Quantum computing and simulation for
soft and biological matter

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.

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