Pith. sign in

REVIEW 1 cited by

Optimal Weighting Scheme in Redshift-space Power Spectrum Analysis and a Prospect for Measuring the Cosmic Equation of State

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

arxiv astro-ph/0208139 v2 pith:KUVH7B5E submitted 2002-08-06 astro-ph

classification astro-ph
keywords analysisequationpowersamplespectrumstateredshiftconstrain
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

We develop a useful formula for power spectrum analysis for high and intermediate redshift galaxy samples, as an extension of the work by Feldman, Kaiser & Peacock (1994). An optimal weight factor, which minimizes the errors of the power spectrum estimator, is obtained so that the light-cone effect and redshift-space distortions are incorporated. Using this formula, we assess the feasibility of the power spectrum analysis with the luminous red galaxy (LRG) sample in the Sloan Digital Sky Survey as a probe of the equation of state of the dark energy. Fisher matrix analysis shows that the LRG sample can be sensitive to the equation of state around redshift z=0.13. It is also demonstrated that the LRG sample can constrain the equation of state with (1-sigma) error of 10% level, if other fundamental cosmological parameters are well determined independently. For the useful constraint, we point out the importance of modeling the bias taking the luminosity dependence into account. We also discuss the optimized strategy to constrain the equation of state using power spectrum analysis. For a sample with fixed total number of objects, it is most advantageous to have the sample with the mean number density $10^{-4} h^3{\rm Mpc}^{-3}$ in the range of the redshift $0.4 \simlt z\simlt 1$.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Fewer simulations, sharper covariances: Reducing mock covariance noise with Zeldovich approximation control variates

    astro-ph.CO 2026-05 unverdicted novelty 7.0 of 10

    Control variates with Zeldovich mocks reduce covariance matrix variance by up to an order of magnitude on large scales in DESI-like mocks.

Pith tools