Eötvös UniversityBudapest

in the

Network

Seniors:• István Csabai (node coordinator):

» Photometric redshift estimation, virtual observatories, science database technology, SDSS

• Zsolt Frei: » Galaxy morphology, galaxy mergers, gravitational waves

Students:• Norbert Purger, Bence Kocsis, Merse Gáspár,• Márton Trencséni, László Dobos, Dávid Koronczay

» Working on SDSS related topics

Network student: • Oliver Vince (Belgrade)

The Team

Focus themes

Development of datamining and visualization techniques – SDSS ‘color space’

Improving photometric redshift estimation Estimation of physical parameters of

galaxies from photometry Bulge/disk separation of large SDSS

galaxies Virtual Observatory, Spectrum Services

Collaboration with other nodes

JHU:• Alex Szalay, Tamas Budavari, Ani Thakar … • Virtual observatories, SDSS database, photometric redshift

estimation• Regular visits for seniors ad students

Paris: • Stephane Charlot• Spectral synthesis models for photo-z, spectral models in VO• Oliver Vince visited Paris, and will visit next year • New joint topic involving several nodes: „Optical attenuation

law of nearby galaxies”

u g r i z

300 million points in 5+ dimensions

300 million points in 5+ dimensions

Datamining: The Color Space

Datamining: Spatial Indexing

Datamining: Speed Up Queries

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SQL

Datamining: Visualization

Adaptively fetch data from database

Datamining:Integration with DatabaseTRADITIONAL APPROACHFlat files, Fortran, C code+ Complex manipulation of data- Sequential slow access

TRADITIONAL APPROACHFlat files, Fortran, C code+ Complex manipulation of data- Sequential slow access

SQL DATABASESOracle, MS SQL Server, …+ Organize, efficiently access data- Hard to implement complex algorithms- Multidimensional indexing (OLAP) is limited to categorical data

SQL DATABASESOracle, MS SQL Server, …+ Organize, efficiently access data- Hard to implement complex algorithms- Multidimensional indexing (OLAP) is limited to categorical data

MULTIDIMENSIONAL INDEXINGB-tree, R-tree, K-d tree, BSP-tree …+ Many for low D, some for high D+ Fast, tuned for various problems- Implemented mostly as memory algorithms, maybe suboptimal in databases

MULTIDIMENSIONAL INDEXINGB-tree, R-tree, K-d tree, BSP-tree …+ Many for low D, some for high D+ Fast, tuned for various problems- Implemented mostly as memory algorithms, maybe suboptimal in databases

VISUALIZATIONTools using OpenGL, DirectX+ Fast- Using files, some tools access database, but not interactive

VISUALIZATIONTools using OpenGL, DirectX+ Fast- Using files, some tools access database, but not interactive

INTEGRATE •Implement in SQL Server•use for astronomical data-mining•and for fast interactive visualization

INTEGRATE •Implement in SQL Server•use for astronomical data-mining•and for fast interactive visualization

• Joint Eötvös & JHU publication at the Conference on Innovative Data Systems Research

Photometric redshift estimation

•Find k nearest neighbors•Use polinomial regression•Estimate redshift

1M galaxies with known photometry and redshift

100M galaxies with known ugriz photometry, but no redshift

ugriz

redshift

Joint work between JHU & Eötvös Photometric redshift calculated for 300M

SDSS objects Included in SDSS DR5 Catalog and Data

Release paper Application: targeting MgII absorbers

collaboration between MPA & Eötvös network postdoc Vivienne Wild involved

Photometric redshift estimation

Virtual Observatory: Spectrum & Filter Services

Developed by Eötvös student Laszlo Dobos & JHU researcher Tamas Budavari

Several joint publications Collaboration with IAP

researcher Stephane Charlot to include spectral synthesis models

Network events

MAGPOP Virtual Observatory Workshop - Budapest, Hungary, 2005. April 25-26

MAGPOP Summer School - Budapest, Hungary, 2006. August 23-25

Hosting the webpage