1 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Name of Meeting Location Date - Change in Slide Master Title of Presentation Andrew Connolly LSST Simulation Scientist 22 nd October 2013 FINAL DESIGN REVIEW October , 2013

2 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Summary of high level requirements Survey PropertyPerformance Main Survey Area18000 sq. deg. Total visits per sky patch825 Filter set6 filters (ugrizy) from 320 to 1050nm Single visit2 x 15 second exposures Single Visit Limiting Magnitude u = 23.9; g = 25.0; r = 24.7; I = 24.0; z = 23.3; y = 22.1 Photometric calibration< 2% absolute, < 0.5% repeatability & colors Median delivered image quality~ 0.7 arcsec. FWHM Transient processing latency< 60 sec after last visit exposure Data releaseFull reprocessing of survey data annually

3 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Simulations are managed through systems engineering Project Manager: Victor Krabbendam Project Scientist : Zeljko Ivezic Science Council Telescope and Site Project Manager Bill Gressler Subsystem Scientist Open Education and Public Outreach Manager Suzanne Jacoby Subsystem Scientist Tim Axelrod Data Management Project Manager Jeff Kantor Subsystem Scientist Mario Juric Camera Project Manager Nadine Kurita Subsystem Scientist Steve Ritz Systems Engineer George Angeli Systems Scientist Chuck Claver Calibration Scientist Tim Axelrod Simulation Scientist Andy Connolly Op. Simulation Scientist Abi Saha Business Manager Daniel Calabrese Safety Manager Chuck Gessner LSST Director Steven Kahn Deputy Director Open Chief Scientist Tony Tyson Science Advisory Committee Michael Strauss

4 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 LSST science and engineering tools

5 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 The tools provide a range of fidelities − Engineering design tools Zemax, FRED, FEA, CFD, Filters, Camera thermal and compensation models Detailed design tools but not coupled to the astrophysics of the sky − Parametric and statistical tools Sizing models, throughput and signal-to-noise generation, pipeQA Efficiently characterize source properties as a function of the system − Survey performance tools Operation simulator, SSTAR Characterize the general survey properties using outputs from the design tools and the science requirements − Catalog and image modeling tools CalSim, ImSim, precursor data End-to-end evaluation of the performance to the LSST (including data management and the impact of the as-delivered sub components)

6 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Data driven models of the universe Extensive use is made of existing ground and space-based data sets to characterize the expected properties of the LSST and the data management frameworks (e.g. SDSS, CFHTLS, Suprimecam, COSMOS) Existing data sets capture the complexity of the data including the impact of the atmosphere, source variability, source density and variations in morphology. Existing data sets do not, however, provide “truth-tables” nor do they enable the impact of individual subsystems to be evaluated Analyses based on precursor data HSTSubaru

7 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Data driven models of the universe − Source counts are based on simulations of the universe matched to observed densities and color of sources. For example, galaxy catalogs are based on the Millennium survey (de Lucia et al 2006) but modified to reproduce the observed number counts, size distributions, and redshifts. − Simulations complement the observed data, providing a simplified view of the sky which can be used as a reference to evaluate the performance of the LSST system A universal model of the sky r magnitude Log 10 (N) (deg) -2 (0.5 mag) -1

8 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Engineering and science are integrated The number of visits as a function of engineering properties Number of Visits Run of the Cadence Simulator

9 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Sensitivity Analyses

10 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Throughput probability Wavelength (nm) Parametric and statistical tools − Throughput simulations Driven by engineering inputs from the optical design, sensor model, filter design, modtran Delivers SNR calculations, depths, colors and counts as a function of SED and integration time − Data sizing models Driven by the universal model, operations simulator, technology predictions, DM projections Enables the trace of the propagation of requirements to final data management outputs (cost, CPUs, disks, etc.). Change in m 5 Instrumental noise

11 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Survey performance tools − Operations simulations The constraints on the operations simulator are provided by the astrophysical properties of the site (e.g. sky background, visibility), the engineering models (settle time, read out time), and the science requirements OpSim delivers, in a queriable database, sequences of observations together with their properties. These outputs drive the sizing models, image simulations, calibration simulations. see talk by Abi Saha

12 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Calibration and source simulations − Calibration simulations take data from the universal model, the observation sequences, engineering designs for the vignetting, illumination correction, scattered light (FRED), atmosphere, and sky background − Observations are generated (with the expected signal and noise) covering large sequences of observations. − A calibration solver performs a self- calibration process, producing calibrated magnitudes, patch zeropoints, and the illumination correction together with performance metrics − The results have been used to refine the flowdown from SRD to system design In two years we meet the 10 year SRD requirements on uniformity and repeatability SRD: 10 mmag SRD: 5 mmag see talk by Tim Axelrod

13 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Data analysis and image generation − For image simulations, LSST telescope and camera optical designs are integrated with outputs from OpSim and the universal model to generate representative data from the LSST − Supplementing observational data sets, the images (and reference catalogs) enable end- to-end comparisons that test the performance of the DM pipelines with realistic source densities, and data footprints − Large scale runs (7TB of images touching 5x10 9 sources) test the robustness and scalability of algorithms − The image simulation system is developing into a framework for the validation of the as- delivered components See talk by John Peterson

14 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Development through construction

15 FINAL DESIGN REVIEW | TUCSON, AZ | OCTOBER 21-25, 2013 Future Development