Fast Parameter Estimation from the CMB Power Spectrum
arXiv:astro-ph/0108315 · doi:10.1046/j.1365-8711.2002.05499.x
Abstract
The statistical properties of a map of the primary fluctuations in the cosmic microwave background (CMB) may be specified to high accuracy by a few thousand power spectra measurements, provided the fluctuations are gaussian, yet the number of parameters relevant for the CMB is probably no more than about 10-20. There is consequently a large degree of redundancy in the power spectrum data. In this paper, we show that the MOPED data compression technique can reduce the CMB power spectrum measurements to about 10-20 numbers (one for each parameter), from which the cosmological parameters can be estimated virtually as accurately as from the complete power spectrum. This offers opportunities for very fast parameter estimation from real and simulated CMB skies, with accurate likelihood calculations at Planck resolution being speeded up by a factor of around five hundred million.
version to appear in MNRAS
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Cited by in corpus (12)
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- Myths and Truths Concerning Estimation of Power Spectra
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- Massive optimal data compression and density estimation for scalable, likelihood-free inference in cosmology
- Star Formation and Metallicity History of the SDSS galaxy survey: unlocking the fossil record
- Automatic physical inference with information maximising neural networks
- Generalized massive optimal data compression
- Massive data compression for parameter-dependent covariance matrices
- Data compression in cosmology: A compressed likelihood for Planck data
- Extreme data compression for the CMB
- An investigation into the Multiple Optimised Parameter Estimation and Data compression algorithm
- Mapping the Cosmological Confidence Ball Surface