Group symmetric neural networks for quantum dimer models
APA
(2025). Group symmetric neural networks for quantum dimer models. SciVideos. https://youtu.be/NlQ3oHTOoEA
MLA
Group symmetric neural networks for quantum dimer models. SciVideos, Apr. 23, 2025, https://youtu.be/NlQ3oHTOoEA
BibTex
@misc{ scivideos_ICTS:31640, doi = {}, url = {https://youtu.be/NlQ3oHTOoEA}, author = {}, keywords = {}, language = {en}, title = {Group symmetric neural networks for quantum dimer models}, publisher = {}, year = {2025}, month = {apr}, note = {ICTS:31640 see, \url{https://scivideos.org/icts-tifr/31640}} }
Abstract
We present results of construction of the ground states of a paradigmatic strongly interacting quantum system namely the square lattice quantum dimer model as a group equivariant convolutional neural network variational state. The network is trained by minimizing, using stochastic gradient descent, the Monte Carlo estimated energy expectation value. We show comparison with exact diagonalization for small systems (size = 8x8) and with quantum Monte Carlo for larger systems up to 48x48.