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Vince Oliver PhD student of ELTE University Budapest. Assignments within MAGPOP project. Introduction. Engagements: Was employed at the AO of Belgrade (Serbia & Mnt) from 1999-2005. - Solar Physics (long time behavior of Solar a b s. spectral lines)
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Vince OliverPhD student of ELTE UniversityBudapest • Assignments within MAGPOP project
Introduction Engagements: Was employed at the AO of Belgrade (Serbia & Mnt) from 1999-2005. - Solar Physics (long time behavior of Solar abs. spectral lines) - Stellar Physics ( inves. of stellar activity and properties) - Atmospheric turbulence invest. Since Nov. 2005 have been employed at the ELTE Univ. of Budapest - Redshift estimation using photometry and its application to SDSS
Redshift estimation (Photo-Z) Methods for photo-z estimation can be divided into two basic classes: Empirical method: based on determination of z vs. colors using galaxies with known photometry and spectral redshift (examples: polynomial fitting, artificial neural networks) Template fitting method: based on comparison of simulated and observed colors.
Advantages • Empirical method: All effects of dust and evolution are implicit within the z vs. color relation • Template fitting method: More physical, beside z we obtain spectral typetoo
Main limitations Empirical method: Estimates redshift only for the objects that have similar z and spectral type to those in the training set (extrapolation problem) Template fitting method: The template SEDs are poorly known - empirical templates are obtained from observation of local galaxies only, aperture bias , limited wavelength range where the spectra are observed and so on. - model templates are uncertain in the UV
Errors for SDSS DR1 METHOD zspec-zphot Polynomial fit: 0.027 Repaired empirical templates: 0.035 (calibration!) Synthetic (BC model) templates: 0.051
Improvements on template fitting We believe that a good choice of initial template spectra obtained by population synthesis model could improve the accuracy of photo-z Positive and negative sides of using population synthesis model + we have a control over the physical parameters of galaxies + no extrapolation problem - continuum properties of models are not perfect yet - too many input parameters to tune Also the use of the morphological information should remove the color degeneracy(close red galaxies vs. high redshift blue ones)
Plans • Find the minimal set/combination of relevant model parameters (metallicity, age, dust attenuation params etc.) responsible for broadband optical features, which are used by photo-z. • Include morphological prior • Apply to SDSS (and other) data and to get redshift, age, metallicity, dust other estimates. • To get reliable error bars, confidence limits, on estimated parameters • We rely onthe experts in this field – Stephan Sharlot, Gian Luigi Granato, Alessandro Bressan and others