Observing superdiffusive fluctuations from Kardar-Parisi-Zhang universality in isotropic integrable spin chains is usually challenging as it requires a fairly large number of spins in interaction. We demonstrate in this paper, in the context of classical spins, that accounting for boundary effects lowers the bar, down to a few dozen spins in some cases. Additionally, boundaries control the relaxation to stationarity, which leads to many new universal scaling functions to explore, both in periodic spin chains and for open chains with magnetization imposed by reservoirs at the ends.

Light can be squeezed by reducing the quantum uncertainty of the electric field for some phases. We show how to use this purely quantum effect to extract net mechanical work from radiation pressure in a simple quantum photon engine. Along the way, we demonstrate that the standard definition of work in quantum systems does not capture the extractable mechanical work, as it does not reflect the energy leaked to these quantum degrees of freedom. We use these results to design an Otto engine able to produce mechanical work from squeezing baths, in the absence of a thermal gradient. Interestingly, while work extraction from squeezing generally improves for low temperatures, there exists a nontrivial squeezing-dependent temperature for which work production is maximal, demonstrating the complex interplay between thermal and squeezing effects.

We study the impact of entangling measurements on the efficiency of quantum measurement-based engines. We first demonstrate that for engines comprising many subsystems the efficiency can be enhanced through the implementation of entangling measurements. Then, we show that when the collective measurement yields the same local state for the subsystems as individual local measurements, the improvement is directly proportional to the amount of correlations among the subsystems. Finally, we present examples for two-level systems where this type of engine can operate at perfect efficiency yielding a finite amount of work in the limit of a large number of subsystems; we also discuss how to generalize this idea to larger systems.

The paper is devoted to analytical and numerical studies of phonon transmittance and thermal conductance through two-dimensional (2D) arrays of nonlinear atomic defects at the interfaces between different crystal lattices. The combination of nonhomogeneity (spatial asymmetry) of the structure and nonlinearity of atomic-scale scatterers can in general result in the nonreciprocity of phonon transmittance and interface thermal conductance (ITC). This phenomenon is caused by the generation of phonon second and third harmonics in the transmitted and reflected waves in the time-reversal system, as was predicted earlier by one of the authors [Yu. A. Kosevich, Phys. Rev. B 52, 1017 (1995)] and firmly confirmed in the present work in several interfaces with nonlinear atomic defects. In the present work, we consider interfaces with 2D arrays of atomic defects with different types of nonlinearity of interatomic bonds. Both one-path and two-path phonon transmission through 2D arrays of atomic defects are considered in spatially symmetric and asymmetric structures. It is shown that physically justified positive quartic nonlinearity enhances phonon transmittance and ITC. In contrast, the cubic nonlinearity, which is responsible for the thermal expansion of solids, can produce either a decrease or enhancement of the phonon transmittance and ITC depending on system parameters. It was found that in asymmetric systems, defect atoms oscillation amplitudes depend on the direction of phonon incidence, which leads to nonreciprocity of phonon transmittance and ITC due to cubic and/or quartic nonlinearity but does not violate reciprocity of phonon transmittance and ITC in linear systems. It is shown that the change in only the atomic mass in 2D array of atomic defects can significantly increase phonon transmittance and ITC through the interface between the lattices, strongly mismatched in atomic masses. The maximal value of the thermal conductance is reached for the optimal atomic defects mass at the given interface, when broad phonon total transmission resonance is realized. In the system with the optimal atomic defect mass, the interatomic bonds nonlinearity, either cubic or quartic, cannot increase phonon transmittance and ITC because the nonlinearity takes the system away from the optimal condition. Interfaces with the Si-Ge-like and diamond-copper-like atomic-mass mismatches are considered, and the corresponding optimal atomic defect masses are determined. Nonlinear and nonreciprocal phonon tunneling, which describes acoustic phonon transmission across the vacuum gap between two nonpiezoelectric solids (e.g., two metals), supported by the weak but long-range interaction between them as was predicted earlier by one of the authors [Yu. A. Kosevich, Phys. Lett. A 155, 295 (1991)], is modeled and analyzed. Different types of nonlinearity of the weak coupling are considered in modeling of acoustic phonon tunneling and ITC in extreme near-field regime. The presented results contribute to better understanding and detailed modeling of the interplay between atomic-scale nonlinearity and nonhomogeneity in reciprocal and nonreciprocal phonon transmittance and ITC through 2D arrays of one-path and two-path nonlinear atomic defects with different topology.

Vascular networks exhibit a remarkable diversity of architectures and transport mechanisms across biological systems. Inspired by embolism propagation in plant xylem, where air invades water-filled conduits under negative pressure, we study air penetration in compliant one-dimensional hydrodynamic networks experiencing mass loss by pervaporation. Using a theoretical framework grounded in biomimetic models, we show that embolism dynamics are shaped by the interplay between network compliance and viscous dissipation. In particular, the competition between two timescales (the pressure diffusion time, ${\tau }_{\mathrm{diff}}$, and the pervaporation time, ${\tau }_{\mathrm{pv}}$) governs the emergence of complex, history-dependent behaviors. When ${\tau }_{\mathrm{diff}}\sim {\tau }_{\mathrm{pv}}$, we uncover a nonlinear feedback between the internal pressure field and the embolism front, leading to transient depressurization and delayed interface motion. These results offer a minimal framework for understanding embolism dynamics in slow-relaxing vascular systems and provide design principles for soft microfluidic circuits with tunable, nonlinear responses.

In the presence of an external magnetic field with strength exceeding a certain critical threshold, a right circularly polarized (RCP) laser pulse propagates through an otherwise opaque target. This significantly alters the conventional laser-plasma interaction dynamics, giving rise to a set of novel physical phenomena that are not observed in the absence of such a magnetic field. Periodic longitudinal electric field structures are generated inside the target due to the formation of a standing whistler wave. These structures play a crucial role in enhancing the acceleration of protons, particularly from thin foil targets with sub-micron thickness. Interestingly, the dependence of maximum proton energy on the applied magnetic field strength exhibits an oscillatory behavior, which is governed by the coupling of the periodic longitudinal electric field and suitable target parameters. Using this mechanism, a significant improvement in collimation and energy enhancement above $40\%$ of the accelerated ions are observed from a thin foil target of thickness 200 nm in the presence of a high magnetic field using PIC simulations. To our knowledge, this is the first report on the possibility of achieving collimated and energetic ions for a given laser intensity by exploiting the concept of enhanced TNSA due to the combined effect of standing wave field and the sheath field in the overdense plasma.

Neural networks are complex functions of both their inputs and parameters. Much prior work in deep learning theory analyzes the distribution of network outputs at a fixed set of inputs (e.g., a training dataset) over random initializations of the network parameters. The purpose of this article is to consider the opposite situation: We view a randomly initialized multilayer perceptron (MLP) as a Hamiltonian over its inputs. For typical realizations of the network parameters, we study the properties of the energy landscape induced by this Hamiltonian, focusing on the structure of near-global minimum in the limit of infinite width. Specifically, we use the replica trick to perform an exact analytic calculation giving the entropy (log volume of space) at a given energy. We further derive saddle-point equations that describe the overlaps between inputs sampled independent and identically distributed from the Gibbs distribution induced by the random MLP. For linear activations we solve these saddle-point equations exactly. But we also solve them numerically for a variety of depths and activation functions, including $tanh,sin,\text{ReLU}$, and shaped nonlinearities. We find even at infinite width a rich range of behaviors. For some nonlinearities, such as $sin$, for instance, we find that the landscapes of random MLPs exhibit full replica symmetry breaking, while shallow $tanh$ and ReLU networks or deep shaped MLPs are instead replica symmetric.

We provide a consistent thermodynamic analysis of stochastic thermal engines driven by finite-size reservoirs, which are in turn coupled to infinite-size reservoirs. We consider a cyclic operation mode, where the working medium couples sequentially to hot and cold reservoirs, and a continuous mode with both reservoirs coupled simultaneously. We derive an effective temperature for the finite-size reservoirs determining the entropy production for two-state engines in the sequential coupling scenario and show that finite-size reservoirs can meaningfully affect the power when compared to infinite-size reservoirs in both sequential and simultaneous coupling scenarios. We also investigate a three-state engine comprising two interacting units and optimize its performance in the presence of a finite reservoir. Notably, we show that the efficiency at maximum power can exceed the Curzon-Ahlborn bound with finite reservoirs. Our work introduces tools to optimize the performance of nanoscale engines under realistic conditions of finite reservoir heat capacity and imperfect thermal isolation.

Dynamical systems in which some of the subsystems are modeled as a population of oscillators and interact with other subsystems through the mean field of oscillators are commonly observed in nature. In this paper, we present a framework for analyzing synchronization in such systems. While these models are conceptually simple, they quickly become computationally expensive and analytically intractable as the number of oscillators grows. To address this challenge, a macroscopic description of the oscillator population is often derived by considering the thermodynamic limit. For analytical purposes, the oscillator distribution is chosen from standard symmetric distributions, simplifying the representation, and the number of equations can be reduced to around the order of 1. However, such standard symmetric distributions are rare in practical systems, and very few works in the literature have attempted to address this problem. In this paper, we propose a generalized framework to reduce the dimensionality of a dynamical system where part of the subsystems exhibit behavior similar to a set of oscillators. The proposed method applies to nonstandard distributions observed in practical systems and uses model reduction methods, such as the Ott-Antonsen ansatz, to obtain a reduced-order model for dynamical systems. Our process reduces the high-dimensional models to around order of ten number of equations. These reduced models can then be studied analytically to identify the stability regimes of the system. We demonstrate the generalizability of our method for a thermoacoustic system, where the heat source is modeled using a set of oscillators based on the previous theoretical studies.

We investigate the wrinkling dynamics of a long, flat filament immersed in a viscous fluid subjected to compression at a constant rate. Typical wrinkling dynamics proceed through three stages: initiation, development, and relaxation. The first stage, during which high mode perturbations increase exponentially while the shape and filament tension remain almost unchanged, is notably longer in the linear and nonlinear simulations than in the experiments by Chopin et al. [Phys. Rev. Lett. 119, 088001 (2017)]. We propose that sudden environmental changes introduce extra high-frequency perturbations beyond thermal fluctuations, which significantly accelerates the first stage. This effect is universal and inevitable for similar processes given the experimental conditions. Finally, we analyze the relationship between the initial perturbations and the duration of the first stage.

We present an aligning active matter model by extending the nematic alignment rule in self-propelled rods to tunable alignment angles, as represented by the collision of cone-shaped particles. Nonvanishing alignment angles introduce frustration in the many-body interactions, and we investigate its effect on the collective behavior of the system. Through numerical simulations of an agent-based microscopic model, we find that the system exhibits distinct phenomenology compared to the original self-propelled rods. In particular, antiparallel bands are observed in an intermediate parameter range. The linear stability analysis of the continuum description derived from the Boltzmann approach demonstrates qualitative consistency with the microscopic model, while frustration due to many-body interactions in the latter destabilizes homogeneous nematic order over a wide range of the alignment angle.

Divergent opinions resulting from polarization are widespread across various fields, including economics, technology, and politics, and are often considered the genesis of disagreement among people. Numerous studies were therefore devoted to achieving complete consensus. However, as we show here, polarization is inevitable when individuals exhibit the self-confidence effect in interpreting social pressure, a psychological mechanism that drives adaptive consolidation of biased opinions. We also demonstrate that polarization, which merely reflects opinion distribution, does not necessarily cause high-level connected disagreement, which is highly related to the random walk normalized Laplacian (RWNL) of a network. By developing a networked dynamical model incorporating the self-confidence effect and analyzing the boundaries of opinion patterns, we find that polarization and its connected disagreement have different formation mechanisms. The level of connected disagreement intensifies as the number of unstable eigenmodes of the RWNL increases, a process greatly influenced by network topology. This finding helps us elucidate how connected disagreement evolves across different social networks and, more importantly, provides insights into developing effective modulation strategies to mitigate the level of connected disagreement when eliminating polarization is difficult.

Different regimes of quasiparticle transport can be observed in condensed matter. We have theoretically analyzed the transport properties of locally excited quasiparticles (for example, excitons) at an initial time in the vicinity of a one-dimensional interface formed by two different, atomically flat materials joined together by a heavy-tailed probability distribution of waiting times, accompanied by relaxation to the ground state. We have demonstrated that the microscopic origin of the heavy-tailed distribution of waiting times can be attributed to interactions with phonons. We showed that the non-Markovian nature of quasiparticle transport leads to a dependence of the mean squared displacement and diffusivity on the drift velocity. We also showed that negative diffusivity, which is measured experimentally for excitons using photoluminescence techniques, arises from the interplay of two effects. The first is the emergence of a subdiffusive regime with positive diffusivity. The second effect is a decrease in the number of excited quasiparticles that contribute to the photoluminescence signal.

The onset of quantum ergodicity is often quantified by the average ratio of consecutive level spacings. The reference values for ergodic quantum systems have been obtained numerically from the spectra of large but finite-dimensional random matrices. This work introduces a weighted ratio of consecutive level spacings, having the propery that the average can be computed numerically for random matrices of infinite dimension. A Painlevé differential equation is solved numerically in order to determine this average for infinite-dimensional orthogonal random matrices, thereby providing a reference value for ergodic quantum systems obeying time-reversal symmetry (provided that the time-reversal operator squares to the identity matrix). A Wigner surmise-inspired analytical calculation is found to yield a qualitatively accurate picture for the statistics of high-dimensional random matrices from each of the symmetry classes. For Poissonian level statistics, a significantly different average is found, indicating that the average weighted ratio of consecutive level spacings can be used as a probe for quantum ergodicity.

Transmission through optical fibers offers ultrafast and long-haul communications. However, the search for its ultimate capacity limits in the presence of distributed amplifier noise is complicated by the competition between wave dispersion and nonlinearity. In this paper, we exploit the integrability of the nonlinear Schrödinger equation, which accurately models optical fiber communications, to derive an expression for the mutual information of an optical fiber communications channel, expressed fully in the scattering data domain of the nonlinear Fourier transform and valid in the limit of low amplifier noise, which when optimized with respect to the input provides the corresponding capacity. We utilize the relationship between the derived noise-covariance operator and the Jacobian of the mapping between the signal and the scattering data to obtain the properties of the former. Emerging from the structure of the covariance operator is the significance of the Gordon-Haus effect in moderating and finally reversing the increase of the mutual information with power. This effect is showcased in numerical simulations for Gaussian input in the high-bandwidth regime.

The weakly asymmetric exclusion process (WASEP) in one dimension is a paradigmatic system of interacting particles described by the macroscopic fluctuation theory (MFT) in the presence of driving. We consider an initial condition with densities ${\varrho }_1,{\varrho }_2$ on either side of the origin, so that for ${\varrho }_1={\varrho }_2$ the gas is stationary. Starting from the microscopic description, we obtain exact formulas for the cumulant generating functions and large deviation rate functions of the time-integrated current and the position of a tracer. As the asymmetry/driving is increased, these describe the crossover between the symmetric exclusion process and the weak-noise regime of the Kardar-Parisi-Zhang (KPZ) equation: we recover the two limits and describe the crossover from the WASEP cubic tail to the $5/2$ and $3/2$ KPZ tail exponents. Finally, we show that the MFT of the WASEP is classically integrable, by exhibiting the explicit Lax pairs, which are obtained through a novel mapping between the MFT of the WASEP and a complex extension of the classical anisotropic Landau-Lifshitz spin chain. This shows integrability of all MFTs of asymmetric models with quadratic mobility as well as their dual versions.

Inspired by the avalanche scenario for many-body localization instability, we reverse the conventional setup and ask whether a large weakly disordered chain can thermalize a smaller, strongly disordered chain when the composite system evolves unitarily. Using transport as a dynamical probe, we identify three distinct thermalization regimes as a function of the disorder strength of the smaller chain: (i) complete thermalization with self-averaging at weak disorder, (ii) realization-dependent thermalization with strong sample-to-sample fluctuations at intermediate disorder, and (iii) absence of thermalization at strong disorder. We find that for a fixed length of the smaller chain, the non-self-averaging regime broadens with the size of the weakly disordered chain, revealing a nuanced interplay between disorder and system size. These results highlight how inhomogeneous disorder can induce emergent thermalization thresholds in closed quantum systems, providing direct access to disorder regimes where thermalization or its absence can be reliably observed.

Flakelike particles suspended in fluid flows exhibit complex orientational dynamics that are highly sensitive to local shear and vorticity. To investigate the conditions under which their initially isotropic orientation distributions evolve into anisotropic states, we model particle orientation as a nonlinear phase oscillator subjected to multifrequency external forcing along Lagrangian trajectories. By applying Fourier decomposition to time-dependent velocity gradients, we identify resonance conditions and formulate phase-locking phenomena as hyperplanes with finite width in multidimensional frequency space. Numerical simulations confirm the emergence, collision, and persistence of these locking hyperplanes, which correspond structurally to Arnold tongues and devil's staircases known from classical synchronization theory. This framework quantitatively predicts anisotropic orientation alignment and unifies particle aggregation with externally driven synchronization phenomena. Beyond fluid mechanics, the generalized description provides a versatile theoretical basis for multifrequency locking in diverse nonlinear oscillator systems such as optics, thermoacoustics, and optomechanics.

We derive the equations governing the motion of Kerr solitons in pair waveforms. Recent experiments in microresonators have studied a variety of interaction effects in multisoliton waveforms, including collisions and formation of soliton molecules and crystals. Here we analyze the effective interaction that arises from the coupling of the soliton-tail overlap nonlinearity with global soliton variables associated with the breaking of translation symmetry. The interaction is either purely repulsive, or alternates between attraction and repulsion, according to whether the decay of the soliton tails is monotone or oscillatory. In the latter case, stable fixed points of the effective dynamical system signify stable soliton molecule configuration, but the exponential weakening of the interaction with increasing intersoliton separation may prevent the molecule from forming in experimentally accessible time scales. Our theory becomes asymptotically exact in the large-separation limit, and we verify the theoretical calculations using soliton trajectories extracted from direct numerical solutions of the wave equation.

Synergy between evolutionary dynamics of cooperation and fluctuating states of a shared resource being consumed by the cooperators is essential for averting the tragedy of the commons. Not only in humans, but also in the cognitively limited organisms, this interplay between the resource and the cooperation is ubiquitously witnessed. The strategically interacting players engaged in such game-environment feedback scenarios naturally pick strategies based on their perception of the environmental state. Such perception invariably happens through some sensory information channels that the players are endowed with. The unfortunate reality is that any sensory channel must be noisy due to various factors; consequently, the perception of the environmental state becomes faulty, rendering the players incapable of adopting the strategy that they otherwise would. Intriguingly, the situation is not as bad as it sounds. Here we introduce the hitherto neglected information channel between players and the environment into the paradigm of stochastic evolutionary games with a view to bringing forward the counterintuitive possibility of emergence and sustenance of cooperation on account of the noise in the channel. Our primary study is in the simplest nontrivial setting of a two-state stochastically fluctuating resource harnessed by a large unstructured population of cooperators and defectors adopting either memory-1 strategies or reactive strategies while engaged in repeated two-player interactions. The effect of a noisy information channel in enhancing the cooperation in a reactive-strategied population is unprecedented. We find that the propensity of cooperation in the population is inversely related to the mutual information (normalized by the channel capacity) of the corresponding information channel.