Laser-accelerated proton beams are applicable to several research areas within high-energy density science, including warm dense matter generation, proton radiography, and inertial confinement fusion, which all involve transport of the beam through matter. We report on experimental measurements of intense proton beam transport through plastic foam blocks. The intense proton beam was accelerated by the $10\text{ps}, 700J$ OMEGA EP laser irradiating a curved foil target, and focused by an attached hollow cone. The protons then entered the foam block of density $0.38\text{g}/{\text{cm}}^3$ and thickness 0.55 or $1.00\text{mm}$. At the rear of the foam block, a Cu layer revealed the cross section of the intense beam via proton- and hot electron-induced Cu-${\mathrm{K}}_{\alpha }$ emission. Images of x-ray emission show a bright spot on the rear Cu film indicative of a forward-directed beam without major breakup. 2D fluid-PIC simulations of the transport were conducted using a unique multi-injection source model incorporating energy-dependent beam divergence. Along with postprocessed calculations of the $\mathrm{Cu}-K_{\alpha }$ emission profile, simulations showed that protons retain their ballistic transport through the foam and are able to heat the foam up to several keV in temperature. The total experimental emission profile for the $1.0\text{mm}$ foam agrees qualitatively with the simulated profile, suggesting that the protons indeed retain their beamlike qualities.

An open quantum system in contact with an infinite bath approaches equilibrium, while the state of the bath remains unchanged. If the bath is finite, the open system still relaxes to equilibrium but it induces a dynamical evolution of the bath state. In this paper, we study the dynamics of open quantum systems in contact with finite baths. We obtain a hierarchy of master equations that improve their accuracy by including more dynamical information of the bath. For instance, as the least accurate but simplest description in the hierarchy, we obtain the conventional Born-Markov-secular master equation. Remarkably, our framework works even if the measurements of the bath energy are imperfect, which not only is more realistic but also unifies the theoretical description. Also, we discuss this formalism in detail for a particular noninteracting environment where the Boltzmann temperature and the Kubo-Martin-Schwinger relation naturally arise. Finally, we apply our hierarchy of master equations to study the central spin model.

The Jarzynski estimator is a powerful tool that uses nonequilibrium statistical physics to numerically obtain partition functions of probability distributions. The estimator reconstructs partition functions with trajectories of the simulated Langevin dynamics through the Jarzynski equality. However, the original estimator suffers from slow convergence because it depends on rare trajectories of stochastic dynamics. In this paper, we present a method to significantly accelerate the convergence by introducing deterministic virtual trajectories generated in augmented state space under the Hamiltonian dynamics. We theoretically show that our approach achieves second-order acceleration compared to a naive estimator with the Langevin dynamics and zero variance estimation on harmonic potentials. We also present numerical experiments on three multimodal distributions and a practical example in which the proposed method outperforms the conventional method, and we provide theoretical explanations.

Matrix models showing a chaotic-integrable transition in the spectral statistics are important for understanding many-body localization (MBL) in physical systems. One such example is the $\beta$ ensemble, known for its structural simplicity. However, eigenvector properties of the $\beta$ ensemble remain largely unexplored, despite energy level correlations being thoroughly studied. In this work we numerically study the eigenvector properties of the $\beta$ ensemble and find that the Anderson transition occurs at $\gamma =1$ and ergodicity breaks down at $\gamma =0$ if we express the repulsion parameter as $\beta =N^{-\gamma }$. Thus other than the Rosenzweig-Porter ensemble (RPE), the $\beta$ ensemble is another example where nonergodic extended (NEE) states are observed over a finite interval of parameter values $(0<\gamma <1)$. We find that the chaotic-integrable transition coincides with the breaking of ergodicity in the $\beta$ ensemble but with the localization transition in the RPE or the 1D disordered spin-1/2 Heisenberg model. As a result, the dynamical timescales in the NEE regime of the $\beta$ ensemble behave differently than the latter models.

We investigate numerically the impact process of a particle of diameter $d$ and velocity $V_i$ onto a cohesive granular packing made of similar particles via two-dimensional discrete element method simulations. The cohesion is ensured by liquid bridges between neighboring particles and described by short range attraction force based on capillary modeling. The outcome of the impact is analyzed through the production of ejected particles from the packing, referred to as the splash process. We quantify this production as a function of the impact velocity for various capillary strength $\mathrm{\Gamma }$ and liquid content $\mathrm{\Omega }$. The numerical data indicate that the splash process is modified when the dimensionless cohesion number $\text{Co}=6\mathrm{\Gamma }/{\rho }_{p}g{d}^2$ (where ${\rho }_p$ is the particle density, $d$ its diameter, and $g$ the gravitational acceleration) exceeds a critical value of the order of the unity. Above this value, we highlight that the ejection process is triggered above a threshold impact Froude number, $\text{Fr}=V_i/\sqrt{gd}$, which depends both on $\mathrm{\Gamma }$ and $\mathrm{\Omega }$ and scales as ${\mathrm{\Gamma }}^{\beta }{\mathrm{\Omega }}^{\delta }$, where the values of the exponents are found close to $1/2$ and $1/6$, respectively, and can be derived from rational physical arguments. Importantly, we show that, above the threshold, the number of splashed particles follows a linear law with the impact Froude number as in the cohesionless case.

The apparent ion temperature and mean velocity of the dense deuterium tritium fuel layer of an inertial confinement fusion target near peak compression have been measured using backscatter neutron spectroscopy. The average isotropic residual kinetic energy of the dense deuterium tritium fuel is estimated using the mean velocity measurement to be $\sim 103$ J across an ensemble of experiments. The apparent ion-temperature measurements from high-implosion velocity experiments are larger than expected from radiation-hydrodynamic simulations and are consistent with enhanced levels of shell decompression. These results suggest that high-mode instabilities may saturate the scaling of implosion performance with the implosion velocity for laser-direct-drive implosions.

We study how the herd immunity threshold and the expected epidemic size depend on homophily with respect to vaccine adoption. We find that the presence of homophily considerably increases the critical vaccine coverage needed for herd immunity and that strong homophily can push the threshold entirely out of reach. The epidemic size monotonically increases as a function of homophily strength for a perfect vaccine, while it is maximized at a nontrivial level of homophily when the vaccine efficacy is limited. Our results highlight the importance of vaccination homophily in epidemic modeling.

The suppression of the gradient-drift driven instability and the transition to the high-magnetic-confinement mode are experimentally observed in a cylindrical partially magnetized $\mathrm{E}\times \mathrm{B}$ plasma using an additional biasable electrode installed at the radial edge. When a positive voltage is applied to the electrode, an electron-loss channel forms in its direction, breaking the spatially symmetric nonambipolar flow. Finally, in the steady state, the plasma density tends to peak in the plasma core, approaching plasma densities that are four times larger than those observed in the case where the instability is the strongest. A high-magnetic-confinement mode with a reduced edge-to-center density ratio of 0.16 is observed, which demonstrates that the saturation of magnetic confinement due to the gradient-drift driven instability can be prevented by an asymmetric nonambipolar flow.

We consider a walker moving in a one-dimensional interval with absorbing boundaries under the effect of Markovian resettings to the initial position. The walker's motion follows a random walk characterized by a general waiting time distribution between consecutive short jumps. We investigate the existence of an optimal reset rate, which minimizes the mean exit passage time, in terms of the statistical properties of the waiting time probability. Generalizing previous results, we find that when the waiting time probability has first and second finite moments, resetting can be either (i) never beneficial, (ii) beneficial depending on the distance of the reset point to the boundary, or (iii) always beneficial. Instead, when the waiting time probability has the first or the two first moments diverging we find that resetting is always beneficial. Finally, we have also found that the optimal strategy to exit the domain depends on the reset rate. For low reset rates, walkers with exponential waiting times are found to be optimal, while for high reset rate, anomalous waiting times optimize the search process.

Recent results revived the interest in the implementation of analog devices able to perform brainlike operations. Here we introduce a training algorithm for a memristor network which is inspired by previous work on biological learning. Robust results are obtained from computer simulations of a network of voltage-controlled memristive devices. Its implementation in hardware is straightforward, being scalable and requiring very little peripheral computation overhead.

Living cells can measure chemical concentrations with remarkable accuracy, even though these measurements are inherently noisy due to the stochastic binding of the ligand to the receptor. A widely used mechanism for reducing the sensing error is to increase the effective number of measurements via receptor time integration. This mechanism is implemented via the signaling network downstream of the receptor, yet how it is implemented optimally given constraints on cellular resources such as protein copies and time remains unknown. To address this question, we employ our sampling framework [Govern and ten Wolde, Proc. Natl. Acad. Sci. USA 111, 17486 (2014)] and extend it here to time-varying ligand concentrations. This framework starts from the observation that the signaling network implements the mechanism of time integration by discretely sampling the ligand-binding state of the receptor and storing these states into chemical modification states of the readout molecules downstream. It reveals that the sensing error has two distinct contributions: a sampling error, which is determined by the number of samples, their independence, and their accuracy, and a dynamical error, which depends on the timescale that these samples are generated. We test our previously identified design principle, which states that in an optimally designed system the number of receptors and their integration time, which determine the number of independent concentration measurements at the receptor level, equals the number of readout proteins, which store these measurements. We show that this principle is robust to the dynamics of the input and the relative costs of the receptor and readout proteins: these resources are fundamental and cannot compensate each other.

Tissues are generally subjected to external stresses, a potential stimulus for their differentiation or remodeling. While single-cell rheology has been extensively studied leading to controversial results about nonlinear response, mechanical tissue behavior under external stress is still poorly understood, in particular, the way individual cell properties translate at the tissue level. Herein, using magnetic cells we were able to form perfectly monitored cellular aggregates (magnetic molding) and to deform them under controlled applied stresses over a wide range of timescales and amplitudes (magnetic rheometer). We explore the rheology of these minimal tissue models using both standard assays (creep and oscillatory response) as well as an innovative broad spectrum solicitation coupled with inference analysis thus being able to determine in a single experiment the best rheological model. We find that multicellular aggregates exhibit a power-law response with nonlinearities leading to tissue stiffening at high stress. Moreover, we reveal the contribution of intracellular (actin network) and intercellular components (cell-cell adhesions) in this aggregate rheology.

We have applied zero-time-averaged alternating electric fields to DNA molecules in a cross-shaped nanofluidic slit. We observed a net drift of DNA molecules, the magnitude of which depends on the square of the electric field amplitude. From the rate of accumulation of DNA at the center of the device, we derive an estimate for the second-order electrophoretic mobility, ${\mu }_2$. We observe that focusing is absent at a dipole rotation frequency >20 Hz, which suggests that ${\mu }_2$ depends on the frequency of the alternating fields. The observation of a nonzero ${\mu }_2$ raises the possibility of frequency-dependent electrophoretic DNA separation by length achievable in the absence of a sieving matrix.

In this paper a combined neutron scattering and quantum simulation study of the collective dynamics in liquid $\mathrm{Ne}\text{−}{\mathrm{D}}_2$ mixtures, at a temperature of $T=30\mathrm{K}$ and in the wave-vector transfer range 4 ${\mathrm{nm}}^{-1}<q<51{\mathrm{nm}}^{-1}$, is presented. Two ${\mathrm{D}}_2$ concentrations are investigated, one close to 25% molar and the other close to 50% molar, together with pure Ne. The dynamic structure factor for the centers of mass of the two molecular species is extracted from the neutron scattering data and subsequently compared with that obtained from three different quantum simulation methods, such as ring polymer molecular dynamics and two slightly different versions of the Feynman-Kleinert approach. A general agreement is found, even though some discrepancies both among simulations, and between simulations and experimental data, can be observed. In order to clarify the physical meaning of the present spectroscopic results, an analysis of the longitudinal current spectral maxima is carried out showing the peculiarities of the ${\mathrm{D}}_2$ center-of-mass dynamics in these mixtures. A comparison with the centroid molecular dynamics results obtained for the ${\mathrm{D}}_2$ center-of-mass self-dynamics in the same liquid mixtures is finally proposed.

Ion field emission from the surface of a dielectric liquid is commonly modeled as a kinetic process with an energy barrier lowered by the strength of the electric field. Expressions for the energy barrier exist for simplified cases such as a planar surface and a conducting sphere. This article derives an analytical expression for the more general case of a dielectric sphere, which is the continuum model and geometry for most cases of interest. The energy barrier is computed using the method of image charges, and compared to existing expressions for simpler models. The energy barrier increases at decreasing dielectric constant and decreasing radius of curvature. Ion emission from typical systems (the ideal Taylor cone and charged nanodroplets) differs substantially when calculated with either our model or with existing simpler models.

We study the equilibration process of a one-dimensional lattice with transverse motions and external magnetic field. Starting from certain initial states, the system commonly reaches a metastable transient state shortly and then stays there for an extremely long time before it finally arrives in the ergodic equilibrium state. The relaxation time $T_{\mathrm{eq}}$ diverges even much more rapidly than exponential, which, compared with the widely reported power-law or even exponential divergence in many other systems, implies much higher stability of the transient state. Two correlation functions, the spatiotemporal correlation of the local energy and the autocorrelation of global heat current, are studied in both the metastable transient and the final equilibrium states. It is revealed that the correlations behave entirely differently in the two different states. In the former case they suggest normal heat diffusion and normal heat conduction; whereas in the latter one they indicate super heat diffusion and anomalous heat conduction. More importantly, we confirm that a general relation which connects the two correlations keeps valid not only in the equilibrium state but in the metastable transient state as well. The universality of the connection is, thus, extended.

One of the most important devices emerging from quantum technology are quantum batteries. However, self-discharging, the process of charge wasting of quantum batteries due to decoherence phenomenon, limits their performance, measured by the concept of ergotropy and half-life time of the quantum battery. The effects of local field fluctuation, introduced by the disorder term in the Hamiltonian of the system, on the performance of the quantum batteries is investigated in this paper. The results reveal that the disorder term could compensate disruptive effects of the decoherence, i.e., self-discharging, and hence improve the performance of the quantum battery via “incoherent gain of ergotropy” procedure. Adjusting the strength of the disorder parameter to a proper value and choosing a suitable initial state of the quantum battery, the amount of free ergotropy, defined with respect to the free Hamiltonian, could exceed the amount of initial stored ergotropy. In addition harnessing the degree of the disorder parameter could help to enhance the half-life time of the quantum battery. This study opens perspective to further investigation of the performance of quantum batteries that explore disorder and many-body effects.

We investigate the performance of entropy estimation methods, based either on block entropies or compression approaches, in the case of bidimensional sequences. We introduce a validation data set made of images produced by a large number of different natural systems, in the vast majority characterized by long-range correlations, which produce a large spectrum of entropies. Results show that the framework based on lossless compressors applied to the one-dimensional projection of the considered data set leads to poor estimates. This is because higher dimensional correlations are lost in the projection operation. The adoption of compression methods which do not introduce dimensionality reduction improves the performance of this approach. By far, the best estimation of the asymptotic entropy is generated by the faster convergence of the traditional block-entropies method. As a by-product of our analysis, we show how a specific compressor method can be used as a potentially interesting technique for automatic detection of symmetries in textures and images.

We address the interplay between local and global symmetries in determining the continuum limit of two-dimensional lattice scalar theories characterized by $\text{SO}\left(N_c\right)$ gauge symmetry and non-Abelian $\text{O}\left(N_f\right)$ global invariance. We argue that, when a quartic interaction is present, the continuum limit of these models corresponds in some cases to the gauged nonlinear $\sigma$ model field theory associated with the real Grassmannian manifold $\text{SO}\left(N_f\right)/(\text{SO}\left(N_c\right)\times \text{SO}(N_f-N_c)$), which is characterized by the invariance under the color-flavor reflection $N_c\leftrightarrow N_f-N_c$. Monte Carlo simulations and finite-size scaling analyses, performed for $N_f=7$ and several values of $N_c$, confirm the emergence of the color-flavor reflection symmetry in the scaling limit and support the identification of the continuum limit.