Publications associées à Identifying clusters as low-lying minima - Efficiency of stochastic and genetic algorithms using inexpensive electronic structure levels

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Karen Ann J Mulleners, Sébastien Le Fouest

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024

Hidden Gems on a Ring: Infant Massive Clusters and Their Formation Timeline Unveiled by ALMA, HST, and JWST in NGC 3351

Robin Gopala Tress, Jiayi Sun, Hamid Hassani, Hao He

We use 0.1 '' observations from the Atacama Large Millimeter Array (ALMA), Hubble Space Telescope (HST), and JWST to study young massive clusters (YMCs) in their embedded "infant" phase across the central starburst ring in NGC 3351. Our new ALMA data revea ...

Iop Publishing Ltd2024

Genetic Algorithms for the Discovery of Homogeneous Catalysts

Rubén Laplaza Solanas, Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Alexandre Alain Schöpfer, Simone Gallarati

In this account, we discuss the use of genetic algorithms in the inverse design process of homogeneous catalysts for chemical transformations. We describe the main components of evolutionary experiments, specifically the nature of the fitness function to o ...

2023

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Pergamon-Elsevier Science Ltd2023

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

Fernando Porté Agel, Nicolas Otto Kirchner Bossi

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

Pergamon-Elsevier Science Ltd2023

Optimization of elastic wave propagation in a reconfigurable medium by genetic algorithms with adaptive mutation probability

Romain Christophe Rémy Fleury, Janez Rus

We introduce a reconfigurable medium for the manipulation of elastic propagation properties of Lamb waves. It is based on a shape memory polymer (SMP) with temperature-dependent Young's modulus. Waves are excited by a laser pulse and detected by a laser vi ...

IOP Publishing Ltd2023

The PHANGS-JWST Treasury Survey: Star Formation, Feedback, and Dust Physics at High Angular Resolution in Nearby GalaxieS

Robin Gopala Tress, Jing Li, Guillaume Blanc, Jiayi Sun, Hamid Hassani, Francesco Santoro

The PHANGS collaboration has been building a reference data set for the multiscale, multiphase study of star formation and the interstellar medium (ISM) in nearby galaxies. With the successful launch and commissioning of JWST, we can now obtain high-resolu ...

IOP Publishing Ltd2023

Molecular and ionized gas in tidal dwarf galaxies: the spatially resolved star formation relation

Yves Revaz

Tidal dwarf galaxies (TDGs) are low-mass objects that form within tidal and/or collisional debris ejected from more massive interacting galaxies. We use CO(1-0) observations from Atacama Large Millimeter/submillimeter Array and integral-field spectroscopy ...

Oxford Univ Press2023

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

A new step forward in realistic cluster lens mass modelling: analysis of Hubble Frontier Field Cluster Abell S1063 from joint lensing, X-ray, and galaxy kinematics data

Jean-Paul Richard Kneib, Benjamin Yvan Alexandre Clement, Benjamin Emmanuel Nicolas Beauchesne, Mathilde Jauzac, Johan Richard

We present a new method to simultaneously and self-consistently model the mass distribution of galaxy clusters that combines constraints from strong lensing features, X-ray emission, and galaxy kinematics measurements. We are able to successfully decompose ...

Oxford Univ Press2023