We present the usage of two-layer targets with laser-illuminated front-side microstructures for x-ray backlighter applications. The targets consisted of a silicon front layer and copper back side layer. The structured layer was irradiated by the 500-fs PHELIX laser with an intensity above ${10}^{20}\mathrm{W}{\mathrm{cm}}^{-2}$. The total emission and one-dimensional extent of the copper $K\alpha$ x-ray emission as well as a wide spectral range between 7.9 and 9.0 keV were recorded with an array of crystal spectrometers. The measurements show that the front-side modifications of the silicon in the form of conical microstructures maintain the same peak brightness of the $K\alpha$ emission as flat copper foils while suppressing the thermal emission background significantly. The observed $K\alpha$ source sizes can be influenced by tilting the conical microstructures with respect to the laser axis. Overall, the recorded copper $K\alpha$ photon yields were in the range of ${10}^{11}{\mathrm{sr}}^{-1}$, demonstrating the suitability of these targets for probing applications without subjecting the probed material to additional heating from thermal line emission.

Excited-state quantum phase transitions (ESQPTs) are critical phenomena that generate singularities in the spectrum of quantum systems. For systems with a classical counterpart, these phenomena have their origin in the classical limit when the separatrix of an unstable periodic orbit divides phase space into different regions. Using a semiclassical theory of wave propagation based on the manifolds of unstable periodic orbits, we describe the quantum states associated with an ESQPT for the quantum standard map: a paradigmatic example of a kicked quantum system. Moreover, we show that finite-size precursors of ESQPTs shrink as chaos increases due to the disturbance of the system. This phenomenon is explained through destructive interference between principal homoclinic orbits.

Odd materials feature antisymmetric response to perturbations. This anomalous property can stem from the nonequilibrium activity of their components, which is sustained by an external energy supply. These materials open the door to designing innovative engines which extract work by applying cyclic deformations, without any equivalent in equilibrium. Here, we reveal that the efficiency of such energy conversion, from local activity to macroscopic work, can be arbitrarily close to unity when the cycles of deformation are properly designed. We illustrate these principles in some canonical viscoelastic materials, which leads us to identify strategies for optimizing power and efficiency according to material properties and to delineate guidelines for the design of more complex odd engines.

The hypothesis of self-organized criticality explains the existence of long-range “space-time” correlations, observed inseparably in many natural dynamical systems. A simple link between these correlations is yet unclear, particularly in fluctuations at an “external drive” timescale. As an example, we consider a class of sandpile models displaying nontrivial correlations. We apply the scaling method and determine spatial cross-correlation by establishing a relationship between local and global temporal correlations. We find that the spatial cross-correlation decays in a power-law manner with an exponent $\gamma =1-\delta$, where $\delta$ characterizes a scaling of the total power of the global temporal process with the system size.

We investigate the concept of molecular-sized outward-swinging gate, which allows for entropy decrease in an isolated system. The theoretical analysis, the Monte Carlo simulation, and the direct solution of governing equations all suggest that under the condition of local nonchaoticity, the probability of particle crossing is asymmetric. It is demonstrated by an experiment on a nanoporous membrane one-sidedly surface-grafted with bendable organic chains. Remarkably, through the membrane, gas spontaneously and repeatedly flows from the low-pressure side to the high-pressure side. While this phenomenon seems counterintuitive, it is compatible with the principle of maximum entropy. The locally nonchaotic gate interrupts the probability distribution of the local microstates, and imposes additional constraints on the global microstates, so that entropy reaches a nonequilibrium maximum. Such a mechanism is fundamentally different from Maxwell's demon and Feynman's ratchet, and is consistent with microscopic reversibility. It implies that useful work may be produced in a cycle from a single thermal reservoir. A generalized form of the second law of thermodynamics is proposed.

The phase diagrams of two models of two confined and dense two-dimensional ring polymers are examined numerically. The ring polymers are modeled by square lattice polygons in a square cavity and are placed to be either unlinked or linked in the plane. The phase diagrams of the two models are found to be a function of the placement of the ring polymers and include multicritical points where first-order and continuous phase boundaries meet. We estimate numerically the critical exponents associated with the phase boundaries and the multicritical points.

We construct the hydrodynamic theory of coherent collective motion (“flocking”) at a solid-liquid interface. The polar order parameter and concentration of a collection of “active” (self-propelled) particles at a planar interface between a passive, isotropic bulk fluid and a solid surface are dynamically coupled to the bulk fluid. We find that such systems are stable, and have long-range orientational order, over a wide range of parameters. When stable, these systems exhibit “giant number fluctuations,” i.e., large fluctuations of the number of active particles in a fixed large area. Specifically, these number fluctuations grow as the $3/4\mathrm{th}$ power of the mean number within the area. Stable systems also exhibit anomalously rapid diffusion of tagged particles suspended in the passive fluid along any directions in a plane parallel to the solid-liquid interface, whereas the diffusivity along the direction perpendicular to the plane is nonanomalous. In other parameter regimes, the system becomes unstable.

Based on results from the physics and mathematics literature which suggest a series of clearly defined conjectures, we formulate three simple scenarios for the fate of hard sphere crystallization in high dimension: in scenario A, crystallization is impeded and the glass phase constitutes the densest packing; in scenario B, crystallization from the liquid is possible, but takes place much beyond the dynamical glass transition and is thus dynamically implausible; and in scenario C, crystallization is possible and takes place before (or just after) dynamical arrest, thus making it plausibly accessible from the liquid state. In order to assess the underlying conjectures and thus obtain insight into which scenario is most likely to be realized, we investigate the densest sphere packings for dimension $d=3\text{−}10$ using cell-cluster expansions as well as numerical simulations. These resulting estimates of the crystal entropy near close packing tend to support scenario C. We additionally confirm that the crystal equation of state is dominated by the free-volume expansion and that a meaningful polynomial correction can be formulated.

We discuss hydrodynamic forces acting on a two-dimensional liquid domain that moves laterally within a supported fluid membrane in the presence of odd viscosity. Since active rotating proteins can accumulate inside the domain, we focus on the difference in odd viscosity between the inside and outside of the domain. Taking into account the momentum leakage from a two-dimensional incompressible fluid to the underlying substrate, we analytically obtain the fluid flow induced by the lateral domain motion and calculate the drag and lift forces acting on the moving liquid domain. In contrast to the passive case without odd viscosity, the lateral lift arises in the active case only when the in and out odd viscosities are different. The in-out contrast in the odd viscosity leads to nonreciprocal hydrodynamic responses of an active liquid domain.

Traffic jams are an everyday hindrance to transport and typically arise when many vehicles have the same or a similar destination. We show, however, that even when uniformly distributed in space and uncorrelated, targets have a crucial effect on transport. At modest densities an instability arises leading to jams with emergent correlations between the targets. By considering limiting cases of the dynamics which map onto active Brownian particles, we argue that motility induced phase separation is the precursor to jams. That is, jams are MIPS seeds that undergo an extra instability due to target accumulation. This provides a quantitative prediction of the onset density for jamming, and suggests how jamming might be delayed or prevented. We study the transition between jammed and flowing phase, and find that transport is most efficient on the cusp of jamming.

Gravity-driven collapses involving large amounts of dense granular material, such as landslides, avalanches, or rock falls, in a geophysical context, represent significant natural hazards. Understanding their complex dynamics is hence a key concern for risk assessment. In the present work, we report experiments on the collapse of quasi-two-dimensional dry granular columns under the effect of gravity, where both the velocity at which the grains are released and the aspect ratio of the column are varied to investigate the dynamics of the falling grains. At high release velocity, classical power laws for the final deposit are recovered, meaning those are representative of a free-fall-like regime. For sufficiently high aspect ratios, the top of the column undergoes an overall free-fall-like motion. In addition, for all experiments, the falling grains also spread horizontally in a free-fall-like motion, and the characteristic time of spreading is related to the horizontal extension reached by the deposit at all altitudes. At low release velocity, a quasistatic state is observed, with scaling laws for the final geometry identical to those of the viscous regime of granular-fluid flow. The velocity at which the grains are released governs the collapse dynamics. Between these two asymptotic regimes, higher release velocity correlates with smaller impact on the collapse dynamics. The criterion $\overline{V}\ge 0.4\sqrt{g{H}_0}$, where $H_0$ is the initial height of the column, is found for the mean release velocity $\overline{V}$ not to influence the granular collapse.

The interaction between gas diffusion and complex microstructures of a nanoporous medium is important to gas diffusion in shale formation, but this interaction is complex and has not been fully understood. Those approaches based on fractal theory can well describe the fractal multiscale microstructure with simple boundaries. The lattice Boltzmann method (LBM) can consider the effects of complex microstructures at one scale. This study proposes a combination approach of fractal theory and LBM to simulate the gas diffusion process in fractal multiscale microstructures of a nanoporous medium. In this study, the gas diffusion in a complex microstructure at base scale is numerically simulated by the LBM and the gas diffusion in finer microstructures is described through a diffusion equation with a local gas diffusion coefficient. First, a microstructure of a nanoporous medium is reconstructed by a random reconstruction algorithm. Then, a local gas diffusion coefficient is proposed based on fractal theory to consider the effects of coupling molecular diffusion and Knudsen diffusion with the fractal structures of a nanoporous medium on the gas diffusion in finer microstructures. This local gas diffusion coefficient is validated by experimental data and introduced into the governing equation of gas diffusion. The LBM simulation is verified with experimental data and two other model results on the effective gas diffusivity of a nanoporous medium. Finally, key parameters for the effective gas diffusivity of a nanoporous medium are identified through sensitivity analysis. It is found that the effective gas diffusivity in a microstructure is higher for a smaller range of Knudsen number. Bigger pore diameter fractal dimension and smaller tortuosity fractal dimension represent lower gas diffusion resistance and have higher effective gas diffusivity. This combination approach provides a powerful tool to estimate the effective gas diffusivity in a complex nanoporous medium.

Lévy walks are a particular type of continuous-time random walks which results in a super-diffusive spreading of an initially localized packet. The original one-dimensional model has a simple schematization that is based on starting a new unidirectional motion event either in the positive or in the negative direction. We consider two-dimensional generalization of Lévy walks in the form of the so-called $XY$ model. It describes a particle moving with a constant velocity along one of the four basic directions and randomly switching between them when starting a new motion event. We address the ballistic regime and derive solutions for the asymptotic density profiles. The solutions have a form of first-order integrals which can be evaluated numerically. For specific values of parameters we derive an exact expression. The analytic results are in agreement with the results of finite-time numerical samplings.

We report the occurrence of a self-emerging frequency chimera state in spatially extended systems of coupled oscillators, where the coherence and incoherence are defined with respect to the emergent frequency of the oscillations. This is generated by the local coupling among nonlinear oscillators evolving under differing dynamical timescales starting from random initial conditions. We show how they self-organize to structured patterns with spatial domains of coherence that are in frequency synchronization, coexisting with domains that are incoherent in frequencies. Our study has relevance in understanding such patterns observed in real-world systems like neuronal systems, power grids, social and ecological networks, where differing dynamical timescales is natural and realistic among the interacting systems.

The small-angle neutron scattering (SANS) on the rat lymphocyte nuclei demonstrates the bifractal nature of the chromatin structural organization. The scattering intensity from rat lymphocyte nuclei is described by power law $Q^{-D}$ with fractal dimension approximately 2.3 on smaller scales and 3 on larger scales. The crossover between two fractal structures is detected at momentum transfer near ${10}^{-1}{\mathrm{nm}}^{-1}$. The use of contrast variation (${\mathrm{D}}_2\mathrm{O}\text{−}{\mathrm{H}}_2\mathrm{O}$) in SANS measurements reveals clear similarity in the structural organizations of nucleic acids (NA) and proteins. Both chromatin components show bifractal behavior with logarithmic fractal structure on the large scale and volume fractal with slightly smaller than 2.5 structure on the small scale. Scattering intensities from chromatin, protein component, and NA component demonstrate an extremely extensive range of logarithmic fractal behavior (from ${10}^{-3}$ to approximately ${10}^{-1}{\mathrm{nm}}^{-1}$). We compare the fractal arrangement of rat lymphocyte nuclei with that of chicken erythrocytes and the immortal HeLa cell line. We conclude that the bifractal nature of the chromatin arrangement is inherent in the nuclei of all these cells. The details of the fractal arrangement—its range and correlation/interaction between nuclear acids and proteins are specific for different cells and is related to their functionality.

We consider transport in a fluid flow of arbitrary complexity but with a dominant flow direction. One of the situations in which this occurs is when describing by an effective flow the dynamics of sufficiently small particles immersed in a turbulent fluid and vertically sinking because of their weight. We develop a formalism characterizing the dynamics of particles released from one layer of fluid and arriving in a second one after traveling along the dominant direction. The main ingredient in our study is the definition of a two-layer map that describes the Lagrangian transport between both layers. We combine geometric approaches and probabilistic network descriptions to analyze the two-layer map. From the geometric point of view, we express the properties of lines, surfaces, and densities transported by the flow in terms of singular values related to Lyapunov exponents, and define a specific quantifier, the finite depth Lyapunov exponent. Within the network approach, degrees and an entropy are considered to characterize transport. We also provide relationships between both methodologies. The formalism is illustrated with numerical results for a modification of the ABC flow, a model commonly studied to characterize three-dimensional chaotic advection.

Physical data are typically generated by experiments and computations in limited parameter regimes. When datasets generated using such disparate methods are combined into one dataset, the resulting dataset is typically sparse, with dense “islands” in a potentially high-dimensional parameter space, and predictions must be interpolated among such islands. Using plasma transport data as our example, we propose a multifidelity Gaussian-process regression framework that incorporates physical data from multiple sources at multiple fidelities. The impact of the proposed framework varies from little improvement over simpler approaches to qualitatively changing the prediction with consistently increased confidence in regions lacking high-fidelity data. By varying low- and high-fidelity data sources, we demonstrate an approach for determining when multifidelity Gaussian-process regression adds value over single-fidelity regression and therefore when its additional computational costs are merited. We also examine the case in which the outputs of the low- and high-fidelity models correspond to different physical quantities, one of which may be intrinsically computationally cheaper to compute. We conclude by analyzing strategies for sampling high-fidelity data for use in this framework, and we develop a simple sampling approach for reducing regression error across large gaps in data.

Colloidal inclusions suspended in a bath of smaller particles experience an effective bath-mediated attraction at small intersurface separations, which is known as the depletion interaction. In an active bath of nonchiral self-propelled particles, the effective force changes from attraction to repulsion, an effect that is suppressed when the active bath particles are chiral. Using Brownian dynamics simulations, we study the effects of channel confinement and bath chirality on the effective forces and torques that are mediated between two inclusions that may be fixed within the channel or may be allowed to rotate freely as a rigid dimer around its center of mass. We show that the confinement has a strong effect on the effective interactions, depending on the orientation of the dimer relative to the channel walls. The active particle chirality leads to a force imbalance and, hence, a net torque on the inclusion dimer, which we investigate as a function of the bath chirality strength and the channel height.

We report a lift force model for intruders in dense, granular shear flows. Our derivation is based on the thermal buoyancy model of Trujillo and Hermann [Physica A 330, 519 (2003)], but it takes into account both granular temperature and pressure differences in the derivation of the net buoyancy force acting on the intruder. In a second step, the model is extended to take into account also density differences between the intruder and the bed particles. The model predicts very well the rising and sinking of intruders, the lift force acting on intruders as determined by discrete element model simulations, and the neutral-buoyancy limit of intruders in shear flows. Phenomenologically, we observe a cooling upon the introduction of an intruder into the system. This cooling effect increases with intruder size and explains the sinking of large intruders. On the other hand, the introduction of small to midsized intruders, i.e., up to four times the bed particle size, leads to a reduction in the granular pressure compared to the hydrostatic pressure, which in turn causes the rising of small to midsized intruders.

Buoyancy-driven convection flows play a crucial role in global heat and momentum transport in atmosphere. Simplified planetary and stellar atmospheres can be described by a spherical gap geometry with special boundary conditions for the temperature. In the spherical gap, the dielectrophoretic effect is used to synthesize the radial gravity field. Lateral thermal boundary conditions are used to model solar radiation at the equator and at the poles. The temperature reaches a maximum value at the equator and becomes colder near the poles. In the case of a rotating gap, the influence of the Coriolis and centrifugal forces are taken into account. Different regimes of the two-dimensional steady basic flow are discussed in dependence on the Taylor number and Rayleigh number and for the radii ratio $\eta =R_{\mathrm{in}}/R_{\mathrm{out}}$, where $R_{\mathrm{in}},R_{\mathrm{out}}$ are the radii of the inner and outer surfaces, respectively. Linear instability theory is used to study when the basic flow becomes unstable. The critical Rayleigh number at which the steady axisymmetric basic flow becomes time-dependently axisymmetric or three dimensional is found to be a function of the Taylor number. Furthermore, the critical azimuthal wave number $m_c$, which is responsible for the structure of the supercritical three-dimensional flow, and the critical frequency of the perturbation ${\omega }_c$ were found. The spatial location of the perturbation helps to understand the origin of the instability.