The effect of covariance estimator error on cosmological parameter constraints

Dodelson, Scott; Schneider, Michael

doi:10.1103/physrevd.88.063537

Cited by 218 publications

(279 citation statements)

References 23 publications

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“…The noise from the finite number of mock realizations requires some corrections to the χ 2 values, the width of the likelihood distribution, and the standard deviation of any parameter determined from the same set of mocks used to define the covariance matrix. These factors are defined in Hartlap et al (2007) ;Dodelson & Schneider (2013) and Percival et al (2014); we apply the factors in the same way as in, e.g., Anderson et al (2014). For our fiducial ξ(s) results, we use 1000 mocks and 18 measurement bins (fitting to the weighted mean of the NGC and SGC results).…”

Section: Parameter Estimationmentioning

confidence: 99%

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: first measurement of baryon acoustic oscillations between redshift 0.8 and 2.2

Ata

Baumgarten

Bautista

et al. 2017

Monthly Notices of the Royal Astronomical Society

402

314

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We present measurements of the Baryon Acoustic Oscillation (BAO) scale in redshift-space using the clustering of quasars. We consider a sample of 147,000 quasars from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) distributed over 2044 square degrees with redshifts 0.8 < z < 2.2 and measure their spherically-averaged clustering in both configuration and Fourier space. Our observational dataset and the 1400 simulated realizations of the dataset allow us to detect a preference for BAO that is greater than 2.8σ. We determine the spherically averaged BAO distance to z = 1.52 to 3.8 per cent precision: D V (z = 1.52) = 3843 ± 147 (r d /r d,fid ) Mpc. This is the first time the location of the BAO feature has been measured between redshifts 1 and 2. Our result is fully consistent with the prediction obtained by extrapolating the Planck flat ΛCDM best-fit cosmology. All of our results are consistent with basic large-scale structure (LSS) theory, confirming quasars to be a reliable tracer of LSS, and provide a starting point for numerous cosmological tests to be performed with eBOSS quasar samples. We combine our result with previous, independent, BAO distance measurements to construct an updated BAO distance-ladder. Using these BAO data alone and marginalizing over the length of the standard ruler, we find Ω Λ > 0 at 6.6σ significance when testing a ΛCDM model with free curvature.

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Section: Parameter Estimationmentioning

confidence: 99%

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: first measurement of baryon acoustic oscillations between redshift 0.8 and 2.2

Ata

Baumgarten

Bautista

et al. 2017

Monthly Notices of the Royal Astronomical Society

402

314

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“…In principle, the precision of w(θ) results should converge to the ξ phot (s ⊥ ) results as the redshift bin size is narrowed and all crosscorrelations between redshift bins are included. The clear advantage of ξ phot (s ⊥ ) is the smaller size of the data vector, which reduces the noise bias in the inverse covariance matrix (Hartlap et al 2007;Dodelson & Schneider 2013;Percival et al 2014).…”

Section: Bao Information In Mock Samplesmentioning

confidence: 99%

Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty

Ross

Banik

Ávila

et al. 2017

Monthly Notices of the Royal Astronomical Society

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We determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty σ z 0.02(1 + z) we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for σ z 0.02(1 + z). For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.

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“…One option is to use an external estimate: generate a large number of simulated realisations of the data, and compute the uncertainty from the distribution of the measurements in them (Dodelson & Schneider 2013;Taylor et al 2013). An alternative is to use internal error estimations, based on the re-sampling of the data itself.…”

Section: Introductionmentioning

confidence: 99%

Internal errors: a valid alternative for clustering estimates?

Arnalte-Mur

Norberg

2014

Proc. IAU

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Abstract. We investigate the validity of internal methods to estimate the uncertainty of the galaxy two-point correlation function. We consider the jackknife and bootstrap methods, which are based on re-sampling sub-regions of the original data. These are cheap computationally, and do not depend on the accuracy of external simulations. We test the different methods over a large range of scales using a set of 160 mock catalogues from the LasDamas set of simulations. Our results show that the standard bootstrap method significantly overestimates the true uncertainty at all scales. We try two possible generalisations of the bootstrap, but find them not to be robust. Regarding jackknife, we obtain that this method provides an unbiased estimation of the error at small and intermediate scales, up to ∼ 40 h −1 Mpc. At larger scales, it typically overestimates the error by a ∼ 13%.

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The effect of covariance estimator error on cosmological parameter constraints

Cited by 218 publications

References 23 publications

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: first measurement of baryon acoustic oscillations between redshift 0.8 and 2.2

The clustering of the SDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: first measurement of baryon acoustic oscillations between redshift 0.8 and 2.2

Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty

Internal errors: a valid alternative for clustering estimates?

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