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Improving Fisher matrix forecasts for galaxy surveys: window function, bin cross-correlation and bin redshift uncertainty

Bailoni, Alberto; Spurio Mancini, Alessio; Amendola, Luca; (2017) Improving Fisher matrix forecasts for galaxy surveys: window function, bin cross-correlation and bin redshift uncertainty. Monthly Notices of the Royal Astronomical Society , 470 (1) pp. 688-705. 10.1093/mnras/stx1209. Green open access

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Abstract

The Fisher matrix is a widely used tool to forecast the performance of future experiments and approximate the likelihood of large data sets. Most of the forecasts for cosmological parameters in galaxy clustering studies rely on the Fisher matrix approach for large-scale experiments like DES, Euclid or SKA. Here, we improve upon the standard method by taking into account three effects: the finite window function, the correlation between redshift bins and the uncertainty on the bin redshift. The first two effects are negligible only in the limit of infinite surveys. The third effect, in contrast, is negligible for infinitely small bins. Here, we show how to take into account these effects and what the impact on forecasts of a Euclid-type experiment will be. The main result of this paper is that the windowing and the bin cross-correlation induce a considerable change in the forecasted errors, of the order of 10–30 per cent for most cosmological parameters, while the redshift bin uncertainty can be neglected for bins smaller than Δz = 0.1 roughly.

Type: Article
Title: Improving Fisher matrix forecasts for galaxy surveys: window function, bin cross-correlation and bin redshift uncertainty
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/mnras/stx1209
Publisher version: https://doi.org/10.1093/mnras/stx1209
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: statistical, surveys, galaxies: statistics, cosmological parameters, 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 Space and Climate Physics
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10173281
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