Science-Driven Optimization of the LSST Observing Strategy

A community white paper about LSST survey strategy ("cadence"), with quantifications via the the Metric Analysis Framework. We will be drafting the individual science cases, and how we expect them to be sensitive to LSST observing strategy, during the first half of 2015. Then, MAF metric calculations designed and executed during the 2015 MAF Workshop (to be held in Bremerton, WA, August 17-21) and afterwards will form the quantitative backbone of the document. You may have heard of the coming "Cadence Wars" - this document represents the Cadnece Diplomacy that will allow us, as a community, to avoid, or at least manage, that conflict.

• Read the current draft of the white paper

• Join the conversation about this project at its issues list

Shortcuts

• Guidelines for how to get involved are in the white paper itself
• For help getting started with git and GitHub, see this handy guide.
• Shortened URL for this repository (for passing around): http://ls.st/o5k
• Community-contributed MAF metric code at the sims_maf_contrib repository

The 2015 MAF Workshop

• Workshop design: homework, tutorial plan, meeting schedule etc.
• Getting started with MAF: check out the LSST sims_maf_contrib wiki to see what people have been working on.
• Meeting website
• List of registered attendees

Contacts

This effort is being coordinated by Zeljko Ivezic, but contributions are welcome from all round the LSST science collaborations. Perhaps we are missing a science area? 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.

The MAF Workshop SOC is: Zeljko Ivezic, Debbie Bard, Andy Connolly, Phil Marshall, Tom Matheson, Steve Ridgway, Michael Strauss, Lucianne Walkowicz, and Beth Willman: any of them can propagate your privately-communicated concerns into a redacted issue on this repository.

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.