Two-dimensional Classical XY Model Research Articles

Geometrical and topological study of the Kosterlitz–Thouless phase transition in the XY model in two dimensions

Phase transitions do not necessarily correspond to a symmetry-breaking phenomenon. This is the case of the Kosterlitz–Thouless (KT) phase transition in a two-dimensional classical XY model, a typical example of a transition stemming from a deeper phenomenon than a symmetry-breaking. Actually, the KT transition is a paradigmatic example of the successful application of topological concepts to the study of phase transition phenomena in the absence of an order parameter. Topology conceptually enters through the meaning of defects in real space. In the present work, the same kind of KT phase transition in a two-dimensional classical XY model is tackled by resorting again to a topological viewpoint, however focussed on the energy level sets in phase space rather than on topological defects in real space. Also from this point of view, the origin of the KT transition can be attributed to a topological phenomenon. In fact, the transition is detected through peculiar geometrical changes of the energy level sets which, after a theorem in differential topology, are direct probes of topological changes of these level sets.

Interpretable Machine Learning for the Thermodynamic Phases in 2D XY Model

We study the interpretable machine learning of thermodynamic phases in the two-dimensional classical XY model. We find that the neural network can accurately classify the different phases. We utilize the anchor algorithm to explain the mechanism of classification during the machine learning. The prediction based on the anchor is very close to that according to the raw spin configurations. With the help of linearity measurement, we find that the neural network shows strong nonlinearity when classifies the low temperature phase and strong linearity when classifies the high temperature thermal equilibrium phase, which means that the machine has strong adaptability to the thermodynamic fluctuation. The interpretable machine learning can be applied to other classical or quantum many-body systems.

Machine learning phases and criticalities without using real data for training

We study the phase transitions of three-dimensional (3D) classical O(3) model and the two-dimensional (2D) classical XY model, as well as both the quantum phase transitions of 2D and 3D dimerized spin-1/2 antiferromagnets, using the techniques of supervised neural network (NN). Moreover, unlike the conventional approaches commonly used in the literature, the training sets employed in our investigation are neither the theoretical nor the real configurations of the considered systems. Remarkably, with such an unconventional set up of the training stage in conjunction with semi-experimental finite-size scaling formulas, the associated critical points determined by the NN method agree well with the established results in the literature. The outcomes obtained here imply that certain unconventional training strategies, like the one used in this study, are not only cost-effective in computation, but are also applicable for a wild range of physical systems.

Critical analysis of two-dimensional classical XY model

We consider the two-dimensional classical XY model on a square lattice in the thermodynamic limit using tensor renormalization group and precisely determine the critical temperature corresponding to the Berezinskii–Kosterlitz–Thouless (BKT) phase transition to be 0.89290(5) which is an improvement compared to earlier studies using tensor network methods.

Approaching the Kosterlitz-Thouless transition for the classical XY model with tensor networks.

We apply variational tensor-network methods for simulating the Kosterlitz-Thouless phase transition in the classical two-dimensional XY model. In particular, using uniform matrix product states (MPS) with non-Abelian O(2) symmetry, we compute the universal drop in the spin stiffness at the critical point. In the critical low-temperature regime, we focus on the MPS entanglement spectrum to characterize the Luttinger-liquid phase. In the high-temperature phase, we confirm the exponential divergence of the correlation length and estimate the critical temperature with high precision. Our MPS approach can be used to study generic two-dimensional phase transitions with continuous symmetries.

Disordered XY model: Effective medium theory and beyond

We study the effect of uncorrelated random disorder on the temperature dependence of the superfluid stiffness in the two-dimensional classical XY model. By means of a perturbative expansion in the disorder potential, equivalent to the T-matrix approximation, we provide an extension of the effective-medium-theory result able to describe the low-temperature stiffness, and its separate diamagnetic and paramagnetic contributions. These analytical results provide an excellent description of the Monte Carlo simulations for two prototype examples of uncorrelated disorder. Our findings offer an interesting perspective on the effects of quenched disorder on longitudinal phase fluctuations in two-dimensional superfluid systems.

Machine learning vortices at the Kosterlitz-Thouless transition

Efficient and automated classification of phases from minimally processed data is one goal of machine learning in condensed matter and statistical physics. Supervised algorithms trained on raw samples of microstates can successfully detect conventional phase transitions via learning a bulk feature such as an order parameter. In this paper, we investigate whether neural networks can learn to classify phases based on topological defects. We address this question on the two-dimensional classical XY model which exhibits a Kosterlitz-Thouless transition. We find significant feature engineering of the raw spin states is required to convincingly claim that features of the vortex configurations are responsible for learning the transition temperature. We further show a single-layer network does not correctly classify the phases of the XY model, while a convolutional network easily performs classification by learning the global magnetization. Finally, we design a deep network capable of learning vortices without feature engineering. We demonstrate the detection of vortices does not necessarily result in the best classification accuracy, especially for lattices of less than approximately 1000 spins. For larger systems, it remains a difficult task to learn vortices.

Finite-size scaling method for the Berezinskii–Kosterlitz–Thouless transition

We test an improved finite-size scaling method for reliably extracting the critical temperature TBKT of a Berezinskii–Kosterlitz–Thouless (BKT) transition. Using known single-parameter logarithmic corrections to the spin stiffness ρs at TBKT in combination with the Kosterlitz–Nelson relation between the transition temperature and the stiffness, ρs(TBKT) = 2TBKT/π, we define a size-dependent transition temperature TBKT(L1,L2) based on a pair of system sizes L1,L2, e.g., L2 = 2L1. We use Monte Carlo data for the standard two-dimensional classical XY model to demonstrate that this quantity is well behaved and can be reliably extrapolated to the thermodynamic limit using the next expected logarithmic correction beyond the ones included in defining TBKT(L1,L2). For the Monte Carlo calculations we use GPU (graphical processing unit) computing to obtain high-precision data for L up to 512. We find that the sub-leading logarithmic corrections have significant effects on the extrapolation. Our result TBKT = 0.8935(1) is several error bars above the previously best estimates of the transition temperature, TBKT ≈ 0.8929. If only the leading log-correction is used, the result is, however, consistent with the lower value, suggesting that previous works have underestimated TBKT because of the neglect of sub-leading logarithms. Our method is easy to implement in practice and should be applicable to generic BKT transitions.

Large-Scale Monte Carlo Simulation of Two-Dimensional Classical XY Model Using Multiple GPUs

We study the two-dimensional classical XY model by the large-scale Monte Carlo simulation of the Swendsen-Wang multi-cluster algorithm using multiple GPUs on the open science supercomputer TSUBAME 2.0. Simulating systems up to the linear system size L =65536, we investigate the Kosterlitz–Thouless (KT) transition. Using the generalized version of the probability-changing cluster algorithm based on the helicity modulus, we locate the KT transition temperature in a self-adapted way. The obtained inverse KT temperature β KT is 1.11996(6). We estimate the exponent to specify the multiplicative logarithmic correction, -2 r , and precisely reproduce the theoretical prediction -2 r =1/8.

Quasi-long-range order in trapped systems

We investigate the effects of a trapping space-dependent potential on the low-temperature quasi-long-range order phase of two-dimensional particle systems with a relevant U(1) symmetry, such as quantum atomic gases. We characterize the universal features of the trap-size dependence using scaling arguments. The resulting scenario is supported by numerical Monte Carlo simulations of a classical two-dimensional XY model with a space-dependent hopping parameter whose inhomogeneity is analogous to that arising from the trapping potential in experiments of atomic gases.

Berezinsky–Kosterlitz–Thouless transition in phase fluctuating superconductors with inhomogeneous Gaussian distributed couplings

Within the framework of phase fluctuation picture for the pseudogap state of cuprate superconductors, we study the effects of both spatial inhomogeneity of coupling strength and thermal phase fluctuations on the superconducting transition temperature. Such a Berezinsky–Kosterlitz–Thouless (BKT) transition is characterized by a two-dimensional (2D) classical XY model, in which the bond coupling is assumed to be roughly proportional to the superconducting bond order parameter. In recent STM experiments with lattice-tracking spectroscopy technique, a Gaussian-like spatially distributed pairing strength is observed. Our Monte Carlo simulations using Wolff cluster update on such 2D classical XY model, in which the bond coupling obeys a similar spatial Gaussian distribution, indicate that the enhancement of the variance of Gaussian distribution may suppress the BKT transition temperature. In addition, we calculate the related physical quantities, including the spin stiffness, free energy, specific heat, magnetization and magnetic susceptibility, by changing the inhomogeneity variance.

High-temperature expansions through order 24 for the two-dimensional classical XY model on the square lattice

The high-temperature expansion of the spin-spin correlation function of the two-dimensional classical XY (planar rotator) model on the square lattice is extended by three terms, from order 21 through order 24, and analyzed to improve the estimates of the critical parameters.

Vortex deconfinement in the XY model with a magnetic field

We study vortex unbinding for the classical two-dimensional XY model in a magnetic field on square and triangular lattices. A renormalization group analysis combined with duality in the model shows that at high temperature and high field, the vortices unbind as the magnetic field is lowered in a two-step process: strings of overturned spins first proliferate and then vortices unbind. The transitions are highly continuous but are not of the Kosterlitz–Thouless type. The unbound vortex fixed point is shown to inherit properties of the underlying lattice, in particular containing a set of nodal lines that reflect the lattice symmetry.

Criticality in self-dual sine-Gordon models

We discuss the nature of criticality in the β 2=2 πN self-dual extension of the sine-Gordon model. This field theory is related to the two-dimensional classical XY model with a N-fold degenerate symmetry-breaking field. We briefly overview the already studied cases N=2,4 and analyze in detail the case N=3 where a single phase transition in the three-state Potts universality class is expected to occur. The Z 3 infrared critical properties of the β 2=6 π self-dual sine-Gordon model are derived using two non-perturbative approaches. On one hand, we map the model onto an integrable deformation of the Z 4 parafermion theory. The latter is known to flow to a massless Z 3 infrared fixed point. Another route is based on the connection with a chirally asymmetric, su(2) 4⊗su(2) 1 Wess–Zumino–Novikov–Witten model with anisotropic current–current interaction, where we explore the existence of a decoupling (Toulouse) point.

Deconfinement in the two-dimensional XY model.

The unbinding of vortex-antivortex pairs for the classical two-dimensional XY model in a magnetic field is studied. A single such pair is connected by a string of overturned spins, leading to linear confinement. We show that this system supports two phase transitions, one in which closed strings proliferate, and a second in which vortices unbind. The transitions are shown to be dual to one another, and are remarkably continuous. Possible consequences for a variety of systems are discussed.

Josephson array of mesoscopic objects. Modulation of system properties through the chemical potential

The phase diagram of a two-dimensional Josephson array of mesoscopic objects is examined. Quantum fluctuations in both the modulus and phase of the superconducting order parameter are taken into account within a lattice boson Hubbard model. Modulating the average occupation number $n_0$ of the sites in the system leads to changes in the state of the array, and the character of these changes depends significantly on the region of the phase diagram being examined. In the region where there are large quantum fluctuations in the phase of the superconducting order parameter, variation of the chemical potential causes oscillations with alternating superconducting (superfluid) and normal states of the array. On the other hand, in the region where the bosons interact weakly, the properties of the system depend monotonically on $n_0$. Lowering the temperature and increasing the particle interaction force lead to a reduction in the width of the region of variation in $n_0$ within which the system properties depend weakly on the average occupation number. The phase diagram of the array is obtained by mapping this quantum system onto a classical two-dimensional XY model with a renormalized Josephson coupling constant and is consistent with our quantum Path-Integral Monte Carlo calculations.

Theory of phase transitions in two-dimensional systems

A detailed description of phase transitions in two dimensions is presented based on the two-dimensional classical XY model. After describing the basic physics of topological ordering, the starting model Hamiltonian is constructed for a detailed study. Following this, a direct space renormalization programme is presented. The obtained phase transition is analysed in detail based on the scaling equations. The systematic renormalization group calculation up to third order based on field-theoretical techniques is also presented. The notion of topological excitations from the viewpoint of the dual model is analysed in detail. The D > 2 cases are analysed through the three-dimensional XY model and layered systems. This article is pedagogical in nature and is intended to be accessible to any graduate student or physicist who is not an expert in this field.

Monte Carlo study of asymmetric 2D XY model

Employing the Polyakov-Susskind approximation in a field theoretical treatment, the t- J model for strongly correlated electrons in two dimensions has recently been shown to map effectively onto an asymmetric two-dimensional classical XY model. The critical temperature at which charge-spin separation occurs in the t- J model is determined by the location of the phase transitions of this effective model. Here we report results of Monte Carlo simulations which map out the complete phase diagram in the two-dimensional parameter space and also shed some light on the critical behaviour of the transitions.

Dynamic finite-size effect in the two-dimensional classical XY model

Explicit dynamic finite-size scaling in the time-dependent correlation functions for the two-dimensional classical XY model is explored. The dynamic scaling method, proposed by us previously, is utilized for finding the time scaling variables of the model. It shows nontrivial dynamic finite-size scaling behavior near and below TKT for the total spin correlation function. Since the model is critical for all temperatures below TKT, the time scaling exponent is markedly different from that of the three-dimensional classical XY model at short times. There also appears to be another dynamic scaling region with a different time scaling exponent at T⩽TKT for a fairly wide intermediate time interval.

Phase transition in the two-dimensional classical XY model

For the two-dimensional classical XY model we present extensive high-temperature-phase bulk data extracted based on a novel finite size scaling (FSS) Monte Carlo technique, along with FSS data near criticality. Our data verify that η = 1 4 sets in near criticality, and clarify the nature of correction to the leading scaling behavior. However, the result of standard FSS analysis near criticality is inconsistent with other predictions of Kosterlitz's renormalization group approach.