Physics-Informed-Neural-Networks for the Wigner-Fokker-Planck model of open quantum systems
In this talk, we will present current work on the use of PINNs (Physics-Informed-Neural-Networks) to solve the Wigner-Fokker-Planck model for open quantum systems. We will first present a brief introduction to PINNs in particular), and then we will describe the Physics of open quantum systems, as well as the Wigner formulation of this problem in a quantum phase space (when it admits a continuous variable description), and our preliminary results for it. This work is being done in collaboration with Isaul Garcia from UTSA.
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- 6220 Culebra Road
- Archives Building 51
- San Antonio, Texas
- United States 78238
- Building: 51
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- Co-sponsored by WIE
- Starts 29 March 2024 05:00 AM UTC
- Ends 08 April 2024 11:00 PM UTC
- No Admission Charge
Speakers
Jose of UT San Antonio
Physics-Informed-Neural-Networks for the Wigner-Fokker-Planck model of open quantum systems
In this talk, we will present current work on the use of PINNs (Physics-Informed-Neural-Networks) to solve the Wigner-Fokker-Planck model for open quantum systems. We will first present a brief introduction to PINNs in particular), and then we will describe the Physics of open quantum systems, as well as the Wigner formulation of this problem in a quantum phase space (when it admits a continuous variable description), and our preliminary results for it. This work is being done in collaboration with Isaul Garcia from UTSA.
Biography:
Jose' Morales Escalante currently works as an Assistant Professor at The University of Texas at San Antonio Departments of Mathematics and Physics & Astronomy. He did his Bachelor in Physics at UNAM, the National University of Mexico, with a thesis on the Theory and Experiments of Solitons in Water, under the advising of Professors María del Carmen Jorge & Panos Panayotaros at IIMAS-UNAM. He did a PhD in Computational Science, Engineering, and Mathematics at the Institute for Computational Engineering and Sciences of The University of Texas at Austin, working on the Math & Computational Modeling of Electron Transport in Semiconductors by means of Discontinuous Galerkin Methods for Boltzmann – Poisson, under the advising of Professor Irene Gamba.
He worked as a Postdoctoral Researcher at the TU Vienna Institute for Analysis and Scientific Computing on deterministic and stochastic numerical methods for Boltzmann – Poisson models of collisional electron transport, under the advising of Associate Professor Clemens Heitzinger.
He worked as a Postdoctoral Fellow in the Department of Mathematics & Statistics at McMaster University, on the mathematical and computational modeling of nonequilibrium electrochemical and thermodynamic processes occurring in Li-ion batteries, under the advising of Professor Bartosz Protas, in a joint project with the McMaster Department of Chemistry and General Motors Canada.
Email:
Address:1 UTSA Circle, FLN 4.01.40, , San Antonio, United States, 78249