REVIEW 1 cited by
The Effect of Systematic Redshift Biases in BAO Cosmology
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
With the remarkable increase in scale and precision provided by upcoming galaxy redshift surveys, systematic errors that were previously negligible may become significant. In this paper, we explore the potential impact of low-magnitude systematic redshift offsets on measurements of the Baryon Acoustic Oscillation (BAO) feature, and the cosmological constraints recovered from such measurements. Using 500 mock galaxy redshift surveys as our baseline sample, we inject a series of systematic redshift biases (ranging from +/-0.2% to +/-2%), and measure the resulting shift in the recovered isotropic BAO scale. When BAO measurements are combined with CMB constraints (in both {\Lambda}CDM and wCDM cosmologies), plausible systematics introduce a negligible offset on combined fits of H0 and {\Omega}m, and systematics must be an order of magnitude greater than this plausible baseline to introduce a 1-{\sigma} shift on such combined fits. We conclude that systematic redshift biases are very unlikely to bias constraints on parameters such as H0 provided by BAO cosmology, either now or in the near future. We also detail a theoretical model that predicts the impact of uniform redshift systematics on {\alpha}, and show this model is in close alignment with the results of our mock survey analysis.
Forward citations
Cited by 1 Pith paper
-
Diagnosing Systematic Effects Using the Inferred Initial Power Spectrum
The inferred initial matter power spectrum from the SELFI algorithm reveals misspecified galaxy bias, selection, mask, redshift, and gravity models, exposing a >2σ cosmological bias before parameter inference.
Discussion (0). Continue with ORCID to comment.