Quantum and Linear-Optical Computation
Raffaele Santagati is a Staff Researcher in the Quantum and Linear-Optical Computation (QLOC) group.
Raffaele’s interests range from quantum information processing to quantum simulation, quantum machine learning and quantum sensing. In QLOC Raffaele is exploring new architectures for quantum computation with photons, methods for efficiently simulate quantum systems with quantum computers and for characterising quantum systems.
Raffaele was awarded a PhD in quantum physics from the University of Bristol (UK) for developing the first devices for quantum information processing in silicon quantum photonics.
He proposed and demonstrated a protocol for calculating eigenvalues of physical Hamiltonians on quantum computers.
At Bristol, he also demonstrated novel methods combining machine learning and quantum computers to characterise quantum systems from experiments and to improve the room-temperature sensitivity of quantum sensors.
- Santagati, Wang, Gentile, Paesani, Wiebe, McClean, Short, Shadbolt, Bonneau, Silverstone, Tew, Zhou, O’Brien, Thompson
Witnessing eigenstates for quantum simulation of Hamiltonian spectra
Science Advances 4, 1, eaap9646 (2018)
- Wang, Paesani, Ding, Santagati, Skrzypczyk, Salavrakos, Tura, Augusiak, Mančinska, Bacco, Bonneau, Silverstone, Gong, Acín, Rottwitt, Oxenløwe, O’Brien, Laing, Thompson
Multidimensional quantum entanglement with large-scale integrated optics
Science, 360, 6386, 285-291 (2018)
- Santagati, Gentile, Knauer, Schmitt, Paesani, Granade, Wiebe, Osterkamp, McGuinness, Wang, Thompson, Rarity, Jelezko, Laing
Magnetic-field-learning using a single electronic spin in diamond with one-photon-readout at room temperature
Phys. Rev. X 9, 021019 (2019)
- Silverstone, Santagati, Bonneau, Strain, Sorel, O’Brien and Thompson
Qubit entanglement between ring-resonator photon-pair sources on a silicon chip
Nature Communications 6, 7948 (2015)
- Wang, Paesani, Santagati, Knauer, Gentile, Wiebe, Petruzzella, L O’Brien, G Rarity, Laing, Thompson
Experimental quantum Hamiltonian learning
Nature Physics 1, 149 (2017)