Quantum advantage in solving physical problems is still hard to assess due to hardware limitations. However, algorithms designed for quantum computers may engender transformative frameworks for modeling and simulating paradigmatically hard systems. Here, we show that the quadratic unconstrained binary optimization encoding enables tackling classical many-body systems that are challenging for conventional Monte Carlo. Specifically, in self-assembled melts of rigid lattice ring polymers, the combination of high density, chain stiffness, and topological constraints results in divergent autocorrelation times for real-space Monte Carlo. Our quantum-inspired encoding overcomes this problem and enables sampling melts of lattice rings with fixed curvature and compactness, unveiling counterintuitive topological effects. Tackling the same problems with the D-Wave quantum annealer leads to substantial performance improvements and advantageous scaling of sampling computational cost with the size of the self-assembled ring melts.

Quantum-inspired encoding enhances stochastic sampling of soft matter systems / Slongo, Francesco; Hauke, Philipp; Faccioli, Pietro; Micheletti, Cristian. - In: SCIENCE ADVANCES. - ISSN 2375-2548. - 9:43(2023), p. adi0204. [10.1126/SCIADV.ADI0204]

Quantum-inspired encoding enhances stochastic sampling of soft matter systems

Hauke, Philipp
Secondo
;
Faccioli, Pietro
Penultimo
;
2023-01-01

Abstract

Quantum advantage in solving physical problems is still hard to assess due to hardware limitations. However, algorithms designed for quantum computers may engender transformative frameworks for modeling and simulating paradigmatically hard systems. Here, we show that the quadratic unconstrained binary optimization encoding enables tackling classical many-body systems that are challenging for conventional Monte Carlo. Specifically, in self-assembled melts of rigid lattice ring polymers, the combination of high density, chain stiffness, and topological constraints results in divergent autocorrelation times for real-space Monte Carlo. Our quantum-inspired encoding overcomes this problem and enables sampling melts of lattice rings with fixed curvature and compactness, unveiling counterintuitive topological effects. Tackling the same problems with the D-Wave quantum annealer leads to substantial performance improvements and advantageous scaling of sampling computational cost with the size of the self-assembled ring melts.
2023
43
Slongo, Francesco; Hauke, Philipp; Faccioli, Pietro; Micheletti, Cristian
Quantum-inspired encoding enhances stochastic sampling of soft matter systems / Slongo, Francesco; Hauke, Philipp; Faccioli, Pietro; Micheletti, Cristian. - In: SCIENCE ADVANCES. - ISSN 2375-2548. - 9:43(2023), p. adi0204. [10.1126/SCIADV.ADI0204]
File in questo prodotto:
File Dimensione Formato  
Quantum-inspired Encoding Enhances Stochastic Sampling of Soft Matter Systems.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Creative commons
Dimensione 841.78 kB
Formato Adobe PDF
841.78 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/403350
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact