Informatiebijeenkomst: toelichting regelingen en planning (Marcel Kleijn) 13 oktober 2016
Gijs Verdoes Kleijn OmegaCEN, Kapteyn Astronomical Institute, University of Groningen
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Transcript of Gijs Verdoes Kleijn OmegaCEN, Kapteyn Astronomical Institute, University of Groningen
ASTRO-WISE Science“A new approach to astronomical
archiving & researching for the data-flooded era”
Gijs Verdoes KleijnOmegaCEN,
Kapteyn Astronomical Institute, University of Groningen
The OmegaCEN team at Kapteyn
• Edwin Valentijn (lead)• Kor Begeman• Danny Boxhoorn • Erik Deul (Leiden)• Ewout Helmich• Philippe Heraudeau• John MacFarland• Michiel Tempelaar • Gijs Verdoes Kleijn• Ronald Vermeij• Willem Jan Vriend (Lofar)• Kovac, Schneider, Sikkema (PhDs)
Archiving your vision• Camera in front of eye:
– resolution ~5/60 degree (my eye)– Field of view 902 degree– 2x2 pixel sampling per resolution element – #pixels= 21602
– Dynamic range: ~103-5: take 216
– One image ~9Mbyte– One image/sec for 70years: 18Pbyte
• Storage cost (at 0.33euro/Gbyte)~ 6million euro
– ~1010-11 neurons
Brain does something smart…
……intensive linking is a key ingredient.
If vision archive were implanted for re-analysis• Applying improved analysis
– (Raw data: improved calibrations as well)
• Analysis of previously deemed uninteresting parts of data
• Variability analysis• if archives from different persons are combined
– Denser coverage in space+time– 3D construction of 2D view
• If fly’s UV eye archives are added:– Same object at different wavelengths
Aim: exploit data for purposes or in ways not yet conceived ...... flexible, internally linked, information system required
Key properties for intelligent information system
• Adaption: facilitate changes1. Changes due to improved encoded methods2. True physical changes of parameter values (e.g., change in instrument/atmospheric
properties)3. Improved insight in 2 or 3
• Learning: “more and better”– take advantage of existing results (from you or others)– Fast (re-)reduction and (re-)analysis – From quick-look to high-quality results– Not only more but also better data over time: ‘accumulation of knowledge
• Anybody– Small Individual research projects– Large projects with many collaborators
• Everywhere: federation– federation of storage and computing capabilities
• Scalability– No limits due to design for storage, databse power/storage processing power,…
A federated ‘brain’ interacting with many users
The Astro-Wise Environment a new archive/research tool for astronomical wide-field imaging
Status•environment is working
•First paper using Astro-Wise based results is out•Expansions and improvements on-going
The Astro-Wise Environment
UserPython prompt (awe>)
Web interfaces
CPUs +algorithms
Database•metadata of images•derived data from images (source lists)•=‘spider spinning AWE web’•Contains ALL input/output
Data server: images calibration & science From raw to reduced
“Archiving”
“Interpreting”
“Processing”
Key properties for intelligent information system
• Adaption: facilitate changes1. Changes due to improved encoded methods2. True physical changes of parameter values (e.g., change in instrument/atmospheric
properties)3. Improved insight in 2 or 3
• Learning– take advantage of existing results (from you or others)– Outdated not-yet existing data– Fast (re-)reduction and (re-)analysis– Not only more but also better data over time: ‘accumulation of knowledge ‘
• Anybody: – Each piece of information carries tag of ‘ownership’– Small Individual research projects – Large projects with many collaborators
• Anywhere: federation: – Own developed compute-grid and storage-grid– Nodes:active={Kapteyn, Bonn} almost={Munich, Paris,Naples}, in
progress={Nijmegen, Leiden, Santiago})• Scalability: performance proportional to I/O speed and processing power.
A federated ‘brain’ interacting with many users
Paradigm shiftAWE “Classical”
Information system
Releases
Dynamic archive Static archive
‘Continous’ releases (VO)
Fixed releases
End result ‘pulled’ via linking of all processing input/output
Raw data ‘pushed’ through pipeline to end-product
Science projects with AWE• PhDs Sikkema, Kovac,
Schneider: galaxy surveys with WFI, WFC, MDM
• Test projects– Variable sources around
CenA• light curves (Δmag~0.03) for
2x104 objects around Centaurus A • Valentijn
– Asteroid detection• Detections in WFI image from
catalog of ~105 numbered asteroids
• Jeffrey Bout (student), myself
Cen A
2dF
Asteroids
Large public data projects with AWE using OmegaCAM
at VST
• KIDS (PI: Kuijken): ESO Public Survey– Weak lensing; high-z QSOs;
galaxy/cluster evolution; baryon oscillations;
– 5000 deg2 u,g,r,i, ~500 nightsKIDS North KIDS South
GTO science with AWE using OmegaCAM at VST
• OmegaWhite (PI: Groot): – discover Galactic Population of
ultracompact binaries from periodic (<2hour) light curves
– 150 deg2 @ b=±5o; Sloan g’ 40sec exposures & additional ugriz’ coverage.
GTO science with AWEusing OmegaCAM at VST
• OmegaTranS (Saglia; Snellen; Alcala)– Searching for planet transits (15-20
new transits expected in first year)– ~1 order more powerful than OGLE-III
GTO science with AWEusing OmegaCAM at VST
• VESUVIO (PIs: Valentijn, Capaccioli) – Galaxy/cluster evolution– Horologium Supercluster: 100 deg2
medium deep (r'<25mag); ugriz– Hercules Supercluster: 12 deg2 deep
ugriz+Hα
Key ingredients to achieve the Astro-Wise environment
– Strict global data acquisition and processing model
– data model -> object model
– storing all I/O in single (distributed) database
– Database environment exploits• OOP inheritance (Python)• Complete linking (associations, references)
Conclusions
• New analysis environment for wide-field imaging in operation by OmegaCEN– Key ingredient: dynamic database
• Containing all I/O• Fully linked data
• Versatile: could be used for other kinds of data– Collaboration with LOFAR on-going
• Large science projects with AWE when OmegaCAM starts operations (early 2007)
• To find out more– Visit : www.astro-wise.org; – download/get now 2 page overview article
Contribution to LOFAR project