sschmidt23 / ObservingStrategy

A community white paper about LSST observing strategy, with quantifications via the the Metric Analysis Framework.

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Science-Driven Optimization of the LSST Observing Strategy

A community white paper about LSST survey strategy ("cadence"), with quantifications via the Metric Analysis Framework. We are drafting some individual science cases, that are either very important, and somehow stress the observing strategy, and descriing how we expect them to be sensitive to LSST observing strategy. MAF metric calculations are then being designed and implemented - we started this during the 2015 LSST Observing Strategy Workshop (in Bremerton, WA, August 17-21): these will form the quantitative backbone of the document. You may have heard of the coming "Cadence Wars" - this document represents the Cadence Diplomacy that will allow us, as a community, to avoid, or at least manage, that conflict. We welcome contributions from all around the LSST Science community.

Shortcuts

The 2015 MAF Workshop, Bremerton

August 19-21, 2015.

Face-to-Face White Paper Workshop, Tucscon

November 19-20, 2015.

Contacts

This effort is being coordinated by Zeljko Ivezic and Beth Willman, while Phil Marshall is the white paper's editor-in-chief. Any of them can propagate your privately-communicated concerns into a redacted issue on this repository. Contributions are very welcome from all round the LSST science collaborations, and beyond. Perhaps we are missing a science case? Or an idea for how to perturb the observing strategy? We'd like to hear from you! Please send all your feedback to this repo's issues.

All white paper content is Copyright 2015 The Authors. If you make use of the ideas and results in the white paper in your research, please cite it as "(LSST Science Collaborations in preparation)", and provide the URL of this repository: https://github.com/LSSTScienceCollaborations/ObservingStrategy. Thanks!

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A community white paper about LSST observing strategy, with quantifications via the the Metric Analysis Framework.


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