activity
20132025
most citedSupervised learning magnetic skyrmion phases

55 citations · 228 across the 18 of their papers we have counts for

collaborators

18 papers

quant-ph2025

Brute-force positivization of model ground states

P. A. Bannykh, O. M. Sotnikov, V. V. Mazurenko

Exploring sign structures of quantum wave functions attracts considerable attention due to the potential for advances in modeling complex phases of matter. This stimulates developi…

quant-ph2025

Quantum-optical reset with classical memory

Evgeniy O. Kiktenko, Oleg M. Sotnikov, Ilia A. Iakovlev +5

Dynamic quantum circuits generate states that depend on the measurement results obtained during circuit execution. To date such a quantum computing model has mainly been implemente…

quant-ph2024★ 2 cited

Exploring entanglement in finite-size quantum systems with degenerate ground state

V. S. Okatev, O. M. Sotnikov, V. V. Mazurenko

We develop an approach for characterizing non-local quantum correlations in spin systems with exactly or nearly degenerate ground states. Starting with linearly independent degener…

quant-ph2024★ 1 cited

Emergence of global receptive fields capturing multipartite quantum correlations

Oleg M. Sotnikov, Ilia A. Iakovlev, Evgeniy O. Kiktenko +3

In quantum physics, even simple data with a well-defined structure at the wave function level can be characterized by extremely complex correlations between its constituent element…

quant-ph2024★ 3 cited

Achieving the volume-law entropy regime with random-sign Dicke states

Oleg M. Sotnikov, Ilia A. Iakovlev, Evgeniy O. Kiktenko +2

Manipulating entanglement, which reflects non-local correlations in a quantum system and defines the complexity of describing its wave function, represents the extremely tough chal…

quant-ph2023★ 6 cited

Benchmarking a boson sampler with Hamming nets

Ilia A. Iakovlev, Oleg M. Sotnikov, Ivan V. Dyakonov +4

Analyzing the properties of complex quantum systems is crucial for further development of quantum devices, yet this task is typically challenging and demanding with respect to requ…

cond-mat.str-el2023★ 17 cited

Estimating Patterns of Classical and Quantum Skyrmion States

Vladimir V. Mazurenko, Ilia A. Iakovlev, Oleg M. Sotnikov +1

In this review we discuss the latest results concerning development of the machine learning algorithms for characterization of the magnetic skyrmions that are topologically-protect…

quant-ph2022★ 14 cited

Reconstruction of classical skyrmions from Anderson towers: quantum Darwinism in action

O. M. Sotnikov, E. A. Stepanov, M. I. Katsnelson +2

The development of the quantum skyrmion concept is aimed at expanding the scope of the fundamental research and practical applications for classical topologically-protected magneti…

quant-ph2021★ 19 cited

Certification of quantum states with hidden structure of their bitstrings

O. M. Sotnikov, I. A. Iakovlev, A. A. Iliasov +3

The rapid development of quantum computing technologies already made it possible to manipulate a collective state of several dozen of qubits. This success poses a strong demand on…

cond-mat.str-el2020★ 45 cited

Probing the topology of the quantum analog of a classical skyrmion

O. M. Sotnikov, V. V. Mazurenko, J. Colbois +3

In magnetism, skyrmions correspond to classical three-dimensional spin textures characterized by a topological invariant that keeps track of the winding of the magnetization in rea…

quant-ph2019★ 6 cited

Neural network agent playing spin Hamiltonian games on a quantum computer

Oleg M. Sotnikov, Vladimir V. Mazurenko

Quantum computing is expected to provide new promising approaches for solving the most challenging problems in material science, communication, search, machine learning and other d…

cond-mat.str-el2018

Quantum Nanoskyrmions

O. M. Sotnikov, V. V. Mazurenko, J. Colbois +3

Skyrmions in condensed matter physics appear as classical topological spin structures. This nontrivial state can be obtained solving the corresponding micromagnetic model, where th…

cond-mat.str-el2018★ 15 cited

Profile approach for recognition of three-dimensional magnetic structures

I. A. Iakovlev, O. M. Sotnikov, V. V. Mazurenko

We propose an approach for low-dimensional visualisation and classification of complex topological magnetic structures formed in magnetic materials. Within the approach one convert…

cond-mat.str-el2018★ 55 cited

Supervised learning magnetic skyrmion phases

I. A. Iakovlev, O. M. Sotnikov, V. V. Mazurenko

We propose and apply simple machine learning approaches for recognition and classification of complex non-collinear magnetic structures in two-dimensional materials. The first appr…

cond-mat.str-el2018★ 23 cited

Bimeron nanoconfined design

I. A. Iakovlev, O. M. Sotnikov, V. V. Mazurenko

We report on the stabilization of the topological bimeron excitations in confined geometries. The Monte Carlo simulations for a ferromagnet with a strong Dzyaloshinskii-Moriya inte…

cond-mat.str-el2017★ 5 cited

Monte Carlo study of magnetic nanoparticles adsorbed on halloysite nanotubes

O. M. Sotnikov, V. V. Mazurenko, A. A. Katanin

We study properties of magnetic nanoparticles adsorbed on the halloysite surface. For that a distinct magnetic Hamiltonian with random distribution of spins on a cylindrical surfac…

cond-mat.str-el2016★ 1 cited

A high-temperature expansion method for calculating paramagnetic exchange interactions

O. M. Sotnikov, V. V. Mazurenko

The method for calculating the isotropic exchange interactions in the paramagnetic phase is proposed. It is based on the mapping of the high-temperature expansion of the spin-spin…

cond-mat.str-el2013★ 16 cited

Correlation effects in insulating surface nanostructures

V. V. Mazurenko, S. N. Iskakov, A. N. Rudenko +4

We study the role of static and dynamical Coulomb correlation effects on the electronic and magnetic properties of individual Mn, Fe and Co adatoms deposited on the CuN surface. Fo…