Finite Size Scaling in the tt'-Hubbard Model and in BCS-Reduced Hubbard Models

Author:

Fettes W.1,Morgenstern I.1

Affiliation:

1. Fakultät Physik, Universität Regensburg, D-93040 Regensburg, Germany

Abstract

With the projector quantum Monte Carlo algorithm and the stochastic diagonalization it is possible to calculate the ground state of the Hubbard model for small finite clusters. Nevertheless the usual finite size scaling of the Hubbard model has problems of deducing the behavior of the infinite system correctly from the numerical data of small system sizes. Therefore we study the finite size scaling of the superconducting correlation functions in superconducting BCS-reduced Hubbard models to analyze the finite size behavior in small finite clusters. The ground state of the BCS-reduced Hubbard models is calculated with the stochastic diagonalization without any approximations. As result of these analyses we propose a new finite size scaling ansatz for the Hubbard model, which is able describe the finite size effects in a consistent way taking the corrections to scaling into account, which are dominant for weak interaction strength and small clusters. With this new finite size scaling ansatz it is possible to give evidence for superconductivity for all interaction strengths for both the attractive tt'-Hubbard model (with s-wave symmetry) and the repulsive tt'-Hubbard model (with dx2-y2-wave symmetry).

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Quantum Monte Carlo study of Spin, Charge, and Pairing correlations in thet−t′−UHubbard model;Physical Review B;2001-10-18

2. Limitations of the stochastic diagonalization and the projector QMC in the 2D Hubbard model;Computer Physics Communications;2000-02

3. GLASS MODEL, HUBBARD MODEL AND HIGH-TEMPERATURE SUPERCONDUCTIVITY;International Journal of Modern Physics C;1999-02

4. Stochastic Diagonalization;Quantum Monte Carlo Methods in Physics and Chemistry;1999

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