Convolutional restricted Boltzmann machine (CRBM) correlated variational wave function for the Hubbard model on a square lattice: Mott metal-insulator transition
Karthik V., Amal Medhi

TL;DR
This paper introduces a convolutional restricted Boltzmann machine (CRBM) based variational wave function for the Hubbard model, efficiently capturing correlations and accurately describing the Mott transition on a square lattice.
Contribution
The paper presents a novel CRBM-based variational wave function that outperforms previous methods in modeling the Hubbard model, with improved efficiency and accuracy in capturing the Mott transition.
Findings
CRBM wave function outperforms long-range backflow-Jastrow wave functions.
Identifies a first-order Mott transition at a critical U.
Spin gapped antiferromagnetic order emerges spontaneously.
Abstract
We use a convolutional restricted Boltzmann machine (CRBM) neural network to construct a variational wave function (WF) for the Hubbard model on a square lattice and study it using the variational Monte Carlo (VMC) method. In the wave function, the CRBM acts as a correlation factor to a mean-field BCS state. The number of variational parameters in the WF does not grow automatically with the lattice size and it is computationally much more efficient compared to other neural network based WFs. We find that in the intermediate to strong coupling regime of the model at half-filling, the wave function outperforms even the highly accurate long range backflow-Jastrow correlated wave function. Using the WF, we study the ground state of the half-filled model as a function of onsite Coulomb repulsion . We consider two cases for the next-nearest-neighbor hopping parameter, e.g., as well…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum many-body systems · Theoretical and Computational Physics · Opinion Dynamics and Social Influence
