The Operations Simulator was used to prototype the Large Synoptic Survey Telescope (LSST) Scheduler. Currently, the Scheduler is being developed separately to interface with the LSST Observatory Control System (OCS). A new Simulator is under concurrent development to adjust to this new architecture. This requires a package simulating enough of the OCS to allow execution of realistic schedules. This new package is called the Simulated OCS (SOCS). In this paper we detail the SOCS construction plan, package structure, LSST communication middleware platform use, provide some interesting use cases that the separated architecture allows and the software engineering practices used in development.
The Transneptunian Automated Occultation Survey (TAOS II) will aim to detect occultations of stars by small (~1 km diameter) objects in the Kuiper Belt and beyond. Such events are very rare (< 10−3 events per star per year) and short in duration (~200 ms), so many stars must be monitored at a high readout cadence. TAOS II will operate three 1.3 meter telescopes at the Observatorio Astronómico Nacional at San Pedro Mártir in Baja California, México. With a 2.3 square degree field of view and a high speed camera comprising CMOS imagers, the survey will monitor 10,000 stars simultaneously with all three telescopes at a readout cadence of 20 Hz. Construction of the site began in the fall of 2013, and the survey will begin in the summer of 2017.
To optimize the observing strategy of a large survey such as the LSST, one needs an accurate model of the night sky emission spectrum across a range of atmospheric conditions and from the near-UV to the near-IR. We have used the ESO SkyCalc Sky Model Calculator1, 2 to construct a library of template spectra for the Chilean night sky. The ESO model includes emission from the upper and lower atmosphere, scattered starlight, scattered moonlight, and zodiacal light. We have then extended the ESO templates with an empirical fit to the twilight sky emission as measured by a Canon all-sky camera installed at the LSST site. With the ESO templates and our twilight model we can quickly interpolate to any arbitrary sky position and date and return the full sky spectrum or surface brightness magnitudes in the LSST filter system. Comparing our model to all-sky observations, we find typical residual RMS values of ±0.2-0.3 magnitudes per square arcsecond.
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 Transneptunian Automated Occultation Survey (TAOS II) will aim to detect occultations of stars by small (~1 km diameter) objects in the Kuiper Belt and beyond. Such events are very rare (< 10-3 events per star per year) and short in duration (~200 ms), so many stars must be monitored at a high readout cadence. TAOS II will operate three 1.3 meter telescopes at the Observatorio Astronómico Nacional at San Pedro Mártir in Baja California, México. With a 2.3 square degree field of view and a high speed camera comprising CMOS imagers, the survey will monitor 10,000 stars simultaneously with all three telescopes at a readout cadence of 20 Hz. Construction of the site began in the fall of 2013.
The Transneptunian Automated Occultation Survey (TAOS II) will aim to detect occultations of stars by small ( 1 km diameter) objects in the Solar System and beyond. Such events are very rare (< 10−3 events per star per year) and short in duration ( 200 ms), so many stars must be monitored at a high readout cadence. TAOS II will operate three 1.3 meter telescopes at the Observatorio Astron´omico Nacional at San Pedro Martir in Baja California, Mexico. With a 2.3 square degree field of view and a high speed camera comprising CMOS imagers, the survey will monitor 10,000 stars simultaneously with all three telescopes at a readout cadence of 20 Hz.
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.
We have developed an operation simulator for the Large Synoptic Survey Telescope (LSST) that is an implementation in Python language using the SimPy extension, with a modular and object-oriented design. The main components include a telescope model, a sky model, a weather database for 3 sites, a scheduler and multiple observing proposals. All the proposals derive from a parent class which is fully configurable through about 75 parameters to implement a specific science survey. These parameters control the target selection region, the composition of the sequence of observations for
each field, the timing restrictions and filter selection criteria of each observation, the lunation handling, seeing limits, etc. The current implemented proposals include Weak Lensing, Near Earth Asteroids, Supernova and Kuiper Belt Objects.
The telescope model computes the slew time delay from the current position to any given target position, using a complete kinematic model for the mount, dome and rotator, as well as optics alignment corrections. The model is fully configurable through about 50 parameters. The scheduler module combines the information received from the proposals and the telescope model for selecting the best target at each moment, promoting targets that fulfill multiple surveys and storing all the simulator activities in a MySQL database for further analysis of the run. This scheduler is also configurable; for example, balancing the weight of the slew time delay in selecting the next field to observe.
This simulator has been very useful in clarifying some of the technical and scientific capabilities of the LSST design, and gives a good baseline for a future observation scheduler.
The 8.4m Large Synoptic Survey Telescope (LSST) is a wide-field telescope facility that will add a qualitatively new capability in astronomy. For the first time, the LSST will provide time-lapse digital imaging of faint astronomical objects across the entire sky. The LSST has been identified as a national scientific priority by diverse national panels, including multiple National Academy of Sciences committees. This judgment is based upon the LSST's ability to address some of the most pressing open questions in astronomy and fundamental physics, while driving advances in data-intensive science and computing. The LSST will provide unprecedented 3-dimensional maps of the mass distribution in the Universe, in addition to the traditional images of luminous stars and galaxies. These mass maps can be used to better understand the nature of the newly discovered and utterly mysterious Dark Energy that is driving the accelerating expansion of the Universe. The LSST will also provide a comprehensive census of our solar system, including potentially hazardous asteroids as small as 100 meters in size. The LSST facility consists of three major subsystems: 1) the telescope, 2) the camera and 3) the data processing system. The baseline design for the LSST telescope is a 8.4m 3-mirror design with a 3.5 degree field of view resulting in an A-Omega product (etendue) of 302deg2m2. The camera consists of 3-element transmisive corrector producing a 64cm diameter flat focal plane. This focal plane will be populated with roughly 3 billion 10μm pixels. The data processing system will include pipelines to monitor and assess the data quality, detect and classify transient events, and establish a large searchable object database. We report on the status of the designs for these three major LSST subsystems along with the overall project structure and management.
We present details of the design, operation and calibration of an astronomical visible-band imaging Fourier transform spectrometer (IFTS). This type of instrument produces a spectrum for every pixel in the field of view where the spectral resolution is flexible. The instrument is a dual-input/dual-output Michelson interferometer coupled to the 3.5 meter telescope at the Apache Point Observatory. Imaging performance, and interferograms and spectra from calibration sources and standard stars are discussed.
The Galactic Exoplanet Survey Telescope (GEST) will observe a 2 square degree field in the Galactic bulge to search for extra-solar planets using a gravitational lensing technique. This gravitational lensing technique is the only method employing currently available technology that can detect Earth-mass planets at high signal-to-noise, and can measure the abundance of terrestrial planets as a function of Galactic position. GEST's sensitivity extends down to the mass of Mars, and it can detect hundreds of terrestrial planets with semi-major axes ranging from 0.7 AU to infinity. GEST will be the first truly comprehensive survey of the Galaxy for planets like those in our own Solar System.
We present an abundance analysis of six main sequence turnoff, subgiant, and giant branch stars toward the Galactic bulge that were observed with Keck/HIRES during microlensing events. This is an early look at the first detailed chemical analysis of main sequence stars in the Galactic bulge. Lensing events allow the effective aperture of Keck to be increased beyond its current dimensions; although, some events still stretched its spectroscopic capabilities. Future large telescopes with high resolution and high throughput spectrometers will allow the study of abundances in distant stellar populations and in less evolved stars with greater ease.
We have acquired spatial-spectral datacubes of astronomical objects using the Livermore visible-band imaging Fourier transform spectrometer at Apache Point Observatory. Each raw datacube contains hundreds of thousands of spectral interferograms. We present in-progress demonstrations of these observations.
The MACHO experiment is searching for dark matter in the halo of the Galaxy by monitoring more than 50 million stars in the LMC, SMC, and Galactic bulge for gravitational microlensing events. The hardware consists of a 50 inch telescope, a two-color 32 megapixel ccd camera and a network of computers. On clear nights the system generates up to 8 GB of raw data and 1 GB of reduced data. The computer system is responsible for all realtime control tasks, for data reduction, and for storing all data associated with each observation in a database. The subject of this paper is the software system that handles these functions. It is an integrated system controlled by Petri nets that consists of multiple processes communicating via mailboxes and a bulletin board. The system is highly automated, readily extensive, and incorporates flexible error recovery capabilities. It is implemented with C++ in a Unix environment.
We are developing an astronomical imaging system which employs a thermoelectrically cooled focal plane consisting of two 'edge-buttable' Loral 2048 X 2048 pixel CCDs. To allow strip scanning, the columns of the CCDs are mutually aligned on a custom Kovar mount. The clocking and bias voltage levels for each CCD are independently adjustable, but both CCDs are operated synchronously. Each chip is read out from one output and measured at 14 bits with commercially available A/D converters at a rate of 250 kpixels/s, permitting scanning across the sky at up to 1000 deg2/hr (about twenty times faster than the equatorial sidereal rate) to a limiting magnitude (S/N equals 3) near V equals 19. The instrument will be used as part of the Lowell Observatory Near-Earth-Object Search (LONEOS) using a 57-cm Schmidt telescope at Lowell Observatory in Flagstaff, Arizona.
We have developed an astronomical imaging system that incorporates a total of eight 2048 X 2048 pixel CCDs into two focal planes, to allow simultaneous imaging in two colors. Each focal plane comprises four 'edge-buttable' detector arrays, on custom Kovar mounts. The clocking and bias voltage levels for each CCD are independently adjustable, but all the CCDs are operated synchronously. The sixteen analog outputs (two per chip) are measured at 16 bits with commercially available correlated double sampling A/D converters. The resulting 74 MBytes of data per frame are transferred over fiber optic links into dual-ported VME memory. The total readout time is just over one minute. We obtain read noise ranging from 6.5 e- to 10 e- for the various channels when digitizing at 34 Kpixels/sec, with full well depths (MPP mode) of approximately 100,000 e- per 15 micrometers X 15 micrometers pixel. This instrument is currently being used in a search of gravitational microlensing from compact objects in our Galactic halo, using the newly refurbished 1.3 m telescope at the Mt. Stromlo Observatory, Australia.