Quantum Scientific Machine Learning: from Quantum Circuit Differentiation to Generative Modelling
In this talk, I will introduce the field of quantum scientific machine learning (SciML). Quantum computing has been developing recently and aims to advance various fields of science.
Time: Wed 2023-04-12 11.15 - 12.00
Location: SeRC Room, PDC, Floor 5, Teknikringen 14
Video link: Zoom-link
Language: English
Participating: Dr. Oleksandr Kyriienko
Contact:
Abstract: In the talk, I will introduce the field of quantum scientific machine learning (SciML). Quantum computing has been developing recently and aims to advance various fields of science. One specific area that may greatly benefit from the increased computational power is scientific computing. While solvers for differential equations were perfected for decades and successfully applied to fluid dynamics and mechanics, many data-driven problems require designing new approaches. These problems are often addressed within the machine learning paradigm.
In my presentation, I will describe how to solve tasks of scientific machine learning on quantum computers. First, I will show how to differentiate quantum circuits with feature maps and embed derivatives of multidimensional functions. This approach relies on automatic differentiation to represent derivatives in an analytical form, thus avoiding inaccurate finite difference procedures. We refer to the underlying circuits as derivative quantum circuits (DQCs). I will describe the proposed hybrid quantum-classical workflow where DQCs are trained to satisfy nonlinear differential equations and specified boundary conditions. As an example, I will apply the algorithm to solve a problem from computational fluid dynamics. Second, I will show that DQCs can give an edge in generative modelling from stochastic differential equations, giving access to sampling from relevant stochastic models. Finally, I will discuss the protocols that may be scaled to treat large industrial problems in the future.
Bio: Dr. Oleksandr Kyriienko is a theoretical physicist and a leader of Quantum Dynamics, Optics, and Computing group [https://kyriienko.github.io/]. He is a Senior Lecturer at the Physics department of the University of Exeter, UK. Oleksandr obtained a Ph.D. degree in 2014 from the University of Iceland and was a visiting Ph.D. in diverse institutions, including Nanyang Technological University in Singapore. From 2014 to 2017, he did postdoctoral research at the Niels Bohr Institute, University of Copenhagen. In 2017-2019 he was a Fellow at the Nordic Institute for Theoretical Physics (NORDITA), located in Stockholm, Sweden.
This event is sponsored by the Swedish e-Science Research Centre (SeRC) (https://e-science.se/)