SCoPE: An efficient method of Cosmological Parameter Estimation

Understand

Markov Chain Monte Carlo (MCMC) sampler is widely used for cosmological parameter estimation from CMB and other data.

• However, due to the intrinsic serial nature of the MCMC sampler, convergence is often very slow.
• Here we present a fast and independently written Monte Carlo method for cosmological parameter estimation named as Slick Cosmological Parameter Estimator (SCoPE), that employs delayed rejection to increase the acceptance rate of a chain, and pre-fetching that helps an individual chain to run on parallel CPUs.
• An inter-chain covariance update is also incorporated to prevent clustering of the chains allowing faster and better mixing of the chains.