Abstract: We studied the structural and spectral properties of a classical system consisting of a finite number of particles, moving in two dimensions, and interacting through a repulsive logarithmic potential and held together by an anisotropic harmonic potential. Increasing the anisotropy of the confinement potential can drive the system from a two-dimensional (2D) to a one-dimensional (1D) configuration. This change occurs through a sequence of structural transitions of first and second order which are reflected in the normal mode frequencies. Our results of the ground state configurations are compared with recent experiments and we obtained a satisfactory agreement. The transition from the 1D line structure to the 2D structure occurs through a zigzag transition which is of second order. We found analytical expressions for the eigenfrequencies before the zigzag transition, which allowed us to obtain an analytical expression for the anisotropy parameter at which the zigzag transition occurs as a function of the number of particles in the system.

Abstract: We study the mixing of two different kinds of particles, having different charge and/or mass, interacting through a pure Coulomb potential, and confined in a parabolic trap. The structure of the cluster and its normal mode spectrum are analyzed as a function of the ratio of the charges (mass ratio) of the two types of particles. We show that particles are not always arranged in a shell structure. Mixing of the particles goes hand in hand with a large number of metastable states. The normal modes of the system are obtained, and we find that some of the special modes can be tuned by varying the ratio between the charges (masses) of the two species. The degree of mixing of the two type of particles is summarized in a phase diagram, and an order parameter that describes quantitatively the mixing between particles is defined.

Abstract: Diffusive properties of a monodisperse system of interacting particles confined to a quasi-one-dimensional channel are studied using molecular dynamics simulations. We calculate numerically the mean-squared displacement (MSD) and investigate the influence of the width of the channel (or the strength of the confinement potential) on diffusion in finite-size channels of different shapes (i.e., straight and circular). The transition from single-file diffusion to the two-dimensional diffusion regime is investigated. This transition [ regarding the calculation of the scaling exponent (alpha) of the MSD <Delta x(2)(t)> proportional to t(alpha)] as a function of the width of the channel is shown to change depending on the channel's confinement profile. In particular, the transition can be either smooth (i.e., for a parabolic confinement potential) or rather sharp (i.e., for a hard-wall potential), as distinct from infinite channels where this transition is abrupt. This result can be explained by qualitatively different distributions of the particle density for the different confinement potentials.

Abstract: In a recent paper, Arita et al. [Phys. Rev. E 90, 052108 (2014)] consider the transport properties of a class of generalized exclusion processes. Analytical expressions for the transport-diffusion coefficient are derived by ignoring correlations. It is claimed that these expressions become exact in the hydrodynamic limit. In this Comment,we point out that (i) the influence of correlations upon the diffusion does not vanish in the hydrodynamic limit, and (ii) the expressions for the self- and transport diffusion derived by Arita et al. are special cases of results derived in Becker et al. [Phys. Rev. Lett. 111, 110601 (2013)].

Abstract: The autoregressive neural networks are emerging as a powerful computational tool to solve relevant problems in classical and quantum mechanics. One of their appealing functionalities is that, after they have learned a probability distribution from a dataset, they allow exact and efficient sampling of typical system configurations. Here we employ a neural autoregressive distribution estimator (NADE) to boost Markov chain Monte Carlo (MCMC) simulations of a paradigmatic classical model of spin-glass theory, namely, the two-dimensional Edwards-Anderson Hamiltonian. We show that a NADE can be trained to accurately mimic the Boltzmann distribution using unsupervised learning from system configurations generated using standard MCMC algorithms. The trained NADE is then employed as smart proposal distribution for the Metropolis-Hastings algorithm. This allows us to perform efficient MCMC simulations, which provide unbiased results even if the expectation value corresponding to the probability distribution learned by the NADE is not exact. Notably, we implement a sequential tempering procedure, whereby a NADE trained at a higher temperature is iteratively employed as proposal distribution in a MCMC simulation run at a slightly lower temperature. This allows one to efficiently simulate the spin-glass model even in the low-temperature regime, avoiding the divergent correlation times that plague MCMC simulations driven by local-update algorithms. Furthermore, we show that the NADE-driven simulations quickly sample ground-state configurations, paving the way to their future utilization to tackle binary optimization problems.

Abstract: Strong terahertz (1THz=1012Hz) radiation can be generated by the electron oscillation in fs-laser-induced wake fields. The interaction of a fs-laser pulse with a low-density plasma layer is studied in detail using numerical simulations. The spatial distribution and temporal evolution of terahertz electron current developed in a low-density plasma layer are presented, which enables us to calculate the intensity distribution of THz radiation. It is shown that laser and plasma parameters, such as laser intensity, pulse width, and background plasma density, are of key importance to the process. The optimum condition for wake-field excitation and terahertz emission is discussed upon the simulation results. Radiation peaked at 6.4 THz, with 900 fs duration and 9% bandwidth, can be generated in a plasma of density 5×1017cm−3. It turns out that the maximum radiation intensity scales as n03a04 when wake field is resonantly excited, where n0 and a0 are, respectively, the plasma density and the normalized field amplitude of the laser pulse.

Abstract: Molecular dynamics simulations are used to study the effects of different cations on the permeation of charged polymers through flat capillaries with heights below 2 nm. Interestingly, we found that, despite being monovalent, Li+ , Na+ , and K+ cations have different effects on polymer permeation, which consequently affects their transmission speed throughout those capillaries. We attribute this phenomenon to the interplay of the cations' hydration free energies and the hydrodynamic drag in front of the polymer when it enters the capillary. Different alkali cations exhibit different surface versus bulk preferences in small clusters of water under the influence of an external electric field. This paper presents a tool to control the speed of charged polymers in confined spaces using cations.

Abstract: A hybrid Monte Carlofluid modeling network is developed for an argon-hydrogen mixture, to predict the effect of small amounts of hydrogen added to a dc argon glow discharge. The species considered in the model include the Ar gas atoms, electrons, Ar+ ions and fast Ar atoms, ArH+, H+, H+2 and H+3 ions, and H atoms and H2 molecules, as well as Ar metastable atoms, sputtered Cu atoms, and the corresponding Cu+ ions. Sixty-five reactions between these species are incorporated in the model. The effect of hydrogen on various calculation results is investigated, such as the species densities, the relative role of different production and loss processes for the various species, the cathode sputtering rate and contributions by different bombarding species, and the dissociation degree of H2 and the ionization degree of Ar and Cu. The calculation results are presented and discussed for 1% H2 addition, and comparison is also made with a pure argon discharge and with only 0.1% H2 addition.

Abstract: The electron distribution function (EDF) in an electron cyclotron resonance (ECR) discharge is far from Maxwellian. The self-consistent simulation of ECR discharges requires a calculation of the EDF on every magnetic line for various ion density profiles. The straightforward self-consistent simulation of ECR discharges using the Monte Carlo technique for the EDF calculation is very computer time expensive, since the electron and ion time scales are very different. An electron Boltzmann kinetic equation averaged over the fast electron bouncing and pitch-angle scattering was derived in order to develop an effective and operative tool for the fast modeling (FM) of low-pressure ECR discharges. An analytical solution for the EDF in a loss cone was derived. To check the validity of the FM, one-dimensional (in coordinate) and two-dimensional (in velocity) Monte Carlo simulation codes were developed. The validity of the fast modeling method is proved by comparison with the Monte Carlo simulations. The complete system of equations for FM is presented and ready for use in a comprehensive study of ECR discharges. The variations of plasma density and of wall and sheath potentials are analyzed by solving a self-consistent set of equations for the EDF.

Abstract: The global relaxation process after pulsed laser induced photodetachment in a rf electronegative SIH4 discharge is studied by a self-consistent kinetic one-dimensional particle-in-cell-Monte Carlo model. Our results reveal a comprehensive physical picture of the relaxation process, including the main plasma variables, after a perturbation up to the full recovery of the steady state. A strong influence of the photodetachment on the discharge is found, which results from an increase of the electron density, leading to a weaker bulk field, and hence to a drop in the high energy tail of the electron energy distribution function (EEDF), a reduction of the reaction rates of electron impact attachment and ionization, and a subsequent decrease of the positive and negative ion densities. All the plasma quantities related to electrons recover synchronously. The recovery time of the ion densities is about 1-2 orders of magnitude longer than that of the electrons due to different recovery mechanisms. The modeled behavior of all the charged particles agrees very well with experimental results from the literature. In addition, our work clarifies some unclear processes assumed in the literature, such as the relaxation of the EEDF, the evolution of the electric field, and the recovery of negative ions.

Abstract: The behavior of nanoparticles in a low-pressure silane discharge is studied with the use of a self-consistent one-dimensional fluid model. Nanoparticles of a given (prescribed) radius are formed in the discharge by the incorporation of a dust growth mechanism, i.e., by including a step in which large anions (typically Si12H−25), produced in successive chemical reactions of anions with silane molecules, are transformed into particles. Typically a few thousand anions are used for one nanoparticle. The resulting particle density and the charge on the particles are calculated with an iterative method. While the spatial distribution and the charge of the particles are influenced by the plasma, the presence of the nanoparticles will in turn influence the plasma properties. Several simulations with different particle radii are performed. The resulting density profile of the dust will greatly depend on the particle size, as it reacts to the shift of the balance of the different forces acting on the particles.