Publications

Order by: publication date number of citations

• TorchGDM: A GPU-accelerated Python toolkit for multi-scale electromagnetic scattering with automatic differentiation

  Sofia Ponomareva, Adelin Patoux, Clément Majorel, Antoine Azéma, Aurélien Cuche, Christian Girard, Arnaud Arbouet, Peter R. Wiecha

  SciPost Phys. Codebases 60 (2025) · published 22 October 2025 | Toggle abstract · pdf

  We present "torchGDM", a numerical framework for nano-optical simulations based on the Green's Dyadic Method (GDM). This toolkit combines a hybrid approach, allowing for both fully discretized nano-structures and structures approximated by sets of effective electric and magnetic dipoles. It supports simulations in three dimensions and for infinitely long, two-dimensional structures. This capability is particularly suited for multi-scale modeling, enabling accurate near-field calculations within or around a discretized structure embedded in a complex environment of scatterers represented by effective models. Importantly, torchGDM is entirely implemented in PyTorch, a well-optimized and GPU-enabled automatic differentiation framework. This allows for the efficient calculation of exact derivatives of any simulated observable with respect to various inputs, including positions, wavelengths or permittivity, but also intermediate parameters like Green's tensor components, which can be interesting for physics informed deep learning applications. We anticipate that this toolkit will be valuable for applications merging nano-photonics and machine learning, as well as for solving nano-photonic optimization and inverse problems, such as the global design and characterization of metasurfaces, where optical interactions between structures are critical.

  1 citation

• Codebase release 0.56 for TorchGDM

  Sofia Ponomareva, Adelin Patoux, Clément Majorel, Antoine Azéma, Aurélien Cuche, Christian Girard, Arnaud Arbouet, Peter R. Wiecha

  SciPost Phys. Codebases 60-r0.56 (2025) · published 22 October 2025 | Toggle abstract · src

  We present "torchGDM", a numerical framework for nano-optical simulations based on the Green's Dyadic Method (GDM). This toolkit combines a hybrid approach, allowing for both fully discretized nano-structures and structures approximated by sets of effective electric and magnetic dipoles. It supports simulations in three dimensions and for infinitely long, two-dimensional structures. This capability is particularly suited for multi-scale modeling, enabling accurate near-field calculations within or around a discretized structure embedded in a complex environment of scatterers represented by effective models. Importantly, torchGDM is entirely implemented in PyTorch, a well-optimized and GPU-enabled automatic differentiation framework. This allows for the efficient calculation of exact derivatives of any simulated observable with respect to various inputs, including positions, wavelengths or permittivity, but also intermediate parameters like Green's tensor components, which can be interesting for physics informed deep learning applications. We anticipate that this toolkit will be valuable for applications merging nano-photonics and machine learning, as well as for solving nano-photonic optimization and inverse problems, such as the global design and characterization of metasurfaces, where optical interactions between structures are critical.

  1 citation

• EERAD3 version 2: QCD corrections in hadronic colour-singlet decays

  Benjamin Campillo Aveleira, Aude Gehrmann-De Ridder, Thomas Gehrmann, Nigel Glover, Gudrun Heinrich, Christian T. Preuss

  SciPost Phys. Codebases 59 (2025) · published 22 October 2025 | Toggle abstract · pdf

  We present a major update of the publicly available EERAD3 package to calculate perturbative corrections in the strong coupling in hadronic Higgs and $Z$-boson decays. We describe the theoretical framework underlying the numerical implementation and provide a guide to the usage of the program.

  1 citation

• Codebase release 2.0 for EERAD3

  Benjamin Campillo Aveleira, Aude Gehrmann-De Ridder, Thomas Gehrmann, Nigel Glover, Gudrun Heinrich, Christian T. Preuss

  SciPost Phys. Codebases 59-r2.0 (2025) · published 22 October 2025 | Toggle abstract · src

  We present a major update of the publicly available EERAD3 package to calculate perturbative corrections in the strong coupling in hadronic Higgs and $Z$-boson decays. We describe the theoretical framework underlying the numerical implementation and provide a guide to the usage of the program.

  1 citation

• Next-generation EDIpack: A Lanczos-based package for quantum impurity models featuring general broken-symmetry phases, flexible bath topologies and multi-platform interoperability

  Lorenzo Crippa, Igor Krivenko, Samuele Giuli, Gabriele Bellomia, Alexander Kowalski, Francesco Petocchi, Alberto Scazzola, Markus Wallerberger, Giacomo Mazza, Luca de Medici, Giorgio Sangiovanni, Massimo Capone, Adriano Amaricci

  SciPost Phys. Codebases 58 (2025) · published 24 September 2025 | Toggle abstract · pdf

  We present a next-generation version of EDIpack, a flexible, high-performance numerical library using Lanczos-based exact diagonalization to solve generic quantum impurity problems, such as those introduced in Dynamical Mean-Field Theory to describe extended strongly correlated materials. This new release efficiently solves impurity problems allowing for different broken-symmetry solutions, including superconductivity, featuring local spin-orbit coupling and/or electron-phonon coupling. It provides quick access to dynamical correlation functions on the entire complex frequency plane at zero and low-temperatures. The modular architecture of the software not only provides Fortran APIs but also includes bindings to C/C++, interfaces with Python and Julia or with TRIQS and w2dynamics research platforms, thus ensuring unprecedented level of inter-operability. The outlook includes further extensions to study quantum materials and cold atoms quantum simulators, as well as quantum information applications.

  2 citations

• Codebase release 5.3 for EDIpack

  Lorenzo Crippa, Igor Krivenko, Samuele Giuli, Gabriele Bellomia, Alexander Kowalski, Francesco Petocchi, Alberto Scazzola, Markus Wallerberger, Giacomo Mazza, Luca de Medici, Giorgio Sangiovanni, Massimo Capone, Adriano Amaricci

  SciPost Phys. Codebases 58-r5.3 (2025) · published 24 September 2025 | Toggle abstract · src

  We present a next-generation version of EDIpack, a flexible, high-performance numerical library using Lanczos-based exact diagonalization to solve generic quantum impurity problems, such as those introduced in Dynamical Mean-Field Theory to describe extended strongly correlated materials. This new release efficiently solves impurity problems allowing for different broken-symmetry solutions, including superconductivity, featuring local spin-orbit coupling and/or electron-phonon coupling. It provides quick access to dynamical correlation functions on the entire complex frequency plane at zero and low-temperatures. The modular architecture of the software not only provides Fortran APIs but also includes bindings to C/C++, interfaces with Python and Julia or with TRIQS and w2dynamics research platforms, thus ensuring unprecedented level of inter-operability. The outlook includes further extensions to study quantum materials and cold atoms quantum simulators, as well as quantum information applications.

  1 citation

• Codebase release 1.0 for NuHepMC

  Steven Gardiner, Joshua Isaacson, Luke Pickering

  SciPost Phys. Codebases 57-r1.0 (2025) · published 22 August 2025 | Toggle abstract · src

  Simulations of neutrino interactions are playing an increasingly important role in the pursuit of high-priority measurements for the field of particle physics. A significant technical barrier for efficient development of these simulations is the lack of a standard data format for representing individual neutrino scattering events. We propose and define such a universal format, named NuHepMC, as a common standard for the output of neutrino event generators. The NuHepMC format uses data structures and concepts from the HepMC3 event record library adopted by other subfields of high-energy physics. These are supplemented with an original set of conventions for generically representing neutrino interaction physics within the HepMC3 infrastructure.

  1 citation

• NuHepMC: A standardized event record format for neutrino event generators

  Steven Gardiner, Joshua Isaacson, Luke Pickering

  SciPost Phys. Codebases 57 (2025) · published 22 August 2025 | Toggle abstract · pdf

  Simulations of neutrino interactions are playing an increasingly important role in the pursuit of high-priority measurements for the field of particle physics. A significant technical barrier for efficient development of these simulations is the lack of a standard data format for representing individual neutrino scattering events. We propose and define such a universal format, named NuHepMC, as a common standard for the output of neutrino event generators. The NuHepMC format uses data structures and concepts from the HepMC3 event record library adopted by other subfields of high-energy physics. These are supplemented with an original set of conventions for generically representing neutrino interaction physics within the HepMC3 infrastructure.

  3 citations

• Codebase release 0.2 for JFSD

  Kim William Torre, Raoul D. Schram, Joost de Graaf

  SciPost Phys. Codebases 56-r0.2 (2025) · published 30 June 2025 | Toggle abstract · src

  Stokesian Dynamics (SD) is a powerful computational framework for simulating the motion of particles in a viscous Newtonian fluid under Stokes-flow conditions. Traditional SD implementations can be computationally expensive as they rely on the inversion of large mobility matrices to determine hydrodynamic interactions. Recently, however, the simulation of thermalized systems with large numbers of particles has become feasible [Fiore and Swan, J. Fluid Mech. 878, 544 (2019)]. Their "fast Stokesian dynamics" (FSD) method leverages a saddle-point formulation to ensure overall scaling of the algorithm that is linear in the number of particles $\mathcal{O}(N)$; performance relies on dedicated graphics-processing-unit computing. Here, we present a different route toward implementing FSD, which instead leverages the Just-in-Time (JIT) compilation capabilities of Google JAX. We refer to this implementation as JFSD and perform benchmarks on it to verify that it has the right scaling and is sufficiently fast by the standards of modern computational physics. In addition, we provide a series of physical test cases that help ensure accuracy and robustness, as the code undergoes further development. Thus, JFSD is ready to facilitate the study of hydrodynamic effects in particle suspensions across the domains of soft, active, and granular matter.

  1 citation

• Python-JAX-based fast Stokesian dynamics

  Kim William Torre, Raoul D. Schram, Joost de Graaf

  SciPost Phys. Codebases 56 (2025) · published 30 June 2025 | Toggle abstract · pdf

  Stokesian Dynamics (SD) is a powerful computational framework for simulating the motion of particles in a viscous Newtonian fluid under Stokes-flow conditions. Traditional SD implementations can be computationally expensive as they rely on the inversion of large mobility matrices to determine hydrodynamic interactions. Recently, however, the simulation of thermalized systems with large numbers of particles has become feasible [Fiore and Swan, J. Fluid Mech. 878, 544 (2019)]. Their "fast Stokesian dynamics" (FSD) method leverages a saddle-point formulation to ensure overall scaling of the algorithm that is linear in the number of particles $\mathcal{O}(N)$; performance relies on dedicated graphics-processing-unit computing. Here, we present a different route toward implementing FSD, which instead leverages the Just-in-Time (JIT) compilation capabilities of Google JAX. We refer to this implementation as JFSD and perform benchmarks on it to verify that it has the right scaling and is sufficiently fast by the standards of modern computational physics. In addition, we provide a series of physical test cases that help ensure accuracy and robustness, as the code undergoes further development. Thus, JFSD is ready to facilitate the study of hydrodynamic effects in particle suspensions across the domains of soft, active, and granular matter.

  3 citations