Quick Navigation

Topics

Quantum Simulation

Statistical mechanics of Monte Carlo sampling and the sign problem

arXiv
Authors: Gustavo During, Jorge Kurchan

Year

2010

Paper ID

9018

Status

Preprint

Abstract Read

~2 min

Abstract Words

128

Citations

N/A

Abstract

Monte Carlo sampling of any system may be analyzed in terms of an associated glass model - a variant of the Random Energy Model - with, whenever there is a sign problem, complex fields. This model has three types of phases (liquid, frozen and `chaotic'), as is characteristic of glass models with complex parameters. Only the liquid one yields the correct answers for the original problem, and the task is to design the simulation to stay inside it. The statistical convergence of the sampling to the correct expectation values may be studied in these terms, yielding a general lower bound for the computer time as a function of the free energy difference between the true system, and a reference one. In this way, importance-sampling strategies may be optimized.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2010 reference point for readers tracking recent quantum research.
  • Monte Carlo sampling of any system may be analyzed in terms of an associated glass model - a variant of the Random Energy Model - with, whenever there is a sign problem...

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #9018 #69599 Tensor network compression usin... #69594 A Collective-Spin Derivation of... #69593 Local correlations in long-rang... #69592 Direct/adaptive-mixture phase-g...

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.