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Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

koopmans: An Open-Source Package for Accurately and Efficiently Predicting Spectral Properties with Koopmans Functionals

Nicola Marzari, Nicola Colonna, Edward Baxter Linscott, Giovanni Borghi, Ngoc Linh Nguyen, Riccardo De Gennaro, Andrea Ferretti

Over the past decade we have developed Koopmans functionals, a computationally efficient approach for predicting spectral properties with an orbital-density-dependent functional framework. These functionals impose a generalized piecewise linearity conditio ...

Amer Chemical Soc2023

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Ursula Röthlisberger, Justin Villard, Martin Peter Bircher

Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

Amer Chemical Soc2023

Predicting nonlinear optical scattering with physics-driven neural networks

Demetri Psaltis, Carlo Gigli, Ahmed Ayoub

Deep neural networks trained on physical losses are emerging as promising surrogates for nonlinear numerical solvers. These tools can predict solutions to Maxwell's equations and compute gradients of output fields with respect to the material and geometric ...

AIP Publishing2023

Two-dimensional Hubbard model at finite temperature: Weak, strong, and long correlation regimes

Riccardo Rossi

We investigate the momentum-resolved spin and charge susceptibilities, as well as the chemical potential and double occupancy in the two-dimensional Hubbard model as functions of doping, temperature, and interaction strength. Through these quantities, we i ...

AMER PHYSICAL SOC2022

Quasi-symmetry-protected topology in a semi-metal

Philip Johannes Walter Moll, Matthias Carsten Putzke, Chunyu Guo, Yi-Chiang Sun, Xiangwei Huang, Jonas De Jesus Diaz Gomez

The concept of quasi-symmetry-a perturbatively small deviation from exact symmetry-is introduced and leads to topological materials with strong resilience to perturbations. ...

NATURE PORTFOLIO2022

A Methodology for Evaluating the Robustness of Anomaly Detectors to Adversarial Attacks in Industrial Scenarios

Javier Alejandro Maroto Morales

Anomaly Detection systems based on Machine and Deep learning are the most promising solutions to detect cyberattacks in the industry. However, these techniques are vulnerable to adversarial attacks that downgrade prediction performance. Several techniques ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Thermal critical points from competing singlet formations in fully frustrated bilayer antiferromagnets

Frédéric Mila, Antoine Yves Dimitri Fache

We examine the ground-state phase diagram and thermal phase transitions in a plaquettized fully frustrated bilayer spin-1/2 Heisenberg model. Based on a combined analysis from sign-problem free quantum Monte Carlo simulations, perturbation theory, and free ...

AMER PHYSICAL SOC2022

The very knotty lenser: Exploring the role of regularization in source and potential reconstructions using Gaussian process regression

Georgios Vernardos

Reconstructing lens potentials and lensed sources can easily become an underconstrained problem, even when the degrees of freedom are low, due to degeneracies, particularly when potential perturbations superimposed on a smooth lens are included. Regulariza ...

OXFORD UNIV PRESS2022

Spectral properties of extended systems from Koopmans-compliant functionals

Riccardo De Gennaro

Electronic-structure simulations have been impacting the study of materials properties thanks to the simplicity of density-functional theory, a method that gives access to the ground state of the system. Although very important, ground-state properties rep ...

EPFL2022

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Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

EPFL2023

koopmans: An Open-Source Package for Accurately and Efficiently Predicting Spectral Properties with Koopmans Functionals

Nicola Marzari, Nicola Colonna, Edward Baxter Linscott, Giovanni Borghi, Ngoc Linh Nguyen, Riccardo De Gennaro, Andrea Ferretti

Amer Chemical Soc2023

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

Ursula Röthlisberger, Justin Villard, Martin Peter Bircher

Amer Chemical Soc2023

NATURE PORTFOLIO2022

The very knotty lenser: Exploring the role of regularization in source and potential reconstructions using Gaussian process regression

Georgios Vernardos

OXFORD UNIV PRESS2022