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October 2011  •  Volume 4 Number 3

The Operations Simulator

Figure 1. The number of visits to a field in each filter in the first year of a 10-year survey (plotted in Aitoff-Hammer projection) is relatively uniform and an estimate of the depth achieved for that field. Darker colors indicate more complete coverage. Note the six “spots” scattered on the sky that appear darkest – they are the LSST “deep drilling fields”, areas of special interest that receive additional coverage.

The LSST will operate as a survey telescope, robotically scanning the sky in a pre-programmed sequence of observations, then storing images in a public database for use by professional and citizen scientists exploring the wide range of LSST science topics. Much like scheduling an elevator to minimize wait time for riders, this sequence of observations, the “observing cadence”, must be optimized to provide data that enables the most science as efficiently as possible. The task of determining the optimum observing cadence to maximize the science is the job of the LSST Operations Simulator.

During its ten-year survey, LSST will acquire about 5.6 million 15-second images, spread over about 20,000 square degrees – their distribution on the sky, over time, and among its six filters has a strong impact on how useful these data are for almost any astronomical investigation. The LSST Project has developed an Operations Simulator (LSST OpSim) to verify whether the current telescope design can acquire a set of observations suitable to address the questions from each of the four main science themes. Currently the question of which field to observe next is answered by ranking fields which are “requested” by each of the science programs. We are exploring a variety of scheduling algorithms to determine the optimal strategy for the design of the scheduler which will drive the largely robotic observatory. The simulator will remain an important tool for operations, allowing LSST to adapt and evaluate its observing strategy in response to the changing scientific demands of the astronomical community.

Figure 2. A figure of merit designed to measure how uniformly in time each field is visited over the 10 year duration of the survey. For each field observed in the g-filter, the sequence (distribution) of visits in days is determined. The mean of this sequence is compared to the midpoint of the survey (x-axis) and plotted against the standard deviation of the distribution (y-axis). This plot separates fields that are observed uniformly in time (center of plot) from ones that are visited more episodically.

The Operations Simulator uses detailed models of site-specific conditions (e.g., cloud cover, seeing) and telescope opto-mechanical capabilities (e.g., the time required to slew to a new position) to create realizations of the set of observations the telescope will make. One output of the simulator is an observing log which includes, among the 50 visit-specific characteristics: the position on the sky, time, and filter of each visit, and the brightness of the sky in that filter. Post-processing adds additional sky brightness estimates (from different sky brightness models) and the signal-to-noise ratio achieved. An analysis pipeline has been developed, which generates a standard report containing measures of the characteristics of the survey, such as the distribution of the mean seeing per field for all visits in a filter, estimates of the depth of the final stacked images in each filter as a function of position on the sky (Figure 1), or other figures of merit relevant to particular science goals (Figure 2).

We are continuing to work on how to best control the survey progress by altering the algorithms and parameters that describe each science program. In the next version of the simulator, we will be developing additional scheduling strategies to explore the effectiveness with which we can address each of the four key science goals. We are working with the LSST Science Collaborations (who have been provided with a username and password to gain access to simulated survey data and analysis on the website) to refine our current cadences by asking them to develop additional figures of merit to measure how well a particular simulated survey can do their science.

Article written by Cathy Petry


LSST is a public-private partnership. Funding for design and development activity comes from the National Science Foundation, private donations, grants to universities, and in-kind support at Department of Energy laboratories and other LSSTC Institutional Members:

Adler Planetarium; Brookhaven National Laboratory (BNL); California Institute of Technology; Carnegie Mellon University; Chile; Cornell University; Drexel University; Fermi National Accelerator Laboratory; George Mason University; Google, Inc.; Harvard-Smithsonian Center for Astrophysics; Institut de Physique Nucléaire et de Physique des Particules (IN2P3); Johns Hopkins University; Kavli Institute for Particle Astrophysics and Cosmology (KIPAC) – Stanford University; Las Cumbres Observatory Global Telescope Network, Inc.; Lawrence Livermore National Laboratory (LLNL); Los Alamos National Laboratory (LANL); National Optical Astronomy Observatory; Princeton University; Purdue University; Research Corporation for Science Advancement; Rutgers University; SLAC National Accelerator Laboratory; Space Telescope Science Institute; Texas A & M University; The Pennsylvania State University; The University of Arizona; University of California at Davis; University of California at Irvine; University of Illinois at Urbana-Champaign; University of Michigan; University of Pennsylvania; University of Pittsburgh; University of Washington; Vanderbilt University

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LSST E-News is a free email publication of the Large Synoptic Survey Telescope Project. It is for informational purposes only, and the information is subject to change without notice.

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