2020
DOI: 10.1093/mnrasl/slaa024
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Anisotropies of galaxy ellipticity correlations in real and redshift space: angular dependence in linear tidal alignment model

Abstract: Investigating intrinsic alignments (IAs) of galaxy shapes is important not only to constrain cosmological parameters unbiasedly from gravitational lensing but also to extract cosmological information complimentary to galaxy clustering analysis. We derive simple and useful formulas for the various IA statistics, including the intrinsic ellipticity-ellipticity correlation, the gravitational shear-intrinsic ellipticity correlation, and the velocity-intrinsic ellipticity correlation functions. The angular dependen… Show more

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Cited by 34 publications
(35 citation statements)
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“…When a Fisher matrix is calculated for multiple model parameters, the inverse of this matrix gives the covariance matrix for these parameters. The Fisher matrix for cosmological parameters is given by [20]…”
Section: Fisher Forecast and Resultsmentioning
confidence: 99%
See 3 more Smart Citations
“…When a Fisher matrix is calculated for multiple model parameters, the inverse of this matrix gives the covariance matrix for these parameters. The Fisher matrix for cosmological parameters is given by [20]…”
Section: Fisher Forecast and Resultsmentioning
confidence: 99%
“…In this article, the aim is to show that measuring the correlation between shapes of galaxies and the underlying velocity field of the large scale structure is within the reach of upcoming galaxy surveys. To this end, we predict this correlation relying on the linear alignment model as described in [18,20,21]. Our prediction gives significant results for measuring the signal of the velocity-shape correlation in the data and therefore, we also describe two possible applications of the velocity-shape correlation.…”
Section: Introductionmentioning
confidence: 97%
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“…Following the convention, we introduce another parameter, A LA , as A LA = C 1 ρ cr /0.0134, where ρ cr is the critical density. The Hankel transform converts the power spectrum into the 3-D GI correlation function Okumura et al 2020):…”
Section: Linear Alignment Modelmentioning
confidence: 99%