Browsing by Author "Pleimling, Michel J."

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    Aging in coarsening diluted ferromagnets
    Park, H.; Pleimling, Michel J. (American Physical Society, 2010-10)
    We comprehensively study nonequilibrium relaxation and aging processes in the two-dimensional randomsite Ising model through numerical simulations. We discuss the dynamical correlation length as well as scaling functions of various two-time quantities as a function of temperature and of the degree of dilution. For already modest values of the dynamical correlation length L deviations from a simple algebraic growth, L(t)similar to t(1/z), are observed. When taking this nonalgebraic growth properly into account, a simple aging behavior of the auto-correlation function is found. This is in stark contrast to earlier studies where, based on the assumption of algebraic growth, a superaging scenario was postulated for the autocorrelation function in disordered ferromagnets. We also study the scaling behavior of the space-time correlation as well as of the time integrated linear response and find again agreement with simple aging. Finally, we briefly discuss the possibility of superuniversality in the scaling properties of space- and time-dependent quantities.
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    Aging processes in complex systems
    Afzal, Nasrin (Virginia Tech, 2013-04-27)
    Recent years have seen remarkable progress in our understanding of physical aging in nondisordered systems with slow, i.e. glassy-like dynamics. In many systems a single dynamical length L(t), that grows as a power-law of time t or, in much more complicated cases, as a logarithmic function of t, governs the dynamics out of equilibrium. In the aging or dynamical scaling regime, these systems are best characterized by two-times quantities, like dynamical correlation and response functions, that transform in a specific way under a dynamical scale transformation. The resulting dynamical scaling functions and the associated non-equilibrium exponents are often found to be universal and to depend only on some global features of the system under investigation. We discuss three different types of systems with simple and complex aging properties, namely reaction diffusion systems with a power growth law, driven diffusive systems with a logarithmic growth law, and a non-equilibrium polymer network that is supposed to capture important properties of the cytoskeleton of living cells. For the reaction diffusion systems, our study focuses on systems with reversible reaction diffusion and we study two-times functions in systems with power law growth. For the driven diffusive systems, we focus on the ABC model and a related domain model and measure two- times quantities in systems undergoing logarithmic growth. For the polymer network model, we explain in some detail its relationship with the cytoskeleton, an organelle that is responsible for the shape and locomotion of cells. Our study of this system sheds new light on the non- equilibrium relaxation properties of the cytoskeleton by investigating through a power law growth of a coarse grained length in our system.
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    Aging processes in systems with anomalous slow dynamics
    Afzal, N.; Pleimling, Michel J. (American Physical Society, 2013-01-14)
    Recently, different numerical studies of coarsening in disordered systems have shown the existence of a crossover from an initial, transient, power-law domain growth to a slower, presumably logarithmic, growth. However, due to the very slow dynamics and the long-lasting transient regime, one is usually not able to fully enter the asymptotic regime when investigating the relaxation of these systems toward equilibrium. We here study two simple driven systems-the one-dimensional ABC model and a related domain model with simplified dynamics-that are known to exhibit anomalous slow relaxation where the asymptotic logarithmic growth regime is readily accessible. Studying two-times correlation and response functions, we focus on aging processes and dynamical scaling during logarithmic growth. Using the time-dependent growth length as the scaling variable, a simple aging picture emerges that is expected to also prevail in the asymptotic regime of disordered ferromagnets and spin glasses.
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    Controlling non-equilibrium dynamics in lattice gas models
    Mukhamadiarov, Ruslan Ilyich (Virginia Tech, 2021-03-05)
    In recent years a new interesting research avenue has emerged in non-equilibrium statistical physics, namely studies of collective responses in spatially inhomogeneous systems. Whereas substantial progress has been made in understanding the origins and the often universal nature of cooperative behavior in systems far from equilibrium, it is still unclear whether it is possible to control their global collective stochastic dynamics through local manipulations. Therefore, a comprehensive characterization of spatially inhomogeneous non-equilibrium systems is required. In the first system, we explore a variant of the Katz–Lebowitz–Spohn (KLS) driven lattice gas in two dimensions, where the lattice is split into two regions that are coupled to heat baths with distinct temperatures T > Tc and Tc respectively, where Tc indicates the critical temperature for phase ordering. The geometry was arranged such that the temperature boundaries are oriented perpendicular or parallel to the external particle drive and resulting net current. For perpendicular orientation of the temperature boundaries, in the hotter region, the system behaves like the (totally) asymmetric exclusion processes (TASEP), and experiences particle blockage in front of the interface to the critical region. This blockage is induced by extended particle clusters, growing logarithmically with system size, in the critical region. We observe the density profiles in both high- and low-temperature subsystems to be similar to the well-characterized coexistence and maximal-current phases in (T)ASEP models with open boundary conditions, which are respectively governed by hyperbolic and trigonometric tangent functions. Yet if the lower temperature is set to Tc, we detect marked fluctuation corrections to the mean-field density profiles, e.g., the corresponding critical KLS power-law density decay near the interfaces into the cooler region. For parallel orientation of the temperature boundaries, we have explored the changes in the dynamical behavior of the hybrid KLS model that are induced by our choice of the hopping rates across the temperature boundaries. If these hopping rates at the interfaces satisfy particle-hole symmetry, the current difference across them generates a vector flow diagram akin to an infinite flat vortex sheet. We have studied the finite-size scaling of the particle density fluctuations in both temperature regions, and observed that it is controlled by the respective temperature values. If the colder subsystem is maintained at the KLS critical temperature, while the hotter subsystem's temperature is set much higher, the interface current greatly suppresses particle exchange between the two regions. As a result of the ensuing effective subsystem decoupling, strong fluctuations persist in the critical region, whence the particle density fluctuations scale with the KLS critical exponents. However, if both temperatures are set well above the critical temperature, the particle density fluctuations scale according to the totally asymmetric exclusion process. We have also measured the entropy production rate in both subsystems; it displays intriguing algebraic decay in the critical region, while it saturates quickly at a small but non-zero level in the hotter region. The second system is a lattice gas that simulates the spread of COVID-19 epidemics using the paradigmatic stochastic Susceptible-Infectious-Recovered (SIR) model. In our effort to control the spread of the infection of a lattice, we robustly find that the intensity and spatial spread on the epidemic recurrence wave can be limited to a manageable extent provided release of these restrictions is delayed sufficiently (for a duration of at least thrice the time until the peak of the unmitigated outbreak).
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    Critical Scaling and Aging near the Flux Line Depinning Transition
    Chaturvedi, Harshwardhan; Dobramysl, Ulrich; Pleimling, Michel J.; Täuber, Uwe C. (2019-12-03)
    We utilize Langevin molecular dynamics simulations to study dynamical critical behavior of magnetic flux lines near the depinning transition in type-II superconductors subject to randomly distributed attractive point defects. We employ a coarse-grained elastic line Hamiltonian for the mutually repulsive vortices and purely relaxational kinetics. In order to infer the stationary-state critical exponents for the continuous non-equilibrium depinning transition at zero temperature T = 0 and at the critical driving current density j_c, we explore two-parameter scaling laws for the flux lines' gyration radius and mean velocity as functions of the two relevant scaling fields T and j - j_c. We also investigate critical aging scaling for the two-time height auto-correlation function in the early-time non-equilibrium relaxation regime to independently measure critical exponents. We provide numerical exponent values for the distinct universality classes of non-interacting and repulsive vortices.
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    Defending Against Trojan Attacks on Neural Network-based Language Models
    Azizi, Ahmadreza (Virginia Tech, 2020-05-15)
    Backdoor (Trojan) attacks are a major threat to the security of deep neural network (DNN) models. They are created by an attacker who adds a certain pattern to a portion of given training dataset, causing the DNN model to misclassify any inputs that contain the pattern. These infected classifiers are called Trojan models and the added pattern is referred to as the trigger. In image domain, a trigger can be a patch of pixel values added to the images and in text domain, it can be a set of words. In this thesis, we propose Trojan-Miner (T-Miner), a defense scheme against such backdoor attacks on text classification deep learning models. The goal of T-Miner is to detect whether a given classifier is a Trojan model or not. To create T-Miner , our approach is based on a sequence-to-sequence text generation model. T-Miner uses feedback from the suspicious (test) classifier to perturb input sentences such that their resulting class label is changed. These perturbations can be different for each of the inputs. T-Miner thus extracts the perturbations to determine whether they include any backdoor trigger and correspondingly flag the suspicious classifier as a Trojan model. We evaluate T-Miner on three text classification datasets: Yelp Restaurant Reviews, Twitter Hate Speech, and Rotten Tomatoes Movie Reviews. To illustrate the effectiveness of T-Miner, we evaluate it on attack models over text classifiers. Hence, we build a set of clean classifiers with no trigger in their training datasets and also using several trigger phrases, we create a set of Trojan models. Then, we compute how many of these models are correctly marked by T-Miner. We show that our system is able to detect trojan and clean models with 97% overall accuracy over 400 classifiers. Finally, we discuss the robustness of T-Miner in the case that the attacker knows T-Miner framework and wants to use this knowledge to weaken T-Miner performance. To this end, we propose four different scenarios for the attacker and report the performance of T-Miner under these new attack methods.
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    Disordered vortex matter out of equilibrium: a Langevin molecular dynamics study
    Assi, H.; Chaturvedi, H.; Dobramysl, U.; Pleimling, Michel J.; Täuber, Uwe C. (2015-11-04)
    We discuss the use of Langevin molecular dynamics in the investigation of the non-equilibrium properties of disordered vortex matter. Our special focus is set on values of system parameters that are realistic for disordered high-$T_c$ superconductors such as YBCO. Using a discretized elastic line model, we study different aspects of vortices far from thermal equilibrium. On the one hand we investigate steady-state properties of driven magnetic flux lines in a disordered environment, namely the current-voltage characteristics, the gyration radius, and the pinning time statistics. On the other hand we study the complex relaxation processes and glassy-like dynamics that emerge in type-II superconductors due to the intricate competition between the long-range vortex-vortex repulsion and flux pinning due to randomly placed point defects. To this end we consider different types of sudden perturbations: temperature, magnetic field, and external current quenches.
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    Dynamic phase transition in the three-dimensional kinetic Ising model in an oscillating field
    Park, H.; Pleimling, Michel J. (American Physical Society, 2013-03-20)
    Using numerical simulations, we investigate the properties of the dynamic phase transition that is encountered in the three-dimensional Ising model subjected to a periodically oscillating magnetic field. The values of the critical exponents are determined through finite-size scaling. Our results show that the studied nonequilibrium phase transition belongs to the universality class of the equilibrium three-dimensional Ising model.
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    Dynamical regimes of vortex flow in type-II superconductors with parallel twin boundaries
    Chaturvedi, H.; Galliher, N.; Dobramysl, U.; Pleimling, Michel J.; Täuber, Uwe C. (2017-10-11)
    We explore the dynamics of driven magnetic flux lines in disordered type-II superconductors in the presence of twin boundaries oriented parallel to the direction of the applied magnetic field, using a three-dimensional elastic line model simulated with Langevin molecular dynamics. The lines are driven perpendicular to the planes to model the effect of an electric current applied parallel to the planes and perpendicular to the magnetic field. A study of the long-time non-equilibrium steady states for several sample thicknesses L and drive strengths F_d reveals a rich collection of dynamical regimes spanning a remarkably broad depinning transition region that separates the pinned and moving-lattice states of vortex matter. We perform novel direct measurements of flux line excitations such as half-loops and double kinks, and quantitatively analyze their excitation occurrence distributions to characterize the topologically rich flux flow profile and generate a boundary curve separating the regions of linear and non-linear transport in the (L, F_d) plane. Rich static and dynamic visualizations of the vortex matter in different drive regimes supplement the quantitative results obtained.
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    Dynamics of Driven Vortices in Disordered Type-II Superconductors
    Chaturvedi, Harshwardhan Nandlal (Virginia Tech, 2019-01-22)
    We numerically investigate the dynamical properties of driven magnetic flux vortices in disordered type-II superconductors for a variety of temperatures, types of disorder and sample thicknesses. We do so with the aid of Langevin molecular dynamics simulations of a coarsegrained elastic line model of flux vortices in the extreme London limit. Some original findings of this doctoral work include the discovery that flux vortices driven through random point disorder show simple aging following drive quenches from the moving lattice state to both the pinned glassy state (non-universal aging) and near the critical depinning region (universal aging); estimations of experimentally consistent critical scaling exponents for the continuous depinning phase transition of vortices in three dimensions; and an estimation of the boundary curve separating regions of linear and non-linear electrical transport for flux lines driven through planar defects via novel direct measurements of vortex excitations.
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    Effect of the Magnus force on skyrmion relaxation dynamics
    Brown, Barton L.; Täuber, Uwe C.; Pleimling, Michel J. (American Physical Society, 2018-01-10)
    We perform systematic Langevin molecular dynamics simulations of interacting skyrmions in thin films. The interplay between Magnus force, repulsive skyrmion-skyrmion interaction and thermal noise yields different regimes during non-equilibrium relaxation. In the noise-dominated regime the Magnus force enhances the disordering effects of the thermal noise. In the Magnus-force-dominated regime, the Magnus force cooperates with the skyrmion-skyrmion interaction to yield a dynamic regime with slow decaying correlations. These two regimes are characterized by different values of the aging exponent. In general, the Magnus force accelerates the approach to the steady state.
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    Entrainment of Bacterial Synthetic Oscillators using Proteolytic Queueing and Aperiodic Signaling
    Hochendoner, Philip Louis (Virginia Tech, 2015-12-12)
    The bulk of this thesis considers how biological rhythms (oscillators) can be made to synchronize their rhythms by virtue of coupling to an external signal. Such externally controlled synchronization, known as entrainment, is explored using a synthetic biology approach in E.~coli, where I have used rationally designed gene circuits as an experimental model. Two novel modes of entrainment are explored: entrainment by competition between components for degradation, and entrainment by a noisy (aperiodic) stimulus. Both of these modes of entrainment can be shown to strongly synchronize ensembles of synthetic gene oscillators, and thus, these modes of entrainment may be important to understand the appearance of synchrony in natural systems. In addition to the study of entrainment, this thesis contains a general background of relevant material, contributions to the biophysics of multisite proteases, and updated protocols for experimental procedures in microfluidics and microscopy.
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    Entropy production in nonequilibrium steady states: A different approach and an exactly solvable canonical model
    Ben-Avraham, D.; Dorosz, S.; Pleimling, Michel J. (American Physical Society, 2011-07-12)
    We discuss entropy production in nonequilibrium steady states by focusing on paths obtained by sampling at regular (small) intervals, instead of sampling on each change of the system's state. This allows us to directly study entropy production in systems with microscopic irreversibility. The two sampling methods are equivalent otherwise, and the fluctuation theorem also holds for the different paths. We focus on a fully irreversible three-state loop, as a canonical model of microscopic irreversibility, finding its entropy distribution, rate of entropy production, and large deviation function in closed analytical form, and showing that the observed kink in the large deviation function arises solely from microscopic irreversibility.
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    Examining the Dynamics of Biologically Inspired Systems Far From Equilibrium
    Carroll, Jacob Alexander (Virginia Tech, 2019-04-23)
    Non-equilibrium systems have no set method of analysis, and a wide array of dynamics can be present in such systems. In this work we present three very different non-equilibrium models, inspired by biological systems and phenomena, that we analyze through computational means to showcase both the range of dynamics encompassed by these systems, as well as various techniques used to analyze them. The first system we model is a surface plasmon resonance (SPR) cell, a device used to determine the binding rates between various species of chemicals. We simulate the SPR cell and compare these computational results with a mean-field approximation, and find that such a simplification fails for a wide range of reaction rates that have been observed between different species of chemicals. Specifically, the mean-field approximation places limits on the possible resolution of the measured rates, and such an analysis fails to capture very fast dynamics between chemicals. The second system we analyzed is an avalanching neural network that models cascading neural activity seen in monkeys, rats, and humans. We used a model devised by Lombardi, Herrmann, de Arcangelis et al. to simulate this system and characterized its behavior as the fraction of inhibitory neurons was changed. At low fractions of inhibitory neurons we observed epileptic-like behavior in the system, as well as extended tails in the avalanche strength and duration distributions, which dominate the system in this regime. We also observed how the connectivity of these networks evolved under the effects of different inhibitory fractions, and found the high fractions of inhibitory neurons cause networks to evolve more sparsely, while networks with low fractions maintain their initial connectivity. We demonstrated two strategies to control the extreme avalanches present at low inhibitory fractions through either the random or targeted disabling of neurons. The final system we present is a sparsely encoding convolutional neural network, a computational system inspired by the human visual cortex that has been engineered to reconstruct images inputted into the network using a series of "patterns" learned from previous images as basis elements. The network attempts to do so "sparsely," so that the fewest number of neurons are used. Such systems are often used for denoising tasks, where noisy or fragmented images are reconstructed. We observed a minimum in this denoising error as the fraction of active neurons was varied, and observed the depth and location of this minimum to obey finite-size scaling laws that suggest the system is undergoing a second-order phase transition. We can use these finite-size scaling relations to further optimize this system by tuning it to the critical point for any given system size.
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    Feedback control of surface roughness in a one-dimensional KPZ growth process
    Priyanka; Täuber, Uwe C.; Pleimling, Michel J. (2019-12-11)
    Control of generically scale-invariant systems, i.e., targeting specific cooperative features in non-linear stochastic interacting systems with many degrees of freedom subject to strong fluctuations and correlations that are characterized by power laws, remains an important open problem. We study the control of surface roughness during a growth process described by the Kardar--Parisi--Zhang (KPZ) equation in $(1+1)$ dimensions. We achieve the saturation of the mean surface roughness to a prescribed value using non-linear feedback control. Numerical integration is performed by means of the pseudospectral method, and the results are used to investigate the coupling effects of controlled (linear) and uncontrolled (non-linear) KPZ dynamics during the control process. While the intermediate time kinetics is governed by KPZ scaling, at later times a linear regime prevails, namely the relaxation towards the desired surface roughness. The temporal crossover region between these two distinct regimes displays intriguing scaling behavior that is characterized by non-trivial exponents and involves the number of controlled Fourier modes. Due to the control, the height probability distribution becomes negatively skewed, which affects the value of the saturation width.
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    Field-theory approaches to nonequilibrium dynamics
    Täuber, Uwe C. (Springer-Verlag Berlin, 2007-01-01)
    It is explained how field-theoretic methods and the dynamic renormalisation group (RG) can be applied to study the universal scaling properties of systems that either undergo a continuous phase transition or display generic scale invariance, both near and far from thermal equilibrium. Part 1 introduces the response functional field theory representation of (nonlinear) Langevin equations. The RG is employed to compute the scaling exponents for several universality classes governing the critical dynamics near second-order phase transitions in equilibrium. The effects of reversible mode-coupling terms, quenching from random initial conditions to the critical point, and violating the detailed balance constraints are briefly discussed. It is shown how the same formalism can be applied to nonequilibrium systems such as driven diffusive lattice gases. Part 2 describes how the master equation for stochastic particle reaction processes can be mapped onto a field theory action. The RG is then used to analyse simple diffusion-limited annihilation reactions as well as generic continuous transitions from active to inactive, absorbing states, which are characterised by the power laws of (critical) directed percolation. Certain other important universality classes are mentioned, and some open issues are listed.
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    Fluctuation Relations for Stochastic Systems far from Equilibrium
    Dorosz, Sven (Virginia Tech, 2010-03-26)
    Fluctuations are of great importance in systems of small length and energy scales. Measuring the pulling of single molecules or the stationary fiow of mesospheres dragged through a viscous media enables the direct analysis of work and entropy distributions. These probability distributions are the result of a large number of repetitions of the same experiment. Due to the small scale of these experiments, the outcome can vary significantly from one realization to the next. Strong theoretical predictions exist, collectively called Fluctuation Theorems, that restrict the shape of these distributions due to an underlying time reversal symmetry of the microscopic dynamics. Fluctuation Theorems are the strongest existing statements on the entropy production of systems that are out of equilibrium. Being the most important ingredient for the Fluctuation Theorems, the probability distribution of the entropy change is itself of great interest. Using numerically exact methods we characterize entropy distributions for various stochastic reaction-diffusion systems that present different properties in their underlying dynamics. We investigate these systems in their steady states and in cases where time dependent forces act on them. This study allows us to clarify the connection between the microscopic rules and the resulting entropy production. The present work also adds to the discussion of the steady state properties of stationary probabilities and discusses a non-equilibrium current amplitude that allows us to quantify the distance from equilibrium. The presented results are part of a greater endeavor to find common rules that will eventually lead to a general understanding of non-equilibrium systems.
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    Flux line relaxation kinetics following current quenches in disordered type-II superconductors
    Chaturvedi, H.; Assi, H.; Dobramysl, U.; Pleimling, Michel J.; Täuber, Uwe C. (2016-06)
    We investigate the relaxation dynamics of magnetic vortex lines in type-II superconductors following rapid changes of the external driving current by means of an elastic line model simulated with Langevin molecular dynamics. A system of flux vortices in a sample with randomly distributed point-like defects is subjected to an external current of appropriate strength for a sufficient period of time so as to be in a moving non-equilibrium steady state. The current is then instantaneously lowered to a value that pertains to either the moving or pinned regime. The ensuing relaxation of the flux lines is studied via one-time observables such as their mean velocity and radius of gyration. We have in addition measured the two-time flux line height autocorrelation function to investigate dynamical scaling and aging behavior in the system, which in particular emerge after quenches into the glassy pinned state.
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    Heavy Tails and Anomalous Diffusion in Human Online Dynamics
    Wang, Xiangwen (Virginia Tech, 2019-02-28)
    In this dissertation, I extend the analysis of human dynamics to human movements in online activities. My work starts with a discussion of the human information foraging process based on three large collections of empirical search click-through logs collected in different time periods. With the analogy of viewing the click-through on search engine result pages as a random walk, a variety of quantities like the distributions of step length and waiting time as well as mean-squared displacements, correlations and entropies are discussed. Notable differences between the different logs reveal an increased efficiency of the search engines, which is found to be related to the vanishing of the heavy-tailed characteristics of step lengths in newer logs as well as the switch from superdiffusion to normal diffusion in the diffusive processes of the random walks. In the language of foraging, the newer logs indicate that online searches overwhelmingly yield local searches, whereas for the older logs the foraging processes are a combination of local searches and relocation phases that are power-law distributed. The investigation highlights the presence of intermittent search processes in online searches, where phases of local explorations are separated by power-law distributed relocation jumps. In the second part of this dissertation I focus on an in-depth analysis of online gambling behaviors. For this analysis the collected empirical gambling logs reveal the wide existence of heavy-tailed statistics in various quantities in different online gambling games. For example, when players are allowed to choose arbitrary bet values, the bet values present log-normal distributions, meanwhile if they are restricted to use items as wagers, the distribution becomes truncated power laws. Under the analogy of viewing the net change of income of each player as a random walk, the mean-squared displacement and first-passage time distribution of these net income random walks both exhibit anomalous diffusion. In particular, in an online lottery game the mean-squared displacement presents a crossover from a superdiffusive to a normal diffusive regime, which is reproduced using simulations and explained analytically. This investigation also reveals the scaling characteristics and probability reweighting in risk attitude of online gamblers, which may help to interpret behaviors in economic systems. This work was supported by the US National Science Foundation through grants DMR-1205309 and DMR-1606814.