Sampling of General Correlators in Worm Algorithm-based Simulations

Abstract

Using the complex ${\varphi }^4$-model as a prototype for a system which is simulated by a worm algorithm, we show that not only the charged correlator $<{\varphi }^{\ast }(x)\varphi (y)>$, but also more general correlators such as $<|\varphi (x)||\varphi (y)|>$ or $<\text{arg}(\varphi (x))\text{arg}(\varphi (y))>$, as well as condensates like $<|\varphi |>$, can be measured at every step of the Monte Carlo evolution of the worm instead of on closed-worm configurations only. The method generalizes straightforwardly to other systems simulated by worms, such as spin or sigma models.

43 pages, 15 figures

References in corpus (5)

• Method for simulating O(N) lattice models at finite density
• Simulating the All-Order Strong Coupling Expansion I: Ising Model Demo
• Dual lattice representations for O(N) and CP(N-1) models with a chemical potential
• Improving Wang-Landau sampling with adaptive windows
• Worm algorithms for the 3-state Potts model with magnetic field and chemical potential

Cited by in corpus (6)

• Approaches to the sign problem in lattice field theory
• Generalization capabilities of translationally equivariant neural networks
• Worm Algorithm for CP(N-1) Model
• Dual formulations of Polyakov loop lattice models
• Oscillating propagators in heavy-dense QCD
• Approximate dual representation for Yang-Mills SU(2) gauge theory