[CS] Elena Orlova Candidacy Exam/May 30, 2024

[via cs]

This is an announcement of Elena Orlova's Candidacy Exam.
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Candidate: Elena Orlova

Date: Thursday, May 30, 2024

Time: 11 am CT

Location: JCL 298

Title: Deep Stochastic Mechanics

Abstract: This work introduces a novel deep-learning-based approach for numerical simulation of a time-evolving Schrödinger equation inspired by stochastic mechanics and generative diffusion models. Unlike existing approaches, which exhibit computational complexity that scales exponentially in the problem dimension, our method allows us to adapt to the latent low-dimensional structure of the wave function by sampling from the Markovian diffusion. Depending on the latent dimension, our method may have far lower computational complexity in higher dimensions. Moreover, we propose novel equations for stochastic quantum mechanics, resulting in quadratic or linear computational complexity with respect to the number of dimensions. Numerical simulations verify our theoretical findings and show a significant advantage of our method compared to other deep-learning-based approaches used for quantum mechanics.

Advisors: Rebecca Willett

Committee Members: Rebecca Willett, Ian Foster, and Yuxin Chen