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Quantum computing and simulation for
In our research, we develop and apply new approaches to macromolecular simulations based on integrating theoretical physics and artificial intelligence with quantum computing and simulation. These novel approaches are applied to a wide range of soft and biological macromolecules. We also develop several applied research projects in partnerships with private companies operating in drug discovery and material science.
Contact: Pietro Faccioli
Selected bibliography
Selected bibliography
Quantum-inspired encoding enhances stochastic sampling of soft matter systems, F. Slongo, P. Hauke, P. Faccioli, and C. Micheletti, Science Advances 9, eadi0204 (2023). DOI: 10.1126/sciadv.adi0204
Polymer Physics by Quantum Computing, C. Micheletti, P. Hauke, and P.Faccioli, Phys. Rev. Lett. 127, 080501 (2021). DOI: 10.1103/PhysRevLett.127.080501
Dominant Reaction Pathways by Quantum Computing, P. Hauke, G. Mattiotti, and P.Faccioli, Phys. Rev. Lett.126, 028104 (2021). DOI:10.1103/PhysRevLett.126.028104
Sampling Rare Conformational Transitions with a Quantum Computer, D. Ghamari, P. Hauke, R. Covino, and P.Faccioli, Scientific Reports 12, 16336 (2022). DOI:10.1038/s41598-022-20032-x
Sampling a Rare Protein Transition Using Quantum Annealing, D. Ghamari, R. Covino, and P. Faccioli, JCTC (2024). DOI:10.1021/acs.jctc.3c01174
Protein Design by Integrating Machine Learning and Quantum Optimization, V. Panizza, P. Hauke, C. Micheletti, and P. Faccioli, PRX-Life 2, 043012 (2024) DOI:10.1103/PRXLife.2.043012
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