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Michael R. Perelshtein
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Hybrid quantum ResNet for car classification and its hyperparameter optimization
A Sagingalieva, M Kordzanganeh, A Kurkin, A Melnikov, D Kuhmistrov, ...
Quantum Machine Intelligence 5 (2), 38, 2023
40*2023
Broadband continuous-variable entanglement generation using a Kerr-free Josephson metamaterial
MR Perelshtein, KV Petrovnin, V Vesterinen, SH Raja, I Lilja, M Will, ...
Physical Review Applied 18 (2), 024063, 2022
362022
Practical application-specific advantage through hybrid quantum computing
M Perelshtein, A Sagingalieva, K Pinto, V Shete, A Pakhomchik, ...
arXiv preprint arXiv:2205.04858, 2022
322022
Solving Large‐Scale Linear Systems of Equations by a Quantum Hybrid Algorithm
MR Perelshtein, AI Pakhomchik, AA Melnikov, AA Novikov, A Glatz, ...
Annalen der Physik, 2200082, 2022
25*2022
Quantum state preparation using tensor networks
AA Melnikov, AA Termanova, SV Dolgov, F Neukart, MR Perelshtein
Quantum Science and Technology 8 (3), 035027, 2023
212023
Broadband lumped-element Josephson parametric amplifier with single-step lithography
T Elo, TS Abhilash, MR Perelshtein, I Lilja, EV Korostylev, PJ Hakonen
Applied Physics Letters 114 (15), 2019
152019
Microwave photon detection at parametric criticality
K Petrovnin, J Wang, M Perelshtein, P Hakonen, GS Paraoanu
PRX Quantum 5 (2), 020342, 2024
102024
Tetra-AML: automatic machine learning via tensor networks
A Naumov, A Melnikov, V Abronin, F Oxanichenko, K Izmailov, M Pflitsch, ...
arXiv preprint arXiv:2303.16214, 2023
102023
Protein-protein docking using a tensor train black-box optimization method
D Morozov, A Melnikov, V Shete, M Perelshtein
arXiv preprint arXiv:2302.03410, 2023
72023
Generation and structuring of multipartite entanglement in a Josephson parametric system
KV Petrovnin, MR Perelshtein, T Korkalainen, V Vesterinen, I Lilja, ...
Advanced Quantum Technologies 6 (1), 2200031, 2023
72023
Linear ascending metrological algorithm
MR Perelshtein, NS Kirsanov, VV Zemlyanov, AV Lebedev, G Blatter, ...
Physical Review Research 3 (1), 013257, 2021
72021
Numerical solution of the incompressible Navier-Stokes equations for chemical mixers via quantum-inspired Tensor Train Finite Element Method
E Kornev, S Dolgov, K Pinto, M Pflitsch, M Perelshtein, A Melnikov
arXiv preprint arXiv:2305.10784, 2023
62023
Phase estimation algorithm for the multibeam optical metrology
VV Zemlyanov, NS Kirsanov, MR Perelshtein, DI Lykov, OV Misochko, ...
Scientific Reports 10 (1), 8715, 2020
62020
NISQ-compatible approximate quantum algorithm for unconstrained and constrained discrete optimization
MR Perelshtein, AI Pakhomchik, AA Melnikov, M Podobrii, A Termanova, ...
Quantum 7, 1186, 2023
52023
Optimization of chemical mixers design via tensor trains and quantum computing
N Belokonev, A Melnikov, M Podapaka, K Pinto, M Pflitsch, M Perelshtein
arXiv preprint arXiv:2304.12307, 2023
52023
Solving workflow scheduling problems with QUBO modeling
AI Pakhomchik, S Yudin, MR Perelshtein, A Alekseyenko, S Yarkoni
arXiv preprint arXiv:2205.04844, 2022
52022
Optimized emulation of quantum magnetometry via superconducting qubits
NN Gusarov, MR Perelshtein, PJ Hakonen, GS Paraoanu
Physical Review A 107 (5), 052609, 2023
32023
Vacuum-induced correlations in superconducting microwave cavity under multiple pump tones
T Korkalainen, I Lilja, MR Perelshtein, KV Petrovnin, GS Paraoanu, ...
AIP Conference Proceedings 2362 (1), 2021
32021
TQCompressor: improving tensor decomposition methods in neural networks via permutations
V Abronin, A Naumov, D Mazur, D Bystrov, K Tsarova, A Melnikov, ...
arXiv preprint arXiv:2401.16367, 2024
22024
Comparison between tensor networks and variational quantum classifier
G Laskaris, AA Melnikov, MR Perelshtein, R Brasher, T Baeck, F Neukart
arXiv preprint arXiv:2311.15663, 2023
22023
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Articles 1–20