University of Cambridge > Talks.cam > DAMTP Data Intensive Science Seminar > Neural network representation of quantum systems

Neural network representation of quantum systems

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Sven Krippendorf.

We provide a novel map with which a wide class of quantum mechanical systems can be cast into the form of a neural network with a statistical summation over network parameters. Our simple idea is to use the universal approximation theorem of neural networks to generate arbitrary paths in the Feynman’s path integral. The map can be applied to interacting quantum systems / field theories, even away from the Gaussian limit. Our findings bring machine learning closer to the quantum world. The talk is based on a collaboration with Y. Hirono, J. Maeda and J. Totsuka-Yoshinaka, https://arxiv.org/abs/2403.11420

This talk is part of the DAMTP Data Intensive Science Seminar series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity