1. Peking University Astronomy Symposium 10/17/2010 Large Synoptic Survey Telescope

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3. 3 Data = Discovery Space A new mode of astronomy research: data mining a new breed: keyboard astronomer

4. 8.4-meter primary 10 deg 2 FOV 3 billion pixels 0.2”/pixel 0.3–1.1 µm ugrizy 15-s exposures 8 hours/field total 30 TB/night 200 PB total Median seeing 0.7” Key Missions: 1.Dark energy/matter 2.Solar system 3.Optical transients 4.Galactic map First light ~ 2016/2017 (funding start +4 years) 20,000 deg 2 u 25.8 mag g 27.0 mag r 27.2 mag i 27.0 mag z 25.7 mag y 24.4 mag 4 A sample of Billions of galaxies Millions of SNe 10 5 galaxy clusters arXiv:0805.2366 Huge discovery space

5. 5 Deep Wide Survey: 20,000 square degrees Northern Ecliptic: 3300 square degrees ~2.1 pairs per lunation Deep-Drilling: ~100 square degrees more frequent visits Galactic Plane: 1700 square degrees to uniform depth of u: 26.1 g: 26.5 r: 26.1 i: 25.6 z: 24.9 y: 23.5 South Pole: 700 square degrees to a uniform depth of u: 25.5 g: 26.4 r: 26.0 i: 25.3 z: 25.0 y:23.4

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8. Bandwidth 2.5 Gbps avg, 10 Gbps peak Data Archive Center NCSA, Champaign, IL 100 to 250 TFLOPS, 75 PB Data Access Centers US (2) Chile (1) 45 TFLOPS, 87 PB Base Camp Cerro Pachon, La Serena, Chile 25 TFLOPS, 150 TB 8 Lots of science work has to be done at the data center.

9. 9 Must secure 1/3 of operations cost from international and private partners. Operations Cost: 36.7M 2009 USD

10. Brookhaven National Laboratory California Institute of Technology Carnegie Mellon University Chile Columbia University Cornell University Drexel University Google Inc. Harvard-Smithsonian Center for Astrophysics IN2P3 Labs France Johns Hopkins University Kavli Institute for Particle Astrophysics and Cosmology at Stanford University Las Cumbres Observatory Global Telescope Network, Inc. Lawrence Livermore National Laboratory Los Alamos National Laboratory National Optical Astronomy Observatory Princeton University Purdue University Research Corporation for Science Advancement Rutgers University Space Telescope Science Institute SLAC National Accelerator Laboratory The Pennsylvania State University The University of Arizona University of California, Davis University of California, Irvine University of Illinois at Urbana-Champaign University of Pennsylvania University of Pittsburgh University of Washington Vanderbilt University 10

11. LSST Science Book ： http://www.lsst.org/lsst/scibook 11

12. 12 Marana, Arizona, Aug 9-13, 2010

13. Orbital inclination and ellipticity of 88000 asteroids from SDSS. The actual color difference is much smaller. 37 families are found. Through long-term monitoring, LSST will provide precise measurements of orbital parameters as well as photometry and time-domain info of millions of asteroids, significantly improving knowledge about solar system. Parker et al. 2008 13

14. Upper left: simulation of Milky Way stellar streams and LSST observable range (main seq. ~ 100 kpc, RR Lyrae ~ 300 kpc). Right: SDSS data. Left: structure of the MW from 2.5M stars well observed by SDSS. LSST will reach 200M stars and can study the MW structure within 100 kpc. Ivezic et al. 2008 14

15. SDSS z = 0.1 MUSYC UVR 29.5mag/sq” Comparable to LSST SB limit 15

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17. 17 “The acceleration of the Universe is, along with dark matter, the observed phenomenon that most directly demonstrates that our theories of fundamental particles and gravity are either incorrect or incomplete. Most experts believe that nothing short of a revolution in our understanding of fundamental physics will be required to achieve a full understanding of the cosmic acceleration.” – the Dark Energy Task Force, a joint committee to advise DoE, NASA, & NSF on future dark energy research. HEPAP NRCNSTC WIMP? (SUSY: neutralino? gravitino?) Axion? Cosmological Constant? Quintessence? Modified Gravity? Back reaction? Brane world? Landscape? NRC

18. automated data quality assessment & discovery scalability of machine learning and mining algorithms development of grid-enabled parallel mining algorithms designing a robust system for brokering classifications multi-resolution methods for exploration visual data mining algorithms indexing of multi-attribute multi-dimensional databases rapid querying of petabyte databases Many surveys face the same challenges! 18

19. detection background deblending astrometry photometry PSF shape classification time sequence redshift extinction mask selection stacking correlation … 19

20. Transient detection: minimizing ||frame1-kernel  frame2||. If we do not consider how to obtain the kernel, just the convolution part would cost at least 2× (several) 2 ×3×10 9 floating point operations (FPOs). A 3GHz CPU could barely process once within the exposure time of 15s, even if at its theoretical peak performance. The actual demand is several 10 4 FPOs per pixel, so LSST will need ~20TFLOPS on site to process data in real time. The hardware part is fairly easy. To process LSST 2000×2000 exposures (3×10 9 pixels each) once, even if just one FPO per pixel, it would take a 100TFLOPS computer 120s. With all the complex processing, the LSST data archive center needs ~200 TFLOPS capacity. The hardware requirement is moderate. Desktop I/O: 6GB÷100MB/s = 60s; 8 years for 4×10 6 exposures. Correlation functions of billions of objects… Parameter fitting/minimization in high-dimensional space… The software challenge is daunting! 20

21. Must understand the system performance and systematics! 21

22. LSST will soon simulation ~50TB of images, taking ~2M CPU hours. 22

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24. Compelling sciences, broad impact… Note: rights to lead key projects will be competed for. Discovering the unexpected Invaluable aspect of surveys: discovery space. New trend: data intensive astronomy Small investment, 100% data Limited only by computing & network resources Accessible to all levels of expertise Highly complementary to future large telescopes Targets Share the same data challenges of other survey projects Dome A, Chinese Space Station Telescope… Anyone in the US: resource-limited free data access; nonmembers outside the US: no data access. 24

25. 25 Policy is being reformulated. Roughly three parts Construction share: $465M x GDP/USGDP x Astro fraction by start. Operations share: $420M x GDP/ AllGDP x Astro fraction. Data access and computation share: Impact on $16M / year Early MoU will receive discounts. Must pay operations share.

26. Questions? Interests? Suggestions? Resources? Actions? 26