Density of states of a binary Lennard-Jones Glass

We calculate the density of states of a binary Lennard-Jones glass using a recently proposed Monte Carlo algorithm. Unlike traditional molecular simulation approaches, the algorithm samples distinct configurations according to self-consistent estimates of the density of states, thereby giving rise to uniform internal-energy histograms. The method is applied to simulate the equilibrium, low-temperature thermodynamic properties of a widely studied glass former consisting of a binary mixture of Lennard-Jones particles. We show how a density-of-states algorithm can be combined with particle identity swaps and configurational bias techniques to study that system. Results are presented for the energy and entropy below the mode coupling temperature.Comment: 6 pages, 3 figures, accepted by J Chem Phy

Constant Pressure Hybrid Molecular Dynamics-Monte Carlo Simulations

New hybrid Molecular Dynamics-Monte Carlo methods are proposed to increase the efficiency of constant-pressure simulations. Two variations of the isobaric Molecular Dynamics component of the algorithms are considered. In the first, we use the extended-ensemble method of Andersen [H. C. Andersen J. Chem. Phys. {\bf 72},2384 (1980)]. In the second, we arrive at a new constant-pressure Monte Carlo technique based on the reversible generalization of the weak-coupling barostat [H. J. C. Berendsen et. al J. Chem. Phys. {\bf 81}, 3684(1984)]. This latter technique turns out to be highly effective in equilibrating and maintaining a target pressure. It is superior to the extended-ensemble method, which in turn is superior to simple volume-rescaling algorithms. The efficiency of the proposed methods is demonstrated by studying two systems. The first is a simple Lennard-Jones fluid. The second is a mixture of polyethylene chains of 200 monomers.Comment: 10 pages, 4 figure

Density of States Monte Carlo Method for Simulation of Fluids

A Monte Carlo method based on a density-of-states sampling is proposed for study of arbitrary statistical mechanical ensembles in a continuum. A random walk in the two-dimensional space of particle number and energy is used to estimate the density of states of the system; this density of states is continuously updated as the random walk visits individual states. The validity and usefulness of the method are demonstrated by applying it to the simulation of a Lennard-Jones fluid. Results for its thermodynamic properties, including the vapor-liquid phase coexistence curve, are shown to be in good agreement with high-accuracy literature data.Comment: 5 pages, 3 figures, accepted by J Chem Phy

Highly-efficient noise-assisted energy transport in classical oscillator systems

Photosynthesis is a biological process that involves the highly-efficient transport of energy captured from the sun to a reaction center, where conversion into useful biochemical energy takes place. Even though one can always use a quantum perspective to describe any physical process, since everything follows the laws of Quantum Mechanics, is the use of quantum theory imperative to explain this high efficiency? Making use of the quantum-classical correspondence of electronic energy transfer recently introduced by Eisfeld and Briggs [Phys. Rev. E 85, 046118 (2012)], we show here that the highly-efficient noise-assisted energy transport described by Rebentrost et al. [New J. Phys. 11, 033003 (2009)], and Plenio and Huelga [New J. Phys. 10, 113019 (2008)], as the result of the interplay between the quantum coherent evolution of the photosynthetic system and noise introduced by its surrounding environment, it can be found as well in purely classical systems. The wider scope of applicability of the enhancement of energy transfer assisted by noise might open new ways for developing new technologies aimed at enhancing the efficiency of a myriad of energy transfer systems, from information channels in micro-electronic circuits to long-distance high-voltage electrical lines.Comment: 4 pages, 3 figure

The Berry phase and the pump flux in stochastic chemical kinetics

We study a classical two-state stochastic system in a sea of substrates and products (absorbing states), which can be interpreted as a single Michaelis-Menten catalyzing enzyme or as a channel on a cell surface. We introduce a novel general method and use it to derive the expression for the full counting statistics of transitions among the absorbing states. For the evolution of the system under a periodic perturbation of the kinetic rates, the latter contains a term with a purely geometrical (the Berry phase) interpretation. This term gives rise to a pump current between the absorbing states, which is due entirely to the stochastic nature of the system. We calculate the first two cumulants of this current, and we argue that it is observable experimentally