Font-Ribera, A;
McDonald, P;
Slosar, A;
(2018)
How to estimate the 3D power spectrum of the Lyman-alpha forest.
Journal of Cosmology and Astroparticle Physics
, 2018
, Article 003. 10.1088/1475-7516/2018/01/003.
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Abstract
We derive and numerically implement an algorithm for estimating the 3D power spectrum of the Lyman-α (Lyα) forest flux fluctuations. The algorithm exploits the unique geometry of Lyα forest data to efficiently measure the cross-spectrum between lines of sight as a function of parallel wavenumber, transverse separation and redshift. We start by approximating the global covariance matrix as block-diagonal, where only pixels from the same spectrum are correlated. We then compute the eigenvectors of the derivative of the signal covariance with respect to cross-spectrum parameters, and project the inverse-covariance-weighted spectra onto them. This acts much like a radial Fourier transform over redshift windows. The resulting cross-spectrum inference is then converted into our final product, an approximation of the likelihood for the 3D power spectrum expressed as second order Taylor expansion around a fiducial model. We demonstrate the accuracy and scalability of the algorithm and comment on possible extensions. Our algorithm will allow efficient analysis of the upcoming Dark Energy Spectroscopic Instrument dataset.
Type: | Article |
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Title: | How to estimate the 3D power spectrum of the Lyman-alpha forest |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1088/1475-7516/2018/01/003 |
Publisher version: | http://doi.org/10.1088/1475-7516/2018/01/003 |
Language: | English |
Additional information: | © 2018 IOP Publishing Ltd and Sissa Medialab. This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Science & Technology, Physical Sciences, Astronomy & Astrophysics, Physics, Particles & Fields, Physics, Lyman alpha forest, power spectrum, baryon acoustic oscillations, redshift surveys, REDSHIFT SURVEYS, DATA SETS |
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/10042056 |
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