arXiv subjects

Pep Español

Publications and source records attributed to Pep Español.

At least 19 recordsLinked to original sources

arXiv2026

Self-averaging parameter estimation for coarse-grained particle models

We introduce a parameter estimation method that utilizes microscopic data, specifically averages and correlations of selected microscopic observables, to determine the parameters of a stochastic differential equation governing coarse-grained degrees of freedom. The method is not limited to static parameters found in the reversible part of the coarse-grained dynamics, such as those in the free energy function or potential of mean force, but also extends to dynamic parameters, including friction coefficients. The method couples the stochastic differential equation with free parameters to dynamic equations for the parameters. The coupled system self-averages, according to Anosov-Kifer's theorem, in such a way that the final state of the parameters gives coincidence between the microscopic and mesoscopic averages and correlations of selected observables. The method is validated in two examples: a Brownian particle in a harmonic potential, and a set of Brownian particles interacting hydrodynamically with the Rotne-Prager-Yamakawa mobility tensor. This latter case illustrates how the method can be used not only to determine coefficients but also state dependent transport properties - in this case, the position dependent form of the mobility tensor. The parameter estimation for these two models yields excellent results. Subsequently we use the methodology to study a bimodal-mass Lennard-Jones fluid for which we infer both the potential of mean force between the heavy particles and its hydrodynamic mobility tensor.

cond-mat.stat-mech↗

arXiv2026

Unraveling Internal Friction in a Coarse-Grained Protein Model

Understanding the dynamic behavior of complex biomolecules requires simplified models that not only make computations feasible but also reveal fundamental mechanisms. Coarse-graining (CG) achieves this by grouping atoms into beads, whose stochastic dynamics can be derived using the Mori-Zwanzig formalism, capturing both reversible and irreversible interactions. In liquid, the dissipative bead-bead interactions have so far been restricted to hydrodynamic couplings. However, friction does not only arises from the solvent but notably, from the internal degrees of freedom missing in the CG beads. This leads to an additional ''internal friction'' whose relevance is studied in this contribution. By comparing with all-atom molecular dynamics (MD), we neatly show that in order to accurately reproduce the dynamics of a globular protein in water using a coarse-grained (CG) model, not only a precise determination of elastic couplings and the Stokesian self-friction of each bead is required. Critically, the inclusion of internal friction between beads is also necessary for a faithful representation of protein dynamics. We propose to optimize the parameters of the CG model through a self-averaging method that integrates the CG dynamics with an evolution equation for the CG parameters. This approach ensures that selected quantities, such as the radial distribution function and the time correlation of bead velocities, match the corresponding MD values.

cond-mat.soft↗

arXiv2024

Hammering at the entropy: A GENERIC-guided approach to learning polymeric rheological constitutive equations using PINNs

We present a versatile framework that employs Physics-Informed Neural Networks (PINNs) to discover the entropic contribution that leads to the constitutive equation for the extra-stress in rheological models of polymer solutions. In this framework the training of the Neural Network is guided by an evolution equation for the conformation tensor which is GENERIC-compliant. We compare two training methodologies for the data-driven PINN constitutive models: one trained on data from the analytical solution of the Oldroyd-B model under steady-state rheometric flows (PINN-rheometric), and another trained on in-silico data generated from complex flow CFD simulations around a cylinder that use the Oldroyd-B model (PINN-complex). The capacity of the PINN models to provide good predictions are evaluated by comparison with CFD simulations using the underlying Oldroyd-B model as a reference. Both models are capable of predicting flow behavior in transient and complex conditions; however, the PINN-complex model, trained on a broader range of mixed flow data, outperforms the PINN-rheometric model in complex flow scenarios. The geometry agnostic character of our methodology allows us to apply the learned PINN models to flows with different topologies than the ones used for training.

physics.flu-dyn↗

arXiv2024

Stochastic Dissipative Euler's equations for a free body

Intrinsic thermal fluctuations within a real solid challenge the rigid body assumption that is central to Euler's equations for the motion of a free body. Recently, we have introduced a dissipative and stochastic version of Euler's equations in a thermodynamically consistent way (European Journal of Mechanics - A/Solids 103, 105184 (2024)). This framework describes the evolution of both orientation and shape of a free body, incorporating internal thermal fluctuations and their concomitant dissipative mechanisms. In the present work, we demonstrate that, in the absence of angular momentum, the theory predicts that principal axis unit vectors of a body undergo an anisotropic Brownian motion on the unit sphere, with the anisotropy arising from the body's varying moments of inertia. The resulting equilibrium time correlation function of the principal eigenvectors decays exponentially. This theoretical prediction is confirmed in molecular dynamics simulations of small bodies. The comparison of theory and equilibrium MD simulations allow us to measure the orientational diffusion tensor. We then use this information in the Stochastic Dissipative Euler's Equations, to describe a non-equilibrium situation of a body spinning around the unstable intermediate axis. The agreement between theory and simulations is excellent, offering a validation of the theoretical framework.

cond-mat.stat-mech↗

arXiv2023

Internal dissipation in the tennis racket effect

The phenomenon known as the tennis racket effect is observed when a rigid body experiences unstable rotation around its intermediate axis. In free space, this leads to the Dzhanibekov effect, where triaxial objects like a spinning wing bolt may continuously flip their rotational axis. Over time, however, dissipation ensures that a torque free spinning body will eventually rotate around its major axis, in a process called precession relaxation, which counteracts the tennis racket effect. Euler's equations for a rigid body effectively describe the tennis racket effect, but cannot account for the precession relaxation effect. A recent theory has put forward a generalization of Euler's equations that includes dissipation in a thermodynamically consistent way. The theory displays two dissipative mechanisms: orientational diffusion and viscoelasticity. Here we show that orientational diffusion, rather than viscoelasticity, primarily drives precession relaxation and effectively suppresses the tennis racket effect.

physics.class-ph↗

arXiv2023

The role of thermal fluctuations in the motion of a free body

The motion of a rigid body is described in Classical Mechanics with the venerable Euler's equations which are based on the assumption that the relative distances among the constituent particles are fixed in time. Real bodies, however, cannot satisfy this property, as a consequence of thermal fluctuations. We generalize Euler's equations for a free body in order to describe dissipative and thermal fluctuation effects in a thermodynamically consistent way. The origin of these effects is internal, i.e. not due to an external thermal bath. The stochastic differential equations governing the orientation and central moments of the body are derived from first principles through the theory of coarse-graining. Within this theory, Euler's equations emerge as the reversible part of the dynamics. For the irreversible part, we identify two distinct dissipative mechanisms; one associated with diffusion of the orientation, whose origin lies in the difference between the spin velocity and the angular velocity, and one associated with the damping of dilations, i.e. inelasticity. We show that a deformable body with zero angular momentum will explore uniformly, through thermal fluctuations, all possible orientations. When the body spins, the equations describe the evolution towards the alignment of the body's major principal axis with the angular momentum vector. In this alignment process, the body increases its temperature. We demonstrate that the origin of the alignment process is not inelasticity but rather orientational diffusion. The theory also predicts the equilibrium shape of a spinning body.

cond-mat.stat-mech↗

arXiv2017

Rapid convergence for simulations that project from particles onto a fixed mesh

The advantage of particle Lagrangian methods in computational fluid dynamics is that advection is accurately modeled. However, this complicates the calculation of space derivatives. If a mesh is employed, it must be updated at each time step. On the other hand, fixed mesh, Eulerian, formulations benefit from the mesh being defined at the beginning of the simulation, but feature non-linear advection terms. It therefore seems natural to combine the two approaches, using a fixed mesh to perform calculations related to space derivatives, and using the particles to advect the information with time. The idea of combining Lagrangian particles and a fixed mesh goes back to Particle-in-Cell methods, and is here considered within the context of the finite element method (FEM) for the fixed mesh, and the particle FEM (pFEM) for the particles. Our results, in agreement with recent works, show that interpolation ("projection") errors, especially from particles to mesh, are the culprits of slow convergence of the method if standard, linear, FEs, are employed. By including quadratically consistent shape functions for the particles, the rate of convergence is restored to values competitive with purely Lagrangian simulations. The procedure is validated on the Zalesak's disk problem, the Taylor-Green vortex sheet flow, and the Rayleigh-Taylor instability.

physics.flu-dyn↗

arXiv2016

Perspective: Dissipative Particle Dynamics

Dissipative particle dynamics (DPD) belongs to a class of models and computational algorithms developed to address mesoscale problems in complex fluids and soft matter in general. It is based on the notion of particles that represent coarse-grained portions of the system under study and allow, therefore, to reach time and length scales that would be otherwise unreachable from microscopic simulations. The method has been conceptually refined since its introduction almost twenty five years ago. This perspective surveys the major conceptual improvements in the original DPD model, along with its microscopic foundation, and discusses outstanding challenges in the field. We summarize some recent advances and suggests avenues for future developments.

cond-mat.stat-mech↗

arXiv2016

Assignment of fields from particles to mesh

In Computational Fluid Dynamics there have been many attempts to combine the power of a fixed mesh on which to carry out spatial calculations with that of a set of particles that moves following the velocity field. These ideas indeed go back to Particle-in-Cell methods, proposed about 60 years ago. Of course, some procedure is needed to transfer field information between particles and mesh. There are many possible choices for this "assignment", or "projection". Several requirements may guide this choice. Two well-known ones are conservativity and stability, which apply to volume integrals of the fields. An additional one is here considered: preservation of information. This means that mesh interpolation, followed by mesh assignment, should leave the field values invariant. The resulting methods are termed "mass" assignments due to their strong similarities with the Finite Element Method. We test several procedures, including the well-known FLIP, on three scenarios: simple 1D convection, 2D convection of Zalesak's disk, and a CFD simulation of the Taylor-Green periodic vortex sheet. The most symmetric mass assignment is seen to be clearly superior to other methods.

physics.flu-dyn↗

arXiv2015

Coupling a nano-particle with isothermal fluctuating hydrodynamics: Coarse-graining from microscopic to mesoscopic dynamics

We derive a coarse-grained description of the dynamics of a nanoparticle immersed in an isothermal simple fluid by performing a systematic coarse graining of the underlying microscopic dynamics. As coarse-grained or relevant variables we select the position of the nanoparticle and the \emph{total} mass and momentum density field of the fluid, which are locally conserved slow variables because they are defined to include the contribution of the nanoparticle. The theory of coarse graining based on the Zwanzing projection operator leads us to a system of stochastic \emph{ordinary} differential equations (SODEs) that are closed in the relevant variables. We demonstrate that our discrete coarse-grained equations are consistent with a Petrov-Galerkin finite-element discretization of a system of formal stochastic \emph{partial} differential equations (SPDEs) which resemble previously-used phenomenological models based on fluctuating hydrodynamics. Under suitable approximations we obtain \emph{closed} approximations of the coarse-grained dynamics in a manner which gives them a clear physical interpretation, and provides \emph{explicit} microscopic expressions for all of the coefficients appearing in the closure. Our work leads to a model for dilute nanocolloidal suspensions that can be simulated effectively using feasibly short molecular dynamics simulations as input to a FEM fluctuating hydrodynamic solver.

cond-mat.mes-hall↗

arXiv2015

Finite element discretization of non-linear diffusion equations with thermal fluctuations

We present a finite element discretization of a non-linear diffusion equation used in the field of critical phenomena and, more recently, in the context of Dynamic Density Functional Theory. The discretized equation preserves the structure of the continuum equation. Specifically, it conserves the total number of particles and fulfills an H-theorem as the original partial differential equation. Guided by the Theory of Coarse-Graining, we discuss the inclusion of thermal fluctuations in the non-linear diffusion equation. This sheds light on the meaning of such a fluctuating hydrodynamics equation and to the limitations of the approximations involved. The methodology proposed for the introduction of thermal fluctuations in finite element methods is general and valid for both regular and irregular grids in arbitrary dimensions. We focus here on simulations of the Ginzburg-Landau free energy functional using both regular and irregular 1D grids. Convergence of the numerical results is obtained for the static and dynamic structure factors as the resolution of the grid is increased.

cond-mat.stat-mech↗

arXiv2014

Statistical Mechanics of Hamiltonian Adaptive Resolution Simulations

The Adaptive Resolution Scheme (AdResS) is a hybrid scheme that allows one to treat a molecular system with different levels of resolution depending on the location of the molecules. The construction of a Hamiltonian based on the this idea (H-AdResS) allows one to formulate the usual tools of ensembles and statistical mechanics. We present a number of exact and approximate results that provide a statistical mechanics foundation for this simulation method. We also present simulation results that illustrate the theory.

cond-mat.stat-mech↗

arXiv2013

Monte Carlo adaptive resolution simulation of multicomponent molecular liquids

Complex soft matter systems can be efficiently studied with the help of adaptive resolution simulation methods, concurrently employing two levels of resolution in different regions of the simulation domain. The non-matching properties of high- and low-resolution models, however, lead to thermodynamic imbalances between the system's subdomains. Such inhomogeneities can be healed by appropriate compensation forces, whose calculation requires nontrivial iterative procedures. In this work we employ the recently developed Hamiltonian Adaptive Resolution Simulation method to perform Monte Carlo simulations of a binary mixture, and propose an efficient scheme, based on Kirkwood Thermodynamic Integration, to regulate the thermodynamic balance of multi-component systems.

cond-mat.stat-mech↗

arXiv2013

Comment on "Logarithmic Oscillators: Ideal Hamiltonian Thermostats" [arXiv 1203.5968]

Campisi, Zhan, Talkner and Hänggi have recently proposed a novel Hamiltonian thermostat which they claim may be used both in simulations and experiments [arXiv:1203.5968v4]. We show, however, that this is not possible due to the length and time scales involved, which depend exponentially on the total energy of the system. The implementation suggested by Campisi et alii implies equilibration times greater than the age of the universe for systems with more than a few dozen particles.

cond-mat.stat-mech↗

arXiv2001

Thermohydrodynamics for a van der Waals fluid

Following a cell-method due to van Kampen for the calculation of a coarse-grained free energy functional for the van der Waals gas, we compute a corresponding entropy functional from microscopic principles. This entropy functional is one of the building blocks of the recently developed GENERIC framework. This framework allows to obtain in a thermodynamically consistent way the continuum hydrodynamic equations for a fluid able to display liquid-vapor coexistence. Surface tension appears naturally and the resulting model describes interfaces as diffuse regions, much in the same spirit as the gradient theory for equilibrium situations. We suggest that using interfacial forces in the integral form obtained in the microscopic derivation instead of third order derivatives of the density field might represent an advantage from a computational point of view.

cond-mat.stat-mech↗

arXiv2000

Thermodynamically consistent mesoscopic fluid particle models for a van der Waals fluid

The GENERIC structure allows for a unified treatment of different discrete models of hydrodynamics. We first propose a finite volume Lagrangian discretization of the continuum equations of hydrodynamics through the Voronoi tessellation. We then show that a slight modification of these discrete equations has the GENERIC structure. The GENERIC structure ensures thermodynamic consistency and allows for the introduction of correct thermal noise. In this way, we obtain a consistent discrete model for Lagrangian fluctuating hydrodynamics. For completeness, we also present the GENERIC versions of the Smoothed Particle Dynamics model and of the Dissipative Particle Dynamics model. The thermodynamic consistency endorsed by the GENERIC framework allows for a coherent discussion of the gas-liquid phase coexistence of a van der Waals fluid.

cond-mat.stat-mech↗

arXiv1999

Dissipative Particle Dynamics with Energy Conservation: Heat Conduction

We study by means of numerical simulations the model of dissipative particle dynamics with energy conservation for the simple case of thermal conduction. It is shown that the model displays correct equilibrium fluctuations and reproduces Fourier law. The connection between "mesoscopic coarse graining" and "resolution" is clarified.

cond-mat.stat-mech↗

arXiv1999

Thermodynamically admissible form for discrete hydrodynamics

We construct a discrete model of fluid particles according to the GENERIC formalism. The model has the form of Smoothed Particle Hydrodynamics including correct thermal fluctuations. A slight variation of the model reproduces the Dissipative Particle Dynamics model with any desired thermodynamic behavior. The resulting algorithm has the following properties: mass, momentum and energy are conserved, entropy is a non-decreasing function of time and the thermal fluctuations produce the correct Einstein distribution function at equilibrium.

cond-mat.stat-mech↗