Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an $\mathrm{unsupervised}$ variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

We propose a phase diagram for the shear flow of dry granular particles in two dimensions based on simulations and a phenomenological Landau theory for a nonequilibrium first-order phase transition. Our approach incorporates both frictional as well as frictionless particles. The most important feature of the frictional phase diagram is reentrant flow and a critical jamming point at finite stress. In the frictionless limit the regime of reentrance vanishes and the jamming transition is continuous with a critical point at zero stress. The jamming phase diagrams derived from the model agree with the experiments of Bi et al. [Nature (London) 480, 355 (2011)] and brings together previously conflicting numerical results.

We investigate the phase sequence of biaxial liquid crystals, based on a general quadratic model Hamiltonian over the relevant parameter space, with a Monte Carlo simulation which constructs equilibrium ensembles of microstates, overcoming possible (free) energy barriers (combining entropic and frontier sampling techniques). The resulting phase diagram qualitatively differs from the universal phase diagram predicted earlier from mean-field theory (MFT), as well as the Monte Carlo simulations with the Metropolis algorithm. The direct isotropic-to-biaxial transition predicted by the MFT is replaced in certain regions of the space by the onset of an additional intermediate biaxial phase of very low order, leading to the sequence $N_B\text{−}{N}_{B1}\text{−}I$. This is due to inherent barriers to fluctuations of the components comprising the total energy, and may explain the difficulties in the experimental realization of these phases.

Based on the Fokker-Planck equation we investigate the transport of an overdamped colloidal particle in a static, asymmetric periodic potential supplemented by a time-dependent, delayed feedback force, $F_{\mathrm{fc}}$. For a given time $t$, $F_{\mathrm{fc}}$ depends on the status of the system at a previous time $t-{\tau }_{\mathrm{D}}$, with ${\tau }_{\mathrm{D}}$ being a delay time, specifically on the delayed mean particle displacement (relative to some “switching position”). For nonzero delay times $F_{\mathrm{fc}}\left(t\right)$ develops nearly regular oscillations, generating a net current in the system. Depending on the switching position, this current is nearly as large or even larger than that in a conventional open-loop rocking ratchet. We also investigate thermodynamic properties of the delayed nonequilibrium system and we suggest an underlying Langevin equation which reproduces the Fokker-Planck results.

The universal bound on specific entropy (entropy-to-energy ratio) was originally inferred from black hole thermodynamics. Here we show from classical thermodynamics alone that for a system at fixed volume or fixed pressure, the entropy-to-energy ratio $S/E$ has a unique maximum, ${(S/E)}_{\max }$. A simple argument from quantum dynamics allows one to set a model-independent upper bound on ${(S/E)}_{\max }$ which is usually much tighter than the universal bound. We illustrate with two examples.

The classic Landauer bound can be lowered when erasure errors are permitted. Here we point out that continuous phase transitions characterized by an order parameter can also be viewed as information erasure by resetting a certain number of bits to a standard value. The information-theoretic expression for the generalized Landauer bound in terms of error probability implies thus a universal form for the thermodynamic entropy in the partially ordered phase. We explicitly show that the thermodynamic entropy as a function of interaction parameters and temperature is identical to the information-theoretic expression in terms of error probability alone in the specific example of the Hopfield neural network model of associative memory, a distributed information-processing system of many interacting stochastic bits. In this framework the Landauer bound sets a lower limit for the work associated with “remembering” rather than “forgetting.”

Motivated by recent experiments in neuroscience which indicate that neuronal avalanches exhibit scale invariant behavior similar to self-organized critical systems, we study the role of noisy (nonconservative) local dynamics on the critical behavior of a sandpile model which can be taken to mimic the dynamics of neuronal avalanches. We find that despite the fact that noise breaks the strict local conservation required to attain criticality, our system exhibits true criticality for a wide range of noise in various dimensions, given that conservation is respected on the average. Although the system remains critical, exhibiting finite-size scaling, the value of critical exponents change depending on the intensity of local noise. Interestingly, for a sufficiently strong noise level, the critical exponents approach and saturate at their mean-field values, consistent with empirical measurements of neuronal avalanches. This is confirmed for both two and three dimensional models. However, the addition of noise does not affect the exponents at the upper critical dimension ($D=4$). In addition to an extensive finite-size scaling analysis of our systems, we also employ a useful time-series analysis method to establish true criticality of noisy systems. Finally, we discuss the implications of our work in neuroscience as well as some implications for the general phenomena of criticality in nonequilibrium systems.

Information erasure inevitably leads to the generation of heat. Minimizing this dissipation will be crucial for developing small-scale information processing systems, but little is known about the optimal procedures required. We have obtained closed-form expressions for maximally efficient erasure cycles for deletion of a classical bit of information stored by the position of a particle diffusing in a double-well potential. We find that the extra heat generated beyond the Landauer bound is proportional to the square of the Hellinger distance between the initial and final states divided by the cycle duration, which quantifies how far out of equilibrium the system is driven. Finally, we demonstrate close agreement between the exact optimal cycle and the protocol found using a linear response framework.

We investigate the effect of a temperature-dependent viscosity on the onset of thermal convection in a horizontal layer of a binary fluid mixture that is heated from below. For an exponential temperature dependence of the viscosity, we find, in binary mixtures as a function of a positive separation ratio $\psi$ and beyond a certain viscosity contrast, a discontinuous transition between two stationary convection modes having different wavelengths. In the range of negative values of the separation ratio $\psi$, a (continuous or discontinuous) transition from an oscillatory to a stationary onset of convection occurs beyond a certain viscosity contrast, and for large values of the viscosity ratio, the oscillatory onset of convection is suppressed.

We present experiments in which we use an electric field to switch between different configurations in the cellular patterns induced in a confined nematic liquid crystal by the contact with a surfactant monolayer that features lateral order and surface defects. By using different combinations of far-field alignment and mesogen dielectric anisotropy, we unravel the nature and stability of point defects and disclinations resulting from the hybrid boundary conditions.

The present work is devoted to the study of the thermo-optical properties of liquid crystals doped with traces of fullerene $C_{60}$ at the vicinity of the nematic–smectic-$A$ phase transition. By using the time-resolved $Z$-scan technique, we measure the temperature dependence of the thermo-optical coefficient and the thermal diffusivity. Our results reveal that the critical behavior of the thermal diffusivity is strongly affected by the fullerene addition. We provide a detailed discussion under the light of the distinct mechanisms behind the thermal transport in liquid-crystal samples.

Using Monte Carlo simulations and advanced knot localization methods, we analyze the length and distribution of prime components in composite knots tied on freely jointed rings. For increasing contour length, we observe the progressive factorization of composite knots into separated prime components. However, we observe that a complete factorization, equivalent to the “decorated ring” picture, is not obtained even for rings of contour lengths $N\simeq 3N_0$, about tens of times the most probable length of the prime knots tied on the rings. The decorated ring hypothesis has been used in the literature to justify the factorization of composite knot probabilities into the knotting probabilities of their prime components. Following our results, we suggest that such a hypothesis may not be necessary to explain the factorization of the knotting probabilities, at least when polymers excluding volume is not relevant. We rationalize the behavior of the system through a simple one-dimensional model in which prime knots are replaced by slip links randomly placed on a circle, with the only constraint being that the length of the loops has the same distribution as that of the length of the corresponding prime knots.

The dynamics of polymer melts in both the unentangled and entangled regimes is described by a Langevin equation for the correlated motion of a group of chains, interacting through both intra- and inter-molecular potentials. Entanglements are represented by an intermolecular monomer-monomer confining potential that has no effect on short chains, while interpolymer interactions, responsible for correlated motion and subdiffusive center-of-mass dynamics, are represented by an intermolecular center-of-mass potential derived from the Ornstein-Zernike equation. This potential ensures that the liquid of phantom chains reproduces the compressibility and free energy of the real samples. For polyethylene melts the calculated dynamic structure factor is found to be in quantitative agreement with neutron spin echo experiments of polyethylene melts with chain lengths that span both the unentangled and the entangled regimes. The theory shows a progressive localization of the cooperative chain dynamics at the crossover from the unentangled to the entangled regime, in the spirit of the reptation model.

Traditionally, the evolution of cooperation has been studied on single, isolated networks. Yet a player, especially in human societies, will typically be a member of many different networks, and those networks will play different roles in the evolutionary process. Multilayer networks are therefore rapidly gaining on popularity as the more apt description of a networked society. With this motivation, we here consider two-layer scale-free networks with all possible combinations of degree mixing, wherein one network layer is used for the accumulation of payoffs and the other is used for strategy updating. We find that breaking the symmetry through assortative mixing in one layer and/or disassortative mixing in the other layer, as well as preserving the symmetry by means of assortative mixing in both layers, impedes the evolution of cooperation. We use degree-dependent distributions of strategies and cluster-size analysis to explain these results, which highlight the importance of hubs and the preservation of symmetry between multilayer networks for the successful resolution of social dilemmas.

By developing the concepts of strength of incoherence and discontinuity measure, we show that a distinct quantitative characterization of chimera and multichimera states which occur in networks of coupled nonlinear dynamical systems admitting nonlocal interactions of finite radius can be made. These measures also clearly distinguish between chimera or multichimera states (both stable and breathing types) and coherent and incoherent as well as cluster states. The measures provide a straightforward and precise characterization of the various dynamical states in coupled chaotic dynamical systems irrespective of the complexity of the underlying attractors.

Achieving ignition in inertial confinement fusion (ICF) requires the formation of a high-temperature ($>$10 keV) central hot spot. Turbulence has been suggested as a mechanism for degrading the hot-spot conditions by altering transport properties, introducing colder, mixed material, or reducing the conversion of radially directed kinetic energy to hot-spot heating. We show, however, that the hot spot is very viscous, and the assumption of turbulent conditions in the hot spot is incorrect. This work presents the first high-resolution, three-dimensional simulations of National Ignition Facility (NIF) implosion experiments using detailed knowledge of implosion dynamics and instability seeds and including an accurate model of physical viscosity. We find that when viscous effects are neglected, the hot spot can exhibit a turbulent kinetic energy cascade. Viscous effects, however, are significant and strongly damp small-scale velocity structures, with a hot-spot Reynolds number in the range of only $10\text{--}100$.

We introduce a class of nonreciprocal metamaterials based on composite assemblies of metallic and biased ferrimagnetic elements. We show that such structures act as ultrathin one-way glasses due to the competition between two modes at the surface of the ferrimagnetic elements—a low-loss surface wave that transmits the signal on the other side of the structure and a surface spin-wave resonance that produces strong isolation levels. These findings can be adapted to existing metamaterial geometries, offering a blueprint to achieve unidirectional propagation in a variety of artificial media at radio, microwave, and millimeter wave frequencies.

The probability distributions and associated Fokker-Planck equation of the recently postulated entropic form, $S_{q,\delta }$, are investigated. This entropy was proposed as an unification of the well-known $S_q$ of nonextensive-statistical mechanics and $S_{\delta }$, which appeared lately as a possibly appropriate candidate for the black-hole entropy. The connection between $S_{q,\delta }$ and a nonlinear Fokker-Planck equation, such as to satisfy an H-theorem, is explored. The stationary-state probability distribution follows a transcendental equation, which is solved numerically for typical values of $q$ and $\delta$. The same transcendental equation is obtained through the maximum-entropy principle, showing that the two procedures are equivalent.

We use the first Betti number of a complex to analyze the morphological structure of granular samples in mechanical equilibrium. We investigate two-dimensional granular packings after a tapping process by means of both simulations and experiments. States with equal packing fraction obtained with different tapping intensities are distinguished after the introduction of a filtration parameter which determines the particles (nodes in the network) that are joined by an edge. This is accomplished by just using the position of the particles obtained experimentally and no other information about the possible contacts, or magnitude of forces.