Astronomy and Astrophysics – Astrophysics
Scientific paper
2008-07-03
Astrophys.J.697:258-268,2009
Astronomy and Astrophysics
Astrophysics
Submitted to ApJ
Scientific paper
10.1088/0004-637X/697/1/258
We present a new Monte Carlo Markov Chain algorithm for CMB analysis in the low signal-to-noise regime. This method builds on and complements the previously described CMB Gibbs sampler, and effectively solves the low signal-to-noise inefficiency problem of the direct Gibbs sampler. The new algorithm is a simple Metropolis-Hastings sampler with a general proposal rule for the power spectrum, C_l, followed by a particular deterministic rescaling operation of the sky signal. The acceptance probability for this joint move depends on the sky map only through the difference of chi-squared between the original and proposed sky sample, which is close to unity in the low signal-to-noise regime. The algorithm is completed by alternating this move with a standard Gibbs move. Together, these two proposals constitute a computationally efficient algorithm for mapping out the full joint CMB posterior, both in the high and low signal-to-noise regimes.
Eriksen Hans Kristian
Górski Kris M.
Huey Greg
Jewell Jeffrey B.
O'Dwyer Ian J.
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