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Milan Žukovič

Publications and source records attributed to Milan Žukovič.

At least 19 recordsLinked to original sources

Competing anisotropies and phase transitions in the $q$-state clock model with a $p$-fold crystalline field

We study the two-dimensional $q$-state clock model in the presence of an additional $p$-fold symmetry-breaking crystalline field using Monte Carlo simulations. While the pure clock model exhibits Berezinskii--Kosterlitz--Thouless (BKT) transitions for sufficiently large $q$, the effect of competing discrete anisotropies on this topological phase remains nontrivial. We show that even weak crystalline fields qualitatively modify the phase diagram by suppressing the BKT phase and inducing transitions to states with true long-range order. The resulting behavior depends sensitively on the interplay between the intrinsic $\mathbb{Z}_q$ symmetry and the imposed $\mathbb{Z}_p$ anisotropy. In particular, in the six-state clock model for $p=2$ we observe qualitatively different scenarios depending on the sign of the field: a single transition for $h_2>0$ and a two-step ordering process for $h_2<0$ with an intermediate ordered phase. For $p=3$, the system exhibits a direct transition consistent with three-state Potts criticality. These results demonstrate that the phase structure cannot be inferred from symmetry considerations alone, but is governed by the competition between distinct locking mechanisms. Our findings provide a discrete counterpart to the multi-frequency sine-Gordon description of generalized $XY$ models and illustrate how additional anisotropies reshape topological phase transitions in two dimensions.

cond-mat.stat-mech↗

Arbitrary number of thermally induced phase transitions in different universality classes in $XY$ models with higher-order terms

We propose generalized variants of the $XY$ model capable of exhibiting an arbitrary number of phase transitions only by varying temperature. They are constructed by supplementing the magnetic coupling with $n_t-1$ nematic terms of exponentially increasing order with the base $q=2,3,4$ and $5$, and increasing interaction strength. It is found that for $q=2,3$ and $4$ with sufficiently large coupling strength of the final term, the models exhibit a number of phase transitions equal to the number of the terms in the generalized Hamiltonian. Starting from the paramagnetic phase, the system transitions through the cascade of $n_t-1$ nematic phases of the orders $q^{k}$, $k=n_t-1,n_t-2,\hdots,1$, that are characterized by $q^{k}$ preferential spin directions symmetrically disposed around the circle, to the ferromagnetic (FM) phase at the lowest temperatures. Besides the BKT transition from the paramagnetic phase, all the remaining transitions have a non-BKT nature: depending on the value of $q$ they belong to either the Ising ($q=2$ and $4$) or the three-states Potts ($q=3$) universality class. For $q=5$, due to the interplay between different terms, the phase transitions between the ordered phases observed for $q<5$ split into two and the number of the ordered phases increases to $2n_t-1$. These phases are characterized by a domain structure with the gradually increasing short-range FM ordering within domains that extends to different kinds of FM ordering in the last two low-temperature phases. The respective transitions do not seem to obey any universality.

cond-mat.stat-mech↗

Crossover from BKT to first-order transition induced by higher-order terms in 2D XY models

We study phase transitions in $XY$ models, generalized by inclusion of $n$ higher-order pairwise interactions of equal strength, by Monte Carlo simulation. It is found that by adding new terms the Berezinskii-Kosterlitz-Thouless (BKT) transition, observed in the standard $XY$ model, gradually changes to the first-order phase transition. We determine the critical number of terms for which the first-order transition appears as $n_c=6$. It is also found that for $n=5$ the transition is pseudo-first-order but it becomes true first-order if the couplings are allowed to increase. In general, a more rapid increase of the coupling intensity supports the first-order transition, however, a too fast increase may result in splitting of the single transition to multiple transitions. Consequently, the minimal number of the terms required for the change of the BKT phase transition to first order in the present model with arbitrary couplings is estimated to be $2 < n_c \leq 5$.

cond-mat.stat-mech↗

Generalized $XY$ model with competing antiferromagnetic and antinematic interactions

We study effects of $q$-order antinematic (AN$_q$) interactions on the critical behavior of the antiferromagnetic (AF) $XY$ model on a square lattice. It is found that the evolution of the phase diagram topology of such AF-AN$_q$ models with the parameter $q$ does not follow the same line as for the corresponding FM-N$_q$ models with the ferromagnetic (FM) and $q$-order nematic (N$_q$) interactions. Their phase diagrams are similar only for odd values of the parameter $q$. In such cases the respective phases reported in the FM-N$_q$ models are observed in the AF-AN$_q$ models on each of the two AF-coupled sublattices and the corresponding phase transitions are concluded to be of the same kind. On the other hand, for even values of $q$ the phase diagrams of the AF-AN$_q$ models are different from the FM-N$_q$ models and their topology does not change with $q$. Besides the pure AF and AN$_q$ phases, observed at higher temperatures in the regions of the dominant respective couplings, at low temperatures there is a new canted (C)AF phase, which results from the competition between the AF and AN$_q$ ordering tendencies and has no counterpart in the FM-N$_q$ model. The phase transitions to the CAF phase from both AF and AN$_q$ phases appear to be of the BKT nature.

cond-mat.stat-mech↗

A parsimonious, computationally efficient machine learning method for spatial regression

We introduce the modified planar rotator method (MPRS), a physically inspired machine learning method for spatial/temporal regression. MPRS is a non-parametric model which incorporates spatial or temporal correlations via short-range, distance-dependent ``interactions'' without assuming a specific form for the underlying probability distribution. Predictions are obtained by means of a fully autonomous learning algorithm which employs equilibrium conditional Monte Carlo simulations. MPRS is able to handle scattered data and arbitrary spatial dimensions. We report tests on various synthetic and real-word data in one, two and three dimensions which demonstrate that the MPRS prediction performance (without parameter tuning) is competitive with standard interpolation methods such as ordinary kriging and inverse distance weighting. In particular, MPRS is a particularly effective gap-filling method for rough and non-Gaussian data (e.g., daily precipitation time series). MPRS shows superior computational efficiency and scalability for large samples. Massive data sets involving millions of nodes can be processed in a few seconds on a standard personal computer.

stat.ML↗

Towards skyrmion crystal stabilization in the antiferromagnetic triangular lattice at ambient conditions

We explore possibilities of stabilizing a skyrmion (SkX) phase in the frustrated antiferromagnetic (AF) Heisenberg model with DMI on a triangular lattice at ambient conditions. We show that by stacking multiple AF layers and coupling them with strong ferromagnetic (F) interaction the SkX phase stability temperature window can be extended by several times. The transition temperature increase is supported by the increasing number of layers and interlayer interaction and thus room-temperature SkX phase could be achievable by proper tailoring of the multilayer structure. Further, we demonstrate that in the sandwich heterostructure, obtained by inserting a stiff F layer in between two AF layers, the required external magnetic field can be completely replaced by the effective field imposed by the F layer. Thus, one can design a heterostructure with the SkX phase stabilized at relatively high temperatures and zero field - the environment favorable for technological applications.

cond-mat.str-el↗

Spatial data modeling by means of Gibbs Markov random fields based on a generalized planar rotator model

We introduce a Gibbs Markov random field for spatial data on Cartesian grids which is based on the generalized planar rotator (GPR) model. The GPR model generalizes the recently proposed modified planar rotator (MPR) model by including in the Hamiltonian additional terms that better capture realistic features of spatial data, such as smoothness, non-Gaussianity, and geometric anisotropy. In particular, the GPR model includes up to infinite number of higher-order harmonics with exponentially vanishing interaction strength, directional dependence of the bilinear interaction term between nearest grid neighbors, longer-distance neighbor interactions, and two types of an external bias field. Hence, in contrast with the single-parameter MPR model, the GPR model features five additional parameters: the number $n$ of higher-order terms and the parameter $α$ controlling their decay rate, the exchange anisotropy parameter $J^{nn}$, the further-neighbor interaction coupling $J^{fn}$, and the external field (bias) parameters $K$ (or $K'$). We present numerical tests on various synthetic data which demonstrate the effects of the respective terms on the model's prediction performance and we discuss these results in connection with the data properties.

stat.ME↗

XY model with competing higher-order interactions

We study effects of competing pairwise higher-order interactions (HOI) with alternating signs and exponentially decreasing intensity on critical behavior of the XY model. It is found that critical properties of such a generalized model can be very different from the standard XY model and can strongly depend on whether the number of HOI terms is odd or even. Inclusion of any odd number of HOI terms results in two consecutive phase transitions to distinct ferromagnetic quasi-long-range order phases. Even number of HOI terms leads to two phase transitions only if the decay of the HOI intensities is relatively slow. Then the high-temperature transition to the ferromagnetic phase is followed by another transition to a peculiar competition-induced canted ferromagnetic phase. In the limit of an infinite number of HOI terms only one phase transition is confirmed, and under the conditions of fierce competition between the even and odd terms the transition temperature can be suppressed practically to zero.

cond-mat.stat-mech↗

Effect of Single-ion Anisotropy on Magnetocaloric Properties of Frustrated Spin-$s$ Ising Nanoclusters

Effects of a single-ion anisotropy on magnetocaloric properties of selected spin-$s\geq 1$ antiferromagnetic Ising clusters with frustration-inducing triangular geometry are studied by exact enumeration. It is found that inclusion of the single-ion anisotropy parameter $D$ can result in a much more complex ground-state behavior, which is also reflected in a magnetocaloric effect (MCE) at finite temperatures. For negative $D$ (easy-plane anisotropy) with increasing $s$ the ground-state magnetization as a function of the external field gradually shows increasing number of plateaus of various heights. Except for the cases of integer $s$ with $D < D_0 \leq 0$, the first magnetization plateau is of non-zero height. This property facilitates an enhanced MCE in the adiabatic demagnetization process in the form of an abrupt decrease in temperature as the magnetic field vanishes to zero. The cooling rate can be considerably enhanced in the systems with larger $s$ and $D>0$ (easy-axis anisotropy), albeit its dependence on these parameters is strongly dependent on the cluster geometry. From the studied systems more favorable conditions for observing a giant MCE were found in the 2CS cluster, consisting of two corner-sharing tetrahedra, the experimental realization of which could be technologically used for efficient refrigeration to ultra-low temperatures.

cond-mat.stat-mech↗

Numerical Precision Effects on GPU Simulation of Massive Spatial Data, Based on the Modified Planar Rotator Model

The present research builds on a recently proposed spatial prediction method for discretized two-dimensional data, based on a suitably modified planar rotator (MPR) spin model from statistical physics. This approach maps the measured data onto interacting spins and, exploiting spatial correlations between them, which are similar to those present in geostatistical data, predicts the data at unmeasured locations. Due to the short-range nature of the spin pair interactions in the MPR model, parallel implementation of the prediction algorithm on graphical processing units (GPUs) is a natural way of increasing its efficiency. In this work we study the effects of reduced computing precision as well as GPU-based hardware intrinsic functions on the speedup and accuracy of the MPR-based prediction and explore which aspects of the simulation can potentially benefit the most from the reduced precision. It is found that, particularly for massive data sets, a thoughtful precision setting of the GPU implementation can significantly increase the computational efficiency, while incurring little to no degradation in the prediction accuracy.

physics.comp-ph↗

Phase Diagram of a Generalized XY Model with Geometrical Frustration

In the present study we investigate the effects of geometrical frustration on the XY model with antiferromagnetic (AFM) coupling on a triangular lattice, generalized by the inclusion of a third-order antinematic term (AN3). We demonstrate that at non-zero temperatures such a generalization leads to a phase diagram consisting of three different quasi-long-range ordered (QLRO) phases. Compared to the model with the second-order AN coupling (AN2), it includes besides the AFM and AN3 phases which appear in the limits of relatively strong AFM and AN3 interactions, respectively, an additional complex noncollinear QLRO phase at lower temperatures wedged between the AFM and AN3 phases. This new phase originates from the competition between the AFM and AN3 couplings, which is absent in the model with the AN2 coupling.

cond-mat.str-el↗

Global Thermodynamic Properties of Complex Spin Systems Calculated from Density of States and Indirectly by Thermodynamic Integration Method

Evaluation of global thermodynamic properties, such as the entropy or the free energy, of complex systems featuring a high degree of frustration or disorder is often desirable. Nevertheless, they cannot be measured directly in standard Monte Carlo simulation. Therefore, they are either evaluated indirectly from the directly measured quantities, for example by the thermodynamic integration method (TIM), or by applying more sophisticated simulation methods, such as the Wang-Landau (WL) algorithm, which can directly sample density of states. In the present investigation we compare the performance of the WL and TIM methods in terms of calculation of the entropy of an Ising antiferromagnetic system on a Kagome lattice - a typical example of a complex spin system with high geometrical frustration resulting in a non-zero residual entropy the value of which is exactly known. It is found that in terms of accuracy the implementationally simpler TIM can deliver results comparable with the more involved WL method.

cond-mat.stat-mech↗

GPU-accelerated Simulation of Massive Spatial Data based on the Modified Planar Rotator Model

A novel Gibbs Markov random field for spatial data on Cartesian grids based on the modified planar rotator (MPR) model of statistical physics has been recently introduced for efficient and automatic interpolation of big data sets, such as satellite and radar images. The MPR model does not rely on Gaussian assumptions. Spatial correlations are captured via nearest-neighbor interactions between transformed variables. This allows vectorization of the model which, along with an efficient hybrid Monte Carlo algorithm, leads to fast execution times that scale approximately linearly with system size. The present study takes advantage of the short-range nature of the interactions between the MPR variables to parallelize the algorithm on graphics processing units (GPU) in the Compute Unified Device Architecture (CUDA) programming environment. It is shown that, for the processors employed, the GPU implementation can lead to impressive computational speedups, up to almost 500 times on large grids, compared to the single-processor calculations. Consequently, massive data sets comprising millions of data points can be automatically processed in less than one second on an ordinary GPU.

physics.comp-ph↗

Efficient and Scalable Approach to Equilibrium Conditional Simulation of Gibbs Markov Random Fields

We study the performance of an automated hybrid Monte Carlo (HMC) approach for conditional simulation of a recently proposed, single-parameter Gibbs Markov random field (Gibbs MRF). The MRF is based on a modified version of the planar rotator (MPR) model and is used for efficient gap filling in gridded data. HMC combines the deterministic over-relaxation method and the stochastic Metropolis update with dynamically adjusted restriction and performs automatic detection of the crossover to the targeted equilibrium state. We focus on the ability of the algorithm to efficiently drive the system to equilibrium at very low temperatures even with sparse conditioning data. These conditions are the most challenging computationally, requiring extremely long relaxation times if simulated by means of the standard Metropolis algorithm. We demonstrate that HMC has considerable benefits in terms of both computational efficiency and prediction performance of the MPR method.

physics.comp-ph↗

$XY$ model with antinematic interaction

We consider the $XY$ model with ferromagnetic (FM) and antinematic (AN) nearest-neighbor interactions on a square lattice for a varying interaction strength ratio. Besides the expected FM and AN quasi-long-range order (QLRO) phases we identify at low temperatures another peculiar canted ferromagnetic (CFM) QLRO phase, resulting from the competition between the collinear FM and non-collinear AN ordering tendencies. In the CFM phase neighboring spins that belong to different sublattices are canted by a non-universal (dependent on the interaction strength ratio) angle and the ordering is characterized by a fast-decaying power-law intra-sublattice correlation function. Compared to the FM phase, in the CFM phase correlations are significantly diminished by the presence of zero-energy domain walls due to the inherent degeneracy caused by the AN interactions. We present the phase diagram as a function of the interaction strength ratio and discuss the character of the respective phases as well as the transitions between them.

cond-mat.stat-mech↗

Gibbs Markov Random Fields with Continuous Values based on the Modified Planar Rotator Model

We introduce a novel Gibbs Markov random field for spatial data on Cartesian grids based on the modified planar rotator (MPR) model of statistical physics. The MPR captures spatial correlations using nearest-neighbor interactions of continuously-valued spins and does not rely on Gaussian assumptions. The only model parameter is the reduced temperature, which we estimate by means of an ergodic specific energy matching principle. We propose an efficient hybrid Monte Carlo simulation algorithm that leads to fast relaxation of the MPR model and allows vectorization. Consequently, the MPR computational time for inference and simulation scales approximately linearly with system size. This makes it more suitable for big data sets, such as satellite and radar images, than conventional geostatistical approaches. The performance (accuracy and computational speed) of the MPR model is validated with conditional simulation of Gaussian synthetic and non-Gaussian real data (atmospheric heat release measurements and Walker-lake DEM-based concentrations) and comparisons with standard gap-filling methods.

cond-mat.stat-mech↗

Multiple phase transitions in the $XY$ model with nematic-like couplings

Critical behavior of the two-dimensional generalized $XY$ model involving solely nematic-like terms of the second, third and fourth orders is studied by Monte Carlo method. We find that such a system can undergo three successive phase transitions. At higher temperatures there is a phase transition of the Berezinskii-Kosterlitz-Thouless type to the $q=4$ nematic-like phase, followed by two more transitions of the Ising type to the $q=2$ nematic-like and ferromagnetic phases, respectively. The $q$ nematic-like phases are characterized by spin alignments with angles $2kπ/q$, where $k \leq q$ is an integer. The ferromagnetic phase appears at low temperatures even without the presence of magnetic interactions owing to a synergic effect of the nematic-like terms.

cond-mat.stat-mech↗

Magnetic quasi-long-range ordering in nematics due to competition between higher-order couplings

Critical properties of the two-dimensional $XY$ model involving solely nematic-like biquadratic and bicubic terms are investigated by spin-wave analysis and Monte Carlo simulation. It is found that, even though neither of the nematic-like terms alone can induce magnetic ordering, their coexistence and competition leads to an extended phase of magnetic quasi-long-range order phase, wedged between the two nematic-like phases induced by the respective couplings. Thus, except for the muticritical point, at which all the phases meet, for any finite value of the coupling parameters ratio there are two phase transition: one from the paramagnetic phase to one of the two nematic-like phases followed by another one at lower temperatures to the magnetic phase. The finite-size scaling analysis indicate that the phase transitions between the magnetic and nematic-like phases belong to the Ising and three-state Potts universality classes. Inside the competition-induced algebraic magnetic phase the spin-pair correlation function is found to decay even much more slowly than in the standard $XY$ model with purely magnetic interactions. Such a magnetic phase is characterized by an extremely low vortex-antivortex pair density attaining a minimum close to the point at which the biquadratic and bicubic couplings are of about equal strengths and thus competition is the fiercest.

cond-mat.stat-mech↗