Dear Colleagues,
I'm sending you this friendly reminder for the upcoming webinar. You are cordially invited to join 2023 Dartmouth Summer Data Science and AI Webinar Series - Week 6. Please take a look at the details of the event below.
Title: Reinforcement Learning for Quantum Control of Interacting Spin Systems
Date/Time: August 10, Thursday, 11:00 AM – 12:00 PM EST.
Abstract:
A key task in almost all quantum technologies is to control the physical platform to execute the desired operations, such as for example to apply a particular quantum gate during a computational task. Accurately controlling the dynamics of quantum systems given the available physical resources is the core challenge of quantum control. One form of quantum control that has a long history in chemistry and spectroscopy is Average Hamiltonian Theory (AHT) which has been used for over 50 years in electron and nuclear magnetic resonance experiments to improve spectroscopic resolution. Though complex, the technique has been remarkably successful in enabling the design of quantum control sequences in magnetic resonance. In this talk I will explore our recent work using reinforcement learning (RL) as an alternative approach to engineer the dynamics of solid-state spin systems. RL is a type of machine learning and treats the system's dynamics as a black box but has the potential to provide robustness to experimental imperfections. However, unconstrained RL algorithms have not outperformed conventional methods to date. Using theoretical insights into the quantum dynamics of the interacting spin systems to constrain the action space of the RL algorithm, we show that RL designed sequences can potentially outperform AHT for the problem of decoupling magnetic dipolar interactions in solid-state spin systems.
Bio of the speaker:
Chandrasekhar Ramanathan is a Professor of Physics and Astronomy at Dartmouth College. He studies quantum sensing and simulation with a strong focus on the experimental control and characterization of many-body quantum dynamics of solid-state spin systems.
This webinar will be offered online via Zoom. Please register to receive the Zoom link (one day before the webinar).
Registration link: libcal.dartmouth.edu/calendar/itc/2023DSAIW6
Look forward to seeing you at the webinar!
------------------------------
Jianjun Hua
Dartmouth College
------------------------------