Panizza Veronica, Roggero Alessandro, Hauke Philipp, Faccioli Pietro
University of Trento, Physics Department, Via Sommarive 14, I-38123 Trento, Italy.
INO-CNR Pitaevskii BEC Center, Via Sommarive 14, I-38123 Trento, Italy.
Phys Rev Lett. 2025 Apr 18;134(15):158101. doi: 10.1103/PhysRevLett.134.158101.
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 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.
晶格模型是深入了解杂聚物统计物理学的宝贵工具。我们严格地将这些模型的配分函数映射为具有费米子和玻色子自由度的(Z_{2})晶格规范理论(LGT)的真空期望值。由于相关的路径积分表达式不受符号问题的影响,与传统的聚合物场论不同,它在序列和结构空间中都适合蒙特卡罗(MC)采样。同时,由于LGT编码依赖于量子比特,它为未来利用量子计算硬件的发展提供了一个框架。我们讨论了我们形式主义的两个说明性应用:首先,我们用它来表征由两种残基组成的小杂聚物的热力学稳定序列和结构。接下来,我们评估其对紧凑结构系综进行采样的效率,发现MC去相关时间仅与链长成线性关系。