Download or read book The Canada France Deep Fields Photometric Redshift Survey microform an Investigation of Galaxy Evolution Using Photometric Redshifts written by Mark Brodwin and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 2004 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progress in the study of galaxy evolution has traditionally followed from improvements in spectroscopic measurement techniques and subsequent groundbreaking surveys. The advent of large format CCD detectors, coupled with the demonstrated success of the photometric redshift method, has given rise to a new, potentially very powerful alternative. It has, in fact, motivated the present detailed investigation of the potential of photometric redshift surveys to complement, or in some cases, supersede traditional spectroscopic surveys in galaxy evolution studies. This Thesis describes a new deep, wide-field, multi-colour imaging survey, 10 times deeper and 30 times larger than its spectroscopic predecessor, the Canada-France Redshift Survey (CFRS). Highly accurate photometric redshifts, calibrated using hundreds of spectroscopic CFRS galaxies, were measured for tens of thousands of objects, with typical dispersions of only sigma/(1 + z) & lsim; 0.06 to IAB = 24 for z & le; 1.3. For the 1- and 2-point statistics of the galaxy distribution studied in this Thesis, the measurement accuracy is limited not by the photometric redshift error, but rather by the effect of cosmic variance, whose contribution to the total error budget is dominant. Therefore, future studies will be well served by adopting the photometric redshift approach, the efficiency of which will enable them to survey the hundreds or thousands of square degrees required to obtain a fair sample of the Universe. We measure the evolution of galaxy correlations with redshift, a primary observable of the structure formation process, correcting for the dilutive effect of photometric redshift errors on the clustering signal. The high z & sim; 3 correlation amplitude seen in this work provides compelling evidence for the biased galaxy formation paradigm. The measured galaxy correlations from 0 & lsim; z & lsim; 3 are in excellent agreement with the findings of the largest, state-of-the-art spectroscopic studies. A new Bayesian method to measure the galaxy redshift distribution is developed. The accuracy of the method, which incorporates the full redshift likelihood function of each galaxy in an iterative analysis, is demonstrated in extensive Monte Carlo simulations. IAB and RAB redshift distributions, along with the run of median redshifts, are measured in various magnitude ranges, with special attention given to quantifying both random and systematic errors.

Download or read book The FORS Deep Field Spectroscopic Survey written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The determination of the properties of galaxy populations at different redshifts provides important constraints on current models of galaxy formation and evolution. In order to investigate this evolutionary process systematically, we obtained high S/N spectra for 265 galaxies at redshifts up to 5.0 with the FORS instruments at the VLT telescopes. The galaxies were selected from the photometric redshift catalogue of the FORS Deep Field (FDF). To achieve an optimal reduction of the spectra of these very faint objects special reduction packages were developed. Redshifts and rough spectral types were determined using a library of empirical SEDs derived from FDF mean spectra with very high S/N. The characteristics of the observed galaxy spectra are presented and the distribution of redshifts and spectral types are discussed. A first analysis of the excellent data set was carried out using mean spectra of redshift-selected galaxy subsamples and line strength measurements in individual galaxy spectra. The results show a steeper UV continuum, an increase of the Lya forest, an increase of the frequency and strength of Lya emission and a decrease of the CIV absorption towards higher redshifts. The CIV evolution is explained by a change of the average metallicity.

Download or read book An Examination of Photometric Redshifts for the Hubble Deep Field North written by Michael Harkness and published by . This book was released on 2001 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Photometric Redshifts for the Dark Energy Survey and VISTA and Implications for Large Scale Structure written by and published by . This book was released on 2007 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: We conduct a detailed analysis of the photometric redshift requirements for the proposed Dark Energy Survey (DES) using two sets of mock galaxy simulations and an artificial neural network code-ANNz. In particular, we examine how optical photometry in the DES grizY bands can be complemented with near infra-red photometry from the planned VISTA Hemisphere Survey (VHS) in the JHK{sub s} bands in order to improve the photometric redshift estimate by a factor of two at z> 1. We draw attention to the effects of galaxy formation scenarios such as reddening on the photo-z estimate and using our neural network code, calculate A{sub v} for these reddened galaxies. We also look at the impact of using different training sets when calculating photometric redshifts. In particular, we find that using the ongoing DEEP2 and VVDS-Deep spectroscopic surveys to calibrate photometric redshifts for DES, will prove effective. However we need to be aware of uncertainties in the photometric redshift bias that arise when using different training sets as these will translate into errors in the dark energy equation of state parameter, w. Furthermore, we show that the neural network error estimate on the photometric redshift may be used to remove outliers from our samples before any kind of cosmological analysis, in particular for large-scale structure experiments. By removing all galaxies with a 1[sigma] photo-z scatter greater than 0.1 from our DES+VHS sample, we can constrain the galaxy power spectrum out to a redshift of 2 and reduce the fractional error on this power spectrum by H"5-20% compared to using the entire catalogue.

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2004 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Synergy of Wide field Infrared Survey Explorer WISE and the Sloan Digital Sky Survey in Stripe 82 written by Marat Musin and published by . This book was released on 2018 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, I aim to study the evolution of galaxies over the last 6 Gyr by measuring the growth of the global stellar mass density (GSMD) since z = 0.8. My work combines the datasets from two very large surveys, namely, the optical data from the Sloan Digital Sky Survey (SDSS) Stripe 82 and the infrared data from the Wide-field Infrared Survey Explorer (WISE), and constructs a unique catalog of galaxies that have their spectral energy distributions (SEDs) measured consistently from 0.3 to 5 [micro]m in seven bands. This catalog, the largest of its kind, contains 9 million galaxies in [approximately] 300 deg[superscript 2] , will have a wide range of applications beyond the scope of this thesis. Extending galaxy SED measurements to restframe near-IR has two significant advantages: (1) dust extinction can be better handled, and (2) emissions from low-mass stars, which are the major contributors to a galaxy's stellar mass, can be better measured. WISE was the only mission to date that provided all-sky IR data that are deep enough for galaxy evolution studies out to z [approximately] 1 (sampling restframe K-band). The only wide-field optical survey data that could match WISE depths are those from the SDSS Stripe 82 over [approximately] 300 deg [superscript 2] . The synergy of the two is therefore natural. The implementation, however, is of tremendous difficulty. This is mainly because of the vastly different spatial resolutions between SDSS and WISE. To overcome this problem, we take an approach that is often referred to as ʺmorphological template fittingʺ, i.e., using the high-resolution image to define the morphological template of the galaxy in question, and de-convolving its light profile in the low-resolution image accordingly. In this way, we obtain the SED measurements over the entire 0.3-5[micro]m range in the most self-consistent manner. Using this SED catalog as the basis, we derive photometric redshifts and stellar masses for all the 9 million galaxies that span z = 0-0.8. This provides us an unprecedented statistics when deriving galaxy stellar mass functions (MFs) and GSMD over multiple redshift bins. Some preliminary results are discussed. As a by-product of our morphological template fitting process, an interesting population of objects called ʺWISE Optical Dropoutsʺ (ʺWoDropsʺ for short) are discovered. These objects are significant detections in WISE data but are invisible in all the SDSS Stripe 82 data. Their nature remains a mystery up to this point. Among all possibilities, the only viable interpretation is that they are very high-mass galaxies with very high dust extinctions. To reveal their nature, future observations at larger facilities will be necessary.

Download or read book Higher Resolution Photometric Redshifts for Cosmological Surveys written by Alex Alarcon Gonzalez and published by . This book was released on 2019 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This PhD thesis is focused on the measurement of photometric redshifts in imaging galaxy surveys and its applications to extract cosmological information. In the first part of this thesis we forecast a galaxy survey with very precise redshift information, which can come either from spectroscopy or many narrow band images, using the Fisher matrix formalism. We use galaxy clustering, how galaxies group together in space, dividing a sample into two subsamples using other observable parameters. Using two overlapping subsamples reduces the sample variance in the observables, which improves the precision with which one can measure the expansion and growth history of the universe. In the second part of this thesis we measure highly precise photometric redshifts using the data from a novel imaging galaxy survey PAUS that contains a unique set of 40 narrow band filters. We develop two algorithms which use maximum likelihood or Bayesian evidence statistics to infer the redshift probability of each galaxy, which requires modeling both the continuum and emission line galaxy flux. The algorithm contains several corrections to account for systematic effects present in the data calibration which are tested in simulations developed for this purpose. The measurement of PAUS redshifts enables the science of the galaxy survey and can also be used to calibrate the redshift distribution of lensing surveys. The last part of this thesis implements for the first time a hierarchical Bayesian model in an N-body simulation to measure the redshift distribution of a lensing survey using both photometric and density information. Weak lensing is a very powerful tool to extract cosmological information, but it is very sensitive to any bias in the mean redshift of a sample of source galaxies. This method consistently combines all sources of information and merges the main techniques used in the literature to estimate redshift distributions.

Download or read book Photometric Redshifts in the IRAC Shallow Survey written by and published by . This book was released on 2006 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate photometric redshifts are calculated for nearly 200,000 galaxies to a 4.5 micron flux limit of H"13 [mu]Jy in the 8.5 deg2 Spitzer/IRAC Shallow survey. Using a hybrid photometric redshift algorithm incorporating both neural-net and template-fitting techniques, calibrated with over 15,000 spectroscopic redshifts, a redshift accuracy of [sigma] = 0.06 (1+z) is achieved for 95% of galaxies at 0 z 1.5. The accuracy is [sigma] = 0.12 (1 + z) for 95% of AGN at 0

Download or read book Probabilistic Photometric Redshifts in the Era of Petascale Astronomy written by and published by . This book was released on 2014 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the growth of large photometric surveys, accurately estimating photometric redshifts, preferably as a probability density function (PDF), and fully understanding the implicit systematic uncertainties in this process has become increasingly important. These surveys are expected to obtain images of billions of distinct galaxies. As a result, storing and analyzing all of these photometric redshift PDFs will be non-trivial, and this challenge becomes even more severe if a survey plans to compute and store multiple different PDFs. In this thesis, we have developed an end-to-end framework that will compute accurate and robust photometric redshift PDFs for massive data sets by using two new, state-of-the-art machine learning techniques that are based on a random forest and a random atlas, respectively. By using data from several photometric surveys, we demonstrate the applicability of these new techniques, and we demonstrate that our new approach is among the best techniques currently available. We also show how different techniques can be combined by using novel Bayesian techniques to improve the photometric redshift precision to unprecedented levels while also presenting new approaches to better identify outliers. In addition, our framework provides supplementary information regarding the data being analyzed, including unbiased estimates of the accuracy of the technique without resorting to a validation data set, identification of poor photometric redshift areas within the parameter space occupied by the spectroscopic training data, and a quantification of the relative importance of the variables used during the estimation process. Furthermore, we present a new approach to represent and store photometric redshift PDFs by using a sparse representation with outstanding compression and reconstruction capabilities. We also demonstrate how this framework can also be directly incorporated into cosmological analyses. The new techniques presented in this thesis are crucial to enable the development of precision cosmology in the era of petascale astronomical surveys.

Download or read book Better Input Better Output written by John Bryce Kalmbach and published by . This book was released on 2019 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are at the beginning of an era of large scale survey astronomy where we will soon measure photometry for billions of galaxies. In order to effectively use these galaxies for dark energy measurements we require measurements of the distances to these galaxies. Spectroscopic redshifts are not feasible for more than a small fraction of these galaxies and thus our primary distance measurements will rely on photometric redshift methods. This thesis highlights three challenges in photometric redshift estimation and techniques we developed to tackle these challenges: Using Information Theory to Optimize Bandpasses for Photometric Redshifts: We apply ideas from information theory to create a method for the design of optimal filters for photometric redshift estimation. We show the method applied to a series of simple example filters in order to motivate an intuition for how photometric redshift estimators respond to the properties of photometric passbands. We then design a realistic set of six filters covering optical wavelengths that optimize photometric redshifts for z [less than or equal to] 2. We create a simulated catalog for these optimal filters and use our filters with a photometric redshift estimation code to compare to the filters for the Large Synoptic Survey Telescope (LSST) which have key features in common with our optimal filters. Expanding Template Sets for Template Based Photo-Z Algorithms: Measuring the physical properties of galaxies such as redshift frequently requires the use of Spectral Energy Distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space. Here we present a new method to estimate SEDs as a function of color from a small training set of template SEDs. We first cover the mathematical background behind the technique before demonstrating our ability to reconstruct spectra based upon colors and then compare to other common interpolation and extrapolation methods. When the photometric filters and spectra overlap we show reduction of error in the estimated spectra of over 65% compared to the more commonly used techniques. We also show an expansion of the method to wavelengths beyond the range of the photometric filters. Finally, we demonstrate the usefulness of our technique by generating 50 additional SED templates from an original set of 10 and applying the new set to photometric redshift estimation. We are able to reduce the photometric redshifts standard deviation by at least 22.0% and the outlier rejected bias by over 86.2% compared to original set for z [less than or equal to] 3. Color Space Data Augmentation for Photometric Redshifts: When training sets for machine learning methods are not representative of the test set then there can be errors in the resulting estimates. In photometric redshifts this can happen when the color space of the spectroscopic data does not match the observed galaxy color space for an empirical photometric redshift estimation method. We first show how a lack of data in a region of color space of the training data affects photometric redshift estimation and then develop three different methods to add in synthetic training data to the missing area to mitigate the errors. Our best performing method lowers the photo-z bias by 51% and reduces the outlier fraction by 9.6% in the test data that lies in the missing area of color space compared to an unrepresentative training catalog.

Download or read book The Redshift Controversy written by George B. Field and published by Addison Wesley Longman. This book was released on 1973 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Group finding with Photometric Redshifts written by Bryan Gillis and published by . This book was released on 2010 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present a galaxy group-finding algorithm, the Photo-z Probability Peaks (P3) algorithm, optimized for locating small galaxy groups using photometric redshift data by searching for peaks in the signal-to-noise of the local overdensity of galaxies in a 3-dimensional grid. This method is an improvement over similar matched-filter methods in reducing background contamination through the use of redshift information, allowing it to accurately detect groups to a much lower size limit. We present the results of tests of our algorithm on galaxy catalogues from the Millennium Simulation. For typical settings of our algorithm and photometric redshift accuracy of sigma_z = 0.05 it attains a purity of 84% and detects ~83 groups/deg.^2 with an average group size of 5.5 members. With photometric redshift accuracy of sigma_z = 0.02, it attains a purity of 94% and detects ~80 groups/deg.^2 with an average group size of 6.3 members. We also test our algorithm on data available for the COSMOS field and the presently-available fields from the CFHTLS-Wide survey, presenting preliminary results of this analysis.

Download or read book Photometric Redshifts and High Redshift Galaxies written by and published by . This book was released on 1999 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimizing Spectroscopic and Photometric Galaxy Surveys written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The combination of multiple cosmological probes can produce measurements of cosmological parameters much more stringent than those possible with any individual probe. We examine the combination of two highly correlated probes of late-time structure growth: (i) weak gravitational lensing from a survey with photometric redshifts and (ii) galaxy clustering and redshift space distortions from a survey with spectroscopic redshifts. We choose generic survey designs so that our results are applicable to a range of current and future photometric redshift (e.g. KiDS, DES, HSC, Euclid) and spectroscopic redshift (e.g. DESI, 4MOST, Sumire) surveys. Combining the surveys greatly improves their power to measure both dark energy and modified gravity. An independent, non-overlapping combination sees a dark energy figure of merit more than 4 times larger than that produced by either survey alone. The powerful synergies between the surveys are strongest for modified gravity, where their constraints are orthogonal, producing a non-overlapping joint figure of merit nearly 2 orders of magnitude larger than either alone. Our projected angular power spectrum formalism makes it easy to model the cross-correlation observable when the surveys overlap on the sky, producing a joint data vector and full covariance matrix. We calculate a same-sky improvement factor, from the inclusion of these cross-correlations, relative to non-overlapping surveys. We find nearly a factor of 4 for dark energy and more than a factor of 2 for modified gravity. The exact forecast figures of merit and same-sky benefits can be radically affected by a range of forecasts assumption, which we explore methodically in a sensitivity analysis. We show that that our fiducial assumptions produce robust results which give a good average picture of the science return from combining photometric and spectroscopic surveys.

Download or read book Cluster Mass Calibration at High Redshift written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We present an HST/ACS weak gravitational lensing analysis of 13 massive high-redshift (z_median=0.88) galaxy clusters discovered in the South Pole Telescope (SPT) Sunyaev-Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass-observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V-I colour. Our estimate of the source redshift distribution is based on CANDELS data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the mass-concentration relation using simulations. In combination with temperature estimates from Chandra we constrain the normalisation of the mass-temperature scaling relation ln(E(z) M_500c/10^14 M_sun)=A+1.5 ln(kT/7.2keV) to A=1.81^{+0.24}_{-0.14}(stat.) +/- 0.09(sys.), consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to c_200c=5.6^{+3.7}_{-1.8}.

Download or read book Probabilistic Photometric Redshift Estimation in Massive Digital Sky Surveys Via Machine Learning written by Antonio D'Isanto and published by . This book was released on 2019* with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: The problem of photometric redshift estimation is a major subject in astronomy, since the need of estimating distances for a huge number of sources, as required by the data deluge of the recent years. The ability to estimate redshifts through spectroscopy does not scale with this avalanche of data. Photometric redshifts provide the required redshift estimates at the cost of some precision. The success of several forthcoming missions is highly dependent on the availability of photometric redshifts. The purpose of this thesis is to provide innovative methods for photometric redshift estimation. Two models are proposed. The first is fully-automatized, based on the combination of a convolutional neural network with a mixture density network, to predict probabilistic multimodal redshifts directly from images. The second model is features-based, performing a massive combination of photometric parameters to apply a forward selection in a huge feature space. The proposed models perform very efficiently compared to some of the most common models used in the literature. An important part of the work is dedicated to the correct estimation of the errors and prediction quality. The proposed models are very general and can be applied to different topics in astronomy and beyond.

Download or read book The SDSS Coadd written by and published by . This book was released on 2011 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Coadd Data. We use the Artificial Neural Network (ANN) technique to calculate photo-z's and the Nearest Neighbor Error (NNE) method to estimate photo-z errors for H"13 million objects classified as galaxies in the coadd with r