9 citations · 10 across the 11 of their papers we have counts for
13 papers
An IMEX multi-level domain-decomposition method for the Boltzmann equation on unstructured meshes
Domenico Caparello, Lorenzo Pareschi, Thomas Rey
We introduce a dynamically adaptive multi-level method for the multiscale Boltzmann equation on unstructured meshes, coupling the compressible Euler, Navier-Stokes, and full Boltzm…
A fast spectral particle method for the Landau equation
Giacomo Borghi, Lorenzo Pareschi
We propose a fast deterministic particle method for the spatially homogeneous Landau equation. The method combines a particle representation of the solution with a Fourier approxim…
Two-Time-Scale Learning Dynamics: A Population View of Neural Network Training
Giacomo Borghi, Hyesung Im, Lorenzo Pareschi
Population-based learning paradigms, including evolutionary strategies, Population-Based Training (PBT), and recent model-merging methods, combine fast within-model optimisation wi…
Collective Annealing by Switching Temperatures: a Boltzmann-type description
Frédéric Blondeel, Lorenzo Pareschi, Giovanni Samaey
The design of effective cooling strategies is a crucial component in simulated annealing algorithms based on the Metropolis method. Traditionally, this is achieved through inverse…
High-Order Asymptotic-Preserving IMEX schemes for an ES-BGK model for Gas Mixtures
Domenico Caparello, Lorenzo Pareschi, Thomas Rey
In this work we construct a high-order Asymptotic-Preserving (AP) Implicit-Explicit (IMEX) scheme for the ES-BGK model for gas mixtures introduced in [Brull, Commun. Math. Sci., 20…
Swarm-based optimization with jumps: a kinetic BGK framework and convergence analysis
Giacomo Borghi, Hyesung Im, Lorenzo Pareschi
Metaheuristic algorithms are powerful tools for global optimization, particularly for non-convex and non-differentiable problems where exact methods are often impractical. Particle…
Hierarchical dynamic domain decomposition for the multiscale Boltzmann equation
Domenico Caparello, Lorenzo Pareschi, Thomas Rey
In this work, we present a hierarchical domain decomposition method for the multi-scale Boltzmann equation based on moment realizability matrices, a concept introduced by Levermore…
Wasserstein convergence rates for stochastic particle approximation of Boltzmann models
Giacomo Borghi, Lorenzo Pareschi
We establish quantitative convergence rates for stochastic particle approximation based on Nanbu-type Monte Carlo schemes applied to a broad class of collisional kinetic models. Us…
A Fourth-Order Finite Volume Scheme for Resistive Relativistic Magnetohydrodynamics
Andrea Mignone, Vittoria Berta, Marco Rossazza +4
We present a finite-volume, genuinely 4th-order accurate numerical method for solving the equations of resistive relativistic magnetohydrodynamics (Res-RMHD) in Cartesian coordinat…
Conservative polynomial approximations and applications to Fokker-Planck equations
Tino Laidin, Lorenzo Pareschi
We address the problem of constructing approximations based on orthogonal polynomials that preserve an arbitrary set of moments of a given function without loosing the spectral con…
Optimization by linear kinetic equations and mean-field Langevin dynamics
Lorenzo Pareschi
Probably one of the most striking examples of the close connections between global optimization processes and statistical physics is the simulated annealing method, inspired by the…
Global high-order numerical schemes for the time evolution of the general relativistic radiation magneto-hydrodynamics equations
Manuel R. Izquierdo, Lorenzo Pareschi, Borja Miñano +2
Modeling correctly the transport of neutrinos is crucial in some astrophysical scenarios such as core-collapse supernovae and binary neutron star mergers. In this paper, we focus o…
Constrained consensus-based optimization
Giacomo Borghi, Michael Herty, Lorenzo Pareschi
In this work we are interested in the construction of numerical methods for high dimensional constrained nonlinear optimization problems by particle-based gradient-free techniques.…