Results!

We’ve had 3 days of learning and sprinting. Here are some of the key results from the meeting.

Andy Rivkin – thoughts about filters for LSST asteroid taxonomy. If you only have 3 out of 4 filters; gri is pretty good if precision is high; grz is okay on average; Sloan filters are not the same as LSST

Josef Durech – experimented with code to get shapes, spin poles, and colors. Took ATLAS data (3 years of data) and took only 50 points (SNR>30) in 2 colors covering a range of phase angles, recovered correct period, color, shape, and spin pole.

Mario Juric – developed updated scheme (data model) for LSST Solar System Data Products and getting reading for DM (Data Management) to implement. For first year, could assume same phase curve slope for all colors. Collaboration Workspace worked well (LSST stack installed already for SSSC Spring Jupyter Hub).

Kat Volk – Toy model of resonant TNO populations and how the North Ecliptic Spur to work. For 2:1 resonance, leading and trailing islands. In baseline sims, 300-500 detected. Without NES, lose much more in leading island than in trailing island; e.g., detections down to 420 and 120. This is ~best case resonance, other resonances will be even more strongly unbalanced.

David Gerdes – DECam Solar System Survey ideas for survey proposal due. Focused on science, but LSST testbed too. Deep TNO survey (26 maybe 26.5 with shift-and-stack), focus on Neptune Trojans; 300 colors / light curves for MBAs; small end size distribution. For LSST, this helps think about a mini deep drilling survey, light curves. Next steps, gather collaborators.

Wes Fraser, Audrey Thirouin, Darin Ragozzine – colors and light curves metric; hardest part is to get correct period. Use LSST cadence from OpSim and power spectrum to make sure that there is a significant peak that matches the period. If there are 30 or more points in given apparition, then the period can usually be recovered. To get resolved light-curve colors, get 30 colors in 2 filters. Number of KBOs that get light curves and colors is about 90% (H=4) on the bright end and 0% at H=8.

Chad Trujillo – outer solar system deep fields; 10, 100, or 1000 square degrees. 2 x 600s images (reaching 26.7). Factor increase of t^(q-1)/4 = ~100 in number. Will post online so others can help. Super-NES could discover ~100 times as many TNOs!

Henry Hsieh – Read the Solar System Roadmap! White paper is coming up that organizes all the things we want. Lays the groundwork for future proposals by identifying software needs and priorities in detail.

Mike Kelley – Cometary Metrics. Added cometary magnitudes; some simulated LSST observations. Jupyter Notebook. One path forward, looking for “blind spots” and “sweet spots” in orbital element space. Goal is to get LSST completeness limits for various cometary populations and writing this up in a papers. Looking at whether NES is important for main belt comets. Looking at Asteroids in Cometary Orbits.

Michael Aye – plans on creating conda package for OpenOrb

Michael Mommert – python OpenOrb, get more information for metrics (e.g., heliocentric longitude, latitude, true anomaly, etc.)

Bryce Bolin – working with Lynne and Ed Lu, simulating detection of impacting asteroids with LSST; with Josef Durech adding real shape information to generate more realistic lightcurves

Thank you to the LSST Corporation and B612 Foundation for supporting and making the 1st LSST Solar System Readiness Sprint possible.

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SSSC Sprint Liveblog – SSSC Update by Schwamb and Trilling

Meg Schwamb and David Trilling are Solar System Science Collaboration Co-Chairs.

LSST will produce incredible solar system science and we need to prepare and support our science. We’ve already provided our SSSC Science Roadmap.

Please join and participate in the working groups, currently mostly by email. For example, polls, which currently haven’t had as much participation as we would like.

Also working on white papers (due Nov) to request Northern Ecliptic Spur and other cadence and survey conditions. Here are white paper ideas and putative leaders so far:

  1. Deep Drilling Fields (Trillling)
  2. Northern Ecliptic Spur (Schwamb)
  3. Defense of two observations per field per night (and in what filters)
  4. Two snaps per visit or one?
  5. Rolling cadence?

Goal: get together and spend 3 days making something or writing something that helps us prepare for LSST. You can lead and pitch a project today.

Meg gave some great tips about how to work together and act during the Sprint. Thanks Meg for all your hard work in organizing the Sprint!

SSSC Sprint Liveblog – Lynne Jones

Lynne Jones (UW/DIRAC/LSST) – OpSim Simulations & Small Body Metrics (with MAF = Metrics Analysis Framework)

OpSim generates simulated pointing histories under realistic conditions; it will eventually be the actual LSST scheduler. Pointing history includes 5-sigma depth, seeing, filter, etc. Generating one OpSim output is ~50 CPU-hours.

sims_movingObjects takes a set of orbits/objects and an output from OpSim to generate observations LSST would acquire (passes along OpSim results). Reports SNR (including trailing losses) for a given H. Current status: it is there and it works, but it may not be efficient. Generating 2000 objects (single thread) is ~4 CPU-hours.

Metrics Analysis Framework (MAF) analyses these observations and applies a “metric” to all observations of the same object. Can separate size and orbit properties, as if cloning same orbit over a range of H magnitudes; can also keep H-orbit correlations if you want. For a discovery metric, for example, ~0.1 CPU-hours.

Current metrics (see Cahpter 3 of Community Observing Strategy Evaluation Paper (COSEP) include: discovery (time of first discovery, number of opportunities for discovery – summarized as completeness as a function of H over population); number of observations or total arc length; light curve inversion; color determination.; likelihood of detecting activity for a given object assuming random distribution of activity times. All of these can be summarized as fraction of population as a function of H.

Potential metrics: number of objects lost; accuracy of orbital parameters as a function of time; does an object receive enough observations to determine rotation period / spin pole / phase curve? Will an object need followup on any given night? Improvements on exiting metrics.

You can calculate metrics over H or over orbital properties, etc. These metrics define performance of a given survey strategy in a quantitative way, allowing for quantitative decision making in cadence and other calculations. [Need also a metric to sceince conversion, e.g., metric X going above level Y enables science Z.] Survey Strategy White Papers are going to explore this in detail; many questions for solar system. Snaps (2x15s vs. 1x30s), Wide-Fast-Deep survey cadence? North Ecliptic Spur (NES) footprint and cadence? Pairs in same or different filters? Filter selection criteria? Other mini surveys for solar system? [For reference, a single visit gets several thousand asteroids in a single visit and pointing at the ecliptic.]

The Survey Strategy Committee is going to review all these and provide a recommendation for the initial survey strategy. As the survey progresses, things could be re-evaluated. COSEP is living document, but White Papers are for our best guesses now.

For us to do: be familiar with all these things and contribute. Contribute metrics to sims_maf_contrib. Add sections to COSEP to include supporting text. Defend your science!

So great to have Lynne’s expertise!

 

SSSC Sprint Liveblog – Mario Juric

Mario Juric – “LSST Solar System Processing Product Owner” for the LSST Solar System Processing Team.

LSST provides 3 types of products to enable Solar System science: Prompt Products = Real-time (60 s) and Daily Catalog; Data Release Orbit Catalog (annual). Data Products Definition Document LSC-163. Daily Catalog is best estimate at that time. Annual Data Release Catalog is like a very well done, self-consistent, single-software, best-result Daily Catalog; will reprocess all the previous data. For example, the Annual Data Release is the most convenient for survey completeness analyses.

Real-time alerts are not precision science, but to enable very rapid follow-up. DIASources (= Difference Image Analysis Sources) are associated with Solar System Objects when known. Every DIASource will be fit with a trailed source model. Comparing PSF models to trailed models should be an excellent method for identifying trailed objects.

Daily (Orbit) Catalog. Why daily? So that LSST can identify objects in tomorrow’s data. Product is orbits, physical properties (H,G), and other things we can study here at the Sprint. The goal is for this catalog to be as complete as possible and cross-matched to external catalogs. This is still to enable rapid follow-up, so software will be updated as needed (e.g., bug fixes). It is not designed for all goals. GAIA catalog. Not clear how the template process is going to work in the early part (first year) of analysis.

Data Release (Annual) Catalog – best for precision photometry and astrometry since computed with self-consistent software and best knowledge of calibration. Note that this will include LSST-data only (not past MPC data).

Current Plan: After observing, find tracklets, run MOPS, recompute catalog (including merging and precovery), make updated SSObject table (“LSSTORB”), and predict for next night. But, currently don’t have firm plan to cross-reference the LSST catalog to the MPC catalog.

New plan would be to send new discoveries to MPC, they produce MPCORB, and then LSST uses MPCORB for its next night predictions. This is a proposal that will probably be detailed by October and approved by the end of the year or so.

Some discussion on possible risks with relying on the MPC, but Mario points out that there are many “third-party risks” in LSST and that there will be back-up plans.

Single tracklets (or even doublets) are, in the initial plan, not reported anywhere. When MPC is able to handle tracklets, those can be passed too.

Team is Joachim Moeyens (40%), Siegfried Eggl (100%), Mario Juric (25%). Lynne Jones and Eric Bellm help. This time is just for solar system; this doesn’t include the other LSST resources which provide all the undergirding.

Glad Mario is on our team!

 

Ready, Set, SSSC Sprint! – Liveblog

Hello SSSC! Meg has asked me to liveblog the SSSC Sprint today (Tues, 7/10), as we get started. About 20 of us have assembled and we’ve started getting some background from LSST.

John Swinbank, Deputy Project Manager, LSST Data Management
“LSST is not just a telescope, it is an integrated survey system.”

It’s exciting to see LSST coming together physically! John’s showing some good pictures and great updates. For example, the Auxiliary Telescope, the nearby 1.2-m telescope used to help characterize atmospheric absorption, has first light and early data processing happening in the next year (mid 2019).

LSST Camera is the size of a small car: 3.2 gigpixels, 2 second readout, 0.2″ pixels. Focal plane is 63 cm diameter of 189 separate CCDs into 21 3×3 rafts. (Kinda similar to my other favorite, the Kepler Space Telescope!) Each raft is independent. 10 rafts have already been assembled and accepted, all done by January 2019. Rafts can be tested and commissioned independently on telescope, starting mid-2019. Commissioning camera will include science verification surveys, but possibly not (publishable) science.

Data Management (DM) System turns raw data into prompt (e.g. “alert”) and data release data products. 11 Data Releases in 10 years (first one after 6 months). (Note that, at the annual data release, all the prompt products are reproduced, just without alerts.) LSST Science Platform designed to let scientists handle the mountain of data. Includes a portal (queries, etc.), Jupyter-style notebooks to process LSST data yourself, and web API for Data Access Centers based on Virtual Observatory (VO) standards.

All DM code is explicitly open-source and scientists are encouraged to use it. The image processing problem is far more complex than other surveys: many different shapes, blended, etc.

LSE-163 describes all the DM Pipelines and Products. I’m impressed with how well thought out it is.

Current status: none of the pipelines are complete, but many parts of the system are quite usable. Primitives and Algorithms – a rich collection of high-performance tools for working with astronomical data you can pick up and use today. Data Release Processing and Alerts, Alert Distribution – working on test data (Hyper Suprime-Came, DECam, ZTF). Some MOPS is available.

DM also manages the Petascale computing facilities doing data processsing. Science Platform coming together, being used someone.

LSST development and construction is on track and feels like it is accelerating and real!

Public Event: July 10th – A Special Solar System Edition of Astronomy on Tap Seattle

2018_07_10

We’re pleased to announce with the help of the Large Synoptic Survey Telecope (LSST) Corporation’s Enabling Science Grant, the LSST Solar System Science Collaboration (SSSC) will be holding a public event as part of our 1st LSST Solar System Sprint in July.  We’ve partnered with Astronomy on Tap: Seattle and Peddler Brewing Company for a special edition of Astronomy on Tap: Seattle. This Solar System Extravaganza will be four public talks:

Location: Peddler Brewing Company, 1514 NW Leary Way Seattle, WA 98107

When: Tuesday July 10, 2018 – 8-10 pm

Cost: Free Entry

Talks:

David Trilling (Northern Arizona University): The Large Synoptic Survey Telescope: What it is and why you should care

Michael Mommert (Lowell Observatory):  It’s an asteroid. It’s a comet. It’s complicated…

Kat Volk (University of Arizona): Tales from the Outer Solar System

Andy Rivkin (Johns Hopkins University/Applied Physics Laboratory): A Crash Course in Asteroid Defense

And a special thanks to Peddler Brewing Company for opening on a special day for this event and to Brett Morris and Nicole Sanchez, Astronomy on Tap: Seattle organizers, for making this possible.

See you in Seattle!

Why I’m excited about what LSST will do for comet science

Today we have a blog from Matthew Knight.  Matthew Knight is a research scientist at the University of Maryland. He has observed comets on hundreds of nights at UV (ultraviolet), optical, and IR (infrared) wavelengths from the ground and with space-based observatories.

For a field that dates back more than 2000 years and has featured successful spacecraft visits to five comets since 2001, there is still quite a bit to learn in comet science.

Much of what we know about comets comes from observations of the occasional bright and spectacular ones – like Hale-Bopp and Halley – that keep astronomers at telescopes for months on end and percolate into the realm of pop culture. Arriving about once a decade, such “great comets” are often bright enough to be studied over a much longer range of time and distance than other comets, and they often permit observations using new and unusual techniques.

Much of the rest of our knowledge comes from the so-called “Jupiter Family Comets” (JFCs), comets with short orbital periods, typically less than 10 years. There are a few hundred known JFCs, and every year or so one approaches Earth favorably enough to be studied in detail. This year’s close approacher is 46P/Wirtanen, while last year featured two, 41P/Tuttle-Giacobini-Kresak and 45P/Honda-Mrkos-Pajdusakova.

Where our knowledge is most fuzzy – and where LSST will excel – is the faintest, and hardest to see comets. These may be faint for a variety of reasons: being far from the Sun, being very small, or having already lost their frozen gases, to name of few. They are difficult or impossible for many telescopes to observe, and they certainly are not studied as regularly or in the level of detail as their brighter, better known brethren.

LSST will allow us, for the first time, to survey huge numbers of the faintest comets. What is more, LSST will reimage these comets every few days, over and over. This will revolutionize our knowledge of the comet population as well as our understanding of how they (and the solar system) evolve.

New discoveries – LSST is predicted to discover ~10,000 comets over its 10-year lifetime. By comparison, about ~5000 comets have been discovered to date, and of these, more than 3000 are tiny fragments of broken up comets seen only by the SOHO spacecraft as they are destroyed close to the Sun. These new discoveries will yield far more robust statistics about the number and variety of comets currently in the Solar System. After a lot of computer modeling, this will greatly improve our understanding of the population of “cometesimals” in the disc of material out of which the planets formed around our proto-Sun 4.6 billion years ago.

LSST will quickly balloon the numbers of all types of comets, from the traditional classes (short period JFCs and long period comets arriving from the Kuiper Belt or the Oort Cloud) to more exotic and confounding recent discoveries like “active asteroids” (apparently cometary bodies on asteroidal orbits), “dead comets” (weakly active or inactive bodies on cometary orbits), and “centaurs” (comet-like objects thought to be migrating in from the Kuiper Belt and currently on nearly-circular orbits between Jupiter and Neptune). Hopefully, it will also detect more interstellar objects like 1I/‘Oumuamua and maybe even things we never imagined exist!

Evolution – I’m also excited about what we’ll learn about how our solar system continues to evolve. As I just noted, LSST will find many objects transitioning into (centaurs) or out of (dead comets) the active comet population. It will also allow us detect spectacular short duration events like fragmentation, outbursts of activity, or even impacts. Often, these phenomena are not discovered until much later, and it is unknown how frequently they are simply missed entirely. LSST’s high cadence will ensure such events are observed soon after they happen, and the rapid data reduction pipeline will make it possible for them to be detected in the data almost immediately. With proper algorithmic triggers in place, astronomers will be able to follow up on unusual developments from other observatories within minutes or hours.

LSST will also give new insight into how comets behave when they are far away from the Sun, a regime where we currently know very little. A hallmark of the modern era of comet science has been the understanding that cometary activity is driven by the sublimation of water ice. Water ice does not sublimate appreciably beyond the so called “snow line” around 3 AU, yet many comets are active at larger distances. This indicates that other frozen gases, likely CO and CO2 but possibly others, are important in at least some comets. Surveying advances in the last decade have pushed detections of comets substantially beyond the snow line, with objects now routinely being discovered beyond 10 AU, and occasionally before they have even started displaying cometary activity. LSST will systematically survey large number of such objects, which will (hopefully) allow us to find patterns and better understand the inner workings of comets.