Peking University Astronomy Symposium 10/17/2010

1. Sciences and Challenges with LSST Hu ZhanNational Astronomical Observatories Chinese Academy of Sciences Peking University Astronomy Symposium 10/17/2010 Large Synoptic Survey Telescope

2. US Astro2010 Decadal Survey

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

4. The Large Synoptic Survey Telescope Huge discovery space • 8.4-meter primary • 10 deg2 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: • Dark energy/matter • Solar system • Optical transients • Galactic map • A sample of • Billions of galaxies • Millions of SNe • 105 galaxy clusters • 20,000 deg2 • u 25.8mag • g 27.0 mag • r 27.2 mag • i 27.0 mag • z 25.7 mag • y 24.4 mag arXiv:0805.2366 www.lsst.org First light ~ 2016/2017 (funding start +4 years)

5. Planned Surveys 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

6. Site & Camera Cerro Pachón

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

8. LSSTCost (LSST Estimates) Operations Cost: 36.7M 2009 USD Must secure 1/3 of operations cost from international and private partners.

9. 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 LSSTMember Institutes

10. LSST Science Collaborations • Solar System: Lynne Jones & Mike Brown • Stellar Populations: Kevin Covey & Knut Olsen • Milky Way Structure: Beth Willman & Marla Geha • Transients/variable stars: Josh Bloom & Lucianne Walkowicz • Galaxies: Harry Ferguson • Active Galactic Nuclei: Niel Brandt • Supernovae: Michael Wood-Vasey & Rick Kessler • Strong gravitational lensing: Phil Marshall • Large-scale Structure/BAO:Hu Zhan & EricGawiser • Weak lensing: David Wittman & Bhuv Jain • Informatics and Statistics: Kirk Borne • More than 300 members. LSST Science Book： http://www.lsst.org/lsst/scibook

11. Recent Collaboration Meeting Marana, Arizona, Aug 9-13, 2010

12. LSST Sciences: the Solar System 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. LSSTSciences: the Milky Way Upper left: simulation of Milky Way stellar streams and LSSTobservable 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. LSSTSciences: Galaxies SDSS z = 0.1 MUSYC UVR 29.5mag/sq” Comparable to LSST SB limit

15. LSSTSciences: Transients

16. LSSTSciences: Cosmology “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. WIMP? (SUSY: neutralino? gravitino?) Axion? HEPAP Cosmological Constant? Quintessence? Modified Gravity? Back reaction? Brane world? Landscape? NRC NRC NSTC

17. Data ChallengesProcessing, Analysis, & Management • 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. Data Processing Challenges detection background deblending astrometry photometry PSF shape classification time sequence redshift extinction mask selection stacking correlation …

19. Computational Needs • 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)2×3×109floating 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 104 FPOs per pixel, so LSST will need ~20TFLOPSon site to process data in real time. The hardware part is fairly easy. • To process LSST 2000×2000 exposures (3×109 pixels each) once, even if just one FPO per pixel, it would take a 100TFLOPScomputer 120s. With all the complex processing, the LSST data archive center needs ~200 TFLOPScapacity. The hardware requirement is moderate. • Desktop I/O: 6GB÷100MB/s = 60s; 8 years for 4×106 exposures. • Correlation functions of billions of objects… • Parameter fitting/minimization in high-dimensional space… • The software challenge is daunting!

20. Learn from End-to-End Simulations Must understand the system performance and systematics!

21. Image Simulation: PSF LSSTwill soon simulation ~50TBof images, taking ~2M CPUhours.

22. Image Simulation

23. Justification for (Joining) LSST • 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. Cost of Foreign Membership in LSST 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.

25. Discussion • Questions? • Interests? • Suggestions? • Resources? • Actions?