Polymer Physics by Quantum Computing
Anno: 2021
Autori: Micheletti C.; Hauke P.; Faccioli P.
Affiliazione autori: 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.
Giornale/Rivista: PHYSICAL REVIEW LETTERS
Volume: 127 (8) Da Pagina: 080501-1 A: 080501-7
Parole chiavi: SELF-AVOIDING WALKS; MONTE-CARLO; RING POLYMERS; SIMULATIONS; ALGORITHMDOI: 10.1103/PhysRevLett.127.080501Citazioni: 19dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2025-02-09Riferimenti tratti da Isi Web of Knowledge: (solo abbonati) Link per visualizzare la scheda su IsiWeb: Clicca quiLink per visualizzare la citazioni su IsiWeb: Clicca qui