A. K. Fedorov & M. S. Gelfand
Towards practical applications in quantum computational biology A.S. Boev, A.S. Rakitko, S.R. Usmanov, A.N. Kobzeva, I.V. Popov, V.V. Ilinsky, E.O. Kiktenko, and A.K. Fedorov,
Genome assembly using quantum and quantum-inspired annealingNature Scientific Reports
The first application of quantum annealing for realistic tasks in genetics.
E.S. Tiunov, V.V. Tiunova, A.E. Ulanov, A.I. Lvovsky, and A.K. Fedorov,
Experimental quantum homodyne tomography via machine learningOptica 7, 448 (2020);
arXiv:1907.06589 E.O. Kiktenko, A.S. Mastiukova, and A.K. Fedorov,
Protecting quantum systems from decoherence with unitary operationsOptical Engineering 59, 061625 (2020);
arXiv:1907.01971 E.O. Kiktenko, A.S. Nikolaeva, Peng Xu, G.V. Shlyapnikov, and A.K. Fedorov,
Scalable quantum computing with qudits on a graphPhysical Review A 101, 064406 (2020);
arXiv:1909.08973New architecture for digital quantum computers.
Y.A. Kharkov, V.E. Sotskov, A.A. Karazeev, E.O. Kiktenko, and A.K. Fedorov,
Revealing quantum chaos with machine learningPhysical Review B 101, 022304 (2020);
arXiv:1902.09216 E.O. Kiktenko, D.N. Kublikova, and A.K. Fedorov,
Estimating the precision for quantum process tomographyOptical Engineering 59, 061614 (2020);
arXiv:1911.00277