Joel R Brownstein

University of Utah
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Articles (14)

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

We introduce the Sloan Digital Sky Survey (SDSS)/ Apache Point Observatory Galactic Evolution Experiment (APOGEE) value-added catalogue of Galactic globular cluster (GC) stars. The catalogue is the result of a critical search of the APOGEE Data Release 17 (DR17) catalogue for candidate members of all known Galactic GCs. Candidate members are assigned to various GCs on the basis of position in the sky, proper motion, and radial velocity. The catalogue contains a total of 7737 entries for 6422 unique stars associated with 72 Galactic GCs. Full APOGEE DR17 information is provided, including radial velocities and abundances for up to 20 elements. Membership probabilities estimated on the basis of precision radial velocities are made available. Comparisons with chemical compositions derived from the GALactic Archaeology with HERMES (GALAH) survey, as well as optical values from the literature, show good agreement. This catalogue represents a significant increase in the public data base of GC star chemical compositions and kinematics, providing a massive homogeneous data set that will enable a variety of studies. The catalogue in fits format is available for public download from the SDSS-IV DR17 value-added catalogue website.

Year:

2023

Year:

2023

Year:

2023

We present the measurements of the small-scale clustering for the emission-line galaxy (ELG) sample from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) in the Sloan Digital Sky Survey IV (SDSS-IV). We use conditional abundance matching method to interpret the clustering measurements from 0.34 to $70\, h^{-1}\, \textrm {Mpc}$. In order to account for the correlation between properties of ELGs and their environment, we add a secondary connection between star formation rate of ELGs and halo accretion rate. Three parameters are introduced to model the ELG [O ii] luminosity and to mimic the target selection of eBOSS ELGs. The parameters in our models are optimized using Markov Chain Monte Carlo (MCMC) method. We find that by conditionally matching star formation rate of galaxies and the halo accretion rate, we are able to reproduce the eBOSS ELG small-scale clustering within 1σ error level. Our best-fitting model shows that the eBOSS ELG sample only consists of $\sim 12{{\ \rm per\ cent}}$ of all star-forming galaxies, and the satellite fraction of eBOSS ELG sample is 19.3 per cent. We show that the effect of assembly bias is $\sim 20{{\ \rm per\ cent}}$ on the two-point correlation function and $\sim 5{{\ \rm per\ cent}}$ on the void probability function at scale of $r\sim 20 \, h^{-1}\, \rm Mpc$.

Year:

2022

Year:

2020

Year:

2020

Year:

2020

Year:

2020

Collaborators (12)

Carles Badenes

University of Pittsburgh

UNITED STATES
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johan comparat

Max Planck Institute for Extraterrestrial Physics

GERMANY
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Yue Shen

University of Illinois at Urbana-Champaign

UNITED STATES
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Andres Almeida

University of Virginia

UNITED STATES
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Guy S Stringfellow

University of Colorado Boulder

UNITED STATES
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Alina Streblyanska

Instituto de Astrofísica de Andalucía

SPAIN
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Kathleen Barger

Assistant Professor

Texas Christian University

UNITED STATES
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Mara Salvato

Max Planck Institute for Extraterrestrial Physics

GERMANY
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Kyle Westfall

University of California

UNITED STATES
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Ignasi Pérez-Ràfols

Sorbonne Université

FRANCE
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Carla Frohlich

Professor

North Carolina State University

UNITED STATES
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Jessie Runnoe

Adjunct Professor of Physics

Fisk University

UNITED STATES
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