相关论文: Archetype-Based Redshift Estimation for the Dark E…

Determining the distribution of redshifts for galaxies in wide-field photometric surveys is essential for robust cosmological studies of weak gravitational lensing. We present the methodology, calibrated redshift distributions, and…

Optical galaxy cluster identification algorithms such as redMaPPer promise to enable an array of astrophysical and cosmological studies, but suffer from biases whereby galaxies in front of and behind a galaxy cluster are mistakenly…

Photometric redshifts are estimated on the basis of template scenarios with the help of the code ZPEG, an extension of the galaxy evolution model PEGASE.2 and available on the PEGASE web site. The spectral energy distribution (SED)…

Dark Energy Spectroscopic Instrument (DESI) observations, when combined with Cosmic Microwave Background (CMB) and Type Ia supernovae (SNe), have led to statistically significant dynamical dark energy (DDE) claims. In this letter we…

The Dark Energy Survey (DES; operations 2009-2015) will address the nature of dark energy using four independent and complementary techniques: (1) a galaxy cluster survey over 4000 deg2 in collaboration with the South Pole Telescope…

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this…

Estimating redshifts from broadband photometry is often limited by how accurately we can map the colors of galaxies to an underlying spectral template. Current techniques utilize spectrophotometric samples of galaxies or spectra derived…

A new method is developed for estimating photometric redshifts to galaxies, using realistic template SEDs, extending over four decades in wavelength (i.e. from 0.05 micron to 1 mm). The template SEDs are constructed for four different…

Wide-field slitless spectroscopic galaxy surveys, such as the one performed by the upcoming Chinese Space Station Survey Telescope (CSST), are crucial for precision cosmology but present formidable data analysis challenges. Because spectra…

We present two methods for determining spectroscopic redshifts of galaxies in the DEEP2 survey which display only one identifiable feature, an emission line, in the observed spectrum ("single-line galaxies"). First, we assume each single…

Chinese Space Station Telescope (CSST) has the capability to conduct slitless spectroscopic survey simultaneously with photometric survey. The spectroscopic survey will measure slitless spectra, potentially providing more accurate…

We describe a method for estimating the power spectrum of density fluctuations from galaxy redshift surveys that yields improvement in both accuracy and resolution over direct Fourier analysis. The key feature of this analysis is expansion…

Estimating galaxy redshifts is crucial for constraining key physical quantities like those in the equation of state of dark energy. Modern telescopes such as the James Webb Space Telescope, the Euclid Space Telescope, and the NASA Nancy…

We present a new method to estimate redshift distributions and galaxy-dark matter bias parameters using correlation functions in a fully data driven and self-consistent manner. Unlike other machine learning, template, or correlation…

In this paper, we employ two model-independent approaches, including redshift binning method and polynomial interpolation method, to reconstruct dark energy (DE) equation of state (EoS) $w(z)$ and DE density function $f(z)$. Our analysis…

Accurately characterizing the redshift distributions of galaxies is essential for analysing deep photometric surveys and testing cosmological models. We present a technique to simultaneously infer redshift distributions and individual…

With the increasing number of deep multi-wavelength galaxy surveys, the spectral energy distribution (SED) of galaxies has become an invaluable tool for studying the formation of their structures and their evolution. In this context,…

Reconstructing the mass density, velocity, and tidal (MTV) fields of dark matter from galaxy surveys is essential for advancing our understanding of the LSS of the Universe. In this work, we present a machine learning-based framework using…

We present the photometric redshift characterization and calibration for the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern…

We present a novel approach to analyzing astronomical spectral survey data using our non-linear extension of an online dictionary learning algorithm. Current and upcoming surveys such as SPHEREx will use spectral data to build a 3D map of…