Related papers: Approximating photo-$z$ PDFs for large surveys
The amount, size, and complexity of astronomical data-sets and databases are growing rapidly in the last decades, due to new technologies and dedicated survey telescopes. Besides dealing with poly-structured and complex data, sparse data…
Weak gravitational lensing surveys using photometric redshifts can have their cosmological constraints severely degraded by errors in the photo-z scale. We explore the cosmological degradation vs the size of the spectroscopic survey…
The class of location-scale finite mixtures is of enduring interest both from applied and theoretical perspectives of probability and statistics. We prove the following results: to an arbitrary degree of accuracy, (a) location-scale…
In the next decade, the LSST will become a major facility for the astronomical community. However accurately determining the redshifts of the observed galaxies without using spectroscopy is a major challenge. Reconstruction of the redshifts…
We describe a new test of photometric redshift performance given a spectroscopic redshift sample. This test complements the traditional comparison of redshift {\it differences} by testing whether the probability density functions $p(z)$…
The probability density function (PDF) associated with a given set of samples is approximated by a piecewise-linear polynomial constructed with respect to a binning of the sample space. The kernel functions are a compactly supported basis…
We present a new method for obtaining photometric redshifts (photo-z) for sources observed by multiple photometric surveys using a combination (conflation) of the redshift probability distributions (PDZs) obtained independently from each…
Wide, deep photometric surveys require robust photometric redshift estimates (photo-z's) for studies of large-scale structure. These estimates depend critically on accurate photometry. We describe the improvements to the photometric…
A set of quasi-parton distribution functions (quasi-PDFs) have been recently proposed by Ji. Defined as the matrix elements of equal-time spatial correlations, they can be computed on the lattice and should reduce to the standard PDFs when…
Recent expansions in multimedia devices gather enormous amounts of real-time images for processing and inference. The images are first compressed using compression schemes, like JPEG, to reduce storage costs and power for transmitting the…
Evaluating the accuracy and calibration of the redshift posteriors produced by photometric redshift (photo-z) estimators is vital for enabling precision cosmology and extragalactic astrophysics with modern wide-field photometric surveys.…
We describe a new program for determining photometric redshifts, dubbed EAZY. The program is optimized for cases where spectroscopic redshifts are not available, or only available for a biased subset of the galaxies. The code combines…
We present a neural network classification (NNC) method for photometric redshift estimation that produces well-calibrated redshift probability density functions (PDFs). The method discretizes the redshift space into ordered bins and…
Accurate photometric redshifts are a lynchpin for many future experiments to pin down the cosmological model and for studies of galaxy evolution. In this study, a novel sparse regression framework for photometric redshift estimation is…
We quantify the cosmological constraining power of the `lensing PDF' - the one-point probability density of weak lensing convergence maps - by modelling this statistic numerically with an emulator trained on $w$CDM cosmic shear simulations.…
Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the…
We developed a Deep Convolutional Neural Network (CNN), used as a classifier, to estimate photometric redshifts and associated probability distribution functions (PDF) for galaxies in the Main Galaxy Sample of the Sloan Digital Sky Survey…
Given sufficiently many components, it is often cited that finite mixture models can approximate any other probability density function (pdf) to an arbitrary degree of accuracy. Unfortunately, the nature of this approximation result is…
When analyzing galaxy clustering in multi-band imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision,…
Current and future weak lensing surveys will rely on photometrically estimated redshifts of very large numbers of galaxies. In this paper, we address several different aspects of the demanding photo-z performance that will be required for…