Gibbs sampling of complex valued distributions

Understand

A new technique is explored for the Monte Carlo sampling of complex-valued distributions.

• The method is based on a heat bath approach where the conditional probability is replaced by a positive representation of it on the complex plane.
• Efficient ways to construct such representations are also introduced.
• The performance of the algorithm is tested on small and large lattices with a $\lambda\phi^4$ theory with quadratic nearest-neighbor complex coupling.