Simulations with Complex Measures
T D Kieu, C J Griffin
TL;DR
This paper introduces a novel simulation method for systems with complex measures, reducing statistical errors compared to traditional Monte Carlo techniques, demonstrated on a 1D complex-coupling Ising model.
Contribution
A new approach for simulating systems with complex measures that improves accuracy over crude Monte Carlo methods.
Findings
Reduced statistical errors in simulations with complex measures
Successful application to the 1D complex-coupling Ising model
Potential for broader application to sign problem challenges
Abstract
Towards a solution to the sign problem in the simulations of systems having indefinite or complex-valued measures, we propose a new approach which yields statistical errors smaller than the crude Monte Carlo using absolute values of the original measures. The 1D complex-coupling Ising model is employed as an illustration.
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