The Large Synoptic Survey Telescope (LSST) is an 8-meter class wide-field telescope now under construction on Cerro Pachon, near La Serena, Chile. This ground-based telescope is designed to conduct a decade-long time domain survey of the optical sky. In order to achieve the LSST scientific goals, the telescope requires delivering seeing limited image quality over the 3.5 degree field-of-view. Like many telescopes, LSST will use an Active Optics System (AOS) to correct in near real-time the system aberrations primarily introduced by gravity and temperature gradients. The LSST AOS uses a combination of 4 curvature wavefront sensors (CWS) located on the outside of the LSST field-of-view. The information coming from the 4 CWS is combined to calculate the appropriate corrections to be sent to the 3 different mirrors composing LSST. The AOS software incorporates a wavefront sensor estimation pipeline (WEP) and an active optics control system (AOCS). The WEP estimates the wavefront residual error from the CWS images. The AOCS determines the correction to be sent to the different degrees of freedom every 30 seconds. In this paper, we describe the design and implementation of the AOS. More particularly, we will focus on the software architecture as well as the AOS interactions with the various subsystems within LSST.
Construction of the Large Synoptic Survey Telescope system involves several different organizations, a situation that poses many challenges at the time of the software integration of the components. To ensure commonality for the purposes of usability, maintainability, and robustness, the LSST software teams have agreed to the following for system software components: a summary state machine, a manner of managing settings, a flexible solution to specify controller/controllee relationships reliably as needed, and a paradigm for responding to and communicating alarms. This paper describes these agreed solutions and the factors that motivated these.
The LSST is an integrated, ground based survey system designed to conduct a decade-long time domain survey of the
optical sky. It consists of an 8-meter class wide-field telescope, a 3.2 Gpixel camera, and an automated data processing
system. In order to realize the scientific potential of the LSST, its optical system has to provide excellent and consistent
image quality across the entire 3.5 degree Field of View. The purpose of the Active Optics System (AOS) is to optimize
the image quality by controlling the surface figures of the telescope mirrors and maintaining the relative positions of the
optical elements. The basic challenge of the wavefront sensor feedback loop for an LSST type 3-mirror telescope is the
near degeneracy of the influence function linking optical degrees of freedom to the measured wavefront errors. Our
approach to mitigate this problem is modal control, where a limited number of modes (combinations of optical degrees
of freedom) are operated at the sampling rate of the wavefront sensing, while the control bandwidth for the barely
observable modes is significantly lower. The paper presents a control strategy based on linear approximations to the
system, and the verification of this strategy against system requirements by simulations using more complete, non-linear
models for LSST optics and the curvature wavefront sensors.
The Operations Simulator for the Large Synoptic Survey Telescope (LSST; http://www.lsst.org) allows the planning of LSST observations that obey explicit science driven observing specifications, patterns, schema, and priorities, while optimizing against the constraints placed by design-specific opto-mechanical system performance of the telescope facility, site specific conditions as well as additional scheduled and unscheduled downtime. It has a detailed model to simulate the external conditions with real weather history data from the site, a fully parameterized kinematic model for the internal conditions of the telescope, camera and dome, and serves as a prototype for an automatic scheduler for the real time survey operations with LSST. The Simulator is a critical tool that has been key since very early in the project, to help validate the design parameters of the observatory against the science requirements and the goals from specific science programs. A simulation run records the characteristics of all observations (e.g., epoch, sky position, seeing, sky brightness) in a MySQL database, which can be queried for any desired purpose. Derivative information digests of the observing history are made with an analysis package called Simulation Survey Tools for Analysis and Reporting (SSTAR). Merit functions and metrics have been designed to examine how suitable a specific simulation run is for several different science applications. Software to efficiently compare the efficacy of different survey strategies for a wide variety of science applications using such a growing set of metrics is under development. A recent restructuring of the code allows us to a) use "look-ahead" strategies that avoid cadence sequences that cannot be completed due to observing constraints; and b) examine alternate optimization strategies, so that the most efficient scheduling algorithm(s) can be identified and used: even few-percent efficiency gains will create substantive scientific opportunity. The enhanced simulator is being used to assess the feasibility of desired observing cadences, study the impact of changing science program priorities and assist with performance margin investigations of the LSST system.
The LSST will, over a 10-year period, produce a multi-color, multi-epoch survey of more than
18000 square degrees of the southern sky. It will generate a multi-petabyte archive of images and
catalogs of astrophysical sources from which a wide variety of high-precision statistical studies can
be undertaken. To accomplish these goals, the LSST project has developed a suite of modeling and
simulation tools for use in validating that the design and the as-delivered components of the LSST
system will yield data products with the required statistical properties. In this paper we describe the
development, and use of the LSST simulation framework, including the generation of simulated
catalogs and images for targeted trade studies, simulations of the observing cadence of the LSST, the
creation of large-scale simulations that test the procedures for data calibration, and use of end-to-end
image simulations to evaluate the performance of the system as a whole.
We describe the Metrics Analysis Framework (MAF), an open-source python framework developed to provide a user-friendly, customizable, easily-extensible set of tools for analyzing data sets. MAF is part of the Large Synoptic Survey Telescope (LSST) Simulations effort. Its initial goal is to provide a tool to evaluate LSST Operations Simulation (OpSim) simulated surveys to help understand the effects of telescope scheduling on survey performance, however MAF can be applied to a much wider range of datasets. The building blocks of the framework are Metrics (algorithms to analyze a given quantity of data), Slicers (subdividing the overall data set into smaller data slices as relevant for each Metric), and Database classes (to access the dataset and read data into memory). We describe how these building blocks work together, and provide an example of using MAF to evaluate different dithering strategies. We also outline how users can write their own custom Metrics and use these within the framework.
The Large Synoptic Survey Telescope (LSST) uses an Active Optics System (AOS) to maintain system alignment and surface figure on its three large mirrors. Corrective actions fed to the LSST AOS are determined from 4 curvature based wavefront sensors located on the corners of the inscribed square within the 3.5 degree field of view. Each wavefront sensor is a split detector such that the halves are 1mm on either side of focus. In this paper we describe the development of the Active Optics Pipeline prototype that simulates processing the raw image data from the wavefront sensors through to wavefront estimation on to the active optics corrective actions. We also describe various wavefront estimation algorithms under development for the LSST active optics system. The algorithms proposed are comprised of the Zernike compensation routine which improve the accuracy of the wavefront estimate. Algorithm development has been aided by a bench top optical simulator which we also describe. The current software prototype combines MATLAB modules for image processing, tomographic reconstruction, atmospheric turbulence and Zemax for optical ray-tracing to simulate the closed loop behavior of the LSST AOS. We describe the overall simulation model and results for image processing using simulated images and initial results of the wavefront estimation algorithms.
The Large Synoptic Survey Telescope (LSST) has a 3.5º field of view and F/1.2 focus that makes the performance quite
sensitive to the perturbations of misalignments and mirror surface deformations. In order to maintain the image quality,
LSST has an active optics system (AOS) to measure and correct those perturbations in a closed loop. The perturbed
wavefront errors are measured by the wavefront sensors (WFS) located at the four corners of the focal plane. The
perturbations are solved by the non-linear least square algorithm by minimizing the rms variation of the measured and
baseline designed wavefront errors. Then the correction is realized by applying the inverse of the perturbations to the
optical system. In this paper, we will describe the correction processing in the LSST AOS. We also will discuss the
application of the algorithm, the properties of the sensitivity matrix and the stabilities of the correction. A simulation
model, using ZEMAX as a ray tracing engine and MATLAB as an analysis platform, is set up to simulate the testing and
correction loop of the LSST AOS. Several simulation examples and results are presented.
The Large Synoptic Survey Telescope will record approximately 2.5x10^6 images over a 10-year interval, using 6
optical filters, with a wide variety of cadences on time scales of seconds to years. The observing program will be of a
complexity that it can only be realized with heavily automated scheduling. The LSST OpSim team has devised a
schedule simulator to support development of that capability. This paper addresses the complex problem of how to
measure the success of a schedule simulation for realization of science objectives. Tools called Merit Functions evaluate
the patterns and other properties of scheduled image acquisitions.
A survey program with multiple science goals will be driven by multiple technical requirements. On a ground-based
telescope, the variability of conditions introduces yet greater complexity. For a program that must be largely autonomous
with minimal dwell time for efficiency it may be quite difficult to foresee the achievable performance. Furthermore,
scheduling will likely involve self-referential constraints and appropriate optimization tools may not be available. The
LSST project faces these issues, and has designed and implemented an approach to performance analysis in its
Operations Simulator and associated post-processing packages. The Simulator has allowed the project to present detailed
performance predictions with a strong basis from the engineering design and measured site conditions. At present, the
Simulator is in regular use for engineering studies and science evaluation, and planning is underway for evolution to an
operations scheduling tool. We will describe the LSST experience, emphasizing the objectives, the accomplishments and
the lessons learned.