Program

Monday, October 7, 2019

Time Event  
09:45 - 10:00 Registration and welcome breakfast - Registration and welcome breakfast  
10:00 - 11:45 General presentation of the project - members, objectives, current tasks, synergies between its components  
12:15 - 14:00 Lunch at the Ardoise on the campus Pierre & Marie Curie (ardoise)  
14:30 - 15:00 Sylvie Boldo - From mathematics to programs: a verification journey  
15:00 - 15:30 Benjamin Stamm : Gradient flow finite element discretizations with energy-based adaptivity for the Gross Pitaevskii Equation - We present an effective adaptive procedure for the numerical approximation of the steady-state Gross-Pitaevskii equation which consists of a combination of gradient flow iterations and adaptive finite element mesh refinements. The mesh-refinement is solely based on energy minimization. Numerical tests show that this strategy is able to provide highly accurate results, with optimal convergence rates with respect to the number of freedom.  
15:30 - 16:00 Coffee break (309, 15-25)  
16:00 - 16:30 Carlo Marcati - Weighted analytic regularity and exponential convergence for electronic structure calculations  
16:30 - 17:00 Alston Misquitta - Development of ab initio force fields  
17:00 - 18:00 Discussions between participants - Discussions between participants  

Tuesday, October 8, 2019

Time Event  
09:00 - 09:30 Jay Ponder - Free energy calculations with AMOEBA  
09:30 - 10:00 Stéphane Mallat - Wavelet Scattering for Predictions of Molecule Properties - S. Mallat with M. Eickenberg, G. Exarchakis, M. Hirn,Mallat,and L. Thiry We present a machine learning algorithm for the prediction of molecule energies inspired by ideas from density functional theory. Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule, from which we compute invariant solid harmonic scattering coefficients that account for different types of interactions at different scales. Multi-linear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state of the art performance, even with relatively few training examples. Predictions over small sets of scattering coe cients can reach a DFT precision while being interpretable.  
10:00 - 10:45 Coffee break  
10:45 - 11:15 Venera Khoromskaia - “Tensor numerical methods in quantum chemistry: from Hartree-Fock energies to optical spectra of compact molecules”.  
11:15 - 11:45 Boris Khoromskij - Range-separated tensor format in bio-molecular modelling and in data scienc  
11:45 - 12:15 Discussions (309, 15-25)  
12:15 - 14:00 Lunch Tour Zamansky (24 étage) (salle de réception au 24 eme étage de la tour Zamanski)  
14:00 - 14:30 Agnieszka Miedlar - Randomized methods and the future of numerical linear algebra  
14:30 - 15:00 Daniel Kressner : Randomized methods for tensor compression - Probabilistic approaches to low-rank matrix approximation, such as the randomized singular value decomposition, have gained popularity during the last few years, thanks to their simplicity, effectiveness, and flexibility. This talk is concerned with various extensions of these approaches to tensors. In particular, we will focus on the benefits and challenges arising from imposing rank-one structure on the involved random vectors. On the one hand, this can increase the efficiency of randomized methods for tensors, sometimes dramatically. On the other hand, this also significantly complicates the probablistic analysis, e.g., for deriving tail bounds and guaranteeing high accuracy with high probability. This talk is based on joint work with Lana Perisa and Zvonimir Bujanovic.  
15:00 - 15:30 discussions - discussions  
15:30 - 16:00 Coffee break  
16:00 - 16:30 Filippo Lipparini - General linear scaling implementation of polarizable embedding schemes  
16:30 - 17:00 Martin Vohralik : A posteriori error estimates & adaptivity with balancing error components - We review how to bound the error between the unknown weak solution of a partial differential equation and its computer approximation via a fully computable a posteriori estimate. This allows to certify the numerical simulation result. The particularity of the presented approach is that the derived estimates are valid on each iteration of a linearization procedure, as well as on each algebraic solver iteration; moreover, they allow to distinguish the different error components (discretization/linearization/numerical linear algebra). Fully adaptive algorithms relying on adequate stopping and balancing criteria combined with mesh refinement are designed. Some theoretical results such as efficiency, reliability, robustness with respect to problem or approximation parameters, or convergence and quasi-optimality of the adaptive algorithms are presented and illustrated on numerical experiments. Applications include underground fluid flows and eigenvalue problems.  
17:00 - 18:00 Discussions between participants  
19:15 - 23:55 Dinner  

Wednesday, October 9, 2019

Time Event  
09:00 - 09:30 Mitchell Luskin - Momentum Space Methods for the Electronic Structure of 2D Heterostructures  
09:30 - 10:00 Paul Cazeaux - Twists and misfits: configuration space approaches for relaxation and electronic structure models of 2D heterostructures  
10:00 - 10:45 Coffee break  
10:45 - 11:15 Thomas Simonsons : Molecular recognition in complex biomolecular systems - TBA  
11:15 - 11:45 Julien Toulouse - Strategies for strong correlation in electronic structure theory  
12:30 - 14:30 Lunch at Tour Zamansky (24th floor) (salle de réception au 24 eme étage de la tour Zamanski)  
14:30 - 18:00 Discussions between participants - Discussions between participants  
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