theory in the vo, garching, 7.4.2008 theory in the virtual observatory (tvo) goals of euro-vo dca...
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Theory in the VO, Garching, 7.4.2008
Theory in the Virtual Theory in the Virtual Observatory (TVO)Observatory (TVO)
Goals of Euro-VO DCA WP4Gerard Lemson, GAVOARI-ZAH, HeidelbergMPE, Garching
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Theory in the VO, Garching, 7.4.2008
OverviewOverview
• Recap VO• Why “Theory in the VO”?• Theory in the IVOA
– Simple Numerical Access Protocol
• Intro to this workshop.
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Theory in the VO, Garching, 7.4.2008
Recap VO Recap VO
• Reminder, what is VO about?– “Universe on your desktop”– All astronomical resources online available– Behind friendly interfaces– Interoperable
• What is an “astronomical resource”?– data (all stored results of astronomical
experiments)– software packages (IRAF,AIPS)– (web) services (Simbad, NED)– publications (LANL, ADS) – people (you)
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Theory in the VO, Garching, 7.4.2008
Web helps to access Web helps to access resourcesresources
• Interesting astronomical resources may be– unavailable– unknown – not here– large (the farther away, the larger!)– complex
• Web technologies help:– Discovery: search engines, Google-like or structured– Documentation: HTML – Retrieval: relatively easy access– Filtering: server-side reduction of data streams– Web applications: services as resources
• Main issue, understanding each other...
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Theory in the VO, Garching, 7.4.2008
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Theory in the VO, Garching, 7.4.2008
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Theory in the VO, Garching, 7.4.2008
EsperantoEsperanto
• Standardisation– Discovery (registries)– Data description (“meta-data”) – Data formats (FITS, VOTable)– Protocols– (Web) Application Interfaces– Query language
• Organised in IVOA
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Theory in the VO, Garching, 7.4.2008
VO’s EsperantoVO’s Esperanto
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Theory in the VO, Garching, 7.4.2008
Observations in the VOObservations in the VO
• Most IVOA standardisation efforts concentrate on observational data sets – image archives– source catalogues– spectra
• Standards observationally biased– Sky-based query protocols: cone search, SIAP,
SSAP– Source catalogue combination: ADQL, XMatch– Data models: spectra, STC, characterisation
(sky/time/energy/flux)
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Theory in the VO, Garching, 7.4.2008
Theory in the VO: issuesTheory in the VO: issues
• Good reasons for emphasis on observations– simple observables: photons detected at a certain time
from a certain area on the sky in a certain wavelength interval
– pre-existing (meta-)data format standards (FITS, “csv”)– long history of archiving– valuable over long time (digitising 80yr old plates)
• Simulations not so simple– more varied “observables”: anything that can be
modelled is explicitly there– no standardisation (not even HDF5)– archiving ad hoc, for local use– Moore’s law makes useful lifetime relatively short: few
years later can do better
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Theory in the VO, Garching, 7.4.2008
““Moore’s law” for N-body Moore’s law” for N-body simulationssimulations
Courtesy Simon White
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Theory in the VO, Garching, 7.4.2008
InteroperabilityInteroperability
• Current IVOA standards not always relevant• Distributed resources hard to join
– no common sky– no common objects– no common observables– data models tailored to observations
• Complex data structures, not supported by messaging format standards – AMR, trees, graphs, Voronoi tesselations
• Individual data products often VERY LARGE and not obviously reduced without explicit user interaction.
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Theory in the VO, Garching, 7.4.2008
So why bother?So why bother?
• Simulations are interesting:– For many cases only way to see processes in action– Others can think of science cases you may not have
thought of– Complex observations require sophisticated models for
interpretation
• Bridging gap in specialisations: not everyone has required expertise or resources to create simulations, though they can analyse them.
• Many use cases do not require the latest/greatest – exposure time calculator– survey design
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Theory in the VO, Garching, 7.4.2008
Di Matteo, Springel and Hernquist, 2005
John Hibbard http://www.cv.nrao.edu/~jhibbard/n4038/n4038.html
NASA/CXC/SAO/G. Fabbiano et al.
Toomre & Toomre, 1972
Courtesy Volker Springel
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Theory in the VO, Garching, 7.4.2008
IVOA: Theory Interest IVOA: Theory Interest GroupGroup
• http://www.ivoa.net/cgi-bin/twiki/bin/view/IVOA/IvoaTheory
• “Provide a forum for discussing theory specific issues in a VO context. “
• Use cases for working groups.• Projects
– Semantics– Micro-simulations– Simple Numerical Access Protocol (SNAP)
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Theory in the VO, Garching, 7.4.2008
SNAPSNAP
• Goal:– create a VO protocol for discovering, querying
and retrieving simulation data – Similar to other S*AP protocols
• Restricted to 3+1D simulations: – At least some common elements– Challenging
• large• complex• diverse• no support in IVOA (compare theory spectra)
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Theory in the VO, Garching, 7.4.2008
Data access protocolsData access protocols
1. Find standard services in registry (say SIAP or SSAP) • Filter on type of service, sky-footprint, wavelength.
2. Query these services using protocol syntax, in general based on location on the sky.• Spectra in a circle on the sky, images overlapping
a certain rectangle• Results in VOTable, providing some metadata per
image/spectrum.3. Retrieve desired results in standardised
format– FITS for images or spectra– VOTable or other XML representation for spectra
or source lists.
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Theory in the VO, Garching, 7.4.2008
SNAP 1: registrySNAP 1: registry
• Different motivations for querying a simulation registry.
– no “interesting patch in the sky”– no object about which more information is
desired– no standard set of variables
• How do we classify simulation archives?
• Need new features for describing SNAP services.
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Theory in the VO, Garching, 7.4.2008
SNAP 2: query protocolSNAP 2: query protocol
• Is it possible to conceive of queries that makes sense for all simulation access services?– No common-sky based simple query to
send to lots of simulation archives
• Need new model to describe simulations and base queries on.
• Less is known, more abstract model.
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Theory in the VO, Garching, 7.4.2008
SNAP Data ModelSNAP Data Model
• Goal: assist in describing and retrieval.• Meta-data model.
– We only know that part of space is evolved in time.– Properties, objects, dimensions, coordinate systemss, units all
flexible.– Compare to (RA/DEC, JD, λ, Flux)
• Should answer common questions about simulations, such as– What type of object is being simulated?– What physics is included?– What “observables” are available?– What are the typical dimensions? – How are the objects represented?– What numerical algorithms were used?
• Support:– “Locate simulations that contain a galaxy cluster of about
1014 Msun, used SPH type hydrodynamics”– etc
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Theory in the VO, Garching, 7.4.2008
PosterBourges et al
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Theory in the VO, Garching, 7.4.2008
SNAP RegistrySNAP Registry
• Difficult to separate steps 1 and 2.• Registries not fine-grained.• Individual institutes may lack expertise to deal
with complex data model.– Metadata describing simulations not easy to fit in “flat”
table. – S*AP-like HTTP GET queries not flexible
• SNAP Registry– Few centers acting as registries for fine grained
simulation data– Registration and browsing interfaces– Evt ADQL query interface based on SNAP data model
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Theory in the VO, Garching, 7.4.2008
SNAP 3: data retrievalSNAP 3: data retrieval
• Often very large datasets.• Need server-side filtering to reduce size of
transferred byte streams:– cut-out (how to decide which part of box?), projection,
gridding, cluster finder, visualisation (full virtual telescopes?)
• What data formats?– FITS, binary VOTable, HDF5?– how about more complex data structures?
• Server side analysis– 2pt correlations, power spectra, density profiles, ...
• For now concentrate on discovery and links to web services.
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Theory in the VO, Garching, 7.4.2008
Theory in the Euro-VO DCATheory in the Euro-VO DCA
• Work package 4: theory in the VO.• Deliverable
– this workshop– whitepaper
A Framework for the inclusion of theory data in the VO
• Theory Experts Group (this workshop’s SAC)
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Theory in the VO, Garching, 7.4.2008
This workshop: goalsThis workshop: goals
• Use cases– Science with TVO-like aspects.– (How) might TVO facilitate work?
• Early implementations• Presentations on VO-like facilities• Discussions• Questionnaire• Whitepaper
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Theory in the VO, Garching, 7.4.2008
This workshop: This workshop: sessionssessions
• 3+1D simulations• micro-simulations• theory-theory interoperability• theory-observational interface• computational infrastructure
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Theory in the VO, Garching, 7.4.2008
Simulation typesSimulation types
• 3+1D simulations– Subject of SNAP
• Overview (V. Springel)• Projects (H. Wozniak, J. Schaye)• VO efforts (R. Wagner, P. Hennebelle)
• Micro-simulations– individually small– different use cases from SNAP-like simulations
• parameter space sampling• MANY parameters• MANY observables• on-line simulations feasible
– Large variety (all speakers)
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Theory in the VO, Garching, 7.4.2008
InteroperabilityInteroperability
• Theory-theory– Not as straightforward as for observations.– Examples
• MODEST (P. Teuben)• Code comparisons (I.Iliev):
– Santa Barbara Cluster Comparison Project– Aspen-Amsterdam Void Finder Comparison Project
• Data reuse (S.Charlot)• Theory-observational
– Assist observers to use theoretical resources (vice versa?).– Use cases.
• survey planning, exposure time calculator• analysis of detailed observations, using detailed models
– Where do theory and observations meet? (Qi Guo)• virtual telescopes (E.Bertin, S. Borgani)• analyse observations as far as possible and compare physical
properties (G.Kauffmann)
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Theory in the VO, Garching, 7.4.2008
Detailed observationsDetailed observations
electron density
gas pressuregas temperature
Courtesy Alexis Finoguenov, Ulrich Briel, Peter Schuecker, (MPE)
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Theory in the VO, Garching, 7.4.2008
Detailed predictionsDetailed predictions
Courtesy Volker Springel
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Theory in the VO, Garching, 7.4.2008
Computational infrastructureComputational infrastructure
• New technologies can assist, or may be required to implement these ideas.
• Real life examples:– Grid (M. Steinmetz, M. Spaans)– Algorithms (L.M.Sarro)– Relational databases (J. Blaizot)– VO aware visualisation tools (G.
Caniglia)
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Theory in the VO, Garching, 7.4.2008
DiscussionsDiscussions
• Address “typical” VO issues– what is it good for, why should I
participate, doesn’t it lead to bad science...?
• Possibly formalised in questionnaire to be sent around to participants after workshop
• Feedback for WP4 whitepaper.
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Theory in the VO, Garching, 7.4.2008
Thank you.Thank you.
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Theory in the VO, Garching, 7.4.2008
Questions IQuestions I
• Which resources are important?– raw simulation results, post-processed, analysis, virtual
observations– services to produce these
• What considerations should we apply to decide what types of resources should be available?– reproducibility, (re-)usability (by ...), ...
• What should accompany resources published on line?– documentation, software readable metadata, help desk– ...
• What scientific content is of most interest?– large vs small
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Theory in the VO, Garching, 7.4.2008
Questions IIQuestions II
• What questions do you want to ask of a registry?– content, methods, physics,
characterisations• What dangers do you see in
publishing resources online?– quality control, bad science
• What reasons do you have to publish resources online?– what reasons to not do this?