Introduction to stochastic error correction methods

Abstract

We propose a method for eliminating the truncation error associated with any subspace diagonalization calculation. The new method, called stochastic error correction, uses Monte Carlo sampling to compute the contribution of the remaining basis vectors not included in the initial diagonalization. The method is part of a new approach to computational quantum physics which combines both diagonalization and Monte Carlo techniques.

11 pages, 1 figure

References in corpus (3)

• Introduction to the Diffusion Monte Carlo Method
• Non-perturbative states in the 3D phi^4 theory
• A non-perturbative analysis of symmetry breaking in two-dimensional phi^4 theory using periodic field methods

Cited by in corpus (18)

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• A Conformal Truncation Framework for Infinite-Volume Dynamics
• Introduction to Lightcone Conformal Truncation: QFT Dynamics from CFT Data
• Hamiltonian Truncation Effective Theory
• Persistent oscillations after quantum quenches in $d$ dimensions
• The renormalized Hamiltonian truncation method in the large $E_T$ expansion
• Ab Initio Simulations of Light Nuclear Systems Using Eigenvector Continuation and Auxiliary Field Monte Carlo
• Bound-state energy of the d=3 Ising model in the broken-symmetry phase: Suppressed finite-size corrections
• Universal critical behavior of the two-magnon-bound-state mass gap for the (2+1)-dimensional Ising model
• Magnon-bound-state hierarchy for the two-dimensional transverse-field Ising model in the ordered phase
• On computing non-equilibrium dynamics following a quench
• Hierarchy of the low-lying excitations for the $(2+1)$-dimensional $q=3$ Potts model in the ordered phase
• Nonperturbative dynamics of (2+1)d ${\varphi }^4$-theory from Hamiltonian truncation
• Quantum quenches with long range interactions
• A First Step Towards Effectively Nonperturbative Scattering Amplitudes in the Perturbative Regime