Title: Galaxy bias in the era of LSST: perturbative bias expansions

Journal Article · · Journal of Cosmology and Astroparticle Physics
 [1];  [2];  [3];  [4];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [13];  [14];  [6];  [4]
  1. Univ. of Bonn (Germany)
  2. Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  3. Univ. of Portsmouth (United Kingdom)
  4. Univ. of Oxford (United Kingdom)
  5. Brookhaven National Laboratory (BNL), Upton, NY (United States)
  6. Duke Univ., Durham, NC (United States)
  7. Stanford Univ., CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
  8. Donostia International Physics Center (DIPC), San Sebastian (Spain); Basque Foundation for Science, Bilbao (Spain). IKERBASQUE
  9. Univ. Nacional Autónoma de México, Cuernavaca (Mexico); Consejo Nacional de Ciencia y Tecnologia (CONACYT), Mexico City (Mexico)
  10. Northeastern Univ., Boston, MA (United States)
  11. Princeton Univ., NJ (United States)
  12. Univ. of Pennsylvania, Philadelphia, PA (United States)
  13. Donostia International Physics Center (DIPC), San Sebastian (Spain)
  14. Univ. of California, Berkeley, CA (United States)
+ Show Author Affiliations

Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the Rubin Observatory Legacy Survey of Space and Time (LSST) bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Year 10 (Y10) data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian perturbation theory (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. Here, we consider a variety of different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale of kmax = 0.4 Mpc-1 for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
European Research Council (ERC); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Organization:
The LSST Dark Energy Science collaboration
Grant/Contract Number:
AC02-05CH11231; AC02-76SF00515; SC0010007; SC0012704
OSTI ID:
2349261
Report Number(s):
BNL-225584-2024-JAAM
Journal Information:
Journal of Cosmology and Astroparticle Physics, Journal Name: Journal of Cosmology and Astroparticle Physics Journal Issue: 02 Vol. 2024; ISSN 1475-7516
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English

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