Science-Driven Optimization of the LSST Observing Strategy
Creators: name: LSST Science Collaboration
name: Marshall, Phil
name: Anguita, Timo
name: Bianco, Federica B.
name: Bellm, Eric C.
name: Brandt, Niel
name: Clarkson, Will
name: Connolly, Andy
name: Gawiser, Eric
name: Ivezic, Zeljko
name: Jones, Lynne
name: Lochner, Michelle
name: Lund, Michael B.
name: Mahabal, Ashish
name: Nidever, David
name: Olsen, Knut
name: Ridgway, Stephen
name: Rhodes, Jason
name: Shemmer, Ohad
name: Trilling, David
name: Vivas, Kathy
name: Walkowicz, Lucianne
name: Willman, Beth
name: Yoachim, Peter
name: Anderson, Scott
name: Antilogus, Pierre
name: Angus, Ruth
name: Arcavi, Iair
name: Awan, Humna
name: Biswas, Rahul
name: Bell, Keaton J.
name: Bennett, David
name: Britt, Chris
name: Buzasi, Derek
name: Casetti-Dinescu, Dana I.
name: Chomiuk, Laura
name: Claver, Chuck
name: Cook, Kem
name: Davenport, James
name: Debattista, Victor
name: Digel, Seth
name: Doctor, Zoheyr
name: Firth, R. E.
name: Foley, Ryan
name: Fong, Wen-fai
name: Galbany, Lluis
name: Giampapa, Mark
name: Gizis, John E.
name: Graham, Melissa L.
name: Grillmair, Carl
name: Gris, Phillipe
name: Haiman, Zoltan
name: Hartigan, Patrick
name: Hawley, Suzanne
name: Hlozek, Renee
name: Jha, Saurabh W.
name: Johns-Krull, C.
name: Kanbur, Shashi
name: Kalogera, Vassiliki
name: Kashyap, Vinay
name: Kasliwal, Vishal
name: Kessler, Richard
name: Kim, Alex
name: Kurczynski, Peter
name: Lahav, Ofer
name: Liu, Michael C.
name: Malz, Alex
name: Margutti, Raffaella
name: Matheson, Tom
name: McEwen, Jason D.
name: McGehee, Peregrine
name: Meibom, Soren
name: Meyers, Josh
name: Monet, Dave
name: Neilsen, Eric
name: Newman, Jeffrey
name: O'Dowd, Matt
name: Peiris, Hiranya V.
name: Penny, Matthew T.
name: Peters, Christina
name: Poleski, Radoslaw
name: Ponder, Kara
name: Richards, Gordon
name: Rho, Jeonghee
name: Rubin, David
name: Schmidt, Samuel
name: Schuhmann, Robert L.
name: Shporer, Avi
name: Slater, Colin
name: Smith, Nathan
name: Soares-Santos, Marcelles
name: Stassun, Keivan
name: Strader, Jay
name: Strauss, Michael
name: Street, Rachel
name: Stubbs, Christopher
name: Sullivan, Mark
name: Szkody, Paula
name: Trimble, Virginia
name: Tyson, Tony
name: de Val-Borro, Miguel
name: Valenti, Stefano
name: Wagoner, Robert
name: Wood-Vasey, W. Michael
name: Zauderer, Bevin Ashley
Publisher: name: arXiv
Year: 2017
Subjects: subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: Earth and Planetary Astrophysics (astro-ph.EP)
subject: Astrophysics of Galaxies (astro-ph.GA)
subject: Solar and Stellar Astrophysics (astro-ph.SR)
subject: FOS: Physical sciences
subject: FOS: Physical sciences

description: The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation. However, exactly how the LSST observations will be taken (the observing strategy or "cadence") is not yet finalized. In this dynamically-evolving community white paper, we explore how the detailed performance of the anticipated science investigations is expected to depend on small changes to the LSST observing strategy. Using realistic simulations of the LSST schedule and observation properties, we design and compute diagnostic metrics and Figures of Merit that provide quantitative evaluations of different observing strategies, analyzing their impact on a wide range of proposed science projects. This is work in progress: we are using this white paper to communicate to each other the relative merits of the observing strategy choices that could be made, in an effort to maximize the scientific value of the survey. The investigation of some science cases leads to suggestions for new strategies that could be simulated and potentially adopted. Notably, we find motivation for exploring departures from a spatially uniform annual tiling of the sky: focusing instead on different parts of the survey area in different years in a "rolling cadence" is likely to have significant benefits for a number of time domain and moving object astronomy projects. The communal assembly of a suite of quantified and homogeneously coded metrics is the vital first step towards an automated, systematic, science-based assessment of any given cadence simulation, that will enable the scheduling of the LSST to be as well-informed as possible.
description: 312 pages, 90 figures. Browse the current version at https://github.com/LSSTScienceCollaborations/ObservingStrategy, new contributions welcome!