Download or read book Precise Photometric Redshifts with Narrow band Filters Quality Cuts and Their Impact on the Measured Galaxy Clustering written by Pol Martí Sanahuja and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Precise Photometric Redshifts with Narrow band Filters Quality Cuts and Their Impact on the Measured Galaxy Clustering written by Pol Martí Sanahuja and published by . This book was released on 2014 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Galaxy Clustering with Photometric Surveys Using PDF Redshift Information written by and published by . This book was released on 2016 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here, photometric surveys produce large-area maps of the galaxy distribution, but with less accurate redshift information than is obtained from spectroscopic methods. Modern photometric redshift (photo-z) algorithms use galaxy magnitudes, or colors, that are obtained through multi-band imaging to produce a probability density function (PDF) for each galaxy in the map. We used simulated data to study the effect of using different photo-z estimators to assign galaxies to redshift bins in order to compare their effects on angular clustering and galaxy bias measurements. We found that if we use the entire PDF, rather than a single-point (mean or mode) estimate, the deviations are less biased, especially when using narrow redshift bins. When the redshift bin widths are $\Delta z=0.1$, the use of the entire PDF reduces the typical measurement bias from 5%, when using single point estimates, to 3%.
Download or read book Astroinformatics IAU S325 written by Massimo Brescia and published by Cambridge University Press. This book was released on 2017-06-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Astronomy has become data-driven in ways that are both quantitatively and qualitatively different from the past: data structures are not simple; procedures to gain astrophysical insights are not obvious; and the informational content of the data sets is so high that archival research and data mining are not merely convenient, but obligatory, as researchers who obtain the data can only extract a small fraction of the science enabled by it. IAU Symposium 325 took place at a crucial stage in the development of the field, when many efforts have carried significant achievements, but the widespread groups have just begun to effectively communicate across specialties, to gather and assimilate their achievements, and to consult cross-disciplinary experts. Bringing together astronomers involved in surveys and large simulation projects, computer scientists, data scientists, and companies, this volume showcases their fruitful exchange of ideas, methods, software, and technical capabilities.
Download or read book Optical Galaxy Cluster Detection Across a Wide Redshift Range written by and published by . This book was released on 2009 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past decade is one of the most exciting period in the history of physics and astronomy. The discovery of cosmic acceleration dramatically changed our understanding about the evolution and constituents of the Universe. To accommodate the new acceleration phase into our well established Big Bang cosmological scenario under the frame work of General Relativity, there must exist a very special substance that has negative pressure and make up about 73% of the total energy density in our Universe. It is called Dark Energy. For the first time people realized that the vast majority of our Universe is made of things that are totally different from the things we are made of. Therefore, one of the major endeavors in physics and astronomy in the coming years is trying to understand, if we can, the nature of dark energy. Understanding dark energy cannot be achieved from pure logic. We need empirical evidence to finally determine about what is dark energy. The better we can constrain the energy density and evolution of the dark energy, the closer we will get to the answer. There are many ways to constrain the energy density and evolution of dark energy, each of which leads to degeneracy in certain directions in the parameter space. Therefore, a combination of complimentary methods will help to reduce the degeneracies and give tighter constraints. Dark energy became dominate over matter in the Universe only very recently (at about z (almost equal to) 1.5) and will affect both the cosmological geometry and large scale structure formation. Among the various experiments, some of them constrain the dark energy mainly via geometry (such as CMB, Supernovae) while some others provides constraints from both structures and geometry (such as BAO, Galaxy Clusters) Galaxy clusters can be used as a sensitive probe for cosmology. A large cluster catalog that extends to high redshift with well measured masses is indispensable for precisely constraining cosmological parameters. Detecting clusters in optical bands is very efficient. Multi-color CCD photometry allows combined detection and redshift estimation for clusters across broad redshift ranges. However, the lack of precise information about galaxy positions along the line of sight leads to contamination by projection, which plagues both cluster detection and the measurement of their properties. The dominance of red sequence galaxies, tightly clustered along the E/S0 ridgeline, provides a powerful method for de-projecting field galaxies. We developed an Error Corrected Gaussian Mixture Model to fit the galaxies color distribution around clusters by taking into account the measurement errors. By this technique, we can detect the red sequence color clustering and extract unbiased information about the evolution of the red sequence ridgeline and its width. Precision measurements of ridgelines yields better estimates of cluster richness and possibly their dynamical state, leading to better estimates of cluster mass. By using the red sequence clustering in color space identified from the Error Corrected Gaussian Mixture Model, together with the projected NFW filter in the projected RA/DEC plane, we developed a new and efficient cluster finding algorithm that can reliably detect galaxy clusters across the redshift range from 0.1 to 1.4. We have also run the cluster finder on legacy SDSS DR7 data and assembled an approximately volume limited cluster catalog across redshifts from 0.1 to 0.5. The algorithm has been tested against a Monte Carlo mock catalog, showing the identified clusters are highly complete and pure. With the completion of this thesis, we build the first and essential step towards precision cluster cosmology. Meanwhile, the large optical cluster catalog across a wide redshift range makes possible the systematic and detailed investigation of cluster formation and evolution.
Download or read book The Distribution of Star forming Galaxies in Intermediate Redshift Galaxy Clusters written by Steven Michael Crawford and published by . This book was released on 2006 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Cosmological Physics written by J. A. Peacock and published by Cambridge University Press. This book was released on 1999 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and authoritative introduction to contemporary cosmology for advanced undergraduate and graduate students.
Download or read book Photometric Properties of Low redshift Galaxy Clusters written by and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Seeing Red written by Halton C. Arp and published by Apeiron. This book was released on 1998 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 360 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Automating the Measurements of Galaxy Redshifts and ISM Properties Using CNN written by Rohan Pattnaik and published by . This book was released on 2021 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Studying the effects that the local environments of galaxies have on their interstellar medium (ISM) properties is crucial for understanding galaxy evolution and large scale structure of the universe. In order to do that we need precise measurements of ISM properties like Star Formation Rate (SFR), metallicity (Z), ionization parameter (U), gas pressure, and extinction. Accurate estimation of redshift and emission line fluxes from a galaxy's spectrum is the first step in measuring these ISM properties. Current techniques for these measurements still rely on time-consuming manual efforts or error-prone cross-correlation codes that are already struggling to process the vast quantities of spectroscopic data that currently exist. With future NASA missions like JWST, Euclid, Roman, and SPHEREx expected to produce even larger amounts of spectroscopic data, a fast and reliable alternative to the current techniques of spectroscopic measurements is the need of the hour. To that end, we train a Convolutional Neural Network (CNN) to estimate redshift directly from an input spectrum. We generate a library of synthetic spectra spanning a wide range of parameter values and use it to train the CNN and later evaluate its performance. We obtain a normalized mean absolute deviation (NMAD) value of 0.0086 and an outlier fraction of 5.36% for our test set. This accuracy and precision is comparable to the current best photometric redshifts estimated using SED fitting codes and is lower than the subset of high quality spectroscopic data estimated using time and labour-intensive techniques. In comparison, our CNN is able to process ~30,000 spectra in around five seconds giving it an important advantage over the current methods of redshift estimation. We plan to extend this technique to estimating other ISM properties from galaxy spectra in the future."--Abstract.
Download or read book Clustering at High Redshift written by Alain Mazure and published by . This book was released on 2000 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Astronomers, astrophysicists, and other scientists and researchers from laboratories, observatories, and universities throughout North America, Europe, Asia, and the Middle East present 60 contributions addressing clustering from low to high redshift; clustering measurements in surveys; IR and sub-mm surveys; theory and models; high-redshift clusters of galaxies; QSO absorption lines; primordial galaxies; clustering around QSOs and radio galaxies; and the physics of the intra-cluster medium. Approximately 40 poster sessions are also presented. Lacks an index. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Download or read book Photometric Calibration Procedures written by Velma I. Burns and published by . This book was released on 1972 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Photometric Redshifts and Physical Properties of Low Redshift Galaxies written by Celine Eminian and published by . This book was released on 2009 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt:
