Maximal compression of the redshift-space galaxy power spectrum and bispectrum. Issue 3 (31st January 2018)
- Record Type:
- Journal Article
- Title:
- Maximal compression of the redshift-space galaxy power spectrum and bispectrum. Issue 3 (31st January 2018)
- Main Title:
- Maximal compression of the redshift-space galaxy power spectrum and bispectrum
- Authors:
- Gualdi, Davide
Manera, Marc
Joachimi, Benjamin
Lahav, Ofer - Abstract:
- Abstract: We explore two methods of compressing the redshift-space galaxy power spectrum and bispectrum with respect to a chosen set of cosmological parameters. Both methods involve reducing the dimension of the original data vector (e.g. 1000 elements) to the number of cosmological parameters considered (e.g. seven ) using the Karhunen–Loève algorithm. In the first case, we run MCMC sampling on the compressed data vector in order to recover the 1D and 2D posterior distributions. The second option, approximately 2000 times faster, works by orthogonalizing the parameter space through diagonalization of the Fisher information matrix before the compression, obtaining the posterior distributions without the need of MCMC sampling. Using these methods for future spectroscopic redshift surveys like DESI, Euclid, and PFS would drastically reduce the number of simulations needed to compute accurate covariance matrices with minimal loss of constraining power. We consider a redshift bin of a DESI-like experiment. Using the power spectrum combined with the bispectrum as a data vector, both compression methods on average recover the $68\, \, \rm{per\, \, cent}$ credible regions to within $0.7\, \, \rm{per\, \, cent}$ and $2\, \, \rm{per\, \, cent}$ of those resulting from standard MCMC sampling, respectively. These confidence intervals are also smaller than the ones obtained using only the power spectrum by 81 per cent, 80 per cent, and 82 per cent respectively, for the bias parameterAbstract: We explore two methods of compressing the redshift-space galaxy power spectrum and bispectrum with respect to a chosen set of cosmological parameters. Both methods involve reducing the dimension of the original data vector (e.g. 1000 elements) to the number of cosmological parameters considered (e.g. seven ) using the Karhunen–Loève algorithm. In the first case, we run MCMC sampling on the compressed data vector in order to recover the 1D and 2D posterior distributions. The second option, approximately 2000 times faster, works by orthogonalizing the parameter space through diagonalization of the Fisher information matrix before the compression, obtaining the posterior distributions without the need of MCMC sampling. Using these methods for future spectroscopic redshift surveys like DESI, Euclid, and PFS would drastically reduce the number of simulations needed to compute accurate covariance matrices with minimal loss of constraining power. We consider a redshift bin of a DESI-like experiment. Using the power spectrum combined with the bispectrum as a data vector, both compression methods on average recover the $68\, \, \rm{per\, \, cent}$ credible regions to within $0.7\, \, \rm{per\, \, cent}$ and $2\, \, \rm{per\, \, cent}$ of those resulting from standard MCMC sampling, respectively. These confidence intervals are also smaller than the ones obtained using only the power spectrum by 81 per cent, 80 per cent, and 82 per cent respectively, for the bias parameter b 1, the growth rate f, and the scalar amplitude parameter A s . … (more)
- Is Part Of:
- Monthly notices of the Royal Astronomical Society. Volume 476:Issue 3(2018)
- Journal:
- Monthly notices of the Royal Astronomical Society
- Issue:
- Volume 476:Issue 3(2018)
- Issue Display:
- Volume 476, Issue 3 (2018)
- Year:
- 2018
- Volume:
- 476
- Issue:
- 3
- Issue Sort Value:
- 2018-0476-0003-0000
- Page Start:
- 4045
- Page End:
- 4070
- Publication Date:
- 2018-01-31
- Subjects:
- methods: analytical -- methods: data analysis -- methods: statistical -- cosmological parameters -- large-scale structure of Universe -- cosmology: miscellaneous
Astronomy -- Periodicals
Periodicals
520.5 - Journal URLs:
- http://mnras.oxfordjournals.org/ ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2966 ↗
http://www.blackwell-synergy.com/issuelist.asp?journal=mnr ↗
http://www.blackwell-synergy.com/loi/mnr ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/mnras/sty261 ↗
- Languages:
- English
- ISSNs:
- 0035-8711
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5943.000000
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British Library HMNTS - ELD Digital store - Ingest File:
- 12214.xml