Science with the VO

Mark Allen (CDS, Observatoire de Strasbourg)

Outline Example Science Drivers Science 'Reference Mission' The 'VO approach' & Common Aspects Demonstrations and Early VO Science Published examples Challenges and Opportunities

Example science drivers Find all info on a given set of objects

Defined by positions, colours, morphology,... Build SEDs from multi-archive data

Accounting for instrumental, sensitivity, aperture effects

“Outlier Science” Multi-d parameter searches

Compare LSS with 'virtually observed' N-body simulations

Re-analyse the SLOAN, MACHO Multi-census of AGN Build a survey to search for Cosmic

Shear

AVO Science Reference Mission

Key scientific results that a European VO should be able to achieve when fully implemented

Consists of science cases over broad range of astronomy and the related requirements

AVO Science Advisory committee (2005)http://www.euro-vo.org/pub/fc/cases/srm.pdff

Science Cases Circumstellar disks: from pre-Main Sequence stars to stars

harbouring planets Intermediate Velocity Clouds Which Star will go Supernova next? Initial Mass Function within 1kpc: Planetary to Stellar Masses Initial Mass Function for Massive Stars Contributions of Low and Intermediate Mass Stars to the ISM Galaxy Formation and Evolution from z=10 to 0.1 Build-up of Supermassive Black Holes Formation and Evolution of Galaxy Clusters Correlation of CMB, radio/mm and optical/NIR Galaxy Surveys

Galactic

Extragalactic

Cosmological

Galaxy Formation and Evolution from z=10 to 0.1

Required data Deep Multi-wave surveys (GOODS, COSMOS) HST+ACS bviz imaging SLOAN Optical spectroscopy MERLIN, GMRT, VLA, ATCA radio Chandra and XMM-Newton X-ray Spitzer mid-IR Future sub-mm GALEX UV imaging

When did the 1st objects form? What are the progenitors of present day massive ellipticals? How many massive galaxies at z>1,2,4? How do SF and galaxy stellar mass densities evolve?

“Only now, and only with through the VO, are the datasets large enough, and the tools mature enough that Galaxy Formation and Evolution can be examined in a meaningful way.”

VO approach to the problem Extract sample from data

Perform Sextractor type photometry Cross correlate with images, catalogues, spectra.

Crucial that output results are scientifically useable and reliable Matching of PSF, consisitent photometric apertures, treatment of noise, and upper limits

Sanity checks like stellar colours Output multi-band catalogue, and colour-colour diagrams

Visualize output colour-colour space Photometric z from SEDs (Template SED libraries, extinction curves etc.) Physical Parameters – L, E(B-V), SFR, M/L stellar mass

Comparison with star formation scenarios and synthetic spectra Morphological analysis

Stack images at same wavelength, or spectra at different redshifts

Build average spectra for specific object classes Angular clustering analysis

Comparison with mock catalogues from theoretical simulations

Common aspects Browsing/searching of data and

distributed information Manage large amounts of distributed

heterogeneous data Combining Multi-wavelength data taking into

account different: Units, photometric systems spatial, wavelength and time coverage resoultions/PSF, observing technique

Cross-Matching Catalogues: Large-Small, Sparse-Dense Taking into account:

positional uncertainties, resolution, completeness extra constraints: e.g. colour, object type, environment

Compare observations with models Virtual observations of models Projection of models to observed parameter

space Spectral fitting/classification

Science Demos and early VO Science

Exploit archives as virtual telescopes (3 proposal cycles 2000-2003)

VO science on HST, ESO: VLT, NTT, WFI, ISO archives

advanced searching of achive exposure/seeing/field density location e.g. for pre-discovery images for asteroids

http://www.euro-vo.org/astrovirtel/index.html 20+ publications listed on AstroVirtel pages

Early demonstration project identifies new L-type Brown Dwarf

Found in SDSS/2MASS correlation designed to reproduce known (~200) Brown Dwarfs

SDSS 15M sources, 2MASS 160M Was done as protoype, now used as NVO

OpenSkyQuery training example

Demo 2004: First Science Searching for type 2 Quasars using Virtual

Observatory tools

Demo 2005 AGB to Plantary Nebulae transition

Workflow: SEDs to Models

Demo 2003: First Light VO Visualisation and Data Discovery

- GOODS Optical ACS data & catalogues - Chandra X-ray catalogues - Select absorbed X-ray sources - Cross-match X-ray and optical - Apply empirical estimator for Lx - Check against spectroscopy Lx>1044 : QSO 2

Discovery of QSO 2s with VO tools

Science Conclusions Using

the deepest Chandra X-ray, and HST imaging

& Empirical estimator for Lx we find 68 New type 2 AGN 31 Qualify as QSO 2, z~4 Many more QSOs than predicted

Published: Padovani, Allen, Rosati, Walton A&A 2004

More published results

• Using VO tools to investigate distant radio starburst hosting obscured AGN in the HDF(N) region, Richards et al., A&A, 472, 805 (2007)

• Albus 1: a very bright White Dwarf candidate, Caballero & Solano, ApJ, 665, L151 (2007)

• Flare productivity of newly-emerged paired and isolated solar active regions, Dalla, Fletcher, & Walton A&A, 468, 1103 (2007)

• Radio-loud Narrow-Line Type 1 Quasars, Komossa et al., AJ, 132, 531 (2006)

• Luminous AGB stars in nearby galaxies. A study using VO tools, Tsalmantza et al., A&A, 447, 89 (2006)

• + more...

Example: Serendipitous Outlier

Caballero & Solano 2007, ApJ, 665, L151 'ALBUS 1: A very bright white dwarf candidate'

found a bright source with very blue VT-Ks colour appreciable proper motion mag. and colours --> White Dwarf

Candidate

Found in optical-NIR study to characterize young stars and brown dwarfs surrounding εOri and δOri

VO aspects: Correlate Tycho-2 and 2MASS catalogs

[in 10 45' radius fields at same Gal. lat.] also: SuperCOSMOS, USNO-B1, NOMAD

and DENIS excluded radio(VLA), mid-IR(IRAS), UV

(EUVE), X-ray(ROSAT)... or object in literature (SIMBAD)

Aladin & VO catalog interoperability

spectrum obtained: ALBUS 1 is a Helium-rich subdwarf Also known as CPD -20 1123 (Gill & Kapteyn

1896) (and in VizieR catalogs...)

published Aug 2007, and then ...

Example: Solar Physics2 papers utilizing AstroGrid workflow

system1. 'Flare productivity of newly-emerged

paired and isolated solar active regions' Dalla et al., 2007, A&A, 468, 1103

2. 'Invisible subspots and rate of magnetic flux emergence' Dalla et al. 2008, A&A, 479, L1

Analysed 7000+ sunspots from over 25 year period

Some areas of the disk are missing new sunspots compared to others

because when they are gowing rotation caries them away from centre of disk

AstroGrid workflows

We used AstroGrid workflows to:

(1) retrieve region catalogues and identify ‘new’ regions;

(2) study the location of emergence with respect to pre-existing regions; and

(3) querying catalogues of flares to establish flare productivity.

Visualisation of results using Topcat.

Slide courtesy of S. Dalla

Fossil Groups in the SDSS US NVO Summer School The National Virtual Observatory:

Tools and Techniques for Astronomical Research. ASP vol. 382

2007 AJ, 134, 1551 Santos, Mendes de Oliveira & Laerte Sodre

Fossil Groups – systems with M and LX comparable to clusters of galaxies, but dominated by single isolated large elliptical galaxy

'Fossil' – comes from formation scenario:collapsed early -> oldest, undisturbed

systems only 15 fossil groups known in literature

VO methods to identify new fossil groups in SDSS DR5 – increasing known by x3

Use of SQL - Structured Query Language ADQL – Anstronomical Data Query

Lang. OpenSkyQuery VO service

Steps Elliptical Galaxy Selection

luminous red galaxies r<19 – 112510 sources Cross-Match with X-ray data

OpenSkyQuery xmatch of SDSS with RASS constrained by positional uncertainties

Selection of Companions spectro. and photom. redshifts

Photometric Condition for Fossil Groups mi > m1 + 2

Analysis of dominant galaxy Cross-check against known systems

Simple expressions applied to large data set in powerful way

-> New Fossil Groups Query Language

expressions published in the paper

My observations of current VO science

largely about getting and combining data

once data obtained/selected analysis is mostly by traditional methods

Workflow systems ramping up (esp. AstroGrid) Scripting with familiar lang. (Python) very

promising End-to-End with VO ?

in practice VO is being used where it is needed more and more papers acknowledging VO

Where's the detailed scientific interoperability?

as required for SRM like problems

first IVOA standards -> good data connectivity

in progress: characterisation of data – data models units, PSFs, time/spatial/energy coverage theory and modeling... (not to mention Grid, VOSpace, Curation, Access

Layers)

Comparing with Theory Simplistic demos

show interoperability but immaturity

Need for meetings like this!

OpportunitiesEuro-VO AIDA Calls for Proposals to carry out Astronomy projects

that would benefit from VO. Support from Euro-VO scientists

Watch for announcements!