相关论文: Red Dragon: A Redshift-Evolving Gaussian Mixture M…
We present a data-driven fuzzy set framework for classifying galaxies into the red sequence, blue cloud, and green-valley populations using multiple observables from the Sloan Digital Sky Survey (SDSS DR18). Unlike traditional methods based…
We describe a new method for measuring the true redshift distribution of any set of objects studied only photometrically. The angular cross-correlation between objects in a photometric sample with objects in some spectroscopic sample as a…
Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time (LSST) are all critically dependent on estimates of…
This is the first paper of a series where we study the clustering of LRG galaxies in the latest spectroscopic SDSS data release, DR6, which has 75000 LRG galaxies covering over 1 $Gpc^3/h^3$ at $0.15<z<0.47$. Here we focus on modeling…
We discuss the construction of a photometric redshift catalogue of Luminous Red Galaxies (LRGs) from the Sloan Digital Sky Survey (SDSS), emphasizing the principal steps necessary for constructing such a catalogue -- (i) photometrically…
Connecting galaxies with their descendants (or progenitors) at different redshifts can yield strong constraints on galaxy evolution. Observational studies have historically selected samples of galaxies using a physical quantity, such as…
Measuring cosmic shear in wide-field imaging surveys requires accurate knowledge of the redshift distribution of all sources. The clustering-redshift technique exploits the angular cross-correlation of a target galaxy sample with unknown…
[Abridged] We assemble a sample of 45 intermediate X-ray luminosity galaxy clusters at low redshifts using SDSS data to conduct a comprehensive investigation into the photometric variation of red sequence modal galaxy colours with…
The redshift evolution of the galaxy two-point correlation function is a fundamental cosmological statistic. To identify similar galaxy populations at different redshifts, we select a strict volume-limited sample culled from the 6100…
We present a new two-color algorithm, the "Stellar Bump Sequence" (SBS), that is optimized for robustly identifying candidate high-redshift galaxy clusters in combined wide-field optical and mid-infrared (MIR) data. The SBS algorithm is a…
We investigate how well the redshift distributions of galaxies sorted into photometric redshift bins can be determined from the galaxy angular two-point correlation functions. We find that the uncertainty in the reconstructed redshift…
In order to study the galaxy population of galaxy clusters with photometric data one must be able to accurately discriminate between cluster members and non-members. The redMaPPer cluster finding algorithm treats this problem…
Understanding galaxy morphology evolution across cosmic time requires models that can generate realistic galaxy populations conditioned on redshift. In this work, we study efficient redshift-conditioned generative modeling for astrophysical…
The low statistical errors on cosmological parameters promised by future galaxy surveys will only be realised with the development of new, fast, analysis methods that reduce potential systematic problems to low levels. We present an…
Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a…
The aim of the Gemini Deep Deep Survey is to push spectroscopic studies of complete galaxy samples (both red and blue objects) significantly beyond z=1; this is the redshift where the current Hubble sequence of ellipticals and spirals is…
Improving distance measurements in large imaging surveys is a major challenge to better reveal the distribution of galaxies on a large scale and to link galaxy properties with their environments. Photometric redshifts can be efficiently…
In this paper we describe a set of models to predict the colours of galaxies over a wide range of redshifts. We present example output from the simulations, and discuss their application to the selection of galaxies at high redshifts,…
We present a modified adaptive matched filter algorithm designed to identify clusters of galaxies in wide-field imaging surveys such as the Sloan Digital Sky Survey. The cluster-finding technique is fully adaptive to imaging surveys with…
Based on the Sloan Digital Sky Survey Data Release 5 Galaxy Sample, we explore photometric morphology classification and redshift estimation of galaxies using photometric data and known spectroscopic redshifts. An unsupervised method,…