Maximum Probability Domains for Hubbard Models
Guillaume Acke, Stijn De Baerdemacker, Pieter W. Claeys, Mario Van, Raemdonck, Ward Poelmans, Dimitri Van Neck, Patrick Bultinck
TL;DR
This paper extends the concept of Maximum Probability Domains (MPDs) to Hubbard models, providing a new analytical approach that reveals key physical insights consistent with Valence Bond Theory.
Contribution
It formulates MPDs for the Hubbard model using projection operators and generating functions, and introduces a fast analysis method for numerical results.
Findings
MPDs effectively expose the essential physics of Hubbard models
MPDs align with Valence Bond Theory expectations
A fast MPD analysis procedure is proposed
Abstract
The theory of Maximum Probability Domains (MPDs) is formulated for the Hubbard model in terms of projection operators and generating functions for both exact eigenstates as well as Slater determinants. A fast MPD analysis procedure is proposed, which is subsequently used to analyse numerical results for the Hubbard model. It is shown that the essential physics behind the considered Hubbard models can be exposed using MPDs. Furthermore, the MPDs appear to be in line with what is expected from Valence Bond Theory-based knowledge.
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.