Astronomy of the Next Decade: From Photons to Petabytes. R. Chris Smith AURA Observatory in Chile CTIO/Gemini/SOAR/LSST

Transcription

1 Astronomy of the Next Decade: From Photons to Petabytes R. Chris Smith AURA Observatory in Chile CTIO/Gemini/SOAR/LSST

2 Classical Astronomy still dominates new facilities Even new large facilities (VLT, Gemini, ALMA, GMT, E-ELT) are and will be scheduled for individual projects Ø In units of nights, sometimes hours! But methods are changing Ø Sloan Digital Sky Survey led the way Statistical analyses -> new discoveries Ø Surveys and science with massive datasets are growing, filling an important need Photons to Petabytes

3 Today s BIG Questions: Dark Energy & Dark Matter Dark Energy is the dominant constituent of the Universe. Dark Matter is next. 95% of the Universe is in Dark Energy and Dark Matter, for which we have little or no detailed understanding and 2003 Science breakthroughs of the year, 2011 Nobel Prize Photons to Petabytes

4 Attacking the Question of Dark Energy & Others Classical approach won t work Ø Not enough telescope time in 2-5 night chunks LARGE SURVEYS Ø Goal: Provide large, uniform, well calibrated, controlled, and documented datasets to allow for advanced statistical analyses Ø Larger and broader collaborations provide both manpower and diverse expertise NEED Ø NEW INSTRUMENTS Ø NEW TELESCOPES Ø NEW METHODS Photons to Petabytes

5 Sociology of Dark Energy While Dark Energy is pushing the universe APART But it is pulling the Astronomy, Physics, Mathematics, and Computer Science communities TOGETHER Ø New physics Ø New facilities, creating LARGE datasets Ø New access methods (fast networks, databases) Ø New processing capabilities (h/w & s/w) Ø New analysis methods, New algorithms AURA Introduction

6 Selected Examples: Coming soon to nearby mountaintops New Instruments (DECam) New Telescopes (LSST) Photons to Petabytes

7 Dark Energy Survey (DES) 5 year project to improve our understanding of Dark Energy Ø Key DOE/NSF collaboration: Fermilab/NOAO/NCSA Ø International collaboration: Brazil, UK, Spain, Germany Characterize Dark Energy with four methods Ø Supernovae Ø Weak Lensing (also measure Dark Matter) Ø Galaxy clustering Ø Baryon Acoustic Oscillations All depend on careful statistical analyses of large datasets Photons to Petabytes

8 Dark Energy Camera CAMERA: x 4096 pixel CCDs 570 Megapixel camera The largest focal plane for astronomy in S. Hemisphere Optical Lenses Photons to Petabytes

9 DECam is here TODAY First light images: September 12, 2012 Fornax galaxy cluster Photons to Petabytes

10 Photons to Petabytes

11 A modest data challenge Each image 1GB; up to ~1 TB of raw data/night Ø Data must be moved from Chile to NCSA before next night begins (<18 hours), preferably in real time Ø YEAR 1: Each image transferred in <120 sec Ø Data must be processed within <24 hours to inform next night s observing: using NCSA resources Ø YEAR 1: Real-time pipeline processing on Tololo with LIneA QuickReduce pipeline: robust and reliable Ø Initial processing completed at NCSA in <24 hours, still with only limited data quality specifications TOTAL 5-year project dataset will be ~5 PB Photons to Petabytes

12 The next step ca POSS (Photographic) ca SDSS (Digital) ca DES (Digital + Depth) ca LSST (Digital Sky +Time Domain) Photons to Petabytes

13 Next Step = LSST: Creating a Digital Universe LSST is designed to image the whole sky every few nights for 10 years, giving us a movie-like window into our dynamic Universe. Photons to Petabytes M Telescope 3.5 Degree Field Of View Telescope Located in Chile on Cerro Pachón 3.2 Billion Pixel Camera ~40 Second Cadence Two 15 second exposures Full sky coverage every few nights Advanced Data Management Systems Public Data Alerts of new events Catalogs of object Archives of images 13

14 The Large Synoptic Survey Telescope Massively Parallel Astrophysics Survey the entire sky every 3-4 nights, to simultaneously detect and study: Ø Dark Matter via Weak gravitational lensing Ø Dark Energy via thousands of SNe per year Ø Potentially hazardous near earth asteroids Ø Tracers of the formation of the solar system Ø Fireworks in the heavens GRBs, quasars Ø Periodic and transient phenomena Ø... the unknown Photons to Petabytes

15 Why is the LSST so unique? Primary Mirror Diameter Field of View 0.2 degrees Gemini South Telescope 8 m 3.5 degrees (Full moon is 0.5 degrees) LSST 8.4 m Photons to Petabytes

16

17 Telescope and Site 30 m diameter dome 1.2 m diameter atmospheric telescope Control room and heat producing equipment (lower level) 1,380 m 2 service and maintenance facility Base Facility 350 ton telescope Includes the facilities, and hardware to collect the light, control the survey, calibrate conditions, and support all LSST summit and base operations. Photons to Petabytes

18 Camera 3.2 Gigapixel science array 10 square degree FOV! Wavefront and guide sensors 2 second readout 5 filters in camera Utility Trunk houses support electronics and utilities Cryostat contains focal plane & its electronics 1.65 m (5-5 ) Filter L3 Lens Focal plane Camera ¾ Section L1 Lens L2 Lens Photons to Petabytes

19 Petascale Data Management Each image roughly 6.5GB Cadence: ~1 image every 18s 15 to 18 TB per night, 30TB reduced! Ø ALL must be transferred to NCSA archive center within image timescale (17s), >>10 Gbps REAL TIME reduction, analysis, & alerts Ø Send out alerts of transient sources within 60s ~2 million events per night every night for 10 years Ø Provide automatic data quality evaluation, alert to problems Ø Change survey observing strategy on the fly based on conditions, last field visited, etc. Photons to Petabytes

20 LSST: Data Science in real time TRANSIENT SCIENCE (Data Stream) Ø >3 Terabytes per hour (reduced) that must be mined in real time for alerts. Ø 20 billion objects will be monitored for important variations in real time. Ø ~2 million events per night every night for 10 years New approaches must be developed for knowledge extraction in real time NON-TRANSIENT SCIENCE Ø >10 10 objects in a 20 PB final database catalog, backed by a 100 PB final image archive New approaches to data mining needed to sift through data to identify samples, or individual objects, of interest Photons to Petabytes

21 Data Management Sites and Centers HQ Site HQ Facility Observatory Management Science Operations Education and Public Outreach Archive Site Archive Center Alert Production Data Release Production Calibration Products Production EPO Infrastructure Long-term Storage (copy 2) Data Access Center Data Access and User Services French Site Proposed Center Base Site Base Facility Long-term storage (copy 1) Data Access Center Data Access and User Services Summit Site Summit Facility Telescope and Camera Data Acquisition Crosstalk Correction Photons to Petabytes

22 LSST Data Management: Baseline Solutions High-speed connectivity Ø Mountain to Base: >100 Gbps Ø Base to Archive: >10 Gbps (hopefully 100Gbps) Ø Archive to User: variable, UI challenge Supercomputer processing & storage Ø Base in La Serena, NCSA, Others? (France?, Brazil?) Ø 100 PB final image archive Ø Distributed (Grid) analysis facilities Petascale DB (~20 PB final catalog) Ø Based on open source RDBMS Photons to Petabytes

23 LSST: Strategic Partnerships Distributed Computing Systems Ø Supercomputer center(s) to provide bulk storage, large scale processing (e.g., NCSA, NLHPC in Chile) Ø Grid processing, storage, advanced DB Ø Data Access for member countries/institutions Connectivity Ø High-speed Chilean bandwidth (REUNA) Ø International bandwidth (AmLIGHT, RedCLARA) Scientific Analysis Challenges: Data Mining & Astro-Informatics or Astro-Statistics Ø Separating small signals from systematic effects Ø Automatically finding unique objects: one in billions Photons to Petabytes

24 LSST Outreach Data will be used in classrooms, science museums, and online Classroom Emphasis on: Data-enabled research experiences Citizen Science College classes Collaboration through Social Networking Photons to Petabytes

25 Integrated Project Schedule with Key Milestones FUNDING STARTS NOW!

26 The Science of Big Data Data growing exponentially, in all sciences Changes the nature of science from hypothesis-driven to data-driven discovery Cuts across all sciences Industry and government face the same challenges Convergence of physical and life sciences through Big Data (statistics and computing) A new scientific revolution Photons to Petabytes

27 27

28 Construction NOW First light in 2019 Operations in 2022 DOE/NSF Joint Interface and Management Review Tucson, Arizona May 30- June 1, 2012