We present HylleraasMD (HyMD), a comprehensive implementation of the recently proposed Hamiltonian formulation hybrid particle-field molecular dynamics. The methodology is based on tunable, grid-independent length-scale coarse graining, obtained by filtering particle densities in reciprocal space. This enables systematic convergence energies and forces grid refinement, also eliminating nonphysical force aliasing. Separating time integration fast modes associated with internal motion from...

Hybrid particle–field molecular dynamics is a simulation strategy, wherein particles couple to density field instead of through ordinary pair potentials. Traditionally considered mean-field theory, momentum and energy-conserving hybrid formalism has recently been introduced, which was demonstrated approach the Gaussian Core model potential in grid-converged limit. Here, we expand on generalize correspondence between Hamiltonian method particle–particle Using spectral procedure suggested by...

We develop ∂-HylleraasMD (∂-HyMD), a fully end-to-end differentiable molecular dynamics software based on the Hamiltonian hybrid particle-field formalism, and use it to establish protocol for automated optimization of force field parameters. ∂-HyMD is templated recently released HylleraaasMD software, while using JAX autodiff framework as main engine dynamics. exploits an embarrassingly parallel algorithm by spawning independent simulations, whose trajectories are simultaneously processed...

Hamiltonian hybrid particle-field molecular dynamics is a computationally efficient method to study large soft matter systems. In this work, we extend approach constant-pressure (NPT) simulations. We reformulate the calculation of internal pressure from density field by taking into account intrinsic spread particles in space, which naturally leads direct anisotropy tensor. The anisotropic contribution crucial for reliably describing physics systems under pressure, as demonstrated series...

Molecular dynamics (MD) is a computational methodology in which the dynamical behavior of systems interacting atoms and molecules investigated by integrating corresponding classical equations motion.The analysis molecular trajectories yields an incredibly powerful microscope with atomic resolution.While prominent examples involving all-atom models exist, many operate on time-and lengths scales too large, precluding use such approach.The intrinsic complexity biological soft-matter has...

Hamiltonian hybrid particle-field molecular dynamics is a computationally efficient method to study large soft matter systems. In this work, we extend approach constant pressure (NPT) simulations. We reformulate the calculation of internal from density field by taking into account intrinsic spread particles in space, which naturally lead direct anisotropy tensor. The anisotropic contribution crucial for reliably describing physics systems under pressure, demonstrated series tests on...

The hybrid particle-field molecular dynamics method is an efficient alternative to standard particle-based coarse grained approaches. In this work, we propose automated protocol for optimisation of the effective parameters that define interaction energy density functional, based on Bayesian optimisation. machine-learning makes use arbitrary fitness function defined upon a set observables relevance, which are optimally matched by iterative process. Employing phospholipid bilayers as test...

We develop ∂-HylleraasMD (∂-HyMD), a fully end-to-end differentiable molecular dynamics software based on the Hamiltonian hybrid particle-field formalism, and use it to establish protocol for automated optimization of force field parameters. ∂-HyMD is templated recently established HylleraaasMD software, while using JAX autodiff framework as main engine dynamics. exploits an embarrassingly parallel algorithm by spawning independent simulations, whose trajectories are simultaneously processed...

We develop ∂-HylleraasMD (∂-HyMD), a fully end-to-end differentiable molecular dynamics software based on the Hamiltonian hybrid particle-field formalism, and use it to establish protocol for automated optimization of force field parameters. ∂-HyMD is templated recently established HylleraaasMD software, while using JAX autodiff framework as main engine dynamics. exploits an embarrassingly parallel algorithm by spawning independent simulations, whose trajectories are simultaneously processed...

We develop ∂-HylleraasMD (∂-HyMD), a fully end-to-end differentiable molecular dynamics software based on the Hamiltonian hybrid particle-field formalism, and use it to establish protocol for automated optimization of force field parameters. ∂-HyMD is templated recently established HylleraaasMD software, while using JAX autodiff framework as main engine dynamics. exploits an embarrassingly parallel algorithm by spawning independent simulations, whose trajectories are simultaneously processed...

This study introduces an implementation of multiple Gaussian filters within the Hamiltonian hybrid particle field (HhPF) theory, aimed at capturing phase co-existence phenomena in mesoscopic molecular simulations. By employing a linear combination two filters, we demonstrate that HhPF approach can generate potentials with attractive components similar to Lennard-Jones potentials, which are crucial for modeling co-existence. We compare performance this multi-Gaussian filter method...

This study introduces an implementation of multiple Gaussian filters within the Hamiltonian hybrid particle-field (HhPF) theory, aimed at capturing phase co-existence phenomena in mesoscopic molecular simulations. By employing a linear combination two Gaussians, we demonstrate that HhPF can generate potentials with attractive and steric components analogous to Lennard-Jones potentials, which are crucial for modeling co-existence. We compare performance this method Multi-Gaussian Core Model...

This study introduces an implementation of multiple Gaussian filters within the Hamiltonian hybrid particle-field (HhPF) theory, aimed at capturing phase coexistence phenomena in mesoscopic molecular simulations. By employing a linear combination two Gaussians, we demonstrate that HhPF can generate potentials with attractive and steric components analogous to Lennard-Jones potentials, which are crucial for modeling coexistence. We compare performance this method Multi-Gaussian Core Model...

This study introduces an implementation of multiple Gaussian filters within the Hamiltonian hybrid particle-field (HhPF) theory, aimed at capturing phase coexistence phenomena in mesoscopic molecular simulations. By employing a linear combination two Gaussians, we demonstrate that HhPF can generate potentials with attractive and steric components analogous to Lennard-Jones (LJ) potentials, which are crucial for modeling coexistence. We compare performance this method multi-Gaussian core...

We present HylleraasMD (HyMD), a comprehensive implementation of the recently proposed Hamiltonian formulation hybrid particle-field molecular dynamics (hPF). The methodology is based on tunable, grid-independent length-scale coarse graining, obtained by filtering particle densities in reciprocal space. This enables systematic convergence energies and forces grid refinement, also eliminating non-physical force aliasing. Separating time integration fast modes associated with internal motion,...

Hybrid particle-field molecular dynamics is a simulation strategy wherein particles couple to density field instead of through ordinary pair potentials. Traditionally considered mean-field theory, momentum and energy-conserving hybrid formalism has recently been introduced, which was demonstrated approach the Gaussian Core model potential in grid-converged limit. Here, we expand on generalize correspondence between Hamiltonian method particle-particle Using spectral procedure suggested by...