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Theory in the Virtual Observatory (TVO). Goals of Euro-VO DCA WP4 Gerard Lemson, GAVO ARI-ZAH, Heidelberg MPE, Garching. Overview. Recap VO Why “Theory in the VO”? Theory in the IVOA Simple Numerical Access Protocol Intro to this workshop. Recap VO. Reminder, what is VO about? - PowerPoint PPT Presentation
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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
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.
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)
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...
Theory in the VO, Garching, 7.4.2008
Theory in the VO, Garching, 7.4.2008
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
Theory in the VO, Garching, 7.4.2008
VO’s EsperantoVO’s Esperanto
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)
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
Theory in the VO, Garching, 7.4.2008
““Moore’s law” for N-body Moore’s law” for N-body simulationssimulations
Courtesy Simon White
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.
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
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
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)
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)
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.
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.
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.
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
Theory in the VO, Garching, 7.4.2008
PosterBourges et al
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
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.
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)
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
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
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)
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)
Theory in the VO, Garching, 7.4.2008
Detailed observationsDetailed observations
electron density
gas pressuregas temperature
Courtesy Alexis Finoguenov, Ulrich Briel, Peter Schuecker, (MPE)
Theory in the VO, Garching, 7.4.2008
Detailed predictionsDetailed predictions
Courtesy Volker Springel
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)
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.
Theory in the VO, Garching, 7.4.2008
Thank you.Thank you.
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
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?