A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf
.
The Acceptance Probability of the Hybrid Monte Carlo Method in High-Dimensional Problems
2010
We investigate the properties of the Hybrid Monte-Carlo algorithm in high dimensions. In the simplified scenario of independent, identically distributed components, we prove that, to obtain an O(1) acceptance probability as the dimension d of the state space tends to ∞, the Verlet/leap-frog step-size h should be scaled as h = × d −1/4 . We also identify analytically the asymptotically optimal acceptance probability, which turns out to be 0.651 (with three decimal places); this is the choice
doi:10.1063/1.3498436
fatcat:j7woefrafvafvkl4vj63wue2c4