Featured Researches

Disordered Systems And Neural Networks

Influence of disorder on a Bragg microcavity

Using the resonant-state expansion for leaky optical modes of a planar Bragg microcavity, we investigate the influence of disorder on its fundamental cavity mode. We model the disorder by randomly varying the thickness of the Bragg-pair slabs (composing the mirrors) and the cavity, and calculate the resonant energy and linewidth of each disordered microcavity exactly, comparing the results with the resonant-state expansion for a large basis set and within its first and second orders of perturbation theory. We show that random shifts of interfaces cause a growth of the inhomogeneous broadening of the fundamental mode that is proportional to the magnitude of disorder. Simultaneously, the quality factor of the microcavity decreases inversely proportional to the square of the magnitude of disorder. We also find that first-order perturbation theory works very accurately up to a reasonably large disorder magnitude, especially for calculating the resonance energy, which allows us to derive qualitatively the scaling of the microcavity properties with disorder strength.

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Disordered Systems And Neural Networks

Influence of long-range interaction on degeneracy of eigenvalues of connection matrix of d-dimensional Ising system

We examine connection matrices of Ising systems with long-rang interaction on d-dimensional hypercube lattices of linear dimensions L. We express the eigenvectors of these matrices as the Kronecker products of the eigenvectors for the one-dimensional Ising system. The eigenvalues of the connection matrices are polynomials of the d-th degree of the eigenvalues for the one-dimensional system. We show that including of the long-range interaction does not remove the degeneracy of the eigenvalues of the connection matrix. We analyze the eigenvalue spectral density in the limit L go to \infty. In the case of the continuous spectrum, for d < 3 we obtain analytical formulas that describe the influence of the long-range interaction on the spectral density and the crucial changes of the spectrum.

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Disordered Systems And Neural Networks

Interpretable and unsupervised phase classification

Fully automated classification methods that yield direct physical insights into phase diagrams are of current interest. Here, we demonstrate an unsupervised machine learning method for phase classification which is rendered interpretable via an analytical derivation of its optimal predictions and allows for an automated construction scheme for order parameters. Based on these findings, we propose and apply an alternative, physically-motivated, data-driven scheme which relies on the difference between mean input features. This mean-based method is computationally cheap and directly interpretable. As an example, we consider the physically rich ground-state phase diagram of the spinless Falicov-Kimball model.

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Disordered Systems And Neural Networks

Interpretation of the apparent activation energy of glass transition

The temperature dependence of the viscosity of glass is a major concern in the field of glass research. Strong deviations from the Arrhenius law make the interpretation of the activation energy difficult. In the present study, a reasonable interpretation of the apparent activation energy is demonstrated along similar lines as those adopted in solid-state physics and chemistry. In contrast to the widely held view that phase transition in glass occurs at the reference temperature T 0 according to the Vogel--Fulcher--Tammann formula, in the present work the transition observed at the glass-transition temperature T g is regarded as a phase transition from the liquid to solid phases. A distinct feature of glass is that the energy barrier significantly changes in the transition range with width Δ T g . This change in the energy barrier alters the manner in which the apparent activation energy constitutes the Arrhenius form. Analysis of available experimental data showed that the actual energy barrier is significantly smaller than the apparent activation energy, and importantly, the values obtained were in the reasonable range of energy expected for chemical bonds. The overestimation of the apparent activation energy depends on the ratio T g /Δ T g , which explains the existence of two types of glasses strong and fragile glasses. The fragility can be re-interpreted as an indication of the degree of increase in the energy barrier when approaching T g from high temperatures. Since no divergence in viscosity was observed below T g , it is unlikely that a transition occurs at T 0 .

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Disordered Systems And Neural Networks

Invariable mobility edge in a quasiperiodic lattice

In this paper, we study a one-dimensional tight-binding model with tunable incommensurate potentials. Through the analysis of the inverse participation rate, we uncover that the wave functions corresponding to the energies of the system exhibit different properties. There exists a critical energy under which the wave functions corresponding to all energies are extended. On the contrary, the wave functions corresponding to all energies above the critical energy are localized. However, we are surprised to find that the critical energy is a constant independent of the potentials. We use the self-dual relation to solve the critical energy, namely the mobility edge, and then we verify the analytical results again by analyzing the spatial distributions of the wave functions. Finally, we give a brief discussion on the possible experimental observation of the invariable mobility edge in the system of ultracold atoms in optical lattices.

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Disordered Systems And Neural Networks

Inverse problem for Ising connection matrix with long-range interaction

In the present paper, we examine Ising systems on d-dimensional hypercube lattices and solve an inverse problem where we have to determine interaction constants of an Ising connection matrix when we know a spectrum of it eigenvalues. In addition, we define restrictions allowing a random number sequence to be a connection matrix spectrum. We use the previously obtained analytical expressions for the eigenvalues of Ising connection matrices accounting for an arbitrary long-range interaction and supposing periodic boundary conditions.

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Disordered Systems And Neural Networks

Inverted many-body mobility edge in a central qudit problem

Many interesting experimental systems, such as cavity QED or central spin models, involve global coupling to a single harmonic mode. Out-of-equilibrium, it remains unclear under what conditions localized phases survive such global coupling. We study energy-dependent localization in the disordered Ising model with transverse and longitudinal fields coupled globally to a d -level system (qudit). Strikingly, we discover an inverted mobility edge, where high energy states are localized while low energy states are delocalized. Our results are supported by shift-and-invert eigenstate targeting and Krylov time evolution up to L=13 and 18 respectively. We argue for a critical energy of the localization phase transition which scales as E c ∝ L 1/2 , consistent with finite size numerics. We also show evidence for a reentrant MBL phase at even lower energies despite the presence of strong effects of the central mode in this regime. Similar results should occur in the central spin- S problem at large S and in certain models of cavity QED.

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Disordered Systems And Neural Networks

Investigation of Finite-size 2D Ising Model with a Noisy Matrix of Spin-Spin Interactions

We analyze changes in the thermodynamic properties of a spin system when it passes from the classical two-dimensional Ising model to the spin glass model, where spin-spin interactions are random in their values and signs. Formally, the transition reduces to a gradual change in the amplitude of the multiplicative noise (distributed uniformly with a mean equal to one) superimposed over the initial Ising matrix of interacting spins. Considering the noise, we obtain analytical expressions that are valid for lattices of finite sizes. We compare our results with the results of computer simulations performed for square N=L×L lattices with linear dimensions L=50÷1000 . We find experimentally the dependencies of the critical values (the critical temperature, the internal energy, entropy and the specific heat) as well as the dependencies of the energy of the ground state and its magnetization on the amplitude of the noise. We show that when the variance of the noise reaches one, there is a jump of the ground state from the fully correlated state to an uncorrelated state and its magnetization jumps from 1 to 0. In the same time, a phase transition that is present at a lower level of the noise disappears.

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Disordered Systems And Neural Networks

Ioffe-Regel criterion and viscoelastic properties of amorphous solids

We show that viscoelastic effects play a crucial role in the damping of vibrational modes in harmonic amorphous solids. The relaxation of a given plane wave is described by a memory function of a semi-infinite one-dimensions mass-spring chain. The initial vibrational energy spreads from the first site of the chain to infinity. In the beginning of the chain, there is a barrier, which significantly reduces the decay of vibrational energy below the Ioffe-Regel frequency. To obtain the parameters of the chain, we present a numerically stable method, based on the Chebyshev expansion of the local vibrational density of states.

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Disordered Systems And Neural Networks

Is there slow particle transport in the MBL phase?

We analyze the saturation value of the bipartite entanglement and number entropy starting from a random product state deep in the MBL phase. By studying the probability distributions of these entropies we find that the growth of the saturation value of the entanglement entropy stems from a significant reshuffling of the weight in the probability distributions from the bulk to the exponential tails. In contrast, the probability distributions of the saturation value of the number entropy are converged with system size, and exhibit a sharp cut-off for values of the number entropy which correspond to one particle fluctuating across the boundary between the two halves of the system. Our results therefore rule out slow particle transport deep in the MBL phase and confirm that the slow entanglement entropy production stems uniquely from configurational entanglement.

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