21 citations · 56 across the 6 of their papers we have counts for
5 papers · 1 filter
Practical application-specific advantage through hybrid quantum computing
Michael Perelshtein, Asel Sagingalieva, Karan Pinto +7
Quantum computing promises to tackle technological and industrial problems insurmountable for classical computers. However, today's quantum computers still have limited demonstrabl…
Setting up experimental Bell test with reinforcement learning
Alexey A. Melnikov, Pavel Sekatski, Nicolas Sangouard
Finding optical setups producing measurement results with a targeted probability distribution is hard as a priori the number of possible experimental implementations grows exponent…
Machine learning transfer efficiencies for noisy quantum walks
Alexey A. Melnikov, Leonid E. Fedichkin, Ray-Kuang Lee +1
Quantum effects are known to provide an advantage in particle transfer across networks. In order to achieve this advantage, requirements on both a graph type and a quantum system c…
Machine learning for long-distance quantum communication
Julius Wallnöfer, Alexey A. Melnikov, Wolfgang Dür +1
Machine learning can help us in solving problems in the context big data analysis and classification, as well as in playing complex games such as Go. But can it also be used to fin…
Hitting time for quantum walks of identical particles
Alexey A. Melnikov, Aleksandr P. Alodjants, Leonid E. Fedichkin
Quantum particles are known to be faster than classical when they propagate stochastically on certain graphs. A time needed for a particle to reach a target node on a distance, the…