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 computer. Our systematic approach offers a promising avenue to harness the rapid development of quantum computers for sampling discrete models of filamentous soft-matter systems.

Polymer Physics by Quantum Computing / Micheletti, Cristian; Hauke, Philipp; Faccioli, Pietro. - In: PHYSICAL REVIEW LETTERS. - ISSN 1079-7114. - ELETTRONICO. - 127:8(2021), pp. 080501.1-080501.7. [10.1103/PhysRevLett.127.080501]

Polymer Physics by Quantum Computing

Hauke, Philipp;Faccioli, Pietro
2021

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 computer. Our systematic approach offers a promising avenue to harness the rapid development of quantum computers for sampling discrete models of filamentous soft-matter systems.
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Micheletti, Cristian; Hauke, Philipp; Faccioli, Pietro
Polymer Physics by Quantum Computing / Micheletti, Cristian; Hauke, Philipp; Faccioli, Pietro. - In: PHYSICAL REVIEW LETTERS. - ISSN 1079-7114. - ELETTRONICO. - 127:8(2021), pp. 080501.1-080501.7. [10.1103/PhysRevLett.127.080501]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/304377
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