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David Williams

16
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  • IdHAL dmg-williams
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Présentation

**ORCID:** [0000-0001-9627-5647](https://orcid.org/0000-0001-9627-5647) **Web of Science:** [AFR-4512-2022](https://www.webofscience.com/wos/author/record/3701240) ## Past Employment **Postdoctoral researcher** with a focus on developing efficient artificial neural network based approaches for accurate, high dimensional excited state dynamics. * **Sep 2023 – Present** European MCSA-Bienvenue postdoctoral fellow at the Institute of Physics Rennes (IPR), France * **Spring 2023** collaborating visit at the IPR, Rennes, France * **Year 2022** postdoctoral researcher in the Martínez group at Stanford University, CA, USA * **Year 2021** postdoctoral reseacher in the Eisfeld group at the University of Bielefeld, Germany * **Jan 2021** PhD under Wolfgang Eisfeld at the University of Bielefeld, Germany ## Research Interests * **Photochemical processes in atmospheric and astrochemistry:** Particular focus on isolated molecules in the gas phase at finite temperature, with research experience in the modelling of photodetachment processes. * **Numerical method development based on artificial neural networks:** Developed and refined schemes for the construction of diabatic potential energy surfaces using artificial neural networks. Particularly focused on preconditioning techniques to imbue models with physical information, reducing the strain of the network. * **Efficient, modularized models of complex systems:** Continued efforts to provide schemes that allow for models to be extended to the full-dimensional problem by building upon restricted-dimensional models to mitigate innate problems of high-dimensional coordinate spaces (curse of dimensionality). * **Molecular quantum dynamics of excited states:** Conducted in-depth theoretical studies of Jahn-Teller type systems and the impact of the geometric phase effect on their spectroscopy. * **Mechanochemistry and photoswitches:** General interest in the development of high quantum yield photoswitches and molecular machines. ## Education * **2016 – Jan. 2021** Dr. rer. nat. (PhD), Theoretical Chemistry, Bielefeld University, Germany - *"Conquering coupled diabatic potential energy surfaces with artificial neural networks for nonadiabatic dynamics''* * **2014 – 2016** Master of Science, Theoretical Chemistry, Bielefeld University, Germany - *"Neural Network Based Methods for the Representation of Diabatic Potential Energy Surfaces''*

Compétences

Excited state modeling Nonadiabatically coupled potential method development Artificial neural network based models

Publications

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Geometric phase in coupled cluster theory

David Williams , Eirik Kjønstad , Todd Martínez
Journal of Chemical Physics, 2023, 158 (21), ⟨10.1063/5.0151856⟩
Article dans une revue hal-04179328v1
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Simulation of the photodetachment spectra of the nitrate anion (NO3-) in the B 2E' energy range and non-adiabatic electronic population dynamics of NO3

David M. G. Williams , Wolfgang Eisfeld , Alexandra Viel
Physical Chemistry Chemical Physics, 2022, 24 (40), pp.24706-24713. ⟨10.1039/D2CP02873E⟩
Article dans une revue hal-03740299v1
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Accurate quantum dynamics simulation of the photodetachment spectrum of the nitrate anion (NO3−) based on an artificial neural network diabatic potential model

Alexandra Viel , David M. G. Williams , Wolfgang Eisfeld
Journal of Chemical Physics, 2021, 154 (8), pp.084302. ⟨10.1063/5.0039503⟩
Article dans une revue hal-03149863v1
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Complete Nuclear Permutation Inversion Invariant Artificial Neural Network (CNPI-ANN) Diabatization for the Accurate Treatment of Vibronic Coupling Problems

David M. G. Williams , Wolfgang Eisfeld
Journal of Physical Chemistry A, 2020, 124 (37), pp.7608-7621. ⟨10.1021/acs.jpca.0c05991⟩
Article dans une revue hal-02984550v1
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Diabatic neural network potentials for accurate vibronic quantum dynamics -The test case of planar NO3

David M. G. Williams , Wolfgang Eisfeld , Alexandra Viel
Journal of Chemical Physics, 2019, 151 (16), pp.164118. ⟨10.1063/1.5125851⟩
Article dans une revue hal-02317939v1
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Quantum dynamics and geometric phase in E ⊗ e Jahn-Teller systems with general Cnv symmetry

Thomas Weike , David M. G. Williams , Alexandra Viel , Wolfgang Eisfeld
Journal of Chemical Physics, 2019, 151 (7), pp.074302. ⟨10.1063/1.5115396⟩
Article dans une revue hal-02267828v1
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Neural network diabatization: A new ansatz for accurate high-dimensional coupled potential energy surfaces

David M. G. Williams , Wolfgang Eisfeld
Journal of Chemical Physics, 2018, 149 (20), pp.204106. ⟨10.1063/1.5053664⟩
Article dans une revue hal-02906091v1
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A new approach for the development of diabatic potential energy surfaces: Hybrid block-diagonalization and diabatization by ansatz

Nils Wittenbrink , Florian Venghaus , David M. G. Williams , Wolfgang Eisfeld
Journal of Chemical Physics, 2016, 145 (18), pp.184108. ⟨10.1063/1.4967258⟩
Article dans une revue hal-02906093v1

Artificial Neural Networks: Toward Efficient Nonadiabatic Dynamics with Coupled Potential Energy Surfaces

David M. G. Williams , Alexandra Viel , Wolfgang Eisfeld , Todd J Martínez
American Conference on Theoretical Chemistry, https://www.actc2022.com/, Jul 2022, Palisades Tahoe, United States
Communication dans un congrès hal-03976934v1

Dynamics on accurate coupled artificial neural network based potential surfaces : NO_3^- photodetachment spectra

Alexandra Viel , David M. G. Williams , Wolfgang Eisfeld
7th High Dimensional Quantum Dynamics (HDQD), https://www.hdqd2022.org/, Jul 2022, Groningen, Netherlands
Communication dans un congrès hal-02262273v1

Photodetachment spectrum of NO3-: Jahn-Teller effect and artificial neuron network

Alexandra Viel , David M. G. Williams , Wolfgang Eisfeld
CECAM2021 : Modeling dilute matter under ultracold solvent: from quantum structure to dynamics and reactivity, May 2021, Grenoble, France
Communication dans un congrès hal-03212344v1

Symmetry, geometric phase and spectroscopy

Wolfgang Eisfeld , Thomas Weike , David M. G. Williams , Alexandra Viel
Electronic Structure, Dynamics & Spectroscopy (Domcke's 70th Birthday), Apr 2018, Garching, Germany
Communication dans un congrès hal-01773875v1

Efficient Nonadiabatic Dynamics with Artificial Neural Networks

David M. G. Williams , Alexandra Viel , Wolfgang Eisfeld , Todd J Martínez
American Conference on Theoretical Chemistry, Jul 2022, Palisades Tahoe, United States
Poster de conférence hal-03976949v1

Accurate vibronic quantum dynamics of NO3 using a diabatic neural network potential

David M. G. Williams , Wolfgang Eisfeld
22nd European Conference on the Dynamics of Molecular Systems, Aug 2018, Dinard, France
Poster de conférence hal-03976972v1

Neural Network Diabatization: A new ansatz for high-dimensional coupled potential energy surfaces

David M. G. Williams , Wolfgang Eisfeld
Symposium on Theoretical Chemistry, Aug 2017, Basel, Switzerland
Poster de conférence hal-03976989v1