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Abundance matching analysis of the emission line galaxy sample in the extended Baryon Oscillation Spectroscopic Survey

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Sicheng Lin, Jeremy L. Tinker, Michael R. Blanton, Hong Guo, Anand Raichoor, Johan Comparat, Joel R. Brownstein

Cosmology and Nongalactic Astrophysics · Submitted 18 Feb 2023

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim 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 1$\sigma$ error level.

how it is stated · asserted 1.00 read the record →

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arXiv ID2302.09199 (version 1)
Pith IDDU5ITZGL, Pith's permanent record of this paper and its review
CitationAnand Raichoor, Hong Guo, Jeremy L. Tinker, Joel R. Brownstein, Johan Comparat, Michael R. Blanton, Sicheng Lin. "Abundance matching analysis of the emission line galaxy sample in the extended Baryon Oscillation Spectroscopic Survey." arXiv:2302.09199 (2023). https://pith.science/paper/DU5ITZGL
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 6,507 input tokens.

What the abstract itself states, as probabilities: claims first 0.02 · states limitation 0.19 · human participants 0.02 · controlled comparison 0.08 · randomized assignment 0.01 · states quantitative result 0.99 · compares with prior results 0.19 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

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 $0.34h^{-1}\textrm{Mpc}$ to $70h^{-1}\textrm{Mpc}$. In order to account for the correlation between properties of emission line galaxies 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 [OII] 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 1$\sigma$ error level. Our best fit model shows that the eBOSS ELG sample only consists of $\sim 12\%$ of all star-forming galaxies, and the satellite fraction of eBOSS ELG sample is 19.3\%. We show that the effect of assembly bias is $\sim20\%$ on the two-point correlation function and $\sim5\%$ on the void probability function at scale of $r\sim 20 h^{-1}\rm Mpc$.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 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). contribution 0.99 0.96 0.03 asserted 1.00
s1 We use conditional abundance matching method to interpret the clustering measurements from $0.34h^{-1}\textrm{Mpc}$ to $70h^{-1}\textrm{Mpc}$. method 0.97 0.94 0.04 asserted 0.99
s2 In order to account for the correlation between properties of emission line galaxies and their environment, we add a secondary connection between star formation rate of ELGs and halo accretion rate. method 0.95 0.88 0.04 asserted 0.93
s3 Three parameters are introduced to model the ELG [OII] luminosity and to mimic the target selection of eBOSS ELGs. method 0.99 0.91 0.02 asserted 0.99
s4 The parameters in our models are optimized using Markov Chain Monte Carlo (MCMC) method. method 1.00 0.92 0.02 asserted 1.00
s5 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 1$\sigma$ error level. result 0.98 0.97 0.65 asserted 1.00
s6 Our best fit model shows that the eBOSS ELG sample only consists of $\sim 12\%$ of all star-forming galaxies, and the satellite fraction of eBOSS ELG sample is 19.3\%. result 1.00 0.96 0.25 asserted 1.00
s7 We show that the effect of assembly bias is $\sim20\%$ on the two-point correlation function and $\sim5\%$ on the void probability function at scale of $r\sim 20 h^{-1}\rm Mpc$. result 1.00 0.94 0.16 asserted 1.00

What kind of paper the classifier reports this is: empirical study 0.74 · evidence from analysis of existing data 0.94.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
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  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

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 $0.34h^{-1}\textrm{Mpc}$ to $70h^{-1}\textrm{Mpc}$. In order to account for the correlation between properties of emission line galaxies 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 [OII] 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 1$\sigma$ error level. Our best fit model shows that the eBOSS ELG sample only consists of $\sim 12\%$ of all star-forming galaxies, and the satellite fraction of eBOSS ELG sample is 19.3\%. We show that the effect of assembly bias is $\sim20\%$ on the two-point correlation function and $\sim5\%$ on the void probability function at scale of $r\sim 20 h^{-1}\rm Mpc$.

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