Quasimonoenergetic GeV-scale protons are predicted to be efficiently generated via radiation pressure acceleration (RPA) when the foil thickness is matched with the laser intensity, e.g., $L_{\mathrm{mat}}$ of several nm to 100 nm for ${10}^{19}-{10}^{22}\mathrm{W}{\mathrm{cm}}^{-2}$ available in laboratory. However, nonmonoenergetic protons with much lower energies than predicted were usually observed in RPA experiments because of too small foil thickness which cannot support insufficient laser contrast and foil surface roughness. Besides the technical problems, we here find that there is an upper-limit thickness $L_{\mathrm{up}}$ derived from the requirement that the laser energy should dominate over the ion source energy in the effective laser-proton interaction zone, and $L_{\mathrm{up}}$ is lower than $L_{\mathrm{mat}}$ with the intensity below ${10}^{22}\mathrm{W}{\mathrm{cm}}^{-2}$, which causes inefficient or unsteady RPA. As the intensity is enhanced to $\ge {10}^{23}\mathrm{W}{\mathrm{cm}}^{-2}$ provided by 10–100 PW laser facilities, $L_{\mathrm{up}}$ can significantly exceed $L_{\mathrm{mat}}$, and therefore RPA becomes efficient. In this regime, $L_{\mathrm{mat}}$ acts as a lower-limit thickness for efficient RPA, so the matching thickness can be extended to a continuous range from $L_{\mathrm{mat}}$ to $L_{\mathrm{up}}$; the range can reach micrometers, within which foil thickness is adjustable. This makes RPA steady and meanwhile the above technical problems can be overcome. Particle-in-cell simulation shows that multi-GeV quasimonoenergetic proton beams can be steadily generated and the fluctuation of the energy peaks and the energy conversation efficiency remains stable although the thickness is taken in a larger range with increasing intensity. This work predicts that near future RPA experiments with 10–100 PW facilities will enter a new regime with a large range of usable foil thicknesses that can be adjusted to the interaction conditions for steady acceleration.

The utility of quantum computers for simulating lattice gauge theories is currently limited by the noisiness of the physical hardware. Various quantum error mitigation strategies exist to reduce the statistical and systematic uncertainties in quantum simulations via improved algorithms and analysis strategies. We perform quantum simulations of ${\mathbb{Z}}_2$ gauge theory with matter to study the efficacy and interplay of different error mitigation methods: readout error mitigation, randomized compiling, rescaling, and dynamical decoupling. We compute Minkowski correlation functions in this confining gauge theory and extract the mass of the lightest spin-1 state from fits to their time dependence. Quantum error mitigation extends the range of times over which our correlation function calculations are accurate by a factor of 6 and is therefore essential for obtaining reliable masses.

We present results for phase-ordering kinetics in the Coulomb glass (CG) model, which describes electrons on a lattice with unscreened Coulombic repulsion. The filling factor is denoted by $K\in [0,1]$. For a square lattice with $K=0.5$ (symmetric CG), the ground state is a checkerboard with alternating electrons and holes. In this paper, we focus on the asymmetric CG where $K\lesssim 0.5$, i.e., the ground state is checkerboard-like with excess holes distributed uniformly. There is no explicit quenched disorder in our system, though the Coulombic interaction gives rise to frustration. We find that the evolution morphology is in the same dynamical universality class as the ordering ferromagnet. Further, the domain growth law is slightly slower than the Lifshitz-Cahn-Allen law, $L\left(t\right)\sim t^{1/2}$, i.e., the growth exponent is underestimated. We speculate that this could be a signature of logarithmic growth in the asymptotic regime.

Source location in quantum networks is a critical area of research with profound implications for cutting-edge fields such as quantum state tomography, quantum computing, and quantum communication. In this study, we present groundbreaking research on the technique and theory of source location in Szegedy's quantum networks. We develop a linear system evolution model for a Szegedy's quantum network system using matrix vectorization techniques. Subsequently, we propose a highly precise and robust source-location algorithm based on compressed sensing specifically tailored for Szegedy's quantum network. To validate the effectiveness and feasibility of our algorithm, we conduct numerical simulations on various model and real networks, yielding compelling results. These findings underscore the potential of our approach in practical applications.

Recently it was predicted, on the basis of a lattice gas model, that scalar active matter in a gravitational field would rise against gravity up a confining wall or inside a thin capillary—in spite of repulsive particle-wall interactions [Phys. Rev. Lett. 124, 048001 (2020)]. In this paper we confirm this prediction with sedimenting active Brownian particles (ABPs) in a box numerically and elucidate the mechanism leading to the formation of a meniscus rising above the bulk of the sedimentation region. The height of the meniscus increases with the activity of the system, algebraically with the Péclet number. The formation of the meniscus is determined by a stationary circular particle current, a vortex, centered at the base of the meniscus, whose size and strength increase with the ABP activity. The origin of these vortices can be traced back to the confinement of the ABPs in a box: already the stationary state of ideal (noninteracting) ABPs without gravitation displays circular currents that arrange in a highly symmetric way in the eight octants of the box. Gravitation distorts this vortex configuration downward, leaving two major vortices at the two side walls, with a strong downward flow along the walls. Repulsive interactions between the ABPs change this situation only as soon as motility induced phase separation (MIPS) sets in and forms a dense, sedimented liquid region at the bottom, which pushes the center of the vortex upwards towards the liquid-gas interface. Self-propelled particles therefore represent an impressive realization of scalar active matter that forms stationary particle currents being able to perform visible work against gravity or any other external field, which we predict to be observable experimentally in active colloids under gravitation.

The viscosity and thermal conductivity coefficients of the Lennard-Jones fluid are extracted through symbolic regression (SR) techniques from data derived from simulations at the atomic scale. This data-oriented approach provides closed form relations that achieve fine accuracy when compared to well-established theoretical, empirical, or approximate equations, fully transparent, with small complexity and high interpretability. The novelty is further outlined by suggesting analytical expressions for estimating fluid transport properties across the whole phase space, from a dilute gas to a dense liquid, by considering only two macroscopic properties (density and temperature). In such expressions, the underlying physical mechanisms are reflected, while, at the same time, it can be a computationally efficient alternative to costly in time and size first principle and/or molecular dynamics simulations.

Genome assembly, the process of reconstructing a long genetic sequence by aligning and merging short fragments, or reads, is known to be NP-hard, either as a version of the shortest common superstring problem or in a Hamiltonian-cycle formulation. That is, the computing time is believed to grow exponentially with the problem size in the worst case. Despite this fact, high-throughput technologies and modern algorithms currently allow bioinformaticians to handle datasets of billions of reads. Using methods from statistical mechanics, we address this conundrum by demonstrating the existence of a phase transition in the computational complexity of the problem and showing that practical instances always fall in the “easy” phase (solvable by polynomial-time algorithms). In addition, we propose a Markov-chain Monte Carlo method that outperforms common deterministic algorithms in the hard regime.

A simple method of measuring the vibrational response of a thin film membrane was developed. Piezoelectric excitation and acoustic detection (using a microphone) allowed the vibrational spectra of thin membranes to be measured in the kHz range. Vibrational frequencies were used to determine Young's modulus in thin ($\mu \text{m}$) solvent tensioned films of polydimethylsiloxane and to measure tension in ultrathin polystyrene films. Simulations of membrane motion generated vibrational spectra that agreed with the results of experiments for different membrane shapes.

Using the three-dimensional discrete element method, we numerically investigate the collapse dynamics and deposition morphology of low-viscocohesive granular columns on a rough-horizontal plane by systematically varying a broad range of values of the initial column aspect ratio, cohesive stress, and liquid viscosity. The results show that the kinetic energy, half runout time, and runout distance increase with increasing the initial column aspect ratio but decrease with increasing the cohesive and viscous effects of the binding liquid, while the toe angle and deposit height decrease with increasing the aspect ratio and increase with increasing cohesive stress and liquid viscosity. Remarkably, by defining a dimensionless scaling number that incorporates the Bond number and initial column aspect ratio, this allows us to nicely describe the kinetic energy, half runout time, deposition height, runout distance, and toe angle. These unified descriptions may provide insights into the physical properties of the collapse dynamics and deposition morphology of low-viscocohesive granular columns, leading to good explanations of the complex properties of natural disaster events.

Three-dimensional magnetohydrodynamic simulations are able to model the generation of disk-shaped plasma, driven by laser ablation from a current-carrying rod in a pulsed-power machine producing azimuthal magnetic fields of $2-3$ MG. The plasma at such extreme conditions is unique in that the parameter space for the plasma $\beta$ and Hall parameter $\chi$ transition from below unity to greater than unity at different stages of the plasma generation. In simulations, the formation of the plasma disk in the azimuthal direction is driven by heat flux from the laser spot and depends on the set of transport coefficients used in simulations. The most recent set of transport coefficients leads to the formation of plasma ejecta at the back end of the rod, which qualitatively matches experiments. Specifically, the cross-gradient Nernst effect, which twists the magnetic field, is shown to have a large effect on the shape of the back-end ejecta. In the direction along the axis of the rod, there is propagation of perturbations from the disk as observed in experiments. In simulations, the period of temperature perturbations is in good agreement with experimental results. An instability due to coupling of heat flux and the magnetic field advection provides a possible explanation for perturbation growth along the axis of the rod, and the instability growth rate is consistent with experimental results.

Simulations of objects with classical dynamics are in fact a particular version of discrete dynamics, since almost all the classical dynamics simulations in natural science are performed with the use of the simple “leapfrog” or “Verlet” algorithm. It was, however, Newton who in Principia, Proposition I in 1687 first formulated the discrete algorithm, which much later in 1967 was rederived by L. Verlet. Verlet also formulated a first-order approximation for the velocity $\mathbf{v}\left(t\right)$ at time $t$, which has been used in simulations since then. The approximated expressions for $\mathbf{v}\left(t\right)$ and the kinetic energy lead to severe errors in the thermodynamics at high densities, temperatures, strong repulsive forces, or for large discrete time increments used in discrete “molecular dynamics” (MD) simulations. Here we derive the exact expressions for the discrete dynamics, and show by simulations of a Lennard-Jones system that these expressions now result in equality between temperatures determined from the kinetic energies and the corresponding configurational temperatures determined from the expresssion of Landau and Lifshitz, derived from the forces.

Volterra's definition of dislocations in crystals geometrically distinguishes edge and screw defects according to whether the Burgers vector is perpendicular or parallel to the defect. A homotopy-theoretic analysis of dislocations as topological defects fails to differentiate edge and screw. Here we bridge the gap between the geometric and topological descriptions by demonstrating that there is a topological difference between screw and edge defects. Our construction distinguishes edge and screw based on the disclination-line pairs at the core of smectic dislocations. By exploiting the connection between topology and geometry in the form of Gaussian curvature, this analysis results in an invariant for dislocations in the saddle-splay vector. This construction can be generalized to crystals with triply periodic order.

The cost of information processing in physical systems calls for a trade-off between performance and energetic expenditure. Here we formulate and study a computation-dissipation bottleneck in mesoscopic systems used as input-output devices. Using both real data sets and synthetic tasks, we show how nonequilibrium leads to enhanced performance. Our framework sheds light on a crucial compromise between information compression, input-output computation and dynamic irreversibility induced by nonreciprocal interactions.

The quantum spin-$1/2$ Ising ladder with homogeneous side rail interaction and disordered rung interaction in the presence of a random site transverse magnetic field has been studied using the method of recurrence relations in the high-temperature limit. The first six recurrants have been exactly calculated, and a linear extrapolation process has been used to obtain a total of 100 recurrants. This extrapolation allows us to extend the analysis to longer times. Both the rung coupling and the transverse field obey a bimodal distribution. The time autocorrelation functions of the $z$-component dynamic spin variable have been obtained. We have considered several cases of rung and transverse field distributions, as well as several values of the Hamiltonian parameters. The results show that the disorder present in the rung interaction and external transverse field affects the behavior of the temporal autocorrelation and the spectral functions in all studied cases. In addition, the interesting case where the rung interactions and the transverse magnetic field are correlated has also been studied. In general, transition in the dynamics of the system from individual to collective mode was observed depending on the dominant kind of interaction in the sites, that is, whether most of the sites were subject to a strong external field or strong interchain local interactions.

The question under which conditions oscillators with slightly different frequencies synchronize appears in various settings. We consider the case of a finite number of harmonic oscillators arranged on a ring, with bilinear, dissipative nearest-neighbor coupling. We show that by tuning the gain and loss appropriately, stable synchronized dynamics may be achieved. These findings are interpreted using the complex eigenvalues and eigenvectors of the non-Hermitian matrix describing the dynamics of the system. We provide a complete discussion for the case of two oscillators. Ring sizes with a small number of oscillators are discussed taking the case of $N=5$ oscillators as an example. For $N\gtrsim 10$ we focus on the case where the frequency fluctuations of each oscillator are chosen from a Gaussian distribution with zero mean and standard deviation $\sigma$. We derive a scaling law for the largest standard deviation ${\sigma }_{\mathrm{full}}$ that still permits all oscillators to be fully synchronized: ${\sigma }_{\mathrm{full}}\sim N^{-3/2}$. Finally, we discuss how such random fluctuations influence the timescale on which the synchronized state is reached and on which timescale the synchronized state then decays.

We study the coevolution of network structure and signaling behavior. We model agents who can preferentially associate with others in a dynamic network while they also learn to play a simple sender-receiver game. We have four major findings. First, signaling interactions in dynamic networks are sufficient to cause the endogenous formation of distinct signaling groups, even in an initially homogeneous population. Second, dynamic networks allow the emergence of novel hybrid signaling groups that do not converge on a single common signaling system but are instead composed of different yet complementary signaling strategies. We show that the presence of these hybrid groups promotes stable diversity in signaling among other groups in the population. Third, we find important distinctions in information processing capacity of different groups: hybrid groups diffuse information more quickly initially but at the cost of taking longer to reach all group members. Fourth, our findings pertain to all common interest signaling games, are robust across many parameters, and mitigate known problems of inefficient communication.

We present a theoretical analysis of the efficiency and rate of excitation transport on a network described by a complete graph in which every site is connected to every other. The long-time transport properties are analytically calculated for networks of arbitrary size that are symmetric except for the trapping site, start with a range of initial states, and are subject to dephasing and excitation decay. Conditions for which dephasing increases transport are identified, and optimal conditions are found for various physical parameters. The optimal conditions demonstrate robustness and a convergence of timescales previously observed in the context of light-harvesting complexes.

The propagation of light across 2D and 3D slabs of reflective colloidal particles in a fluidlike state has been investigated by simulation. The colloids are represented as hard spheres with and without an attractive square-well tail. Representative configurations of particles have been generated by Monte Carlo. The path of rays entering the slab normal to its planar surface has been determined by exact geometric scattering conditions, assuming that particles are macroscopic spheres fully reflective at the surface of their hard-core potential. The analysis of light paths provides the transmission and reflection coefficients, the mean-free path, the average length of transmitted and reflected paths, the distribution of scattering events across the slab, the angular spread of the outcoming rays as a function of dimensionality, and thermodynamic state. The results highlight the presence of a sizable population of very long paths, which play an important role in random lasing from solutions of metal particles in an optically active fluid. The output power spectrum resulting from the stimulated emission amplification decays asymptotically as an inverse power law. The present study goes beyond the standard approach based on a random walk confined between two planar interfaces and parametrized in terms of the mean-free path and scattering matrix. Here, instead, the mean-free path, the correlation among scattering events, and memory effects are not assumed a priori, but emerge from the underlying statistical mechanics model of interacting particles. In this way the dependence of properties on the thermodynamic state, the effect of particle-particle and particle-interface correlations and of spatial inhomogeneity, and memory effects are accounted for in a transparent way. Moreover, the approach joins smoothly the ballistic regime of light propagation at low density with the diffusive regime at high density of scattering centers. These properties are exploited to investigate the effect of weak polydispersivity and of large density fluctuations at the critical point of the model with the attractive potential tail.

Particles trapped at a fluid-fluid interface by capillary forces can form a monolayer that jams and buckles when subject to uniaxial compression. Here we investigate experimentally the buckling mechanics of monolayers of millimeter-sized rigid plates trapped at a planar fluid-fluid interface subject to uniaxial compression in a Langmuir trough. We quantified the buckling wavelength and the associated force on the trough barriers as a function of the degree of compression. To explain the observed buckling wavelength and forces in the two-dimensional (2D) monolayer, we consider a simplified system composed of a linear chain of platelike particles. The chain system enables us to build a theoretical model which is then compared to the 2D monolayer data. Both the experiments and analytical model show that the wavelength of buckling of a monolayer of platelike particles is of the order of the particle size, a different scaling from the one usually reported for monolayers of spheres. A simple model of buckling surface pressure is also proposed, and an analysis of the effect of the bending rigidity resulting from a small overlap between nanosheet particles is presented. These results can be applied to the modeling of the interfacial rheology and buckling dynamics of interfacial layers of 2D nanomaterials.