Polymer Physics by Quantum Computing
Year: 2021
Authors: Micheletti C.; Hauke P.; Faccioli P.
Autors Affiliation: Scuola Internazionale Superiore di Studi Avanzati (SISSA), Via Bonomea 265, I-34136 Trieste, Italy; Physics Department of Trento University and INO-CNR BEC Center, Via Sommarive 14, I-38123 Povo (Trento), Italy; Physics Department of Trento University and INFN-TIFPA, Via Sommarive 14, I-38123 Povo (Trento), Italy
Abstract: Sampling equilibrium ensembles of dense polymer mixtures is a paradigmatically hard problem in computational physics, even in lattice-based models. Here, we develop a formalism based on interacting binary tensors that allows for tackling this problem using quantum annealing machines. Our approach is general in that properties such as self-Avoidance, branching, and looping can all be specified in terms of quadratic interactions of the tensors. Microstates? realizations of different lattice polymer ensembles are then seamlessly generated by solving suitable discrete energy-minimization problems. This approach enables us to capitalize on the strengths of quantum annealing machines, as we demonstrate by sampling polymer mixtures from low to high densities, using the D-Wave quantum annealer. Our systematic approach offers a promising avenue to harness the rapid development of quantum machines for sampling discrete models of filamentous soft-matter systems.
Journal/Review: PHYSICAL REVIEW LETTERS
Volume: 127 (8) Pages from: 080501-1 to: 080501-7
KeyWords: SELF-AVOIDING WALKS; MONTE-CARLO; RING POLYMERS; SIMULATIONS; ALGORITHMDOI: 10.1103/PhysRevLett.127.080501