226 citations · 695 across the 31 of their papers we have counts for
12 papers · 1 filter
The bliss of dimensionality: how an unsupervised criterion identifies optimal low-resolution representations of high-dimensional datasets
Margherita Mele, Daniel Campos Moreno, Raffaello Potestio
Selecting the optimal resolution for discretizing high-dimensional data is a central problem in physics and data analysis, particularly in unsupervised settings where the underlyin…
Density of states in neural networks: an in-depth exploration of learning in parameter space
Margherita Mele, Roberto Menichetti, Alessandro Ingrosso +1
Learning in neural networks critically hinges on the intricate geometry of the loss landscape associated with a given task. Traditionally, most research has focused on finding spec…
Making sense of complex systems through resolution, relevance, and mapping entropy
Roi Holtzman, Marco Giulini, Raffaello Potestio
Complex systems are characterised by a tight, nontrivial interplay of their constituents, which gives rise to a multi-scale spectrum of emergent properties. In this scenario, it is…
Coarse-grained Mori-Zwanzig dynamics in a time-non-local stationary-action framework
Piero Luchi, Roberto Menichetti, Gianluca Lattanzi +1
Coarse-grained (CG) models are simplified representations of soft matter systems that are commonly employed to overcome size and time limitations in computational studies. Many app…
An information theory-based approach for optimal model reduction of biomolecules
Marco Giulini, Roberto Menichetti, M. Scott Shell +1
In the theoretical modelling of a physical system a crucial step consists in the identification of those degrees of freedom that enable a synthetic, yet informative representation…
Open-Boundary Hamiltonian adaptive resolution. From grand canonical to non-equilibrium molecular dynamics simulations
Maziar Heidari, Kurt Kremer, Ramin Golestanian +2
We propose an open-boundary molecular dynamics method in which an atomistic system is in contact with an infinite particle reservoir at constant temperature, volume and chemical po…
From Classical to Quantum and Back: Hamiltonian Adaptive Resolution Path Integral, Ring Polymer, and Centroid Molecular Dynamics
Karsten Kreis, Kurt Kremer, Raffaello Potestio +1
Path integral-based simulation methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are si…
From classical to quantum and back: Hamiltonian coupling of classical and Path Integral models of atoms
Karsten Kreis, Mark E. Tuckerman, Davide Donadio +2
In computer simulations, quantum delocalization of atomic nuclei can be modeled making use of the Path Integral (PI) formulation of quantum statistical mechanics. This approach, ho…
Advantages and challenges in coupling an ideal gas to atomistic models in adaptive resolution simulations
Karsten Kreis, Aoife C. Fogarty, Kurt Kremer +1
In adaptive resolution simulations, molecular fluids are modeled employing different levels of resolution in different subregions of the system. When traveling from one region to t…
Statistical Mechanics of Hamiltonian Adaptive Resolution Simulations
Pep Español, Rafael Delgado-Buscalioni, Ralf Everaers +3
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 molecule…
Monte Carlo adaptive resolution simulation of multicomponent molecular liquids
Raffaello Potestio, Pep Español, Rafael Delgado-Buscalioni +3
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…
Hamiltonian adaptive resolution simulation for molecular liquids
Raffaello Potestio, Sebastian Fritsch, Pep Espanol +4
Adaptive resolution schemes allow the simulation of a molecular fluid treating simultaneously different subregions of the system at different levels of resolution. In this work we…