Polymer Physics by Quantum Computing

Year: 2021

Authors: Micheletti C.; Hauke P.; Faccioli P.

Autors Affiliation: Scuola Int Super Studi Avanzati SISSA, Via Bonomea 265, I-34136 Trieste, Italy; Trento Univ, Dept Phys, Via Sommar 14, I-38123 Povo, Trento, Italy; INO CNR BEC Ctr, Via Sommar 14, I-38123 Povo, Trento, Italy; INFN TIFPA, Via Sommar 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; ALGORITHM
DOI: 10.1103/PhysRevLett.127.080501

Citations: 17
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