From Photons to Petabytes:

Astronomy in the Era of Large Scale Surveys and Virtual Observatories

R. Chris Smith AURA/NOAO/CTIO

• • • • • •

“Classical” (Optical) Astronomy

1-4 investigators propose for telescope time Obtain 1 to 5 nights, or 1 to 5 hours!

 Oversubscription on largest telescopes (e.g. Gemini!) severely limits time per investigator Travel to distant telescope site  or not: Remote Observing, Service Observing, Queue Observe  or not: clouds (OUCH!) Take 5 to 50 GB of data home (on tapes) Reduce & Analyze “by hand”   Extract every detail from those bits Often takes months per night of data

Optical Windows

QuickTime™ and a Motion JPEG A decompressor are needed to see this picture.

Can “classical” techniques answer the BIG questions?

• • • • Where do we come from?

 Star Formation, Nucleosynthesis Are we alone?

 Proto-planetary disks, search for planets Where are we going?

 Big Bang & the Expansion of the Universe What is the Universe made of?

 What types of matter? What types of energy?

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.

1998 and 2003 Science breakthroughs of the year

Brief History of Dark Energy

• 1990s  Wanted to measure the DECELERATION of the Universe  Use SUPERNOVAE as cosmic yardsticks

Type Ia Supernovae are powerful cosmological probes Distances to ~6% from brightness Redshifts from features in spectra (Pete Challis, Harvard-Smithsonian Center for Astrophyics Hubble Space Telescope, NASA)

Type Ia SNe:

One Parameter Family

Standardizable Candles

Color Rate of decline Peak brightness -- gives - δd/d ~ 0.06

 ~ 0.13 mag (Supernova Cosmology Project, Kim et al)

An Accelerating Universe?!

Riess et. al. 1998

A Repulsive Result

• Expansion of Universe is accelerating ?

• Implies something WRONG?

 Two independent competing teams: SAME result  Some sort of dust? Evolution?

“Higher-z” SN team: 8 new SN @ z>1.0

Riess et al, ApJ, 2004

A Repulsive Result

• Expansion of Universe is accelerating !!!

• Implies something NEW!

• Regions of empty space REPEL each other!

 “Cosmological constant”? • Einstein’s greatest blunder… OR NOT?!!

 Something going on in the vacuum?

What is Dark Energy?

G  + f(g  ) = 8  G [ T  (matter) + T  (new) ] ????

● ●

Two philosophically distinct possibilities:

Gravitational effect, e.g. Cosmological Constant, or gravity “leaking” into extra dimensions A “Vacuum energy” effect, decaying scalar field

New Fundamental Physics!

Sociology of Dark Energy

• Dark Energy may be pushing the universe APART • But it is pulling the Astronomy & Physics communities TOGETHER  HEP interests in fundamental physics  HEP experience in large datasets

Attacking the Question of Dark Energy

• • “Classical” approach won’t work   Not enough telescope time Difficult to control calibrations & systematics LARGE SURVEYS  Goal: Provide large, uniform, well calibrated, controlled, and documented datasets to allow for advanced statistical analyses  Control calibrations & systematics to <1%  Larger collaborations provide both manpower and diverse expertise • Including both traditional astronomers and high-energy physicists

Dark Energy ROADMAP to understanding

• • • • Today  ESSENCE , large international group of astronomers Coming Soon to a telescope nearby  Dark Energy Survey • Camera built by Fermilab, majority DOE funding • Data Management System led by NCSA • Groups from Spain and United Kingdom recently joined The next BIG step  LSST • Camera built by SLAC, Data Mgmt with NCSA, • NSF + DOE funding, also inc. LLNL, Brookhaven, others Stepping UP  Space-based work: JDEM • NASA + DOE funding (SNAP and/or others)

Today: ESSENCE (+SuperMACHO)

• • • Use a LARGE (~200 SNe), UNIFORM set of supernova light curves to allow us to study the evolution of the expansion of the universe  Constrain “w”, the equation of state parameter of Dark Energy, to ~10% 30 half-nights per year for 5 years (2002-2006) Use other half of nights to constrain possible DARK MATTER candidates   The ‘SuperMACHO’ project Search the Large Magellanic Cloud for microlensing

Searching for Supernovae (and other transients)

High-z SN Team

The Strategy

• • • • • Repeatable Reliable Wide-field Multi-color Imaging • • CTIO Blanco 4m + MOSAIC II Every other night, Oct - Dec, 2002-2006

ESSENCE+SuperMACHO The data flows…

• • • • • • The telescope  CTIO’s Blanco 4m The camera  MOSAIC 8Kx8K imager (67 megapixels) Exposures of 60s to 400s Collect 20GB of RAW data per night Data must be reduced and analyzed in near REAL TIME (within ~10min) Data ‘Reduction’ = 5x EXPANSION!

 Roughly 3TB per year

… and flows

• • MUCH larger data flow than most other astronomical projects With ADDITIONAL complication of real-time reduction & alert requirement  Must plan spectroscopic follow up on LARGEST telescopes (Gemini, Keck, VLT, Magellan, …) • • We THOUGHT we were ready  A few CPUs (cluster of 20 x 1GHz)  A few disks (4 x 4TB “data bricks”) But…

Challenges

• • • Moving the data  From Chile to the U.S.

Storing the data    Filling up racks with “data bricks” Keeping track of the data Initial database didn’t cut it Reprocessing the data  Pipeline can keep up with real time flow  But need to reprocess past years of data when improvements are made to software

Coming Soon (2009?): Dark Energy Survey

• Investigate Dark Energy using 4 complementary and independent methods  Various types of distance measurements, based on standard luminosities, standard yardsticks, and standard volumes • Combine the results to provide the best (to date) constraints on the equation of state of Dark Energy

The Instrument: Dark Energy Camera

• •

Focal Plane:

64 2k x 4k CCDs • Plus guiding and WFS 0.5 GIGApixel camera • Will be the largest focal plane built to date

The Data: Dark Energy Survey

• • • • • • Each image = 1GB 350 GB of raw data / night Data must be moved to NCSA before next night begins (<24 hours)  >36Mbps internationally Data must be processed within ~24 hours  Need to inform next night’s observing Total raw data ~0.2 PB TOTAL Dataset 1 to 5 PB  Reprocessing planned using Grid resources

Astrophysical Exploration

• • • • • Wavelength Angular resolution Area surveyed Depth Time resolution Image from DLS & Tony Tyson

LSST: The Instrument

• • • 8.2m telescope  Optimized for WIDE field of view (FOV) 3.5 degree FOV 3.5 GIGApixel camera • • • Deep images in 15-30s Able to scan whole sky every 4-5 nights Site: either Baja, CA or Northern Chile

LSST: The Data Flow

• • • • Each image roughly 6.5GB

Cadence: ~1 image every 15s 15 to 18 TB per night  ALL must be transferred to U.S. “data center” • within <24 hours, 4Gbps internationally • Possibly within image timescale (15s), ~10Gbps REAL TIME reduction, analysis, & alerts  Send out alerts of transient sources within minutes  Provide automatic data quality evaluation, alert to problems  Change survey observing strategy on the fly based on conditions, last field visited, etc.

LSST: The Data Flow

LSST: The Data Flow

DES, LSST, … and now for the REST of the Science

• • • Ongoing (ESSENCE, SuperMACHO, etc.) and future (DES, LSST, etc.) projects will provide PETABYTES of archived data Only a small fraction of the science potential will be realized by the planned investigations How do we maximize the investment in these datasets and provide for their future scientific use?

The Virtual Observatory

• • What is VO?

 Provides the framework for global access to the various data archives by facilitating the standardization of archiving and data-mining protocols.

 Enables data analysis by providing common standards and state-of-the-art analysis tools which work over high-speed wide area networks What is VO not?

 An organization funded to provide a single universal archive of all astronomical data  A provider of resources (storage, computation, bandwidth)

A Global Effort

VO Challenges

• • Provide Access to the Content  Multiple distributed archives, some on the scale of many petabytes  Archives provide content, the VO knits those resources together Provide the Standards  Allow variety of archives talk to each other  Develop generalized data model(s) for different instruments/different wavelengths

VO Challenges

• • • Provide the User Interfaces  Streamline data discovery, data understanding, data movement, and data analysis Support the Analysis  Support large queries across distributed DBs  Support statistical analysis across results (Grid) All the “boring” bits (infrastructure)  Security, handshaking, resource management

Chris Miller/NOAO

One Archive’s View of VO

NOAO’s Data Products Program

• • • Management of data from all NOAO and some affiliated facilities  KPNO, including Mayall 4m (MOSAIC, NEWFIRM)  CTIO, including Blanco 4m (MOSAIC, ISPI)  SOAR & WIYN systems Provide access to large volume (TBs to PBs) of archived ground-based optical & infrared data and data products  Virtual Observatory “back end”; CONTENT Enable science based upon distributed data and data products, developing tools and services  Virtual Observatory “front end”; UI and TOOLS

Strategic Partnerships

• • • • In Local Systems  Vendors: Local Storage, Processing, Servers In Remote Systems  Supercomputer center(s) to provide bulk storage, large scale processing (e.g. NCSA, SDSC’s SRB)  Grid processing, storage Connectivity  High-speed national and international bandwidth Scientific   VO Partners to develop standards, provide tools  Providing services to, and collecting feedback from, physics and astronomy user communities Providing strong VO node in South America

• Hi ho, hi ho… • Back to looking for dark energy and other diamonds in the data mines…