Noé Blassel
I am a postdoctoral researcher in the institute of Mathematics of EPFL working within the MatMat group on data-driven methods in quantum chemistry.
I recently defended my PhD thesis in Mathematics at the CERMICS lab of École Nationale des Ponts et Chaussées, in the MATHERIALS INRIA research project. During my PhD, I studied and constructed algorithms in molecular dynamics to accelerate the sampling of rare events (such as transitions between metastable configurations) and the computation of transport coefficients.
Session
Transport coefficients are quantities measuring sensitivities in various fluxes for equilibrium molecular systems subject to thermodynamic forcings driving them out of equilibrium. Typical examples are diffusivity, shear viscosity or thermal conductivity, which enter as parameters in macroscopic models of fluids and materials. Unfortunately, these are notoriously difficult to compute, and there is still a need to develop more efficient algorithms.
We will present three algorithms to compute transport coefficients in stochastic MD: the Green-Kubo method, the nonequilibrium molecular dynamics (NEMD) method, and the constant-flux approach recently proposed in this work.
We discuss how Molly.jl, with its highly extensible design, allows to rapidly implement these methods and assess their relative performance. This leads in particular to discover promising properties of the constant-flux approach, narrowing the gap between mathematical ideas in statistical physics and applications in computational science.
This is joint work with Gabriel Stoltz.