The LSST Metrics Analysis Framework (MAF)
Abstract
Studying potential observing strategies or cadences for the Large Synoptic Survey Telescope (LSST) is a complicated but important problem. To address this, LSST has created an Operations Simulator (OpSim) to create simulated surveys, including realistic weather and sky conditions. Analyzing the results of these simulated surveys for the wide variety of science cases to be considered for LSST is, however, difficult. We have created a Metric Analysis Framework (MAF), an open-source python framework, to be a user-friendly, customizable and easily extensible tool to help analyze the outputs of the OpSim.MAF reads the pointing history of the LSST generated by the OpSim, then enables the subdivision of these pointings based on position on the sky (RA/Dec, etc.) or the characteristics of the observations (e.g. airmass or sky brightness) and a calculation of how well these observations meet a specified science objective (or metric). An example simple metric could be the mean single visit limiting magnitude for each position in the sky; a more complex metric might be the expected astrometric precision. The output of these metrics can be generated for a full survey, for specified time intervals, or for regions of the sky, and can be easily visualized using a web interface.An important goal for MAF is to facilitate analysis of the OpSim outputs for a wide variety of science cases. A user can often write a new metric to evaluate OpSim for new science goals in less than a day once they are familiar with the framework. Some of these new metrics are illustrated in the accompanying poster, "Analyzing Simulated LSST Survey Performance With MAF".While MAF has been developed primarily for application to OpSim outputs, it can be applied to any dataset. The most obvious examples are examining pointing histories of other survey projects or telescopes, such as CFHT.
- Publication:
-
American Astronomical Society Meeting Abstracts #225
- Pub Date:
- January 2015
- Bibcode:
- 2015AAS...22533640J