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Dive into the research topics where Alexander Gray is active.

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Featured researches published by Alexander Gray.


The Astrophysical Journal | 2006

First Measurement of the Clustering Evolution of Photometrically Classified Quasars

Adam D. Myers; Robert J. Brunner; Gordon T. Richards; Robert C. Nichol; Donald P. Schneider; Daniel E. Vanden Berk; Ryan Scranton; Alexander Gray; J. Brinkmann

We present new measurements of the quasar angular autocorrelation function from a sample of ~80,000 photometrically classified quasars taken from the First Data Release of the Sloan Digital Sky Survey. We find a best-fit model of ω(θ) = (0.066)θ-(0.98±0.15) for the angular correlation function, consistent with estimates of the slope from spectroscopic quasar surveys. We show that only models with little or no evolution in the clustering of quasars in comoving coordinates since a median redshift of z ~ 1.4 can recover a scale length consistent with local galaxies and active galactic nuclei (AGNs). A model with little evolution of quasar clustering in comoving coordinates is best explained in the current cosmological paradigm by rapid evolution in quasar bias. We show that quasar biasing must have changed from bQ ~ 3 at a (photometric) redshift of phot = 2.2 to bQ ~ 1.2-1.3 by phot = 0.75. Such a rapid increase with redshift in biasing implies that quasars at z ~ 2 cannot be the progenitors of modern L* objects; rather they must now reside in dense environments, such as clusters. Similarly, the duration of the UVX (ultraviolet-excess) quasar phase must be short enough to explain why local UVX quasars reside in essentially unbiased structures. Our estimates of bQ are in good agreement with recent spectroscopic results (Croom et al. 2005), which demonstrate that the implied evolution in bQ is consistent with quasars inhabiting halos of similar mass at every redshift. Treating quasar clustering as a bivariate function of both redshift and luminosity, we find no evidence for luminosity dependence in quasar clustering, and that redshift evolution thus affects quasar clustering more than changes in quasars luminosity. Our results are robust against a range of systematic uncertainties. We provide a new method for quantifying stellar contamination in photometrically classified quasar catalogs via the correlation function.


Archive | 2015

Configurable machine learning method selection and parameter optimization system and method

Maxsim Gibiansky; Ryan Riegel; Yi Yang; Parikshit Ram; Alexander Gray


Archive | 2017

Interoperability of Transforms Under a Unified Platform and Extensible Transformation Library of Those Interoperable Transforms

Abhimanyu Aditya; Abhishek Gupta; Alexander Gray; Bradley Simmons; Maxsim Gibiansky; Nicholas Ball; Sanjay Mehta; Sergey Kirshner; Terison Gregory


Archive | 2016

User Interface for Unified Data Science Platform Including Management of Models, Experiments, Data Sets, Projects, Actions and Features

Alexander Gray; Christopher Nelson; Vladimir Rodeski; Lawrence Kite; Nitesh Kumar; Maxsim Gibiansky; Sachinder Chawla; Philip Song; Abhimanyu Aditya


Archive | 2012

Multitree Algorithms for Large-Scale Astrostatistics

William B. March; Arkadas Ozakin; Dongryeol Lee; Ryan Riegel; Alexander Gray


Archive | 2017

Supervised Learning Based Recommendation System

Nitesh Kumar; Arkadas Ozakin; Alexander Gray; Abhimanyu Aditya


Archive | 2017

Modeling of Geospatial Location Over Time

Sergey Kirshner; Alexander Gray; Lawrence Kite


Archive | 2016

System and Method for Using Machine Learning to Generate a Model from Audited Data

Alexander Gray; Sergey Kirshner


Archive | 2016

Modélisation d'un emplacement géo-spatial au cours du temps

Sergey Kirshner; Alexander Gray; Lawrence Kite


Archive | 2015

Sélection configurable de procédé d'apprentissage automatique et système et procédé d'optimisation de paramètres

Maxsim Gibiansky; Ryan Riegel; Yi Yang; Parikshit Ram; Alexander Gray

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Arkadas Ozakin

Georgia Tech Research Institute

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Daniel E. Vanden Berk

Pennsylvania State University

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Dongryeol Lee

Georgia Institute of Technology

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Nikolaos Vasiloglou

Georgia Institute of Technology

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