Gualdi, D;
Gil-Marín, H;
Manera, M;
Joachimi, B;
Lahav, O;
(2019)
Geometrical compression: a new method to enhance the BOSS galaxy bispectrum monopole constraints.
Monthly Notices of the Royal Astronomical Society: Letters
, 484
(1)
L29-L34.
10.1093/mnrasl/sly242.
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Abstract
We present a novel method to compress galaxy clustering three-point statistics and apply it to redshift space galaxy bispectrum monopole measurements from BOSS DR12 CMASS data considering a k-space range of 0.3 - 0.12 h/Mpc. The method consists in binning together bispectra evaluated at sets of wavenumbers forming closed triangles with similar geometrical properties: the area, the cosine of the largest angle, and the ratio between the cosines of the remaining two angles. This enables us to increase the number of bispectrum measurements, for example by a factor of 23 over the standard binning (from 116 to 2734 triangles used), which is otherwise limited by the number of mock catalogues available to estimate the covariance matrix needed to derive parameter constraints. The 68 per cent credible intervals for the inferred parameters (b₁, b₂, ƒ, σ8) are thus reduced by (-39 per cent, - 49 per cent, - 29 per cent, - 22 per cent), respectively. We find very good agreement with the posteriors recently obtained by alternative maximal compression methods. This new method does not require the a-priori computation of the data vector covariance matrix and has the potential to be directly applicable to other three-point statistics (e.g. galaxy clustering, weak gravitational lensing, 21-cm emission line) measured from future surveys such as DESI, Euclid, PFS, and SKA.
Type: | Article |
---|---|
Title: | Geometrical compression: a new method to enhance the BOSS galaxy bispectrum monopole constraints |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1093/mnrasl/sly242 |
Publisher version: | https://doi.org/10.1093/mnrasl/sly242 |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | methods: analytical, methods: data analysis, methods: statistical, cosmology: cosmological parameters, cosmology: large-scale structure of Universe |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10067032 |
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