1.1k citations · 6.3k across the 68 of their papers we have counts for
68 papers
Training neural networks with end-to-end optical backpropagation
James Spall, Xianxin Guo, A. I. Lvovsky
Optics is an exciting route for the next generation of computing hardware for machine learning, promising several orders of magnitude enhancement in both computational speed and en…
Continuous-variable quantum tomography of high-amplitude states
Ekaterina Fedotova, Nikolai Kuznetsov, Egor Tiunov +2
Quantum state tomography is an essential component of modern quantum technology. In application to continuous-variable harmonic-oscilator systems, such as the electromagnetic field…
Reconstructing complex states of a 20-qubit quantum simulator
Murali K. Kurmapu, V. V. Tiunova, E. S. Tiunov +6
A prerequisite to the successful development of quantum computers and simulators is precise understanding of physical processes occurring therein, which can be achieved by measurin…
Quantum computing at the quantum advantage threshold: a down-to-business review
A. K. Fedorov, N. Gisin, S. M. Beloussov +1
It is expected that quantum computers would enable solving various problems that are beyond the capabilities of the most powerful current supercomputers, which are based on classic…
Hybrid training of optical neural networks
James Spall, Xianxin Guo, A. I. Lvovsky
Optical neural networks are emerging as a promising type of machine learning hardware capable of energy-efficient, parallel computation. Today's optical neural networks are mainly…
Dual-laser self-injection locking to an integrated microresonator
Dmitry A. Chermoshentsev, Artem E. Shitikov, Evgeny A. Lonshakov +7
Diode laser self-injection locking (SIL) to a whispering gallery mode of a high quality factor resonator is a widely used method for laser linewidth narrowing and high-frequency no…