: So…
Lynne Jones: I'm going to say thank you all very much for coming and sharing and, talking with us today.
Lynne Jones: And all of the… all of you community members and all of the SCOC members, thank you, as well. It's been, a lot to go through and to talk about, and I hope we all have some good ideas of how the survey will start.
Lynne Jones: What we're doing in terms of the strategy, and where we might be going for the next year or two, as well as over the 10 years of the survey.
Lynne Jones: you know what, I think we can be done. We can have a few minutes back out of your day, and thank you all for coming. We do have Monday coming up, and, I'm…
Lynne Jones: hoping that Fed will be back to, help us coordinate for that, but otherwise, we'll be reaching out to the science collaborations to organize feedback. Monday is a little bit more for
Lynne Jones: feedback from you in the science collaborations to the SEOC.
Lynne Jones: So, thanks very much.
Lynne Jones: We'll talk to you on Monday.
Phil Marshall (SLAC/Rubin): Excellent.