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Title: Renormalization group computation of likelihood functions for cosmological data sets

Journal Article · · Physical Review. D.
 [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
+ Show Author Affiliations

I show how a renormalization group (RG) method can be used to incrementally integrate the information in cosmological large-scale structure data sets (including CMB, galaxy redshift surveys, etc.). I show numerical tests for Gaussian fields, where the method allows arbitrarily close to exact computation of the likelihood function in order N time, even for problems with no symmetry, compared to N3 for brute force linear algebra (where N is the number of data points - to be fair, methods already exist to solve the Gaussian problem in at worst N log N time, and this method will not necessarily be faster in practice). The method requires no sampling or other Monte Carlo (random) element. Nonlinearity/non-Gaussianity can be accounted for to the extent that terms generated by integrating out small scale modes can be projected onto a sufficient basis, e.g., at least in the sufficiently perturbative regime. The formulas to evaluate are straightforward and require no understanding of quantum field theory, but this paper may also serve as a pedagogical introduction to Wilsonian RG for astronomers.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1564010
Alternate ID(s):
OSTI ID: 1546321
Journal Information:
Physical Review. D., Vol. 99, Issue 4; ISSN 2470-0010
Publisher:
American Physical Society (APS)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 2 works
Citation information provided by
Web of Science

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