This post follows a Blue Jeans conference call on 8 November 2017. Approximately 20 people participated.
Items to work on:
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Upcoming Call for Mini-Surveys and Deep Drilling Fields.
This is our major task for next year. We will hold a Blue Jeans online meeting in late-January/early-February to plan our response. -
Get a platform for DM analysis
We need a project-supported to allow tests of the performance of the actual DM software (example: centroiding on real or simulated data): DM installation can be difficult, tests need to use up-to-date versions, and we need to enable useful interactions with DM people. -
The Astrometry Joint Calibration Discussion
We understand that the current written documentation (from the pre-Gaia era) does not yet match actual plans for the future. We need to understand what is actually planned and to ensure the necessary tests are done. Look in SMWLV email archive for specific issues raised by Monet earlier this year. -
Future presentation on photometric calibration
We realized we know very little about plans for photometric calibration (esp. absolute photometric calibration, the role of Gaia) and a future presentation on this subject would be helpful. [Gizis, post-call: Some interesting documents are here: https://www.lsst.org/category/calibration ] -
Star-galaxy separation
This remains a critical issue for our collaboration. Some interesting results are said to close to being ready for publication and/or reports. We should revisit this topic soon. -
Crowded Field Photometry
Another critical issue. Colin Slater may be able to report on progress with DM testing in a few months. -
Crowded Field Astrometry
Another area of concern. Simulations may be helpful here. Rather that revive the dormant DAWG mailing list (“Differential Astrometry Working Group”) plan discussion on general SMWLV email list until volume gets too high. -
Commissioning Field Selection
Slater gave a report on commissioing plans. Slides to be distributed. Project will likely seek community input on science verification fields. Gizis will bring up issues of participation and sharing through LSST Science Collaboration Coordinator. -
Existing data
We highlighted the recent and upcoming data releases of Subaru data and its value for testing and verification of algorithms, etc.