SEARCH · Searcharxiv

Results for “cond-mat.dis-nn”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4Linked to original sources

arXiv2010

Smeared quantum phase transition in the dissipative random quantum Ising model

We investigate the quantum phase transition in the random transverse-field Ising model under the influence of Ohmic dissipation. To this end, we numerically implement a strong-disorder renormalization-group scheme. We find that Ohmic dissipation destroys the quantum critical point and the associated quantum Griffiths phase by smearing. Our results quantitatively confirm a recent theory [Phys. Rev. Lett. {\bf 100}, 240601 (2008)] of smeared quantum phase transitions.

cond-mat.str-el↗

arXiv2010

Generalised Kramers model

We study a particular generalisation of the classical Kramers model describing Brownian particles in the external potential. The generalised model includes the stochastic force which is modelled as an additive random noise that depends upon the position of the particle, as well as time. The stationary solution of the Fokker-Planck equation is analysed in two limits: weak external forcing, where the solution is equivalent to the increase of the potential compared to the classical model, and strong external forcing, where the solution yields a non-zero probability flux for the motion in a periodic potential with a broken reflection symmetry.

cond-mat.stat-mech↗

arXiv2008

Magnetism of frustrated regular networks

We consider a regular random network where each node has exactly three neighbours. Ising spins at the network nodes interact antiferromagnetically along the links. The clustering coefficient $C$ is tuned from zero to 1/3 by adding new links. At the same time, the density of geometrically frustrated links increases. We calculate the magnetic specific heat, the spin susceptibility and the Edwards-Anderson order parameter $q$ by means of the heat-bath Monte Carlo simulations. The aim is the transition temperature $T_x$ dependence on the clustering coefficient $C$. The results are compared with the predictions of the Bethe approximation. At C=0, the network is bipartite and the low temperature phase is antiferromagnetic. When $C$ increases, the critical temperature falls down towards the values which are close to the theoretical predictions for the spin-glass phase.

cond-mat.dis-nn↗

arXiv2009

On the Financial Crisis 2008 from a Physicist's viewpoint: A Spin-Glass Interpretation

In an informal way, a number of thoughts on the financial crisis 2008 are presented from a physicist's viewpoint, considering the problem as a nonergodicity transition of a spin-glass type of system. Some tentative suggestions concerning the way out of the crisis are also discussed, concerning Keynesian "deficit spending" methods, tax reductions, and finally the method "ruin and recreate" known from optimization theory. Also the de Almeida-Thouless instability line of spin-glass theory is given a financial interpretation.

cond-mat.dis-nn↗

arXiv2009

Anomalous non-linear response of glassy liquids: general arguments and a Mode-Coupling approach

We study theoretically the non-linear response properties of glass formers. We establish several general results which, together with the assumption of Time-Temperature Superposition, lead to a relation between the non-linear response and the derivative of the linear response with respect to temperature. Using results from Mode-Coupling Theory (MCT) and scaling arguments valid close to the glass transition, we obtain the frequency and temperature dependence of the non-linear response in the $α$ and $β$-regimes. Our results demonstrate that supercooled liquids are characterized by responses to external perturbations that become increasingly non-linear as the glass transition is approached. These results are extended to the case of inhomogeneous perturbing fields.

cond-mat.stat-mech↗

arXiv2009

Phase Transitions in Transportation Networks with Nonlinearities

We investigate a model of transportation networks with nonlinear elements which may represent local shortage of resources. Frustrations arise from competition for resources. When the initial resources are uniform, different regimes with discrete fractions of satisfied nodes are observed, resembling the Devil's staircase. We demonstrate how functional recursions are converted to simple recursions of probabilities. Behavior similar to those in the vertex cover or close packing problems are found. When the initial resources are bimodally distributed, increases in the fraction of rich nodes induce a glassy transition, entering an algorithmically hard regime.

cond-mat.dis-nn↗

arXiv2009

Bayesian Inference Based on Stationary Fokker-Planck Sampling

A novel formalism for Bayesian learning in the context of complex inference models is proposed. The method is based on the use of the Stationary Fokker--Planck (SFP) approach to sample from the posterior density. Stationary Fokker--Planck sampling generalizes the Gibbs sampler algorithm for arbitrary and unknown conditional densities. By the SFP procedure approximate analytical expressions for the conditionals and marginals of the posterior can be constructed. At each stage of SFP, the approximate conditionals are used to define a Gibbs sampling process, which is convergent to the full joint posterior. By the analytical marginals efficient learning methods in the context of Artificial Neural Networks are outlined. Off--line and incremental Bayesian inference and Maximum Likelihood Estimation from the posterior is performed in classification and regression examples. A comparison of SFP with other Monte Carlo strategies in the general problem of sampling from arbitrary densities is also presented. It is shown that SFP is able to jump large low--probabilty regions without the need of a careful tuning of any step size parameter. In fact, the SFP method requires only a small set of meaningful parameters which can be selected following clear, problem--independent guidelines. The computation cost of SFP, measured in terms of loss function evaluations, grows linearly with the given model's dimension.

cond-mat.dis-nn↗

arXiv2009

Scattering of electrons by clusters of charged impurities in graphene

It is shown that clustering of charged impurities on graphene can suppress their contribution to the resistivity by a large factor of about the number of impurities per cluster, while leaving the density dependence unchanged. If the cluster size is large in comparison with the Fermi wavelength, the scattering cross section shows sharp resonances as a function of incident angle and electron wavevector. In this regime, due to dominant contribution of scattering by small angles, the transport cross section can be much smaller than the quantum one, which can be verified experimentally by comparing the Dingle temperature and the electron mean free path.

cond-mat.mes-hall↗

arXiv2009

Localization of light by magnetically tuned correlated disorder: Trapping of light in ferrofluids

The mean free path of light ($l^*$) calculated for elastic scattering on a system of nanoparticles with spatially correlated disorder is found to have a minimum when the correlation length is of the order of the wavelength of light. For a typical choice of parameters for the scattering system, this minimum mean free path ($l^*_{min}$) turns out to satisfy the Ioffe-Regel criterion for wave localization, $l^*_{min} \sim λ$, over a range of the correlation length, defining thus a stop-band for light transmission. It also provides a semi-phenomenological explanation for several interesting findings reported recently on the transmission/ reflection and the trapping/storage of light in a magnetically tunable ferrofluidic system. The subtle effect of structural anisotropy, induced by the external magnetic field on the scattering by the medium, is briefly discussed in physical terms of the anisotropic Anderson localization.

cond-mat.dis-nn↗

arXiv2009

A new universality class of aging in glassy systems

Glassy systems are ubiquitous in nature, and are characterized by slow relaxations to equilibrium without a typical timescale, aging and memory effects. Understanding these is a long-standing problem in physics. We study the aging of the electron glass, a system showing remarkable slow relaxations in the conductance. We find that the broad distribution of relaxation rates leads to a universal relaxation of the form log(1+t_w/t) for the usual aging protocol, where t_w is the length of time the perturbation driving the system out-of-equilibrium was on, and t the time of measurement. These results agree well with several experiments performed on different glasses, and examining different physical observables, for times ranging from seconds to several hours. The suggested theoretical framework appears to offer a paradigm for aging in a broad class of glassy materials.

cond-mat.dis-nn↗

arXiv2009

Avalanches in directed complex networks of neurons connected by stochastic synapses

Directed complex network of two-state model neurons linked by synapses which can be blocked or activated stochastically in time undergoes phase transition between the quiescent phase with zero activity and the active one with persistent activity. Avalanches of activity appear in the quiescent phase after occasional excitation of randomly chosen neuron. Size and duration distributions of long avalanches which we observe near phase transition point are exponential. Only a small fraction of all neurons are active at any moment of a long avalanche.

cond-mat.dis-nn↗

arXiv2010

Spatial Correlation of the Dynamic Propensity in a Glass-Forming Liquid

We present computer simulation results on the dynamic propensity [as defined by Widmer- Cooper, Harrowell, and Fynewever, Phys. Rev. Lett. 93, 135701 (2004)] in a Kob-Andersen binary Lennard-Jones liquid system consisting of 8788 particles. We compute the spatial correlation function of the dynamic propensity as a function of both the reduced temperature T, and the time scale on which the particle displacements are measured. For T\leq0.6, we find that nonzero correlations occur at the largest length scale accessible in our system. We also show that a cluster-size analysis of particles with extremal values of the dynamic propensity, as well as 3D visualizations, reveal spatially correlated regions that approach the size of our system as T decreases, consistent with the behavior of the spatial correlation function. Next, we define and examine the "coordination propensity", the isoconfigurational average of the coordination number of the minority B particles around the majority A particles. We show that a significant correlation exists between the spatial fluctuations of the dynamic and coordination propensities. In addition, we find non-zero correlations of the coordination propensity occurring at the largest length scale accessible in our system for all T in the range 0.466<T<1.0. We discuss the implications of these results for understanding the length scales of dynamical heterogeneity in glass-forming liquids.

cond-mat.mtrl-sci↗

arXiv2009

Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes

Identifying the spatio-temporal network structure of brain activity from multi-neuronal data streams is one of the biggest challenges in neuroscience. Repeating patterns of precisely timed activity across a group of neurons is potentially indicative of a microcircuit in the underlying neural tissue. Frequent episode discovery, a temporal data mining framework, has recently been shown to be a computationally efficient method of counting the occurrences of such patterns. In this paper, we propose a framework to determine when the counts are statistically significant by modeling the counting process. Our model allows direct estimation of the strengths of functional connections between neurons with improved resolution over previously published methods. It can also be used to rank the patterns discovered in a network of neurons according to their strengths and begin to reconstruct the graph structure of the network that produced the spike data. We validate our methods on simulated data and present analysis of patterns discovered in data from cultures of cortical neurons.

q-bio.NC↗

arXiv2011

An analytical application of Niedermayer's algorithm to the Edwards-Anderson model: analytical results for the multicritical point on the Nishimori line

We apply analytically Niedermayer's algorithm to the Edwards-Anderson model on random graphs with arbitary degree distributions. The results for the multicritical point on the Nishimori line are shown. The results are shown by applying a criterion for spin models on the random graphs with arbitary degree distributions. The application of Niedermayer's algorithm makes the size of the Fortuin-Kasteleyn cluster small and shifts the percolation threshold. The results for the $\pm J$ model and the Gaussian model are respectively shown. In the present article, it is respectively shown for the $\pm J$ model and the Gaussian model that, by adjusting an introduced parameter for Niedermayer's algorithm, the percolation threshold obtained in the present article agrees with the location of the multicritical point. We naively estimate the locations of the multicritical points for the $\pm J$ model and the Gaussian model on the randam graphs with arbitary degree distributions.

cond-mat.dis-nn↗

arXiv2009

Phase transitions and random quantum satisfiability

Alongside the effort underway to build quantum computers, it is important to better understand which classes of problems they will find easy and which others even they will find intractable. We study random ensembles of the QMA$_1$-complete quantum satisfiability (QSAT) problem introduced by Bravyi. QSAT appropriately generalizes the NP-complete classical satisfiability (SAT) problem. We show that, as the density of clauses/projectors is varied, the ensembles exhibit quantum phase transitions between phases that are satisfiable and unsatisfiable. Remarkably, almost all instances of QSAT for any hypergraph exhibit the same dimension of the satisfying manifold. This establishes the QSAT decision problem as equivalent to a, potentially new, graph theoretic problem and that the hardest typical instances are likely to be localized in a bounded range of clause density.

quant-ph↗

arXiv2010

Self-dual planar hypergraphs and exact bond percolation thresholds

Recent research on percolation has led to the construction of an infinite class of lattices for which the percolation thresholds can be determined exactly. We discuss the mathematical basis for the solutions of bond percolation models, and, in particular, attempt to address some misconceptions that might arise from the seminal articles by Ziff and Scullard. As one consequence, we show that there exist infinitely many real numbers $a \in [0,1]$ for which there are infinitely many lattices that have bond percolation threshold equal to $a$.

cond-mat.stat-mech↗

arXiv2009

Explosive growth in biased dynamic percolation on two-dimensional regular lattice networks

The growth of two-dimensional lattice bond percolation clusters through a cooperative Achlioptas-type of process, where the choice of which bond to occupy next depends upon the masses of the clusters it connects, is shown to go through an explosive, first-order kinetic phase transition with a sharp jump in the mass of the largest cluster as the number of bonds is increased. The critical behavior of this growth model is shown to be of a different universality class than standard percolation.

cond-mat.dis-nn↗

arXiv2009

Typical case behaviour of spin systems in random graph and composite ensembles

This thesis includes analysis of disordered spin ensembles corresponding to Exact Cover, a multi-access channel problem, and composite models combining sparse and dense interactions. The satisfiability problem in Exact Cover is addressed using a statistical analysis of a simple branch and bound algorithm. The algorithm can be formulated in the large system limit as a branching process, for which critical properties can be analysed. Far from the critical point a set of differential equations may be used to model the process, and these are solved by numerical integration and exact bounding methods. The multi-access channel problem is formulated as an equilibrium statistical physics problem for the case of bit transmission on a channel with power control and synchronisation. A sparse code division multiple access method is considered and the optimal detection properties are examined in typical case by use of the replica method, and compared to detection performance achieved by iterative decoding methods. These codes are found to have phenomena closely resembling the well-understood dense codes. The composite model is introduced as an abstraction of canonical sparse and dense disordered spin models. The model includes couplings due to both dense and sparse topologies simultaneously. Through an exact replica analysis at high temperature, and variational approaches at low temperature, several phenomena uncharacteristic of either sparse or dense models are demonstrated. An extension of the composite interaction structure to a code division multiple access method is presented. The new type of codes are shown to outperform sparse and dense codes in some regimes both in optimal performance, and in performance achieved by iterative detection methods in finite systems.

cond-mat.dis-nn↗