activity
20192026
most citedMulticlass classification using quantum convolutional neural networks with hybrid quantum-classical learning

82 citations · 132 across the 9 of their papers we have counts for

collaborators

10 papers

quant-ph2026

Reservoir Support Sets the Minimum Loss for Non-Hermitian Dynamics

Alena Mastiukova

The minimum loss required to reproduce non-Hermitian dynamics depends on how many physical modes each reservoir can address coherently. Established positive-matrix criteria bound t…

quant-ph2025★ 2 cited

Regularizing quantum loss landscapes by noise injection

Daniil S. Bagaev, Maxim A. Gavreev, Alena S. Mastiukova +2

The difficulty of training variational quantum algorithms and quantum machine learning models is well established. In particular, quantum loss landscapes are often highly non-conve…

quant-ph2022★ 9 cited

Quantum-inspired optimization for wavelength assignment

Aleksey S. Boev, Sergey R. Usmanov, Alexander M. Semenov +5

Problems related to wavelength assignment (WA) in optical communications networks involve allocating transmission wavelengths for known transmission paths between nodes that minimi…

quant-ph2022★ 1 cited

Suppressing decoherence in quantum state transfer with unitary operations

Maxim A. Gavreev, Evgeniy O. Kiktenko, Alena S. Mastiukova +1

Decoherence is the fundamental obstacle limiting the performance of quantum information processing devices. The problem of transmitting a quantum state (known or unknown) from one…

cond-mat.quant-gas2022★ 1 cited

Free Fock parafermions in the tight-binding model with dissipation

A. S. Mastiukova, D. V. Kurlov, V. Gritsev +1

Parafermions that generalize (Majorana or usual) fermions appear as interacting quasi-particles because of their nature. Although attempts to develop models with free (non-interact…

quant-ph2022★ 82 cited

Multiclass classification using quantum convolutional neural networks with hybrid quantum-classical learning

Denis Bokhan, Alena S. Mastiukova, Aleksey S. Boev +2

Multiclass classification is of great interest for various applications, for example, it is a common task in computer vision, where one needs to categorize an image into three or m…

quant-ph2022★ 11 cited

Learning entanglement breakdown as a phase transition by confusion

M. A. Gavreev, A. S. Mastiukova, E. O. Kiktenko +1

Quantum technologies require methods for preparing and manipulating entangled multiparticle states. However, the problem of determining whether a given quantum state is entangled o…

eess.SP2020

Tomographic and entropic analysis of modulated signals

A. S. Mastiukova, M. A. Gavreev, E. O. Kiktenko +1

We study an application of the quantum tomography framework for the time-frequency analysis of modulated signals. In particular, we calculate optical tomographic representations an…

quant-ph2019★ 26 cited

Probability representation of quantum dynamics using pseudostochastic maps

E. O. Kiktenko, A. O. Malyshev, A. S. Mastiukova +3

In this work, we consider a probability representation of quantum dynamics for finite-dimensional quantum systems with the use of pseudostochastic maps acting on true probability d…

quant-ph2019

Protecting quantum systems from decoherence with unitary operations

E. O. Kiktenko, A. S. Mastiukova, A. K. Fedorov

Decoherence is a fundamental obstacle to the implementation of large-scale and low-noise quantum information processing devices. In this work, we suggest an approach for suppressin…