Using the large-deviation formalism, we study the statistics of current fluctuations in a diffusive nonequilibrium quantum spin chain. The boundary-driven $XX$ chain with dephasing consists of a coherent bulk hopping and a local dissipative dephasing. We analytically calculate the exact expression for the second current moment in a system of any length and then numerically demonstrate that in the thermodynamic limit, higher-order cumulants and the large-deviation function can be calculated using the additivity principle or macroscopic hydrodynamic theory. This shows that the additivity principle can also hold in systems that are not purely stochastic, and can in particular be valid in quantum systems. We also show that in large systems, the current fluctuations are the same as in the classical symmetric simple exclusion process.

Magnetic particles are widely used in biological research and bioanalytical applications. As the corresponding tools are progressively being miniaturized and integrated, the understanding of particle dynamics and the control of particles down to the level of single particles become important. Here, we describe a numerical model to simulate the dynamic behavior of ensembles of magnetic particles, taking account of magnetic interparticle interactions, interactions with the liquid medium and solid surfaces, as well as thermal diffusive motion of the particles. The model is verified using experimental data of magnetic field-induced disaggregation of magnetic particle clusters near a physical surface, wherein the magnetic field properties, particle size, cluster size, and cluster geometry were varied. Furthermore, the model clarifies how the cluster configuration, cluster alignment, magnitude of the field gradient, and the field repetition rate play a role in the particle disaggregation process. The simulation model will be very useful for further in silico studies on magnetic particle dynamics in biotechnological tools.

We experimentally show that the neuron functions as a precise time integrator, where the accumulated changes in neuronal response latencies, under complex and random stimulation patterns, are solely a function of a global quantity, the average time lag between stimulations. In contrast, momentary leaps in the neuronal response latency follow trends of consecutive stimulations, indicating ultrafast neuronal plasticity. On a circuit level, this ultrafast neuronal plasticity phenomenon implements error-correction mechanisms and fast detectors for misplaced stimulations. Additionally, at moderate (high) stimulation rates this phenomenon destabilizes (stabilizes) a periodic neuronal activity disrupted by misplaced stimulations.

An interface treatment for conjugate heat and mass transfer in the lattice Boltzmann equation method is proposed based on our previously proposed second-order accurate Dirichlet and Neumann boundary schemes. The continuity of temperature (concentration) and its flux at the interface for heat (mass) transfer is intrinsically satisfied without iterative computations, and the interfacial temperature (concentration) and their fluxes are conveniently obtained from the microscopic distribution functions without finite-difference calculations. The present treatment takes into account the local geometry of the interface so that it can be directly applied to curved interface problems such as conjugate heat and mass transfer in porous media. For straight interfaces or curved interfaces with no tangential gradient, the coupling between the interfacial fluxes along the discrete lattice velocity directions is eliminated and thus the proposed interface schemes can be greatly simplified. Several numerical tests are conducted to verify the applicability and accuracy of the proposed conjugate interface treatment, including (i) steady convection-diffusion in a channel containing two different fluids, (ii) unsteady convection-diffusion in the channel, (iii) steady heat conduction inside a circular domain with two different solid materials, and (iv) unsteady mass transfer from a spherical droplet in an extensional creeping flow. The accuracy and order of convergence of the simulated interior temperature (concentration) field, the interfacial temperature (concentration), and heat (mass) flux are examined in detail and compared with those obtained from the “half-lattice division” treatment in the literature. The present analysis and numerical results show that the half-lattice division scheme is second-order accurate only when the interface is fixed at the center of the lattice links, while the present treatment preserves second-order accuracy for arbitrary link fractions. For curved interfaces, the present treatment yields second-order accurate interior and interfacial temperatures (concentrations) and first-order accurate interfacial heat (mass) flux. An increase of order of convergence by one degree is obtained for each of these three quantities compared with the half-lattice division scheme. The surface-averaged Sherwood numbers computed in test (iv) agree well with published results.

We investigate the microresponse of the quasi-two-dimensional dusty plasma liquid around freezing to the shear force from a laser beam through the center of the liquid cluster. It is found that the cold liquid can be viewed as a patchwork of crystalline ordered domains (CODs) which are solidlike but can be cracked and rearranged by weak thermal agitation and external stress, through COD rotations and drifting. Under weak external stress comparable to thermal agitation, the laser zone is not the preferred region mastering cracking initiation. CODs in the laser zone can either break locally, or sustain and propagate the stress to remote regions for cracking, in the form of intermittent bursts. The COD rotation and drifting induced by the persistent torques and momentum from the stress causes the formation of the center shear band with a higher longitudinal speed. Increasing stress can enhance cracking initiation around the shear zone and then spread to other remote regions. It deteriorates the local structural order and causes strong shear banding dominated by longitudinal cooperative hopping.

We consider two random walkers starting at the same time $t=0$ from different points in space separated by a given distance $R$. We compute the average volume of the space visited by both walkers up to time $t$ as a function of $R$ and $t$ and dimensionality of space $d$. For $d<4$, this volume, after proper renormalization, is shown to be expressed through a scaling function of a single variable $R/\sqrt{t}$. We provide general integral formulas for scaling functions for arbitrary dimensionality $d<4$. In contrast, we show that no scaling function exists for higher dimensionalities $d\ge 4$.

Resonant activation is an effect of a noise-induced escape over a modulated potential barrier. The modulation of an energy landscape facilitates the escape kinetics and makes it optimal as measured by the mean first-passage time. A canonical example of resonant activation is a Brownian particle moving in a time-dependent potential under action of Gaussian white noise. Resonant activation is observed not only in typical Markovian-Gaussian systems but also in far-from-equilibrium and far-from-Markovianity regimes. We demonstrate that using an alternative to the mean first-passage time, robust measures of resonant activation, the signature of this effect can be observed in general continuous-time random walks in modulated potentials, even in situations when the mean first-passage time diverges.

In spin-glass systems, frustration can be adjusted continuously and considerably, without changing the antiferromagnetic bond probability $p$, by using locally correlated quenched randomness, as we demonstrate here on hypercubic lattices and hierarchical lattices. Such overfrustrated and underfrustrated Ising systems on hierarchical lattices in $d=3$ and 2 are studied. With the removal of just 51% of frustration, a spin-glass phase occurs in $d=2$. With the addition of just 33% frustration, the spin-glass phase disappears in $d=3$. Sequences of 18 different phase diagrams for different levels of frustration are calculated in both dimensions. In general, frustration lowers the spin-glass ordering temperature. At low temperatures, increased frustration favors the spin-glass phase (before it disappears) over the ferromagnetic phase and symmetrically the antiferromagnetic phase. When any amount, including infinitesimal, frustration is introduced, the chaotic rescaling of local interactions occurs in the spin-glass phase. Chaos increases with increasing frustration, as can be seen from the increased positive value of the calculated Lyapunov exponent $\lambda$, starting from $\lambda =0$ when frustration is absent. The calculated runaway exponent $y_R$ of the renormalization-group flows decreases with increasing frustration to $y_R=0$ when the spin-glass phase disappears. From our calculations of entropy and specific-heat curves in $d=3$, it is shown that frustration lowers in temperature the onset of both long- and short-range order in spin-glass phases, but is more effective on the former. From calculations of the entropy as a function of antiferromagnetic bond concentration $p$, it is shown that the ground-state and low-temperature entropy already mostly sets in within the ferromagnetic and antiferromagnetic phases, before the spin-glass phase is reached.

In this paper we describe a viscoelastic type of phase separation in a simulated binary fluid with a sticky and an inert component, without any external gradients. Phase segregation under simple shear occurs due to transient network formation of the sticky component, expelling the inert particles from the network. When model parameters are adjusted to reduce network formation and rearrangement, the segregation effect is significantly smaller or absent. The behavior is independent of shear rate; segregation increases mainly with shear strain. The model is applied to wheat dough. Recent experiments have shown that prolonged shear flow of wheat dough can even give macroscopic segregation.

Generating and controlling chiral symmetry breaking and enantiomeric excess is not only interesting from a fundamental perspective but can also lead to novel functional materials. In this work, we show how the dark conglomerate (DC) liquid crystalline phase characterized by macroscopic chiral domains offers such a possibility if formed under an electric field. In addition the chiral domains are electro-optically switchable. The chiral segregation in the DC phase can be tuned by using dc or ac fields at different frequencies. Consequently, the enantioselectivity, dielectric parameters and switching polarization in the DC phase become tunable. Another interesting aspect is that the nucleating conglomerate domains formed under ac fields exhibit frequency dependent shape transitions which have a striking resemblance to domain shape changes observed in two-dimensional monolayers. This can therefore be used as a model experimental system to get a physical insight into the effects of chiral and electrostatic interactions, under external fields, on domain growth and interface structures. The domain shape transitions can also be used to investigate the role of growth morphology in coarsening and scaling hypotheses. From a technological point of view this opens up the possibility of obtaining chiral thin films with preferential sense of chirality which can be useful in chiroptical and nonlinear optical applications.

In this work we investigate the development of stable dynamical structures along interfaces separating domains belonging to enemy partnerships in the context of cyclic predator-prey models with an even number of species $N\ge 8$. We use both stochastic and field theory simulations in one and two spatial dimensions, as well as analytical arguments, to describe the association at the interfaces of mutually neutral individuals belonging to enemy partnerships and to probe their role in the development of the dynamical structures at the interfaces. We identify an interesting behavior associated with the symmetric or asymmetric evolution of the interface profiles depending on whether $N/2$ is odd or even, respectively. We also show that the macroscopic evolution of the interface network is not very sensitive to the internal structure of the interfaces. Although this work focuses on cyclic predator-prey models with an even number of species, we argue that the results are expected to be quite generic in the context of spatial stochastic May-Leonard models.

The cytoskeleton is a network of crosslinked, semiflexible filaments, and it has been suggested that it has properties of a glassy state. Here we employ optical-trap-based microrheology to apply forces to a model cytoskeleton and measure the high-bandwidth response at an anterior point. Simulating the highly nonlinear and anisotropic stress-strain propagation assuming affinity, we found that theoretical predictions for the quasistatic response of semiflexible polymers are only realized at high frequencies inaccessible to conventional rheometers. We give a theoretical basis for determining the frequency when both affinity and quasistaticity are valid, and we discuss with experimental evidence that the relaxations at lower frequencies can be characterized by the experimentally obtained nonaffinity parameter.

We study the robustness properties of multiplex networks consisting of multiple layers of distinct types of links, focusing on the role of correlations between degrees of a node in different layers. We use generating function formalism to address various notions of the network robustness relevant to multiplex networks, such as the resilience of ordinary and mutual connectivity under random or targeted node removals, as well as the biconnectivity. We found that correlated coupling can affect the structural robustness of multiplex networks in diverse fashion. For example, for maximally correlated duplex networks, all pairs of nodes in the giant component are connected via at least two independent paths and network structure is highly resilient to random failure. In contrast, anticorrelated duplex networks are on one hand robust against targeted attack on high-degree nodes, but on the other hand they can be vulnerable to random failure.

Bose-Einstein condensates with time varying two- and three-body interatomic interactions, confined in a linear potential and exchanging atoms with the thermal cloud are investigated. Using the extended tanh-function method with an auxiliary equation, i.e., the Lenard equation, many exact solutions describing the dynamics of matter-wave condensates are derived. An important issue is the time management of the cubic and the quintic nonlinearities by tuning the rate of exchange of atoms between the condensate and the thermal background. In addition, adjusting the strength of the linear potential, the rate of exchange of atoms, and many other free parameters allow one to control many features of the condensate such as its height, width, position, velocity, acceleration, and its direction, respectively. Full numerical solutions corroborate the analytical predictions.

This study extends previous analytical solutions of concentration polarization occurring solely in the depleted region, to the more realistic geometry consisting of a three-dimensional (3D) heterogeneous ion-permselective medium connecting two opposite microchambers (i.e., a three-layer system). Under the local electroneutrality approximation, the separation of variable methods is used to derive an analytical solution of the electrodiffusive problem for the two opposing asymmetric microchambers. The assumption of an ideal permselective medium allows for the analytic calculation of the 3D concentration and electric potential distributions as well as a current-voltage relation. It is shown that any asymmetry in the microchamber geometries will result in current rectification. Moreover, it is demonstrated that for non-negligible microchamber resistances, the conductance does not exhibit the expected saturation at low concentrations but instead shows a continuous decrease. The results are intended to facilitate a more direct comparison between theory and experiments, as now the voltage drop is across a realistic 3D and three-layer system.

The mobility of a charged projectile in a strongly coupled dusty plasma is simulated. A net force $F$, opposed by a combination of collisional scattering and gas friction, causes projectiles to drift at a mobility-limited velocity $u_p$. The mobility ${\mu }_p=u_p/F$ of the projectile's motion is obtained. Two regimes depending on $F$ are identified. In the high-force regime, ${\mu }_p\propto F^{0.23}$, and the scattering cross section ${\sigma }_s$ diminishes as $u_p^{-6/5}$. Results for ${\sigma }_s$ are compared with those for a weakly coupled plasma and for two-body collisions in a Yukawa potential. The simulation parameters are based on microgravity plasma experiments.

Reaction fronts evolving in a porous medium exhibit a rich dynamical behavior. In the presence of an adverse flow, experiments show that the front slows down and eventually gets pinned, displaying a particular sawtooth shape. Extensive numerical simulations of the hydrodynamic equations confirm the experimental observations. Here we propose a stylized model, predicting two possible outcomes of the experiments for large adverse flow: either the front develops a sawtooth shape or it acquires a complicated structure with islands and overhangs. A simple criterion allows one to distinguish between the two scenarios and its validity is reproduced by direct hydrodynamical simulations. Our model gives a better understanding of the transition and is relevant in a variety of domains, when the pinning regime is strong and only relies on a small number of sites.

The laws of thermodynamics apply equally well to quantum systems as to classical systems, and because of this, quantum effects do not change the fundamental thermodynamic efficiency of isothermal refrigerators or engines. We show that, despite this fact, quantum mechanics permits measurement-based feedback control protocols that are more thermodynamically efficient than their classical counterparts. As part of our analysis, we perform a detailed accounting of the thermodynamics of unitary feedback control and elucidate the sources of inefficiency in measurement-based and coherent feedback.

We consider two important time scales—the Markov and cryptic orders—that monitor how an observer synchronizes to a finitary stochastic process. We show how to compute these orders exactly and that they are most efficiently calculated from the $\epsilon$-machine, a process's minimal unifilar model. Surprisingly, though the Markov order is a basic concept from stochastic process theory, it is not a probabilistic property of a process. Rather, it is a topological property and, moreover, it is not computable from any finite-state model other than the $\epsilon$-machine. Via an exhaustive survey, we close by demonstrating that infinite Markov and infinite cryptic orders are a dominant feature in the space of finite-memory processes. We draw out the roles played in statistical mechanical spin systems by these two complementary length scales.