The LSST Science Collaborations - LSST Chile meeting 2019

Transcript

1. The Large Synoptic Survey Telescope Science Collaborations @fedhere fedhere federica b. bianco University of Delaware Department of Physics and Astronomy - Biden School for Public Policy Data Science Institute LSST Science Collaborations Coordinator, LSSTC LSST Transient and Variable Stars Science Collaborations Co-Chair
2. federica bianco NYU LSST LSST 2023-2033 2023-2033 2023-2033
3. federica bianco NYU
4. federica bianco UDel The LSST Science Collaborations
5. federica bianco UDel The LSST Science Collaborations Formed by the LSST Project in 2008 to provide a forum to engage the community in interacting with the LSST Project Science Team played an essential part in producing the LSST Science Book in 2009 LSST was recognized as the first large ground-based priority of the astronomical community in the 2010 Decadal Survey
6. federica bianco UDel The LSST Science Collaborations
7. federica bianco UDel The LSST Science Collaborations LSST’s four key science themes Exploring the transient and variable sky Census of the Solar System Mapping the Milky Way Understanding dark energy and dark matter
8. federica bianco UDel The LSST Science Collaborations LSST’s four key science themes Exploring the transient and variable sky Census of the Solar System Mapping the Milky Way Understanding dark energy and dark matter
9. federica bianco UDel The LSST Science Collaborations LSST’s four key science themes Exploring the transient and variable sky Census of the Solar System Mapping the Milky Way Understanding dark energy and dark matter
10. federica bianco UDel The LSST Science Collaborations LSST’s four key science themes Exploring the transient and variable sky Census of the Solar System Mapping the Milky Way Understanding dark energy and dark matter
11. federica bianco UDel The LSST Science Collaborations Exploring the transient and variable sky Census of the Solar System Mapping the Milky Way Understanding dark energy and dark matter LSST’s four key science themes
12. federica bianco UDel The LSST Science Collaborations Exploring the transient and variable sky Census of the Solar System Mapping the Milky Way Understanding dark energy and dark matter LSST’s four key science themes
13. federica bianco UDel The LSST Science Collaborations A Network-to-Network system https://cosmo.nyu.edu/~fb55/LSSTSCaffiliations/LSSTSCaffiliations/
14. federica bianco UDel The LSST Science Collaborations A Network-to-Network system https://cosmo.nyu.edu/~fb55/LSSTSCaffiliations/LSSTSCaffiliations/
15. federica bianco UDel The LSST Science Collaborations A Network-to-Network system
16. federica bianco UDel The LSST Science Collaborations Chile: 69 UK: 57 Italy: 60 France:45 
 California: 144 Washington: 88 Arizona: 52 Pennsylvania: 40
17. federica bianco UDel The LSST Science Collaborations
18. federica bianco UDel The LSST Science Collaborations direct contact with the Project https://www.youtube.com/playlist? list=PLPINAcUH0dXacwsNrhNnQSq0rOTRf0IfU
19. federica bianco UDel The LSST Science Collaborations LSST SCs current activities include: • designing and scoping LSST observing strategies for different science cases • learning and testing the LSST pipeline and science platform 
 • identifying gap in scientific preparation that would impair the LSST success in theoretical advancement (e.g. predictions on photometric observables, sparse time series analysis), software (e.g. sparse time series analysis tools, crowded field photometry, TOM), existing data (e.g. multiwavelenght coverage of Deep Drilling Fields) 
 • preparing of User-Generated data products
20. federica bianco UDel The LSST Science Collaborations LSST SCs current activities include: • designing and scoping LSST observing strategies for different science cases • learning and testing the LSST pipeline and science platform 
 • identifying gap in scientific preparation that would impair the LSST success in theoretical advancement (e.g. predictions on photometric observables, sparse time series analysis), software (e.g. sparse time series analysis tools, crowded field photometry, TOM), existing data (e.g. multiwavelenght coverage of Deep Drilling Fields) 
 • preparing of User-Generated data products
21. federica bianco UDel LSST LSST Deep Drilling Fields DDF (4.5%) North Ecliptic Survey The NES is an extension to reach the Ecliptic at higher airmass than the WFD survey typically covers, no u Galactic Plane (1.7%): covers the region where LSST is expected to be highly confused by the density of stellar sources; fewer total exposures/ field and does not collect in pairs South Celestial Pole (2.2%): higher airmass decl>−65 degrees. includes ugrizy, but takes fewer exposures/field than the WFD and does not collect in pairs. Wide-Fast-Deep (85.1%) Refining the observing strategy 2023-2033 2023-2033 2023-2033
22. federica bianco NYU Refining the observing strategy LSST Science Collaborations COSEP living document testing LSST observing strategies for different science cases https://github.com/ LSSTScienceCollaborations/ ObservingStrategy
23. federica bianco UDel - COSEP Refining the observing strategy https://github.com/ LSSTScienceCollaboratio ns/ ObservingStrategy
24. federica bianco NYU - 2018 White Paper Refining the observing strategy
25. federica bianco NYU - 2018 White Paper Refining the observing strategy https://cosmo.nyu.edu/~fb55/LSSTWP
26. federica bianco NYU - New footprint? Refining the observing strategy simulating the LSST observing strategy https://www.lsst.org/node/656
27. federica bianco NYU - New footprint? Refining the observing strategy
28. federica bianco NYU - New footprint? Refining the observing strategy
29. federica bianco NYU - More colors? Refining the observing strategy • u-band • more g-band • specific filter pairs • filters for triplets (smaless plug… ) Bianco et al. 2019 PASP, Special issue on Time Domain Astronomy, in publication
30. federica bianco NYU - snap or no snap? Refining the observing strategy • Snap/visit exposure times:
 Many prefer ~30s (1snap/visit) [7% more efficient] • Some prefer 2x15s snaps - limited area only? (white dwarf transits, rapid variability/saturation) • 1 request for 2s/28s snaps • 1 minisurvey for 5s visits • 1 minisurvey for 1s-15s trailed images
31. federica bianco UDel The LSST Science Collaborations LSST SCs current activities include: • designing and scoping LSST observing strategies for different science cases • learning and testing the LSST pipeline and science platform 
 • identifying gap in scientific preparation that would impair the LSST success in theoretical advancement (e.g. predictions on photometric observables, sparse time series analysis), software (e.g. sparse time series analysis tools, crowded field photometry, TOM), existing data (e.g. multiwavelenght coverage of Deep Drilling Fields) 
 • preparing of User-Generated data products
32. federica bianco NYU LSST learning testing tuning LSP and stack- LSP review
33. federica bianco NYU Review Committee Composition Representation across all LSST stakeholders, including within the project, LSST science collaborations, representatives from the SAC and external experts The committee is asked to provide science-oriented feedback and recommendations on the design of the LSST Science Platform LSST Project • Keith Bechtol: LSST Commissioning Science Verification (DESC) • Richard Dubois: LSST Camera External • Ani Thakar: SciServer LSST Science Collaborations • Rachel Street: TVS, (LCO, archives) • David Kirkby: DESC, (SAC) • Michael Mommert: SSSC • Christian Johnson: SMWLV • Lee Steven Kelvin: Galaxies • Tina Peters: AGN LSP Review April 2019 LSST learning testing tuning LSP and stack- LSP review
34. federica bianco NYU LSST learning testing tuning LSP and stack- stack club
35. federica bianco UDel The LSST Science Collaborations LSST SCs current activities include: • designing and scoping LSST observing strategies for different science cases • learning and testing the LSST pipeline and science platform 
 • identifying gap in scientific preparation that would impair the LSST success in theoretical advancement (e.g. predictions on photometric observables, sparse time series analysis), software (e.g. sparse time series analysis tools, crowded field photometry, TOM), existing data (e.g. multiwavelenght coverage of Deep Drilling Fields) 
 • preparing of User-Generated data products
36. federica bianco UDel LSST scientific readiness: data collection Gathering legacy data in sight of the LSST survey, e.g. AGN SC (Chen et al. 2018) 5 Ms XMM-SERVS
37. federica bianco NYU LSST scientific readiness: Software - brokers & TOMs
38. federica bianco NYU LSST scientific readiness: Software - brokers & TOMs
39. federica bianco NYU LSST scientific readiness: Software - brokers & TOMs https://lsst-tvssc.github.io/broker_task_force_work_plan.html
40. federica bianco NYU LSST scientific readiness: Software - brokers & TOMs https://lsst-tvssc.github.io/broker_task_force_work_plan.html
41. federica bianco NYU LSST scientific readiness: ISSC Introducing... #ask-the-ISSC Slack channel for general stats and ML issues Effort to increase the ISSC’s “consulting” reach, and also stimulate collaborations involving the ISSC
42. federica bianco NYU LSST scientific readiness: ISSC Introducing... #ask-the-ISSC Slack channel for general stats and ML issues Effort to increase the ISSC’s “consulting” reach, and also stimulate collaborations involving the ISSC ISSC ToO …. expect an invitation! meeting hosted by CMU to pitch astrostats problems to the ISSC and form teams to work on them … pending funding …
43. federica bianco UDel The LSST Science Collaborations LSST SCs current activities include: • designing and scoping LSST observing strategies for different science cases • learning and testing the LSST pipeline and science platform 
 • identifying gap in scientific preparation that would impair the LSST success in theoretical advancement (e.g. predictions on photometric observables, sparse time series analysis), software (e.g. sparse time series analysis tools, crowded field photometry, TOM), existing data (e.g. multiwavelenght coverage of Deep Drilling Fields) 
 • preparing of User-Generated data products
44. federica bianco NYU AGN - synergistic data analysis DESC - systematics Galaxies - deblending, morphology Solar System - refining MOPs SMWLV - crowded fields photometry Strong Lensing - morphology TVS - classification and follow-up LSST User Generated Pipelines
45. federica bianco UDel The LSST Science Collaborations https://www.lsstcorporation.org/science-collaborations Join us! contact the SC coordinator: fbianco@udel.edu
46. Somewhere, something incredible is waiting to be known. Carl Segan fbianco@udel.edu - LSST SC coordinator, LSST TVSSC co-chair