Related papers: The Zurich Extragalactic Bayesian Redshift Analyze…
We have developed and characterized an imaging instrument to measure the spatial properties of the diffuse near-infrared extragalactic background light in a search for fluctuations from z > 6 galaxies during the epoch of reionization. The…
Accurately characterizing the true redshift (true-$z$) distribution of a photometric redshift (photo-$z$) sample is critical for cosmological analyses in imaging surveys. Clustering-based techniques, which include clustering-redshift (CZ)…
We present zea (pronounced ze-yah), a Python package for cognitive ultrasound imaging that offers a flexible, modular, and differentiable pipeline for ultrasound data processing. Additionally, it includes a collection of pre-defined models…
We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1…
We present a comparison between the published optical, IR and CO spectroscopic redshifts of 86 (sub-)mm galaxies and their photometric redshifts as derived from long-wavelength radio-mm-FIR photometric data. The redshift accuracy measured…
Supernova cosmology without spectra will be an important component of future surveys such as LSST. This lack of supernova spectra results in uncertainty in the redshifts which, if ignored, leads to significantly biased estimates of…
Due to their highly luminous nature, gamma-ray bursts (GRBs) are useful tools in studying the early Universe (up to z = 10). We consider whether the available subset of Swift high redshift GRBs are unusual when compared to analogous…
We perform a systematic analysis of the effects of photometric redshift uncertainties on weak lensing tomography. We describe the photo-z distribution with a bias and Gaussian scatter that are allowed to vary arbitrarily between intervals…
Context. Knowing the exact shape of the UV luminosity function of high-redshift galaxies is important in order to understand the star formation history of the early universe. However, the uncertainties, especially at the faint and bright…
We investigate colour selection techniques for high redshift galaxies in the UKIDSS Ultra Deep Survey Early Data Release (UDS EDR). Combined with very deep Subaru optical photometry, the depth (K_AB = 22.5) and area (0.62 deg^2) of the UDS…
Machine learning techniques offer a plethora of opportunities in tackling big data within the astronomical community. We present the set of Generalized Linear Models as a fast alternative for determining photometric redshifts of galaxies, a…
Photometric redshifts (photo-$z$'s) will be crucial for studies of galaxy evolution, large-scale structure, and transients with the Nancy Grace Roman Space Telescope. Deep learning methods leverage pixel-level information from ground-based…
The Euclid survey aims to trace the evolution of cosmic structures up to redshift $z$ $\sim$ 3 and beyond. Its success depends critically on obtaining highly accurate mean redshifts for ensembles of galaxies $n(z)$ in all tomographic bins,…
We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…
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 describe the Einstein Toolkit, a community-driven, freely accessible computational infrastructure intended for use in numerical relativity, relativistic astrophysics, and other applications. The Toolkit, developed by a collaboration…
We apply instance-based machine learning in the form of a k-nearest neighbor algorithm to the task of estimating photometric redshifts for 55,746 objects spectroscopically classified as quasars in the Fifth Data Release of the Sloan Digital…
The SKA will be a unique instrument with which to study the evolution of the gas content of galaxies. A proposed deep (~8 Msec) 'pencil-beam' survey is simulated using recently updated specifications for SKA sensitivity and survey speed.…
This dissertation as a whole aims to provide means to better understand hot-Jupiter planets through observing, performing thermochemical calculations, and modeling their atmospheres. We used Spitzer multi-wavelength secondary-eclipse…
We present a proof-of-concept analysis of photometric redshifts with Bayesian priors on physical properties of galaxies. This concept is particularly suited for upcoming/on-going large imaging surveys, in which only several broad-band…