The Vera C. Rubin Observatory will advance many areas of astronomy over the next decade with its unique widefast- deep multi-color imaging survey, the Legacy Survey of Space and Time (LSST).1 The LSST will produce approximately 20TB of raw data per night, which will be automatically processed by the LSST Science Pipelines to generate science-ready data products – processed images, catalogs and alerts. To ensure that these data products enable transformative science with LSST, stringent requirements have been placed on their quality and scientific fidelity, for example on image quality and depth, astrometric and photometric performance, and object recovery completeness. In this paper we introduce faro, a framework for automatically and efficiently computing scientific performance metrics on the LSST data products for units of data of varying granularity, ranging from single-detector to full-survey summary statistics. By measuring and monitoring metrics, we are able to evaluate trends in algorithmic performance and conduct regression testing during development, compare the performance of one algorithm against another, and verify that the LSST data products will meet performance requirements by comparing to specifications. We present initial results using faro to characterize the performance of the data products produced on simulated and precursor data sets, and discuss plans to use faro to verify the performance of the LSST commissioning data products.
KEYWORDS: Observatories, System integration, Imaging systems, Data processing, Data acquisition, Control systems, Cameras, Telescopes, Image processing, Software development
The Rubin Observatory has entered its latter stages of the construction effort with system integration, test and commissioning. All system elements are coming together including components of the telescope, the science camera and software systems for control and data processing. In this paper we report on the progress, status, plans and schedule for integrating the system elements into a fully functional observatory to carry out the 10-year Legacy Survey of Space and Time.
The Vera C. Rubin Observatory is a joint NSF and DOE construction project with facilities distributed across multiple sites. These sites include the Summit Facility on Cerro Pachón, Chile; the Base Facility in La Serena, Chile; the Project and Operations Center in Tucson, AZ; the Camera integration and testing laboratories at SLAC National Accelerator Laboratory in Menlo Park, CA; and the data support center based at the National Center for SuperComputing Applications at Urbana-Champaign, IL. The Rubin Observatory construction Project has entered its system integration and testing phase where major subsystem components are coming together and being tested and verified at a system level for the first time. The system integration phase of the Project requires a closely coordinated and organized plan to merge, manage, and be able to adapt the complex set of subsystems and activities across the entire observatory as real effects are discovered. In this paper we present our strategy to successfully complete integration, test and commissioning of the systems making up the Rubin Observatory. We include discussion on (i) our strategy for integration activities and the verification of requirements (ii) a brief summary of construction status at the time of this paper, (iii) early integration activities that are used to mitigate risks including the use of the Rubin Observatory's commissioning camera (ComCam), planning for the integration, testing and verification of the primary science instrument - LSSTCam, and lastly, (v) Science Verification through short concentrated survey-like campaigns. Throughout this paper we identify where key performance metrics are addressed that directly impact the Rubin Observatory's 10{year Legacy Survey of Space and Time (LSST) science capabilities - e.g. image quality, telescope dynamics, alert latency, etc...
The Data Management (DM) subsystem of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) is responsible for creating the software, services, and systems that will be used to produce science ready data products. The software, currently under development, is heterogeneous, comprising both C++ and Python components, and is designed to facilitate both the processing of the observatory images and to enable value-added contributions from the broader scientific community. Verification and validation of these software products, services, and systems is an essential yet time-consuming task. In this paper, we present the tooling and procedures developed to ensure a systematic approach to the production of documentation for verification and validation. By adopting a systematic approach, we guarantee full traceability to system requirements, integration with the project’s Systems Engineering model, and substantially reduce the time required for the whole process.
H. T. Diehl, E. Neilsen, R. Gruendl, T. M. Abbott, S. Allam, O. Alvarez, J. Annis, E. Balbinot, S. Bhargava, K. Bechtol, G. Bernstein, R. Bhatawdekar, S. Bocquet, D. Brout, R. Capasso, R. Cawthon, C. Chang, E. Cook, C. Conselice, J. Cruz, C. D'Andrea, L. da Costa, R. Das, D. DePoy, A. Drlica-Wagner, A. Elliott, S. Everett, J. Frieman, A. Fausti Neto, A. Ferté, I. Friswell, K. Furnell, L. Gelman, D. Gerdes, M. S. Gill, D. Goldstein, D. Gruen, D. Gulledge, S. Hamilton, D. Hollowood, K. Honscheid, D. James, M. Johnson, M. W. Johnson, S. Kent, R. Kessler, G. Khullar, E. Kovacs, A. Kremin, R. Kron, N. Kuropatkin, J. Lasker, A. Lathrop, T. Li, M. Manera, M. March, J. Marshall, M. Medford, F. Menanteau, I. Mohammed, M. Monroy, B. Moraes, E. Morganson, J. Muir, M. Murphy, B. Nord, A. Pace, A. Palmese, Y. Park, F. Paz-Chinchón, M. E. Pereira, D. Petravick, A. Plazas, J. Poh, T. Prochaska, A. Romer, K. Reil, A. Roodman, M. Sako, M. Sauseda, D. Scolnic, L. Secco, I. Sevilla-Noarbe, N. Shipp, J. Smith, M Soares-Santos, B. Soergel, A. Stebbins, K. Story, K. Stringer, F. Tarsitano, B. Thomas, D. Tucker, K. Vivas, A. Walker, M.-Y. Wang, C. Weaverdyck, N. Weaverdyck, W. Wester, C. Wethers, R. Wilkenson, H.-Y Wu, B. Yanny, A. Zenteno, Y. Zhang
The Dark Energy Survey (DES) is an operating optical survey aimed at understanding the accelerating expansion of the universe using four complementary methods: weak gravitational lensing, galaxy cluster counts, baryon acoustic oscillations, and Type Ia supernovae. To perform the 5000 sq-degree wide field and 30 sq-degree supernova surveys, the DES Collaboration built the Dark Energy Camera (DECam), a 3 square-degree, 570-Megapixel CCD camera that was installed at the prime focus of the Blanco 4-meter telescope at the Cerro Tololo Inter-American Observatory (CTIO). DES has completed its third observing season out of a nominal five. This paper describes DES “Year 4” (Y4) and “Year 5” (Y5), the survey strategy, an outline of the survey operations procedures, the efficiency of operations and the causes of lost observing time. It provides details about the quality of these two-season's data, a summary of the overall status, and plans for the final survey season.
KEYWORDS: Large Synoptic Survey Telescope, Imaging systems, System integration, Cameras, Telescopes, Observatories, Data processing, Interfaces, Control systems, Computing systems
The Commissioning Phase of the LSST Project is the final stage in the combined NSF and DOE funded LSST construction project. The LSST commission phase is planned to start early in 2020 and be completed near the end of 2022, ending with the LSST Observatory system ready to start survey operations. Commissioning includes the assembly of the three principal subsystems (Telescope, Camera and Data Management) into the LSST Observatory System and the integration and test (AI&T) efforts as well as the science verification activities. The LSST System AI&T and Commissioning Plan is driven by a combination of engineering and scientifically oriented activities to show compliance with technical requirements and readiness to conduct science operations (acquiring data, processing data, and serving data and derived data products to users). LSST System AI&T and Commissioning will be carried out over four phases of activity: Phase-0) Pre-commissioning preparations (work breakdown structure; Phase-1) Early System AI&T with a commissioning camera (ComCam); Phase-2) Full System AI&T when the LSST Science Camera is shipped to Chile, integrated on the telescope and the data management system (DMS) is exercised with full scale data; and Phase-3) Science Validation where a series of mini-surveys are used to characterize the system with respect to the survey performance specifications in the SRD/LSR and functionality of the, leading to operations readiness. The Science Validation Phase concludes with an Operations Readiness Review (ORR).
The LSST System Assembly, Integration and Test and Commissioning effort has been planned out over several phases The first phase of commissioning under Early AI&T is designed to test and verify the system level interfaces using ComCam – a 144Mpixel imager utilizing the same control components as the full science camera. During this period, the telescope active optics system will be brought into compliance with system requirements; the scheduler will be exercised and all safety checks verified for autonomous operation; and early DM algorithm testing will be performed with on-sky data from ComCam using a commissioning computing cluster at the Base Facility.
The second phase of activities under Full System AI&T is designed to complete the technical integration of the three principal subsystems and EPO, show full compliance with system level requirements as detailed in the Observatory System Specifications and system level interface control documents, and provide full scale data for further DM/EPO software and algorithmic testing and development. System level requirements that flow directly to subsystems without any further derivation will be tested for compliance, at the subsystem level and below, under the supervision of Project Systems Engineering. This document includes the general approach and goals for these tests. It is expected that roughly four (4) months into the Full System AI&T phase the telescope and camera will be fully integrated and routinely producing science grade images over the full field of view (FOV), at which point “System First Light” will be declared. Following System First Light will be an intensive data acquisition period design to test the image processing pipelines and validate the derived science products that are to be delivered by the LSST survey.
The third and final phase of activities under Science Validation is designed to fully characterize the system performance specifications detailed in LSST System Requirements Document and the range of demonstrated performance per the LSST Science Requirements. These activities are based on the measured “On-Sky” performance and informed simulations of the LSST system.
In this paper we describe the inputs and assumptions to the commissioning plan, a summary of the activities in each phase, management strategies and expected outcomes.
H. T. Diehl, E. Neilsen, R. Gruendl, B. Yanny, T. M. Abbott, J. Aleksić, S. Allam, J. Annis, E. Balbinot, M. Baumer, L. Beaufore, K. Bechtol, G. Bernstein, S. Birrer, C. Bonnett, D. Brout, C. Bruderer, E. Buckley-Geer, D. Capozzi, A. Carnero Rosell, F. Castander, R. Cawthon, C. Chang, L. Clerkin, R. Covarrubias, C. Cuhna, C. D'Andrea, L. da Costa, R. Das, C. Davis, J. Dietrich, A. Drlica-Wagner, A. Elliott, T. Eifler, J. Etherington, B. Flaugher, J. Frieman, A. Fausti Neto, M. Fernández, C. Furlanetto, D. Gangkofner, D. Gerdes, D. Goldstein, K. Grabowski, R. Gupta, S. Hamilton, H. Head, J. Helsby, D. Hollowood, K. Honscheid, D. James, M. Johnson, S. Jouvel, T. Kacprzac, S. Kent, R. Kessler, A. Kim, E. Krause, C. Krawiec, A. Kremin, R. Kron, S. Kuhlmann, N. Kuropatkin, O. Lahav, J. Lasker, T. Li, E. Luque, N. Maccrann, M. March, J. Marshall, N. Mondrik, E. Morganson, D. Mudd, A. Nadolski, P. Nugent, P. Melchior, F. Menanteau, D. Nagasawa, B. Nord, R. Ogando, L. Old, A. Palmese, D. Petravick, A. Plazas, A. Pujol, A. Queiroz, K. Reil, A. Romer, R. Rosenfeld, A. Roodman, P. Rooney, M. Sako, A. Salvador, C. Sánchez, E. Sánchez Álvaro, B. Santiago, A. Schooneveld, M. Schubnell, E. Sheldon, A. Smith, R. Smith, M. Soares-Santos, F. Sobreira, M. Soumagnac, H. Spinka, S. Tie, D. Tucker, V. Vikram, K. Vivas, A. Walker, W. Wester, M. Wiesner, H. Wilcox, P. Williams, A. Zenteno, Y. Zhang, Z. Zhang
The Dark Energy Survey (DES) is an operating optical survey aimed at understanding the accelerating expansion of the universe using four complementary methods: weak gravitational lensing, galaxy cluster counts, baryon acoustic oscillations, and Type Ia supernovae. To perform the 5000 sq-degree wide field and 30 sq-degree supernova surveys, the DES Collaboration built the Dark Energy Camera (DECam), a 3 square-degree, 570-Megapixel CCD camera that was installed at the prime focus of the Blanco 4-meter telescope at the Cerro Tololo Inter-American Observatory (CTIO). DES has completed its third observing season out of a nominal five. This paper describes DES “Year 1” (Y1) to “Year 3” (Y3), the strategy, an outline of the survey operations procedures, the efficiency of operations and the causes of lost observing time. It provides details about the quality of the first three season's data, and describes how we are adjusting the survey strategy in the face of the El Niño Southern Oscillation.
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