arXiv subjects

Vladimir V. Mazurenko

Publications and source records attributed to Vladimir V. Mazurenko.

At least 19 recordsLinked to original sources

arXiv2026

Quantum-optical reset with classical memory

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 implemented with qubit-based superconducting hardware utilizing reset operations and classical logic. Here we develop a model of optical reset by using time-bin self-looped interferometers demonstrated in recent experiments. Synchronizing the optical reset with a simple classical device storing history of measurement results allows one to decrease uncertainty of future measurements, which suggests new possibilities for constructing dynamical circuits on optical platforms. Information flow with significant multi-time correlations and memory depth is identified through distinct information-theoretic measures. We discuss potential applications of the proposed reset model, including the realization of boson sampling and experimental tests of the quantum-mechanical formulation of Landauer's principle.

quant-ph↗

arXiv2026

Dzyaloshinskii-Moriya-driven instabilities in square-kagome quantum antiferromagnets

Decorated square-kagome quantum antiferromagnets provide a natural setting in which strong frustration, lattice decoration, and spin-orbit-induced anisotropy compete on comparable energy scales. Here we show that in Na$_6$Cu$_7$BiO$_4$(PO$_4$)$_4$Cl$_3$ the coupling ($J_{10}$) which links the decorating Cu(3) sites to the square-kagome backbone, stabilizes the gapped quantum-paramagnetic regime, while symmetry-allowed Dzyaloshinskii-Moriya (DM) interactions systematically suppress the minimum spinon gap $Δ_{\mathrm{spinon}}$ and drive the system toward magnetic condensation. To establish this, we combine ab initio calculation of the DM vectors with a generalized Schwinger-boson self-consistent mean-field theory that treats singlet and triplet hopping/pairing channels on equal footing. As a benchmark, the isotropic square-kagome Heisenberg model exhibits four competing low-energy saddle points distinguished by their Wilson-loop fluxes and by characteristic static and dynamical structure-factor fingerprints. A minimal DM perturbation does not qualitatively reshape this competing landscape, but already enhances the tendency towards order. For the realistic decorated Hamiltonian, finite-size scaling of $Δ_{\mathrm{spinon}}$ together with momentum-resolved structure factors identifies $J_{10}$ (exchange with decorating Cu) as the control parameter of the gapped regime and shows that the full symmetry-allowed DM pattern shifts the system further toward condensation. Our results place Na$_6$Cu$_7$BiO$_4$(PO$_4$)$_4$Cl$_3$ in close proximity to a magnetic instability and provide experimentally testable predictions for anisotropy-enhanced soft modes in decorated square-kagome materials.

cond-mat.str-el↗

arXiv2025

Emergence of global receptive fields capturing multipartite quantum correlations

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 elements. The inherent non-locality of the quantum correlations generally prevents one from providing their simple and transparent interpretation, which also remains a challenging problem for advanced classical techniques that approximate quantum states with neural networks. Here we show that monitoring the neural network weight space while learning quantum statistics from measurements allows to develop physical intuition about complex multipartite patterns and thus helps to construct more effective classical representations of the wave functions. Particularly, we observe the formation of distinct global convolutional structures, receptive fields in the hidden layer of the Restricted Boltzmann Machine (RBM) within the neural quantum tomography of the highly-entangled Dicke states. On this basis we propose an exact two-parameter classical representation not only for a specific quantum wave function, but for the whole family of the N-qubit Dicke states of different entanglement. Our findings suggest a fresh look at constructing convolutional neural networks for processing data with non-local patterns and pave the way for developing exact learning-based representations of entangled quantum states.

quant-ph↗

arXiv2024

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

Manipulating entanglement, which reflects non-local correlations in a quantum system and defines the complexity of describing its wave function, represents the extremely tough challenge in the fields of quantum computing, quantum information, and condensed matter physics. In this work, by the example of the well-structured Dicke states we demonstrate that the complexity of these real-valued wave functions can be accurately tuned by introducing a random-sign structure, which allows us to explore the regime of the volume-law entanglement. Importantly, setting nontrivial sign structure one can increase the entanglement entropy of the Dicke state to the values that are close to Page's estimates for Haar-random states. The practical realization of these random-sign Dicke states is possible on different physical platforms with shallow quantum circuits. On the level of the measurements the change in the quantum state complexity due to sign structure can be traced out with the dissimilarity measure that estimates multi-scale variety of patterns in bit-string arrays.

quant-ph↗

arXiv2023

An effective spin model on the honeycomb lattice for the description of magnetic properties in two-dimensional Fe$_3$GeTe$_2$

Fe$_3$GeTe$_2$ attracts significant attention due to technological perspectives of realizing room temperature ferromagnetism in two-dimensional materials. Here we show that due to structural peculiarities of the Fe$_3$GeTe$_2$ monolayer, short distance between the neighboring iron atoms induces a strong exchange coupling. This strong coupling allows us to consider them as an effective cluster with a magnetic moment $\sim$5 $μ_B$, giving rise to a simplified spin model on a bipartite honeycomb lattice with the reduced number of long-range interactions. The simplified model perfectly reproduces the results of the conventional spin model, but allows for a more tractable description of the magnetic properties of Fe$_3$GeTe$_2$, which is important, e.g., for large-scale simulations. Also, we discuss the role of biaxial strain in the stabilization of ferromagnetic ordering in Fe$_3$GeTe$_2$.

cond-mat.mtrl-sci↗

arXiv2023

Benchmarking a boson sampler with Hamming nets

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 required amount of measurements. A special attention to this problem appears within the context of characterizing outcomes of noisy intermediate-scale quantum devices, which produce quantum states with specific properties so that it is expected to be hard to simulate such states using classical resources. In this work, we address the problem of characterization of a boson sampling device, which uses interference of input photons to produce samples of non-trivial probability distributions that at certain condition are hard to obtain classically. For realistic experimental conditions the problem is to probe multi-photon interference with a limited number of the measurement outcomes without collisions and repetitions. By constructing networks on the measurements outcomes, we demonstrate a possibility to discriminate between regimes of indistinguishable and distinguishable bosons by quantifying the structures of the corresponding networks. Based on this we propose a machine-learning-based protocol to benchmark a boson sampler with unknown scattering matrix. Notably, the protocol works in the most challenging regimes of having a very limited number of bitstrings without collisions and repetitions. As we expect, our framework can be directly applied for characterizing boson sampling devices that are currently available in experiments.

quant-ph↗

arXiv2023

On the Nature of Interlayer Bonds in Two-dimensional Materials

The role of interlayer bonds in the two-dimensional (2D) materials "beyond graphene" and so-called van der Waals heterostructures is vital, and understanding the nature of these bonds in terms of strength and type is essential due to a wide range of their prospective technological applications. However, this issue has not yet been properly addressed in the previous investigations devoted to 2D materials. In our work, by using first-principles calculations we perform a systematic study of the interlayer bonds and charge redistribution of several representative 2D materials that are traditionally referred as van der Waals systems. Our results demonstrate that one can distinguish three main types of inter-layer couplings in the considered 2D structures: one atom thick membranes bonded by London dispersion forces (graphene, hBN), systems with leading electrostatic interaction between layers (diselenides, InSe and bilayer silica) and materials with so-called dative or coordination chemical bonds between layers (ditelurides). We also propose a protocol for recognising the leading type of interlayer bonds in a system that includes comparison of interlayer distances, binding energies and redistribution of the charge densities in interlayer space. Such an approach is computationally cheap and can be used to further prediction of chemical and physical properties such as charge density waves (CDW), work function and chemical stability at ambient conditions.

cond-mat.str-el↗

arXiv2023

Estimating Patterns of Classical and Quantum Skyrmion States

In this review we discuss the latest results concerning development of the machine learning algorithms for characterization of the magnetic skyrmions that are topologically-protected magnetic textures originated from the Dzyaloshinskii-Moriya interaction that competes Heisenberg isotropic exchange in ferromagnets. We show that for classical spin systems there is a whole pool of machine approaches allowing their accurate phase classification and quantitative description on the basis of few magnetization snapshots. In turn, investigation of the quantum skyrmions is a less explored issue, since there are fundamental limitations on the simulation of such wave functions with classical supercomputers. One needs to find the ways to imitate quantum skyrmions on near-term quantum computers. In this respect, we discuss implementation of the method for estimating structural complexity of classical objects for characterization of the quantum skyrmion state on the basis of limited number of bitstrings obtained from the projective measurements.

cond-mat.str-el↗

arXiv2021

Quantifying the interplay between fine structure and geometry of an individual molecule on a surface

The pathway toward the tailored synthesis of materials starts with precise characterization of the conformational properties and dynamics of individual molecules. Electron spin resonance based scanning tunneling microscopy can potentially address molecular structure with unprecedented resolution. Here, we determine the fine structure and geometry of an individual TiH molecule, utilizing a combination of a newly developed mK ESR-STM in a vector magnetic field and ab initio approaches. We demonstrate a strikingly large anisotropy of the g-tensor unusual for a spin doublet ground state, resulting from a non-trivial orbital angular momentum stemming from the molecular ground state. We quantify the relationship between the resultant fine structure, hindered rotational modes, and orbital excitations. Our model system provides new avenues to determine the structure and dynamics of individual molecules.

cond-mat.mes-hall↗

arXiv2020

Multi-scale structural complexity of natural patterns

Complexity of patterns is a key information for human brain to differ objects of about the same size and shape. Like other innate human senses, the complexity perception cannot be easily quantified. We propose a transparent and universal machine method for estimating structural (effective) complexity of two- and three-dimensional patterns that can be straightforwardly generalized onto other classes of objects. It is based on multi-step renormalization of the pattern of interest and computing the overlap between neighboring renormalized layers. This way, we can define a single number characterizing the structural complexity of an object. We apply this definition to quantify complexity of various magnetic patterns and demonstrate that not only does it reflect the intuitive feeling of what is "complex" and what is "simple", but also can be used to accurately detect different phase transitions and gain information about dynamics of non-equilibrium systems. When employed for that, the proposed scheme is much simpler and numerically cheaper than the standard methods based on computing correlation functions or using machine learning techniques.

nlin.PS↗

arXiv2020

Nature of the magnetic moment of cobalt in ordered FeCo alloy

The magnets are typically classified into Stoner and Heisenberg type, depending on the itinerant or localized nature of the constituent magnetic moments. In this work, we investigate theoretically the behaviour of the magnetic moments of iron and cobalt in their B2-ordered alloy. The results based on local spin density approximation (LSDA) for the density functional theory (DFT) suggest that the Co magnetic moment strongly depends on the directions of the surrounding magnetic moments, which usually indicates the Stoner-type mechanism of magnetism. This is consistent with the disordered local moment (DLM) picture of the paramagnetic state, where the magnetic moment of cobalt gets substantially suppressed. We argue that this is due to the lack of strong on-site electron correlations, which we take into account by employing a combination of DFT and dynamical mean-field theory (DMFT). Within LDA+DMFT, we find a substantial quasiparticle mass renormalization and a non Fermi-liquid behaviour of Fe-$3d$ orbitals. The resulting spectral functions are in very good agreement with measured spin-resolved photoemission spectra. Our results suggest that local correlations play an essential role in stabilizing a robust local moment on Co in the absence of magnetic order at high temperatures.

cond-mat.mtrl-sci↗

arXiv2020

Field evolution of the spin-liquid candidate YbMgGaO$_4$

We report magnetization, heat capacity, thermal expansion, and magnetostriction measurements down to millikelvin temperatures on the triangular antiferromagnet YbMgGaO$_4$. Our data exclude the formation of the distinct $\frac13$ plateau phase observed in other triangular antiferromagnets, but reveal plateaulike features in second derivatives of the free energy, magnetic susceptibility and specific heat, at $μ_0H$ = 1.0 - 2.5 T for $H\parallel{}c$ and 2 - 5 T for $H\perp{}c$. Using Monte-Carlo simulations of a realistic spin Hamiltonian, we ascribe these features to nonmonotonic changes in the magnetization and the $\frac12$ plateau that is smeared out by the random distribution of exchange couplings in YbMgGaO$_4$.

cond-mat.str-el↗

arXiv2020

Control of magnetic interactions between surface adatoms via orbital repopulation

We propose a reversible mechanism for switching Heisenberg-type exchange interactions between deposited transition metal adatoms from ferromagnetic to antiferromagnetic. Using first-principles calculations, we show that this mechanism can be realized for cobalt atoms on the surface of black phosphorus by making use of electrically-controlled orbital repopulation, as recently demonstrated by scanning probe techniques [Nat. Commun. 9, 3904 (2018)]. We find that field-induced repopulation not only affects the spin state, but also causes considerable modification of exchange interaction between adatoms, including its sign. Our model analysis demonstrates that variable adatom-substrate hybridization is a key factor responsible for this modification. We perform quantum simulations of inelastic tunneling characteristics and discuss possible ways to verify the proposed mechanism experimentally.

cond-mat.str-el↗

arXiv2020

SrCu$_2$(BO$_3$)$_2$ under pressure: a first-principle study

Using density-functional theory (DFT) band-structure calculations, we study the crystal structure, the lattice dynamics, and the magnetic interactions in the Shastry-Sutherland magnet SrCu$_2$(BO$_3$)$_2$ under pressure, concentrating on experimentally relevant pressures up to 4 GPa. All tendencies inside the candidate intermediate phases are thoroughly worked out, including specific predictions for some Raman active phonon modes that could be used to pin down the nature of the intermediate phase.

cond-mat.str-el↗

arXiv2019

The origin of up-up-down-down magnetic order in Cu$_2$GeO$_4$

We use density-functional band-structure calculations to explore the origin of the up-up-down-down (UUDD) magnetic order in Cu$_2$GeO$_4$ with the frustrated $J_1-J_2$ spin chains coupled into layers within the spinel-like crystal structure. In contrast to earlier studies, we find that the nearest-neighbor coupling $J_1$ may be negligibly small, owing to a nearly perfect compensation of the ferromagnetic direct exchange and antiferromagnetic superexchange. Under this condition, weak symmetric anisotropy of the exchange couplings gives rise to the UUDD order observed experimentally and also elucidates the non-trivial ordering pattern between the layers, whereas a small Dzyaloshinsky-Moriya interaction causes a spin canting that may generate local electric polarization. We argue that the buckling of the copper chains plays a crucial role in the suppression of $J_1$ in Cu$_2$GeO$_4$ and sets this compound apart from other $J_1-J_2$ chain magnets.

cond-mat.mtrl-sci↗

arXiv2019

Neural network agent playing spin Hamiltonian games on a quantum computer

Quantum computing is expected to provide new promising approaches for solving the most challenging problems in material science, communication, search, machine learning and other domains. However, due to the decoherence and gate imperfection errors modern quantum computer systems are characterized by a very complex, dynamical, uncertain and fluctuating computational environment. We develop an autonomous agent effectively interacting with such an environment to solve magnetism problems. By using the reinforcement learning the agent is trained to find the best-possible approximation of a spin Hamiltonian ground state from self-play on quantum devices. We show that the agent can learn the entanglement to imitate the ground state of the quantum spin dimer. The experiments were conducted on quantum computers provided by IBM. To compensate the decoherence we use local spin correction procedure derived from a general sum rule for spin-spin correlation functions of a quantum system with even number of antiferromagnetically-coupled spins in the ground state. Our study paves a way to create a new family of the neural network eigensolvers for quantum computers.

quant-ph↗

arXiv2019

Structural phase transitions in VSe2: energetics, electronic structure and magnetism

First principles calculations of magnetic and electronic properties of VSe2 describing the transition between two structural phases(H,T) were performed. Results of the calculations evidence rather low energy barrier ( 0.60 eV for monolayer) for transition betweenthe phases. The energy required for the deviation of Se atom or whole layer of selenium atoms on a small angle up to 10 degrees from initial positions is also rather low, 0.32 and 0.19 eV/Se, respectively. The changes in band structure of VSe2 caused by these motions of Se atoms should be taken into account for analysis of the experimental data. Simulations of the strain effects suggest that the experimentally observed T phase of VSe2 monolayer is the ground state due a substrate-induced strain. Calculations of the difference in total energies of ferromagnetic and antiferromagnetic configurations evidence that the ferromagnetic configuration is the ground state of the system for all stable and intermediate atomic structures. Calculated phonon dispersions suggest visible influence of magnetic configurations on vibrational properties.

cond-mat.str-el↗

arXiv2018

Stripe order and magnetic anisotropy in the $S=1$ antiferromagnet BaMoP$_2$O$_8$

Magnetic behavior of BaMoP$_2$O$_8$ with the spatially anisotropic triangular arrangement of the $S=1$ Mo$^{4+}$ ions is explored using thermodynamic measurements, neutron diffraction, and density-functional band-structure calculations. A broad maximum in the magnetic susceptibility around 46\,K is followed by the stripe antiferromagnetic order with the propagation vector ${\mathbf k}=(\frac{1}{2},\frac{1}{2},\frac{1}{2})$ formed below $T_N\simeq 21$ K. This stripe phase is triggered by a pronounced one-dimensionality of the spin lattice, where one of the in-plane couplings, $J_2\simeq 4.6$ meV, is much stronger than its $J_1\simeq 0.4$ meV counterpart, and stabilized by the weak easy-axis anisotropy. The ordered moment of 1.42(9) $μ_B$ at 1.5 K is significantly lower than the spin-only moment of 2 $μ_B$ due to a combined effect of quantum fluctuations and spin-orbit coupling.

cond-mat.str-el↗