Statistical Mechanics of Heteropolymers from Lattice Gauge Theory

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Main Authors: Panizza, Veronica, Roggero, Alessandro, Hauke, Philipp, Faccioli, Pietro
Format: Preprint
Published: 2024
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author Panizza, Veronica
Roggero, Alessandro
Hauke, Philipp
Faccioli, Pietro
author_facet Panizza, Veronica
Roggero, Alessandro
Hauke, Philipp
Faccioli, Pietro
contents Lattice models are valuable tools to gain insight into the statistical physics of heteropolymers. We rigorously map the partition function of these models into a vacuum expectation value of a $\mathbb{Z}_2$ lattice gauge theory (LGT), with both fermionic and bosonic degrees of freedom. Because the associated path integral expression is not affected by a sign problem, it is amenable to Monte Carlo (MC) sampling in both the sequence and structure space, unlike conventional polymer field theory. At the same time, since the LGT encoding relies on qubits, it provides a framework for future efforts to capitalize on the development of quantum computing hardware. We discuss two illustrative applications of our formalism: first, we use it to characterize the thermodynamically stable sequences and structures of small heteropolymers consisting of two types of residues. Next, we assess its efficiency to sample ensembles of compact structures, finding that the MC decorrelation time scales only linearly with the chain length.
format Preprint
id arxiv_https___arxiv_org_abs_2411_11476
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Statistical Mechanics of Heteropolymers from Lattice Gauge Theory
Panizza, Veronica
Roggero, Alessandro
Hauke, Philipp
Faccioli, Pietro
Statistical Mechanics
High Energy Physics - Lattice
Lattice models are valuable tools to gain insight into the statistical physics of heteropolymers. We rigorously map the partition function of these models into a vacuum expectation value of a $\mathbb{Z}_2$ lattice gauge theory (LGT), with both fermionic and bosonic degrees of freedom. Because the associated path integral expression is not affected by a sign problem, it is amenable to Monte Carlo (MC) sampling in both the sequence and structure space, unlike conventional polymer field theory. At the same time, since the LGT encoding relies on qubits, it provides a framework for future efforts to capitalize on the development of quantum computing hardware. We discuss two illustrative applications of our formalism: first, we use it to characterize the thermodynamically stable sequences and structures of small heteropolymers consisting of two types of residues. Next, we assess its efficiency to sample ensembles of compact structures, finding that the MC decorrelation time scales only linearly with the chain length.
title Statistical Mechanics of Heteropolymers from Lattice Gauge Theory
topic Statistical Mechanics
High Energy Physics - Lattice
url https://arxiv.org/abs/2411.11476