Tomographic halo model of the unWISE-Blue galaxies using cross-correlations with BOSS CMASS galaxies
The halo model offers a framework for investigating galaxy clustering, and for understanding the growth of galaxies and the distribution of galaxies of different types. Here, we use the halo model to study the small-scale clustering and halo occupation distribution (HOD) of the unWISE-Blue galaxy sample, an infrared-selected sample of $$100 million galaxies across the entire extragalactic sky at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>z</mml:mi> <mml:mo>∼</mml:mo> <mml:mn>0.5</mml:mn> </mml:mrow> </mml:math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mo>−</mml:mo> </mml:math> similar redshifts to the Baryon Oscillation Spectroscopic Survey (BOSS) CMASS sample. Although the photometric unWISE galaxies cannot be easily split in redshift, we use their cross-correlation with the BOSS CMASS sample to tomographically probe the HOD of the unWISE galaxies at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mn>0.45</mml:mn> <mml:mo><</mml:mo> <mml:mi>z</mml:mi> <mml:mo><</mml:mo> <mml:mn>0.75</mml:mn> </mml:mrow> </mml:math> . To do so, we develop a new method for applying the halo model to cross-correlations between a photometric sample and a spectroscopic sample in narrow redshift bins, incorporating halo exclusion, post-Limber corrections, and redshift-space distortions. We reveal strong evolution in the CMASS HOD, and modest evolution in the unWISE-Blue HOD. For unWISE-Blue, we find that the average bias and mean halo mass drop from <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>b</mml:mi> <mml:mo>=</mml:mo> <mml:mn>1.6</mml:mn> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:msub> <mml:mo>log</mml:mo> <mml:mn>10</mml:mn> </mml:msub> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mi mathvariant="normal">h</mml:mi> </mml:msub> <mml:mi>/</mml:mi> <mml:msub> <mml:mi>M</mml:mi> <mml:mo>⊙</mml:mo> </mml:msub> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo>∼</mml:mo> <mml:mn>13.4</mml:mn> </mml:mrow> </mml:math> at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>z</mml:mi> <mml:mo>∼</mml:mo> <mml:mn>0.5</mml:mn> </mml:mrow> </mml:math> to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>b</mml:mi> <mml:mo>=</mml:mo> <mml:mn>1.4</mml:mn> </mml:mrow> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:msub> <mml:mo>log</mml:mo> <mml:mn>10</mml:mn> </mml:msub> <mml:mrow> <mml:mo stretchy="true" form="prefix">(</mml:mo> <mml:msub> <mml:mi>M</mml:mi> <mml:mi mathvariant="normal">h</mml:mi> </mml:msub> <mml:mi>/</mml:mi> <mml:msub> <mml:mi>M</mml:mi> <mml:mo>⊙</mml:mo> </mml:msub> <mml:mo stretchy="true" form="postfix">)</mml:mo> </mml:mrow> <mml:mo>∼</mml:mo> <mml:mn>13.1</mml:mn> </mml:mrow> </mml:math> at <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow> <mml:mi>z</mml:mi> <mml:mo>∼</mml:mo> <mml:mn>0.7</mml:mn> </mml:mrow> </mml:math> , and that the satellite fraction drops modestly from $$20% to $$10% in the same range. These results are useful for creating mock samples of the unWISE-Blue galaxies. Furthermore, the techniques developed to obtain these results are applicable to other tomographic cross-correlations between photometric samples and narrowly-binned spectroscopic samples, such as clustering redshifts.
Authors
- Will J. Percival (ORCID: https://orcid.org/0000-0002-0644-5727)
- Alex Krolewski (ORCID: https://orcid.org/0000-0003-2183-7021)
- Jensen Lawrence (ORCID: https://orcid.org/0009-0007-5371-3548)
Publication Details
- Journal
- The Open Journal of Astrophysics
- Published
- 2025-04-29
- DOI
- https://doi.org/10.33232/001c.137297
- Citations
- 1
- Primary Topic
- Statistical and numerical algorithms
- Type
- article
- Field-Weighted Citation Impact
- 3.73