Many studies of quantum-size heat engines assume that the dynamics of an internal system is unitary and that the extracted work is equal to the energy loss of the internal system. Both assumptions, however, should be under scrutiny. In the present paper, we analyze quantum-scale heat engines, employing the measurement-based formulation of the work extraction recently introduced by Hayashi and Tajima [M. Hayashi and H. Tajima, arXiv:1504.06150]. We first demonstrate the inappropriateness of the unitary time evolution of the internal system (namely, the first assumption above) using a simple two-level system; we show that the variance of the energy transferred to an external system diverges when the dynamics of the internal system is approximated to a unitary time evolution. Second, we derive the quantum Jarzynski equality based on the formulation of Hayashi and Tajima as a relation for the work measured by an external macroscopic apparatus. The right-hand side of the equality reduces to unity for “natural” cyclic processes but fluctuates wildly for noncyclic ones, exceeding unity often. This fluctuation should be detectable in experiments and provide evidence for the present formulation.

We formulate a theory for the collective phase reduction of globally coupled noisy dynamical elements exhibiting macroscopic rhythms. We first transform the Langevin-type equation that represents a group of globally coupled noisy dynamical elements into the corresponding nonlinear Fokker-Planck equation and then develop the phase reduction method for limit-cycle solutions to the nonlinear Fokker-Planck equation. The theory enables us to describe the collective dynamics of a group of globally coupled noisy dynamical elements by a single degree of freedom called the collective phase. As long as the group collectively exhibits macroscopic rhythms, the theory is applicable even when the coupling and noise are strong; it is also independent of the assumption that each element of the group is a self-sustained oscillator. We also provide a simple and accurate numerical algorithm for the collective phase description method and numerically illustrate the theory using a group of globally coupled noisy FitzHugh-Nagumo elements.

We consider a dipolar Bose-Einstein condensate trapped in an array of two-well systems with an arbitrary orientation of the dipoles relative to the system's axis. The system can be built as a chain of local traps sliced into two parallel lattices by a repelling laser sheet. It is modeled by a pair of coupled discrete Gross-Pitaevskii equations, with dipole-dipole self-interactions and cross interactions. When the dipoles are not polarized perpendicular or parallel to the lattice, the cross interaction is asymmetric, replacing the familiar symmetric two-component discrete solitons by two new species of cross-symmetric ones, viz., on-site- and off-site-centered solitons, which are strongly affected by the orientation of the dipoles and separation between the parallel lattices. A very narrow region of intermediate asymmetric discrete solitons is found at the boundary between the on- and off-site families. Two different types of solitons in the $\mathcal{PT}$-symmetric version of the system are constructed too, and stability areas are identified for them.

Transfer entropy has been used to quantify the directed flow of information between source and target variables in many complex systems. While transfer entropy was originally formulated in discrete time, in this paper we provide a framework for considering transfer entropy in continuous time systems, based on Radon-Nikodym derivatives between measures of complete path realizations. To describe the information dynamics of individual path realizations, we introduce the pathwise transfer entropy, the expectation of which is the transfer entropy accumulated over a finite time interval. We demonstrate that this formalism permits an instantaneous transfer entropy rate. These properties are analogous to the behavior of physical quantities defined along paths such as work and heat. We use this approach to produce an explicit form for the transfer entropy for pure jump processes, and highlight the simplified form in the specific case of point processes (frequently used in neuroscience to model neural spike trains). Finally, we present two synthetic spiking neuron model examples to exhibit the pertinent features of our formalism, namely, that the information flow for point processes consists of discontinuous jump contributions (at spikes in the target) interrupting a continuously varying contribution (relating to waiting times between target spikes). Numerical schemes based on our formalism promise significant benefits over existing strategies based on discrete time formalisms.

Inspired by an old and almost in oblivion urban plan, we report the behavior of the Biham-Middleton-Levine (BML) model—a paradigm for studying phase transitions of traffic flow—on a hypothetical city with a perfect honeycomb street network. In contrast with the original BML model on a square lattice, the same model on a honeycomb does not show any anisotropy or intermediate states, but a single continuous phase transition between free and totally congested flow, a transition that can be completely characterized by the tools of classical percolation. Although the transition occurs at a lower density than for the conventional BML, simple modifications, like randomly stopping the cars with a very small probability or increasing the traffic light periods, drives the model to perform better on honeycomb lattices. As traffic lights and disordered perturbations are inherent in real traffic, these results question the actual role of the square gridlike designs and suggest the honeycomb topology as an interesting alternative for urban planning in real cities.

We outline a statistical mechanics of the triple gas-solid-liquid contact line on a rough plane. The analysis regards the neighborhood of the line as a solid dotted with cavities. It adopts the simplest mean-field statistical mechanics, in which each cavity is either full or empty, while being connected to near neighbors by thin necks. The theory predicts equilibrium angles for advance and recession in terms of the Young contact angle and the joint statistical distribution of two quantifiable geometrical parameters representing specific neck cross-section and specific cavity opening. It attributes contact angle hysteresis to first-order phase transitions among adjacent cavities, as they collectively imbibe or reject liquid. It also calculates the potential energy barriers that hysteresis erects against overcoming contact line pinning. By determining whether the phase transitions can release latent energy, this ab initio analysis distinguishes six regimes, including two metastable recession states. We compare predictions with data for superhydrophobia on microscopic rods; for hysteresis in the “Wenzel state”; and for variations of the advancing contact angle with surface energies of the liquid.

Avalanchelike behavior reflected in power-law statistics is a ubiquitous property of extended systems addressed in a number of generic models. The paper presents an experimental investigation of the effect of thresholding on the statistics of durations and waiting times between avalanches using acoustic emission accompanying unstable plastic deformation. It is found that durations of acoustic events obey power-law statistical distributions robust against thresholding. The quiescent time distributions follow the Poisson law for low threshold values. Both these results corroborate the hypothesis that plastic deformation is akin to the phenomena associated with self-organized criticality (SOC), often advanced on the basis of power-law amplitude statistics. Increasing the threshold height enforces deviation from the Poisson distributions toward apparent power-law behavior. Such a thresholding effect may hinder the experimental determination of SOC-like dynamics because of the inevitable noise.

The time evolution governed by the Boltzmann kinetic equation is compatible with mechanics and thermodynamics. The former compatibility is mathematically expressed in the Hamiltonian and Godunov structures, the latter in the structure of gradient dynamics guaranteeing the growth of entropy and consequently the approach to equilibrium. We carry all three structures to the Grad reformulation of the Boltzmann equation (to the Grad hierarchy). First, we recognize the structures in the infinite Grad hierarchy and then in several examples of finite hierarchies representing extended hydrodynamic equations. In the context of Grad's hierarchies, we also investigate relations between Hamiltonian and Godunov structures.

Neutral toroidal droplets can break via the surface-tension-driven Rayleigh-Plateau instability. They can additionally exhibit a shrinking instability, which is also driven by surface tension, whereby the handle progressively disappears. We find that charging a toroidal droplet can qualitatively change the behavior and cause the droplet to expand. We successfully model the transition from shrinking to expanding, considering the pressure balance across the interface of the torus. However, despite the change in behavior, charged toroidal droplets end up breaking into spherical droplets. We quantify how the wavelength of the fastest unstable mode associated to this breakup depends on the applied voltage and compare the results with theoretical expectations for charged cylindrical jets.

The present study investigates the role of thermal nonequilibrium on natural convection in a fluid-saturated porous medium heated from below. We conduct high-resolution direct numerical simulation at the pore scale in a two-dimensional regular porous structure by means of the thermal lattice-Boltzmann method (LBM). We perform a combination of linear stability analysis of continuum-scale heat transfer models, and pore-scale and continuum-scale simulations to study the role of thermal conductivity contrasts among phases on natural convection. The comparison of pore-scale lattice-Boltzmann simulations with linear stability analysis reveals that traditional continuum-scale models fail to capture the correct onset of convection, convection mode, and heat transfer when the thermal conductivity of the solid obstacles does not match that of the fluid.

Channel flow of an incompressible fluid at Reynolds numbers above 2400 possesses a number of different spatially localized solutions that approach laminar flow far upstream and downstream. We use one such relative time-periodic solution, which corresponds to a spatially localized version of a Tollmien-Schlichting wave, to illustrate how the upstream and downstream asymptotics can be computed analytically. In particular, we show that for these spanwise uniform states the asymptotics predict the exponential localization that has been observed for numerically computed solutions of several canonical shear flows but never properly understood theoretically.

We report on the detection of the time-dependent B-field amplitude and topology in a laser-driven solenoid. The B-field inferred from both proton deflectometry and Faraday rotation ramps up linearly in time reaching 210 $\pm$ 35 T at the end of a 0.75-ns laser drive with 1 TW at 351 nm. A lumped-element circuit model agrees well with the linear rise and suggests that the blow-off plasma screens the field between the plates leading to an increased plate capacitance that converts the laser-generated hot-electron current into a voltage source that drives current through the solenoid. ALE3D modeling shows that target disassembly and current diffusion may limit the B-field increase for longer laser drive. Scaling of these experimental results to a National Ignition Facility (NIF) hohlraum target size ($\sim 0.2{\mathrm{cm}}^3$) indicates that it is possible to achieve several tens of Tesla.

In this work, we present an alternative derivation of the Navier-Stokes equations from Bhatnagar-Gross-Krook models of the lattice Boltzmann method with diffusive scaling. This derivation is based on the Maxwell iteration and can expose certain important features of the lattice Boltzmann solutions. Moreover, it will be seen to be much more straightforward and logically clearer than the existing approaches including the Chapman-Enskog expansion.

Measurements of hydrodynamic instability growth for a high-density carbon ablator for indirectly driven inertial confinement fusion implosions on the National Ignition Facility are reported. We observe significant unexpected features on the capsule surface created by shadows of the capsule fill tube, as illuminated by laser-irradiated x-ray spots on the hohlraum wall. These shadows increase the spatial size and shape of the fill tube perturbation in a way that can significantly degrade performance in layered implosions compared to previous expectations. The measurements were performed at a convergence ratio of ∼2 using in-flight x-ray radiography. The initial seed due to shadow imprint is estimated to be equivalent to ∼50–100 nm of solid ablator material. This discovery has prompted the need for a mitigation strategy for future inertial confinement fusion designs as proposed here.

We study the thermal rectification efficiency, i.e., quantification of asymmetric heat flow, of a one-dimensional mass-graded anharmonic oscillator Fermi-Pasta-Ulam lattice both with nearest-neighbor (NN) and next-nearest-neighbor (NNN) interactions. The system presents a maximum rectification efficiency for a very precise value of the parameter that controls the coupling strength of the NNN interactions, which also optimizes the rectification figure when its dependence on mass asymmetry and temperature differences is considered. The origin of the enhanced rectification is the asymmetric local heat flow response as the heat reservoirs are swapped when a finely tuned NNN contribution is taken into account. A simple theoretical analysis gives an estimate of the optimal NNN coupling in excellent agreement with our simulation results.

The influence of an external magnetic field on the static shear strain and the effective shear modulus of a magnetoactive elastomer (MAE) is studied theoretically in the framework of a recently introduced approach to the single-particle magnetostriction mechanism [V. M. Kalita et al., Phys. Rev. E 93, 062503 (2016)]. The planar problem of magnetostriction in an MAE with magnetically soft inclusions in the form of a thin disk (platelet) having the magnetic anisotropy in the plane of this disk is solved analytically. An external magnetic field acts with torques on magnetic filler particles, creates mechanical stresses in the vicinity of inclusions, induces shear strain, and increases the effective shear modulus of these composite materials. It is shown that the largest effect of the magnetic field on the effective shear modulus should be expected in MAEs with soft elastomer matrices, where the shear modulus of the matrix is less than the magnetic anisotropy constant of inclusions. It is derived that the effective shear modulus is nonlinearly dependent on the external magnetic field and approaches the saturation value in magnetic fields exceeding the field of particle anisotropy. It is shown that model calculations of the effective shear modulus correspond to a phenomenological definition of effective elastic moduli and magnetoelastic coupling constants. The obtained theoretical results compare well with known experimental data. Determination of effective elastic coefficients in MAEs and their dependence on magnetic field is discussed. The concentration dependence of the effective shear modulus at higher filler concentrations has been estimated using the method of Padé approximants, which predicts that both the absolute and relative changes of the magnetic-field-dependent effective shear modulus will significantly increase with the growing concentration of filler particles.

The ability of a feed-forward neural network to learn and classify different states of polymer configurations is systematically explored. Performing numerical experiments, we find that a simple network model can, after adequate training, recognize multiple structures, including gaslike coil, liquidlike globular, and crystalline anti-Mackay and Mackay structures. The network can be trained to identify the transition points between various states, which compare well with those identified by independent specific-heat calculations. Our study demonstrates that neural networks provide an unconventional tool to study the phase transitions in polymeric systems.

Langevin dynamics simulation is used to study the suspension of interacting magnetic nanoparticles (dipolar spheres) in a zero applied magnetic field and in the presence of a gravitational (centrifugal) field. A particular emphasis is placed on the equilibrium vertical distribution of particles in the infinite horizontal slab. An increase in the dipolar coupling constant $\lambda$ (the ratio of dipole-dipole interaction energy to thermal energy) from zero to seven units causes an increase in the particle segregation coefficient by several orders of magnitude. The effect of anisotropic dipole-dipole interactions on the concentration profile of particles is the same as that of the isotropic van der Waals attraction modeled by the Lennard-Jones potential. In both cases, the area with a high-density gradient separating the area with high and low particle concentration is formed on the profiles. Qualitative difference between two potentials manifests itself only in the fact that in the absence of a gravitational field the dipole-dipole interactions do not lead to the “gas-liquid” phase transition: no separation of the system into weakly and highly concentrated phases is observed. At high particle concentration and at large values of $\lambda$, the orientational ordering of magnetic dipoles takes place in the system. Magnetic structure of the system strongly depends on the imposed boundary conditions. Spontaneous magnetization occurs in the infinite horizontal slab (i.e., in the rectangular cell with two-dimensional periodic boundary conditions). Replacement of the infinite slab by the finite-size hard-wall vertical cylinder leads to the formation of azimuthal (vortex-like) order. The critical values of the coupling constant corresponding to the transition into an ordered state are very close for two geometries.

We study a model of fully developed turbulence of a compressible fluid, based on the stochastic Navier-Stokes equation, by means of the field-theoretic renormalization group. In this approach, scaling properties are related to the fixed points of the renormalization group equations. Previous analysis of this model near the real-world space dimension 3 identified a scaling regime [N. V. Antonov et al., Theor. Math. Phys. 110, 305 (1997)]. The aim of the present paper is to explore the existence of additional regimes, which could not be found using the direct perturbative approach of the previous work, and to analyze the crossover between different regimes. It seems possible to determine them near the special value of space dimension 4 in the framework of double $y$ and $\varepsilon$ expansion, where $y$ is the exponent associated with the random force and $\varepsilon =4-d$ is the deviation from the space dimension 4. Our calculations show that there exists an additional fixed point that governs scaling behavior. Turbulent advection of a passive scalar (density) field by this velocity ensemble is considered as well. We demonstrate that various correlation functions of the scalar field exhibit anomalous scaling behavior in the inertial-convective range. The corresponding anomalous exponents, identified as scaling dimensions of certain composite fields, can be systematically calculated as a series in $y$ and $\varepsilon$. All calculations are performed in the leading one-loop approximation.

We numerically examine clogging transitions for bidisperse disks flowing through a two-dimensional periodic obstacle array. We show that clogging is a probabilistic event that occurs through a transition from a homogeneous flowing state to a heterogeneous or phase-separated jammed state where the disks form dense connected clusters. The probability for clogging to occur during a fixed time increases with increasing particle packing and obstacle number. For driving at different angles with respect to the symmetry direction of the obstacle array, we show that certain directions have a higher clogging susceptibility. It is also possible to have a size-specific clogging transition in which one disk size becomes completely immobile while the other disk size continues to flow.