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Photometric Redshifts and Properties of Galaxies from the Sloan Digital Sky Survey

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Photometric Redshifts and Properties of Galaxies from the Sloan Digital Sky Survey Photometric Redshifts and Properties of Galaxies from the Sloan Digital Sky Survey Natascha Greisel Photometric Redshifts and Properties of Galaxies from the Sloan Digital Sky Survey Natascha Greisel Dissertation der Fakult¨at f¨ur Physik Dissertation of the Faculty of Physics der Ludwig-Maximilians-Universit¨at M¨unchen at the Ludwig Maximilian University of Munich f¨ur den Grad des for the degree of Doctor rerum naturalium vorgelegt von Natascha Greisel presented by aus M¨unchen, Deutschland (Germany) from Munich, 18 December 2014 1st Evaluator: Prof. Dr. Ralf Bender 2nd Evaluator: Prof. Dr. Jochen Weller Date of the oral exam: 25 February 2015 Zusammenfassung Die Bestimmung kosmologischer Rotverschiebungen ist f¨ur viele Untersuchungen in der Kosmologie und extragalaktischen Astronomie essentiell. Dies sind z.B. Analysen der großskali- gen Struktur des Universums, des Gravitationslinseneffekts oder der Galaxienentwicklung. In der Kosmologie statistisch aussagekr¨aftige Volumina werden heutzutage meist durch Breit- bandfilter beobachtet. Mit diesen photometrischen Beobachtungen kann man nur Aussagen ¨uber die grobe Form des Spektrums machen, weshalb man sich statistischer Mittel bedienen muss um die Rotverschiebung zu sch¨atzen. Eine Methode zur Bestimmung photometrischer Rotverschiebungen ist es, Fl¨usse von Modellgalaxien in den Filtern bei verschiedenen Rotver- schiebungen z vorherzusagen und mit den beobachteten Fl¨ussen zu vergleichen (template fitting). Danach wird eine Likelihood-Analyse durchgef¨uhrt, in der die Vorhersagen mit den Beobachtungen verglichen werden, um die Wahrscheinlichkeitsdichte P (z) und die wahrschein- lichste Rotverschiebung zu bestimmen. Um mit template fitting Methoden m¨oglichst genaue Ergebnisse zu erzielen, m¨ussen die Modellspektren, sowie die zugeh¨origen a priori Wahrschein- lichkeiten sorgf¨altig ausgew¨ahlt werden. In dieser Arbeit nutze ich photometrische und spektroskopische Daten leuchtkr¨aftiger roter Galaxien (LRGs) aus dem Sloan Digital Sky Survey (SDSS). Ich untersuche die Genauigkeit photometrischer Rotverschiebungen, die mit Modellspektren erreicht werden, welche von mir speziell f¨ur den Satz LRGs bei z . 0.5 (SDSS-II) entwickelt wurden, und vergleiche sie mit publizierten Ergebnissen. Diese Modelle wurden ohne Informationen aus Wellenl¨angenberei- chen, die kurzwelliger als das SDSS u Band sind, erstellt. Die Galaxieneigenschaften, die wir aus den Modellen f¨ur den UV Bereich vorhersagen k¨onnen decken sich allerdings mit denen aus anderen Beobachtungen. Dar¨uber hinaus analysiere ich die sich daraus ergebenden Eigen- schaften der am besten fittenden Modellspektren und vergleiche sie mit den spektroskopischen Daten. Aus den Ergebnissen ist abzuleiten, dass leuchtschw¨achere rote Galaxien bei niedriger Rotverschiebung im Mittel gr¨oßere Anzeichen von Sternentstehung zeigen als leuchtkr¨aftige, was durch Analysen der Spektren best¨atigt wird. Uberdies¨ k¨onnen wir einen Abfall im UV Fluss von h¨oheren zu niedrigeren Rotverschiebungen hin beobachten, welcher durch die Al- terung der Galaxienpopulation erzeugt wird. Desweiteren generiere ich Modellspektren f¨ur leuchtkr¨aftige rote Galaxien aus SDSS-III bei h¨oheren Rotverschiebungen 0.45 ≤ z ≤ 0.9. Ich modifiziere hierzu die Form theoretischer spektraler Energieverteilungen um die Farben der untersuchten Galaxien mit den Modellen bestm¨oglich wiedergeben zu k¨onnen. Ich reduziere die Dimension des Raums, der durch die Farben und absoluten Helligkeiten aufgespannt wird, auf zwei Dimensionen mit einer selbst- organisierenden Karte. Diese wird mit einem k-means Algorithmus partitioniert indem wir H¨aufungspunkte der Daten identifizieren. Aus den sich ergebenden Partitionen selektiere ich einzelne Modellspektren, die die zugrundeliegenden Galaxien repr¨asentieren. Eine Auswahl aus den erstellten Modellen wird danach f¨ur die Sch¨atzung photometrischer Rotverschiebun- gen verwendet, deren Genauigkeit ¨uber die von SDSS publizierten Ergebnisse hinausgeht. Abstract The determination of photometric redshifts is essential for many subjects in cosmology and extragalactic astronomy, like the large scale structure of the Universe, gravitational lens- ing, or galaxy evolution. If the spectral energy distribution (SED) of a galaxy is measured with high enough spectral resolution, the redshift can be easily derived through the absorp- tion and emission lines which are created by the elements in the galaxy. However, currently more telescopes are equipped with large cameras with charged coupled devices (CCDs) that observe the sky through optical filters. With these photometric observations it is possible to detect much fainter astronomical objects than with spectroscopy. Furthermore, photometric observations are less time consuming and cheaper in comparison, wherefore they are pref- erentially used for observations of statistical meaningful cosmological volumes. Nonetheless, photometric data, which are often gained by observations through broadband filters, are not as precisely resolved as spectra. Therefore one does not have information about the accurate position in wavelength of spectral lines, but only about the overall shape of the SED. This is the reason why so-called photometric redshifts have to be derived by statistical means. One approach to estimate the redshift through photometry alone are template fitting methods which compare the fluxes predicted by model spectra with the observations. After that, a likelihood analysis is performed with which a probability density function P (z) and the most probable value of z can be derived. To achieve high accuracies with photometric redshift tem- plate fitting techniques, the model spectra as well as their corresponding prior probabilities have to be chosen carefully. In this work I use photometric and spectroscopic data of luminous red galaxies from the Sloan Digital Sky Survey (SDSS). I analyze the precision of photometric redshifts estimated with model SEDs specifically designed to match the set of luminous red galaxies of SDSS- II at redshifts z . 0.5 in color and I compare them with published results. These models were created without information on their properties at wavelengths shorter than the SDSS u band. However, the galaxy UV characteristics derived from the model SEDs match those of other observations. Furthermore, I investigate the SED properties derived from the best fitting models with respect to spectroscopic data as functions of redshift and luminosity. At lower redshifts less luminous galaxies from our sample on average show increased signs of star formation in comparison to galaxies with higher luminosities. This is supported by analyses of the line strengths in the spectra. Moreover, star formation activity increases with increasing redshift which is caused by the aging of the galaxy population from higher to lower redshifts. I also generate model spectra for red galaxies from the SDSS-III located at even higher red- shifts 0.45 ≤ z ≤ 0.9. For this I modify the shape of theoretical spectra to match the data of the analyzed galaxies to a better extent. The multidimensional space defined by the colors and the absolute magnitude of the galaxies is reduced to two dimensions through a self-organizing map. The map is then partitioned by a k-means algorithm which identifies clusters in the data. From the cluster cells I select model spectra which represent the galaxies from within the same cell. A selection of the models is then used as a template set for photometric redshift estimation. I find that our models improve the redshift accuracy in comparison to the results published by SDSS. Contents Zusammenfassung vii Abstract ix Contents xii List of Figures xv List of Tables xvii 1 Preface 1 2 Photometric Redshifts 7 2.1 Introduction to Astronomical Observations . ......... 7 2.2 PhotometricRedshifts . 11 2.2.1 EmpiricalMethods............................. 11 2.2.2 TemplateFitting .............................. 13 3 SDSS Data 21 3.1 TheSDSS-IILRGSample............................. 24 3.2 TheBOSSLOWZandCMASSSamples . 27 4 Model SEDs 31 4.1 Galaxies....................................... 31 4.1.1 Elliptical Galaxies . 32 4.2 Model Spectral Energy Distributions . ....... 37 4.2.1 Galaxy Stellar Population Evolution . ..... 37 4.2.2 ModelSEDsandLRGData. .. .. .. .. .. .. 40 5 Novel SED Templates for SDSS-II LRGs 51 5.1 SEDsforLRGsbySEDFitting . 51 5.2 Selection of Novel LRG Templates . 53 5.3 Photo-z Precision with Novel LRG Templates . ....... 55 5.4 ComparisontoSDSSDatabaseResults. ..... 57 5.5 Properties of the Novel Template Set . ...... 62 xii CONTENTS 5.5.1 UV colors of the Novel Templates and M09 Models . 62 5.5.2 Differences in the SEDs within z − MR Bins............... 64 5.6 Summary ...................................... 70 6 Templates and Photo-zs for CMASS Galaxies 71 6.1 TheBOSSCMASSSample ............................ 72 6.1.1 Colors of M09 Models and BOSS CMASS Galaxies . 72 6.2 NewSEDTemplates ................................ 73 6.2.1 Generating Model SEDs for CMASS Galaxies by SED Fitting..... 75 6.2.2 Selection of Best Fitting SEDs for the New Template Set ....... 83 6.3 PhotometricRedshifts . 90 6.3.1 Photometric Redshifts with the Novel Template SEDs . ....... 90 6.3.2 Comparison to SDSS Photometric Redshifts . ..... 98 6.3.3 Deviations in Color Predictions . 103 6.4 Summary ...................................... 105 7 Photo-zs from DES-SV Data 107 8 Physical Properties of a Lensed High-z System 117 9 Summary and Conclusion 127 Bibliography 143 A Photo-z Quality Metrics 145 B
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