Cosmological parameters from VSA, CBI and other data: a Monte-Carlo approach

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Abstract
We present a fast Markov Chain Monte-Carlo exploration of cosmological parameter space. We perform a joint analysis of results from the recent CMB experiments, including CBI and VSA, and provide a practical set of parameter constraints from the CMB independent of other data. We next combine CMB, HST Key Project, large scale structure, supernovae and nucleosynthesis data. The Monte Carlo method allows us to rapidly investigate a large number of parameters, and we present results from an 11 cosmological parameter analysis, as well as results from a better constrained 9 parameter analysis motivated by inflationary models. In a series of appendices we describe the publically available code, explain the use of importance sampling for quickly computing results from new data and discuss the different ways of converting parameter samples to parameter constraints. We also assess the goodness of fit and consistency, and describe the use of analytic marginalization over normalization parameters.

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