Science-Driven Optimization of the LSST Observing Strategy
Abstract
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.
Cite
@article{arxiv.1708.04058,
title = {Science-Driven Optimization of the LSST Observing Strategy},
author = {LSST Science Collaboration and Phil Marshall and Timo Anguita and Federica B. Bianco and Eric C. Bellm and Niel Brandt and Will Clarkson and Andy Connolly and Eric Gawiser and Zeljko Ivezic and Lynne Jones and Michelle Lochner and Michael B. Lund and Ashish Mahabal and David Nidever and Knut Olsen and Stephen Ridgway and Jason Rhodes and Ohad Shemmer and David Trilling and Kathy Vivas and Lucianne Walkowicz and Beth Willman and Peter Yoachim and Scott Anderson and Pierre Antilogus and Ruth Angus and Iair Arcavi and Humna Awan and Rahul Biswas and Keaton J. Bell and David Bennett and Chris Britt and Derek Buzasi and Dana I. Casetti-Dinescu and Laura Chomiuk and Chuck Claver and Kem Cook and James Davenport and Victor Debattista and Seth Digel and Zoheyr Doctor and R. E. Firth and Ryan Foley and Wen-fai Fong and Lluis Galbany and Mark Giampapa and John E. Gizis and Melissa L. Graham and Carl Grillmair and Phillipe Gris and Zoltan Haiman and Patrick Hartigan and Suzanne Hawley and Renee Hlozek and Saurabh W. Jha and C. Johns-Krull and Shashi Kanbur and Vassiliki Kalogera and Vinay Kashyap and Vishal Kasliwal and Richard Kessler and Alex Kim and Peter Kurczynski and Ofer Lahav and Michael C. Liu and Alex Malz and Raffaella Margutti and Tom Matheson and Jason D. McEwen and Peregrine McGehee and Soren Meibom and Josh Meyers and Dave Monet and Eric Neilsen and Jeffrey Newman and Matt O'Dowd and Hiranya V. Peiris and Matthew T. Penny and Christina Peters and Radoslaw Poleski and Kara Ponder and Gordon Richards and Jeonghee Rho and David Rubin and Samuel Schmidt and Robert L. Schuhmann and Avi Shporer and Colin Slater and Nathan Smith and Marcelles Soares-Santos and Keivan Stassun and Jay Strader and Michael Strauss and Rachel Street and Christopher Stubbs and Mark Sullivan and Paula Szkody and Virginia Trimble and Tony Tyson and Miguel de Val-Borro and Stefano Valenti and Robert Wagoner and W. Michael Wood-Vasey and Bevin Ashley Zauderer},
journal= {arXiv preprint arXiv:1708.04058},
year = {2017}
}
Comments
312 pages, 90 figures. Browse the current version at https://github.com/LSSTScienceCollaborations/ObservingStrategy, new contributions welcome!