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Next Generation Sky Surveys
Astronomical Opportunities
and Computational Challenges
Bob MannWide-Field Astronomy UnitSchool of
Physics Astronomy University of Edinburgh
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Outline

• Survey Astronomy 101
• Next Generation Sky Surveys
• Astronomical Opportunities
• Computational Challenges
• eSI Theme
• Summary and Conclusions

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Observational astronomy
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Observational astronomy

• Old Style
• Many small programmes
• Target specific objects
• Manual data reduction
• Data ends up in astronomers desk drawer
• Cold nights in the dome

• New Style
• Few large surveys
• Map large areas of sky
• Automated pipelines
• Data ends up inqueryable database
• Days at the computer

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What is driving these changes?

• Policy common user instruments
• Software archive part of instrument project
• Economics
• More science per night of telescope time
• Technology
• Detectors capable of higher throughput
• IT can handle the resultant higher data rates

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How big is a sky survey dataset?

• 1. How big is the sky?

dOsin? d? df
?dO 4p steradians 4p (180/p)2 square
degrees 41,253 square degrees
c.f. area of full moon 0.2 square degrees
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How big is a sky survey dataset?

• 2. How detailed a map?
• Resolution of ground-basedimages limited by
  seeing
• Point-source disk 0.5 arcsec
• (1 arcsec 1/3600th of a degree)
• Sample images adequately
• few 100 million pixels per square degree
• (i.e. cover full moon with few 10s of million
  pixels)

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How big is a sky survey dataset?

• 3. How much storage?
• 2-4 Bytes per pixel adequate for dynamic range
• Full sky image map few x 10 TB
• Catalogue 10 of image size
• Full sky catalogue few TB

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Comparing survey systems

• Figure-of-merit étendue
• Quantifies speed to map a given area of sky to a
  given depth under fixed observing conditions
• Conventional optics A O

• A x O

Field of View
Area of telescope primary mirror


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Three generations of sky surveys

• The Photographic Era 1950-2000

Schmidt Telescope
Digitisation
SuperCOSMOS 1 plate 2GB image, 105-106 objects
O huge A modest
2,500 SuperCOSMOS requests per day
Hubble GuideStar Catalog
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Three generations of sky surveys

• 2. First Born-Digital Era 1995-2015
• 1997-2001 2MASS (near-IR)
• 2000-2014 SDSS (optical)
• 2005-2012 UKIDSS (near-IR)
• 2009-2015 VISTA (near-IR)

Smaller AO than Schmidts, but digital detectors
much more sensitive that photographic emulsions
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Three generations of sky surveys

• 3. Synoptic surveys 2009-2030
• Map observable sky every few nights huge AO
• Pan-STARRS PS1-2009 PS2-2012
• PS4-2015? PS16-??
• LSST 2017-2027

LSST
Mass production of detectors can afford to
cover large O
Pan-STARRS 1.4 Gigapixel camera
PS4
LSST 3.2 Gigapixel camera
PS1
SDSS
VISTA
Worlds largest camera in civilian use
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Three generations of sky surveysData Volumes

• Schmidt surveys
• 60 years of observing time
• 10 years of digitisation by SuperCOSMOS
• 20TB of image data
• VISTA
• 20TB of image data per year
• LSST
• 20TB of image data per night for a decade

How come? - Full sky image map few x 10 TB
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Astronomical discovery space
Area
Temporal Resolution
Polarization
Wavelength
Angular Resolution
Depth
Different science goals require coverageof
different regions of this space
Surveys covering a larger region of thisspace
can address more science goals
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Examples

• LSST
• Five optical bands
• Large area
• Deep
• 1000 visits per field

• Gaia
• Wide wavelength coverage
• Large area
• Good positional accuracy
• 100 visits per field

• Euclid
• Large area
• Good image quality

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Summary of Survey Astronomy 101

• Systematic survey astronomy gt 50 years old
• UK world-leaders throughout this history
• Progress through advances in detector technology
• Photographic Digital
  Cheap(er) Digital
• Multi-dimensional discovery space
• Specific science goals target specific regions of
  it
• High-grasp telescopes cover greater volume more
  science
• Data volumes increasing dramatically
• Importance of computation increasing as a result

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Outline

• Survey Astronomy 101
• Next Generation Sky Surveys
• Astronomical Opportunities
• Computational Challenges
• eSI Theme
• Summary and Conclusions

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Next Generation Sky Surveys

• Ground-based
• Pan-STARRS PS1, PS2, PS4,
• Dark Energy Survey
• LSST
• Space-based
• Gaia
• Euclid
• All large international projects
• UK share in each would be 10s of M
• Can we afford a significant role in all of them?

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Outline

• Survey Astronomy 101
• Next Generation Sky Surveys
• Astronomical Opportunities
• Computational Challenges
• eSI Theme
• Summary and Conclusions

Illustrate with LSST
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Astronomical Opportunities

• Survey science is statistical in nature
• Describing properties of populations
• e.g. clustering of galaxies stellar
  populations within galaxies
• Detecting outliers from those populations
• e.g. very distant quasars very low mass
  stars

Needlargesamples
Rare
Need to sample large volume
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Science with LSST

• Four themes
• Probing dark energy dark matter
• Taking an inventory of the solar system
• Exploring the transient optical sky
• Mapping the Milky Way
• Quantity scientific goals from themes
• Parameterize survey system
• Mirror size, pixel scale, cadence of observations
• Optimise system parameters
• Ivezic et al http//arxiv.org/abs/0805.2366

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LSST opportunities challenges

• Opportunities
• 60PB of image data
• 6PB of catalogue
• Catalogue will contain
• 10 billion stars
• 10 billion galaxies
• 1 million supernovae
• 5 million asteroids
• New phenomenae!

• Challenges
• How to ship and store all the data?
• How to keep up with data processing?
• How to find transients in real-time?
• How to provide data to user community?
• How to recognise new classes of variable?

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Example challenges1. Data Management

• Users will want to analyse subsets of LSST data
  that are too large to download
• Must run data analysis code at the data centre
• Relational model doesnt support all sorts of
  astronomical analysis well
• SciDB generalisation of relational model based
  on multidimensional arrays
• Better coupling to analysis code

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Example challenges2. Data Analysis

• Many classes of transient require rapid follow-up
  observations for identification
• Requirement issue alerts for transient discovery
  within 1 minute of observation being made
• High-performance data reduction system - both
  hardware and software 2TB/hour data rate
• Real-time pattern-matching algorithms, yielding
  few false positives

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Its clear that astronomers need interaction with
computer scientists, but is the converse true?
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Outline

• Survey Astronomy 101
• Next Generation Sky Surveys
• Astronomical Opportunities
• Computational Challenges
• eSI Theme
• Summary and Conclusions

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Three strands

• Scientific Prioritisation
• We cant afford significant roles in all
  surveyswhich should we go for?
• Data Management
• Can we retain the RDBMS-based approach were used
  to? or do we need Sci-DB?
• Data Analysis
• Can we produce scalable algorithms for the kinds
  of analysis we want to run?

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Goals of the theme

• Prepare a Road Map for future survey astronomy in
  the UK for STFC
• Identify those computational topics where further
  RD is required
• Engage computer science community in addressing
  those problems

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Summary Conclusions

• Next generation of sky surveys are different in
  kind
• Enabling new kinds of science time domain
• Requiring new computational techniques
• To prepare for them the astronomy community must
• Agree on its priorities amongst them
• Assess the feasibility of the desired options
• Identify the problems needing additional RD
• Engage the computer science community in solving
  them
• This Theme should make progress on all these
• Many thanks to eSI for giving us the opportunity
  to do so!