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Hubbard model

Known as: Hubbard 
The Hubbard model is an approximate model used, especially in solid state physics, to describe the transition between conducting and insulating… 
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Related topics

Related topics

22 relations
Anderson impurity modelAuxiliary field Monte CarloBose–Hubbard modelBound state

Papers overview

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Highly Cited
2018
Highly Cited
2018
Maximally Localized Wannier Orbitals and the Extended Hubbard Model for Twisted Bilayer Graphene
We develop an effective extended Hubbard model to describe the low-energy electronic properties of the twisted bilayer graphene… 
Highly Cited
2012
Highly Cited
2012
Fermionic transport and out-of-equilibrium dynamics in a homogeneous Hubbard model with ultracold atoms
Transport properties are among the defining characteristics of many important phases in condensed-matter physics. In the presence… 
Highly Cited
2006
Highly Cited
2006
Dual fermion approach to nonlocal correlations in the Hubbard model
A diagrammatic technique is developed to describe nonlocal effects (e.g., pseudogap formation) in the Hubbard-like models. In… 
Highly Cited
2005
Highly Cited
2005
The One-Dimensional Hubbard Model: Index
Preface 1. Introduction 2. The Hubbard Hamiltonian and its symmetries 3. The Bethe ansatz solution 4. String hypothesis 5… 
Highly Cited
1999
Highly Cited
1999
Understanding the Determinants of Managerial Ownership and the Link Between Ownership and Performance
Highly Cited
1997
Highly Cited
1997
Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?
No. This paper investigates the relationship between financing constraints and investment-cash flow sensitivities by analyzing… 
Review
1997
Review
1997
FROM NAGAOKA'S FERROMAGNETISM TO FLAT-BAND FERROMAGNETISM AND BEYOND : AN INTRODUCTION TO FERROMAGNETISM IN THE HUBBARD MODEL
This is a self-contained review about ferromagnetism in the Hubbard model, which should be accessible to readers with various… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Highly Cited
1992
Highly Cited
1992
Liquidation Values and Debt Capacity: A Market Equilibrium Approach
We explore the determinants of liquidation values of assets, particularly focusing on the potential buyers of assets. When a firm… 
Highly Cited
1992
Highly Cited
1992
Debt, liquidity constraints, and corporate investment: evidence from panel data
This paper presents evidence supporting the theory that problems of asymmetric information in debt markets affect financially… 
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