Related papers: Machine Learning Techniques for Astrophysics and C…
Redshift estimation and the classification of gamma-ray AGNs represent crucial challenges in the field of gamma-ray astronomy. Recent efforts have been made to tackle these problems using traditional machine learning methods. However, the…
I review selected current observations of distant galaxies and our interpretation of the fragile (and occasionally contradictory) data. Galaxies at the ``contemporary limit'' of technology and redshift (z~6) are difficult to locate in the…
We present a metric to quantify systematic labeling bias in galaxy morphology data sets stemming from the quality of the labeled data. This labeling bias is independent from labeling errors and requires knowledge about the intrinsic…
We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectral energy distributions with a population model and a noise…
We discuss a method aiming to use photometric redshifts in lensing clusters to access the population of distant background sources. The amplification provided by gravitational lensing allows to calibrate photometric redshifts 1 to 3…
Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy…
The development of the state-of-the-art telescopic systems capable of performing expansive sky surveys such as the Sloan Digital Sky Survey, Euclid, and the Rubin Observatory's Legacy Survey of Space and Time (LSST) has significantly…
In Lima et al. 2008 we presented a new method for estimating the redshift distribution, N(z), of a photometric galaxy sample, using photometric observables and weighted sampling from a spectroscopic subsample of the data. In this paper, we…
We explore the enhanced self-calibration of photometric galaxy redshift distributions, $n(z)$, through the combination of up to six two-point functions. Our $\rm 3\times2pt$ configuration is comprised of photometric shear, spectroscopic…
Current and upcoming imaging galaxy surveys are pushing galaxy samples to higher and higher redshifts. This push will be more pronounced for lens galaxies, for which we only need to measure galaxy positions, not shapes. As a result, we will…
We describe an Artificial Neural Network (ANN) approach to classification of galaxy images and spectra. ANNs can replicate the classification of galaxy images by a human expert to the same degree of agreement as that between two human…
We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased…
The inclination of galaxies induces both reddening and extinction to their observed spectral energy distribution, which in turn impact the derived properties of the galaxies. Here we report a significant dependence of the error in…
We conduct a comprehensive study of the effects of incorporating galaxy morphology information in photometric redshift estimation. Using machine learning methods, we assess the changes in the scatter and catastrophic outlier fraction of…
This paper explores the application of machine learning methods for classifying astronomical sources using photometric data, including normal and emission line galaxies (ELGs; starforming, starburst, AGN, broad line), quasars, and stars. We…
In Astronomy, a huge amount of image data is generated daily by photometric surveys, which scan the sky to collect data from stars, galaxies and other celestial objects. In this paper, we propose a technique to leverage unlabeled…
Three-dimensional wide-field galaxy surveys are fundamental for cosmological studies. For higher redshifts (z > 1.0), where galaxies are too faint, quasars still trace the large-scale structure of the Universe. Since available telescope…
We calculate photometric redshifts from the Sloan Digital Sky Survey Main Galaxy Sample, The Galaxy Evolution Explorer All Sky Survey, and The Two Micron All Sky Survey using two new training-set methods. We utilize the broad-band…
Wide field images taken in several photometric bands allow simultaneous measurement of redshifts for thousands of galaxies. A variety of algorithms to make this measurement have appeared in the last few years, the majority of which can be…
The galaxy intrinsic alignment causes the galaxy ellipticity-ellipticity power spectrum between two photometric redshifts to decrease faster with respect to the redshift separation $\Delta z^P$, for fixed mean redshift. This offers a…