arXiv subjects

Niels Grønbech-Jensen

Publications and source records attributed to Niels Grønbech-Jensen.

At least 19 recordsLinked to original sources

arXiv2026

Linear Analysis of Stochastic Verlet-Type Integrators for Langevin Equations

We provide an analytical framework for analyzing the quality of stochastic Verlet-type integrators for simulating the Langevin equation. Focusing only on basic objective measures, we consider the ability of an integrator to correctly simulate two characteristic configurational quantities of transport, a) diffusion on a flat surface and b) drift on a tilted planar surface, as well as c) statistical sampling of a harmonic potential. For any stochastic Verlet-type integrator expressed in its configurational form, we develop closed form expressions to directly assess these three most basic quantities as a function of the applied time step. The applicability of the analysis is exemplified through twelve representative integrators developed over the past five decades, and algorithm performance is conveniently visualized through the three characteristic measures for each integrator. The GJ set of integrators stands out as the only option for correctly simulating diffusion, drift, and Boltzmann distribution in linear systems, and we therefore suggest that this general method is the one best suited for high quality thermodynamic simulations of nonlinear and complex systems, including for relatively high time steps compared to simulations with other integrators.

physics.comp-ph↗

arXiv2025

A Concurrent Multiscale Framework Coupling Direct Simulation Monte Carlo and Molecular Dynamics

We present a new method to couple the Direct Simulation Monte Carlo (DSMC) algorithm with molecular dynamics (MD). The coupling approach generalizes prior coupling methods using a cell-based decision. The approach is supported by a lifting and restricting operator, which translate length and time scales between DSMC and MD. We verify the framework on basic conservation laws, and demonstrate its usability on a hypersonic flow example. Its accuracy gain is discussed in light of conventional DSMC simulations. Advantages and limitations are discussed, and additional use cases are highlighted.

physics.comp-ph↗

arXiv2024

On the Definition of Velocity in Discrete-Time, Stochastic Langevin Simulations

We systematically develop beneficial and practical velocity measures for accurate and efficient statistical simulations of the Langevin equation with direct applications to computational statistical mechanics and molecular dynamics sampling. Recognizing that the existing velocity measures for the most statistically accurate discrete-time Verlet-type algorithms are inconsistent with the simulated configurational coordinate, we seek to create and analyze new velocity companions that both improve existing methods as well as offer practical options for implementation in existing computer codes. The work is based on the set of GJ methods that, of all methods, for any time step within the stability criteria correctly reproduces the most basic statistical features of a Langevin system; namely correct Boltzmann distribution for harmonic potentials and correct transport in the form of drift and diffusion for linear potentials. Several new and improved velocities exhibiting correct drift are identified, and we expand on an earlier conclusion that, generally, only half-step velocities can exhibit correct, time-step independent Maxwell-Boltzmann distributions. Specific practical and efficient algorithms are given in familiar forms, and these are used to numerically validate the analytically derived expectations. One especially simple algorithm is highlighted, and the ability of one of the new on-site velocities to produce statistically correct averages for a particular damping value is specified.

cond-mat.stat-mech↗

arXiv2023

On the Application of Non-Gaussian Noise in Stochastic Langevin Simulations

In light of recent advances in time-step independent stochastic integrators for Langevin equations, we revisit the considerations for using non-Gaussian distributions for the thermal noise term in discrete-time thermostats. We find that the desirable time-step invariance of the modern methods is rooted in the Gaussian noise, and that deviations from this distribution will distort the Boltzmann statistics arising from the fluctuation-dissipation balance of the integrators. We use the GJ stochastic Verlet methods as the focus of our investigation since these methods are the ones that contain the most accurate thermodynamic measures of existing methods. Within this set of methods we find that any distribution of applied noise, which satisfies the two first moments given by the fluctuation-dissipation theorem, will result in correct, time-step independent results that are generated by the first two moments of the system coordinates. However, if non-Gaussian noise is applied, undesired deviations in higher moments of the system coordinates will appear to the detriment of several important thermodynamic measures that depend especially on the fourth moments. The deviations, induced by non-Gaussian noise, become significant with the one-time-step velocity attenuation, thereby inhibiting the benefits of the methods. Thus, we conclude that the application of Gaussian noise is necessary for reliable thermodynamic results when using modern stochastic thermostats with large time steps.

cond-mat.stat-mech↗

arXiv2021

Bringing discrete-time Langevin splitting methods into agreement with thermodynamics

In light of the recently published complete set of statistically correct Gronbech-Jensen (GJ) methods for discrete-time thermodynamics, we revise a differential operator splitting method for the Langevin equation in order to comply with the basic GJ thermodynamic sampling features, namely the Boltzmann distribution and Einstein diffusion, in linear systems. This revision, which is based on the introduction of time scaling along with flexibility of a discrete-time velocity attenuation parameter, provides a direct link between the ABO splitting formalism and the GJ methods. This link brings about the conclusion that any GJ method has at least weak second order accuracy in the applied time step. It further helps identify a novel half-step velocity, which simultaneously produces both correct kinetic statistics and correct transport measures for any of the statistically sound GJ methods. Explicit algorithmic expressions are given for the integration of the new half-step velocity into the GJ set of methods. Numerical simulations, including quantum-based molecular dynamics (QMD) using the QMD suite LATTE, highlight the discussed properties of the algorithms as well as exhibit the direct application of robust, time step independent stochastic integrators to quantum-based molecular dynamics.

physics.comp-ph↗

arXiv2020

The Challenge of Stochastic Størmer-Verlet Thermostats Generating Correct Statistics

In light of the recently developed complete GJ set of single random variable stochastic, discrete-time Størmer-Verlet algorithms for statistically accurate simulations of Langevin equations, we investigate two outstanding questions: 1) Are there any algorithmic or statistical benefits from including multiple random variables per time-step, and 2) are there objective reasons for using one or more methods from the available set of statistically correct algorithms? To address the first question, we assume a general form for the discrete-time equations with two random variables and then follow the systematic, brute-force GJ methodology by enforcing correct thermodynamics in linear systems. It is concluded that correct configurational Boltzmann sampling of a particle in a harmonic potential implies correct configurational free-particle diffusion, and that these requirements only can be accomplished if the two random variables per time step are identical. We consequently submit that the GJ set represents all possible stochastic Størmer-Verlet methods that can reproduce time-step-independent statistics of linear systems. The second question is thus addressed within the GJ set. Based in part on numerical simulations of complex molecular systems, and in part on analytic scaling of time, we analyze the apparent difference in stability between different methods. We attribute this difference to the inherent time scaling in each method, and suggest that this scaling may lead to inconsistencies in the interpretation of dynamical and statistical simulation results. We therefore suggest that the method with the least inherent time-scaling, the GJ-I/GJF-2GJ method, be preferred for statistical applications where spurious rescaling of time is undesirable.

cond-mat.stat-mech↗

arXiv2020

Modeling Escape from a One-Dimensional Potential Well at Zero or Very Low Temperatures

The process of activation out a one-dimensional potential is investigated systematically in zero and nonzero temperature conditions. The features of the potential are traced through statistical escape out of its wells whose depths are tuned in time by a forcing term. The process is carried out on the damped pendulum system imposing specific initial conditions on the potential variable. While for relatively high values of the dissipation the statistical properties follow a behavior that can be derived from the standard Kramers model, decreasing the dissipation we observe responses/deviations which have regular dependencies on initial conditions, temperature, and loss parameter itself. It is shown that failures of the thermal activation model are originated at low temperatures, and very low dissipation, by the initial conditions and intrinsic, namely T=0, characteristic oscillations of the potential-generated dynamical equation.

cond-mat.stat-mech↗

arXiv2020

Defining velocities for accurate kinetic statistics in the GJF thermostat

We expand on two previous developments in the modeling of discrete-time Langevin systems. One is the well-documented Grønbech-Jensen Farago (GJF) thermostat, which has been demonstrated to give robust and accurate configurational sampling of the phase space. Another is the recent discovery that also kinetics can be accurately sampled for the GJF method. Through a complete investigation of all possible finite difference approximations to the velocity, we arrive at two main conclusions:~1) It is not possible to define a so-called on-site velocity such that kinetic temperature will be correct and independent of the time step, and~2) there exists a set of infinitely many possibilities for defining a two-point (leap-frog) velocity that measures kinetic energy correctly for linear systems in addition to the correct configurational statistics obtained from the GJF algorithm. We give explicit expressions for the possible definitions, and we incorporate these into convenient and practical algorithmic forms of the normal Verlet-type algorithms along with a set of suggested criteria for selecting a useful definition of velocity.

cond-mat.stat-mech↗

arXiv2019

Complete Set of Stochastic Verlet-Type Thermostats for Correct Langevin Simulations

We present the complete set of stochastic Verlet-type algorithms that can provide correct statistical measures for both configurational and kinetic sampling in discrete-time Langevin systems. The approach is a brute-force general representation of the Verlet-algorithm with free parameter coefficients that are determined by requiring correct Boltzmann sampling for linear systems, regardless of time step. The result is a set of statistically correct methods given by one free functional parameter, which can be interpreted as the one-time-step velocity attenuation factor. We define the statistical characteristics of both true on-site $v^n$ and true half-step $u^{n+\frac{1}{2}}$ velocities, and use these definitions for each statistically correct Stormer-Verlet method to find a unique associated half-step velocity expression, which yields correct kinetic Maxwell-Boltzmann statistics for linear systems. It is shown that no other similar, statistically correct on-site velocity exists. We further discuss the use and features of finite-difference velocity definitions that are neither true on-site, nor true half-step. The set of methods is written in convenient and conventional stochastic Verlet forms that lend themselves to direct implementation for, e.g., Molecular Dynamics applications. We highlight a few specific examples, and validate the algorithms through comprehensive Langevin simulations of both simple nonlinear oscillators and complex Molecular Dynamics.

cond-mat.stat-mech↗

arXiv2019

The Effects of Intrinsic Dynamical Ghost Modes in Discrete-Time Langevin Simulations

Using the recently published GJF-2GJ Langevin thermostat, which can produce time-step-independent statistical measures even for large time steps, we analyze and discuss the causes for abrupt deviations in statistical data as the time step is increased for some simulations of nonlinear oscillators. Exemplified by the pendulum, we identify a couple of discrete-time dynamical modes in the purely damped pendulum equation as the cause of the observed discrepancies in statistics. The existence, stability and kinetics of the modes are consistent with the acquired velocity distribution functions from Langevin simulations, and we conclude that the simulation deviations from physical expectations are not due to normal, systematic algorithmic time-step errors, but instead due to the inherent properties of discrete time in nonlinear dynamics.

cond-mat.stat-mech↗

arXiv2019

Accurate Configurational and Kinetic Statistics in Discrete-Time Langevin Systems

We expand on the previously published Grønbech-Jensen Farago (GJF) thermostat, which is a thermodynamically sound variation on the Størmer-Verlet algorithm for simulating discrete-time Langevin equations. The GJF method has been demonstrated to give robust and accurate configurational sampling of the phase space, and its applications to, e.g., Molecular Dynamics is well established. A new definition of the discrete-time velocity variable is proposed based on analytical calculations of the kinetic response of a harmonic oscillator subjected to friction and noise. The new companion velocity to the GJF method is demonstrated to yield correct and time-step-independent kinetic responses for, e.g., kinetic energy, its fluctuations, and Green-Kubo diffusion based on velocity autocorrelations. This observation allows for a new and convenient Leap-Frog algorithm, which efficiently and precisely represents statistical measures of both kinetic and configurational properties at any time step within the stability limit for the harmonic oscillator. We outline the simplicity of the algorithm and demonstrate its attractive time-step-independent features for nonlinear and complex systems through applications to a one-dimensional nonlinear oscillator and three-dimensional Molecular Dynamics.

physics.comp-ph↗

arXiv2016

Isothermal Langevin dynamics in systems with power-law spatially-dependent friction

We study the dynamics of Brownian particles in a heterogeneous one-dimensional medium with a spatially-dependent diffusion coefficient of the form $D(x)\sim |x|^c$, at constant temperature. The particle's probability distribution function (PDF) is calculated both analytically, by solving Fick's diffusion equation, and from numerical simulations of the underdamped Langevin equation. At large times, the PDFs calculated by both approaches yield identical results, corresponding to subdiffusion for $c<0$, and superdiffusion for $0 1$, the diffusion equation predicts that the particles accelerate. Here, we show that this phenomenon, previously considered in several works as an illustration for the possible dramatic effects of spatially-dependent thermal noise, is unphysical. We argue that in an isothermal medium, the motion cannot exceed the ballistic limit ($\left\langle x^2\right\rangle \sim t^2$). The ballistic limit is reached when the friction coefficient drops sufficiently fast at large distances from the origin, and is correctly captured by Langevin's equation.

cond-mat.stat-mech↗

arXiv2016

The Thermodynamics of Endosomal Escape and DNA Release from Lipoplexes

Complexes of cationic and neutral lipids and DNA (lipoplexes) are emerging as promising vectors for gene therapy applications. Their appeal stems from their non pathogenic nature and the fact that they self-assemble under conditions of thermal equilibrium. Lipoplex adhesion to the cell plasma membrane initiates a three-stage process termed transfection, consisting of (i) endocytosis, (ii) lipoplex breakdown, and (iii) DNA release followed by gene expression. As successful transfection requires lipoplex degradation, it tends to be hindered by the lipoplex thermodynamic stability; nevertheless, it is known that the transfection process may proceed spontaneously. Here, we use a simple model to study the thermodynamic driving forces governing transfection. We demonstrate that after endocytosis [stage (i)], the lipoplex becomes inherently unstable. This instability, which is triggered by interactions between the cationic lipids of the lipoplex and the anionic lipids of the enveloping plasma membrane, is entropically controlled involving both remixing of the lipids and counterions release. Our detailed calculation shows that the free energy gain during stage (ii) is approximately linear in $Φ_+$, the mole fraction of cationic lipids in the lipoplex. This free energy gain, $ΔF$, reduces the barrier for fusion between the enveloping and the lipoplex bilayers, which produces a hole allowing for DNA release [stage (iii)]. The linear relationship between $ΔF$ and the fraction of cationic lipids explains the experimentally observed exponential increase of transfection efficiency with $Φ_+$ in lamellar lipoplexes.

cond-mat.soft↗

arXiv2016

The G-JF Thermostat for Accurate Configurational Sampling in Soft-Matter Simulations

We implement the statistically sound G-JF thermostat for Langevin Dynamics simulations into the ESPREesSo molecular package for large-scale simulations of soft matter systems. The implemented integration method is tested against the integrator currently used by the molecular package in simulations of a fluid bilayer membrane. While the latter exhibits deviations in the sampling statistics that increase with the integration time step dt, the former reproduces near-correct configurational statistics for all dt within the stability range of the simulations. We conclude that, with very modest revisions to existing codes, one can significantly improve the performance of statistical sampling using Langevin thermostats.

physics.comp-ph↗

arXiv2016

A survey of classical and quantum interpretations of experiments on Josephson junctions at very low temperatures

For decades following its introduction in 1968, the resistively and capacitively shunted junction (RCSJ) model, sometimes referred to as the Stewart-McCumber model, was successfully applied to study the dynamics of Josephson junctions embedded in a variety of superconducting circuits. In 1980 a theoretical conjecture by A.J. Leggett suggested a possible new and quite different behavior for Josephson junctions at very low temperatures. A number of experiments seemed to confirm this prediction and soon it was taken as a given that junctions at tens of millikelvins should be regarded as macroscopic quantum entities. As such, they would possess discrete levels in their effective potential wells, and would escape from those wells (with the appearance of a finite junction voltage) via a macroscopic quantum tunneling process. A zeal to pursue this new physics led to a virtual abandonment of the RCSJ model in this low temperature regime. In this paper we consider a selection of essentially prototypical experiments that were carried out with the intention of confirming aspects of anticipated macroscopic quantum behavior in Josephson junctions. We address two questions: (1) How successful is the non-quantum theory (RCSJ model) in replicating those experiments? (2) How strong is the evidence that data from these same experiments does indeed reflect macroscopic quantum behavior?

cond-mat.supr-con↗

arXiv2016

On the connection between dissipative particle dynamics and the Itô-Stratonovich dilemma

Dissipative Particle Dynamics (DPD) is a popular simulation model for investigating hydrodynamic behavior of systems with non-negligible equilibrium thermal fluctuations. DPD employs soft core repulsive interactions between the system particles, thus allowing them to overlap. This supposedly permits relatively large integration time steps, which is an important feature for simulations on large temporal scales. In practice, however, an increase in the integration time step leads to increasingly larger systematic errors in the sampling statistics. Here, we demonstrate that the prime origin of these systematic errors is the multiplicative nature of the thermal noise term in Langevin's equation, i.e., the fact that it depends on the instantaneous coordinates of the particles. This lead to an ambiguity in the interpretation of the stochastic differential Langevin equation, known as the Itô-Stratonovich dilemma. Based on insights from previous studies of the dilemma, we propose a novel algorithm for DPD simulations exhibiting almost an order of magnitude improvement in accuracy, and nearly twice the efficiency of commonly used DPD Langevin thermostats.

cond-mat.stat-mech↗

arXiv2014

Effects of applied strain on radiation damage generation in body-centered cubic iron

Radiation damage in body-centered cubic (BCC) Fe has been extensively studied by computer simulations to quantify effects of temperature, impinging particle energy, and the presence of extrinsic particles. However, limited investigation has been conducted into the effects of mechanical stresses and strain. In a reactor environment, structural materials are often mechanically strained, and an expanded understanding of how this strain affects the generation of defects may be important for predicting microstructural evolution and damage accumulation under such conditions. In this study, we have performed molecular dynamics simulations in which various types of homogeneous strains are applied to BCC Fe and the effect on defect generation is examined. It is found that volume-conserving shear strains yield no statistically significant variations in the stable number of defects created via cascades in BCC Fe. However, strains that result in volume changes are found to produce significant effects on defect generation.

cond-mat.mtrl-sci↗

arXiv2014

Constant pressure and temperature discrete-time Langevin molecular dynamics

We present a new and improved method for simultaneous control of temperature and pressure in molecular dynamics simulations with periodic boundary conditions. The thermostat-barostat equations are build on our previously developed stochastic thermostat, which has been shown to provide correct statistical configurational sampling for any time step that yields stable trajectories. Here, we extend the method and develop a set of discrete-time equations of motion for both particle dynamics and system volume in order to seek pressure control that is insensitive to the choice of the numerical time step. The resulting method is simple, practical, and efficient. The method is demonstrated through direct numerical simulations of two characteristic model systems - a one dimensional particle chain for which exact statistical results can be obtained and used as benchmarks, and a three dimensional system of Lennard-Jones interacting particles simulated in both solid and liquid phases. The results, which are compared against the method of Kolb & Dunweg, show that the new method behaves according to the objective, namely that acquired statistical averages and fluctuations of configurational measures are accurate and robust against the chosen time step applied to the simulation.

cond-mat.stat-mech↗