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This page details completed, ongoing and future planned science studies to be carried out by the Data Management Subsystem Science Team.

Current and Past SST projects:

PDAC user experience study  

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Suggestions for future SST projects:

WhatSuggested byDescription
variability characterization parameters

At some point, DM will have to select which variability characterization parameters (VCP) are included in the source catalogs (Prompt and DRP). This is JIRA issue

Jira
serverJIRA
serverId9da94fb6-5771-303d-a785-1b6c5ab0f2d2
keyDM-11962
. This will depend on what is needed by the science community and by the mini-brokers, and what can be computationally supported by the DM system. Regarding the former, the TVS has a task force to evaluate which VCPs are needed for their science goals which should conclude around the end of 2018. It is anticipated that a similar selection process for VCPs as e.g., photo-z, will be needed.

This project will also address PST-31

documentation of photometric calibration

Produce user-facing documentation for LSST's photometric calibrations that are derived from Robert Lupton's documents: easy and hard.

Moving variable star

Moving variable star: a bias in motion due to flux=const.? (see science case for moving variable stars above)

This topic comes from Zeljko Ivezic (note in the DPDD)

Review and overhaul of science pipelines documentationThe LSST Science Pipelines documentation at needs to be reviewed and overhauled.
(re-)Review of the number alerts/objects that LSST expect to observe

Jira
serverJIRA
serverId9da94fb6-5771-303d-a785-1b6c5ab0f2d2
keyRM-1778

Target of Opportunity policies and implementation 

Are there special considerations DM needs to take into account to support ToO science? Collecting our understanding of ToOs in one tech note would be helpful.

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