Energy spectrum for a atrongly correlated network and local magnetism

Li-li LIU (刘莉丽) , Qiao BI (毕桥)

Front. Phys. ›› 2009, Vol. 4 ›› Issue (2) : 218 -224.

PDF (452KB)
Front. Phys. ›› 2009, Vol. 4 ›› Issue (2) : 218 -224. DOI: 10.1007/s11467-009-0047-1
RESEARCH ARTICLE

Energy spectrum for a atrongly correlated network and local magnetism

Author information +
History +
PDF (452KB)

Abstract

In this work, we consider a quantum strongly correlated network described by an Anderson s - d mixing model. By introducing the Green function on the projected formalism of the Schrieffer and Wolf transformation, the energy spectrum of the system can be obtained. Using this result we calculate the survivability distribution of the network and discuss the local magnetism in the network, which shows that the survivability is an important statistical characteristic quantity not just to reflect the network topological property but also dynamics.

Keywords

strongly correlated system / quantum network / Green function

Cite this article

Download citation ▾
Li-li LIU (刘莉丽), Qiao BI (毕桥). Energy spectrum for a atrongly correlated network and local magnetism. Front. Phys., 2009, 4(2): 218-224 DOI:10.1007/s11467-009-0047-1

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

P. W. Anderson, Phys. Rev., 1961, 124: 41

[2]

J. R. Schrieffer and P. A. Wolff, Phys. Rev., 1966, 149: 491

[3]

G. Bianconi, arXiv: cond-mat/0204506v2

[4]

G. Bianconi, Phys. Rev. E, 2002, 66: 056123

[5]

D. Baeriswyl, D. K. Campbell, J. M. P. Carmelo, F. Guinea, and E. Louis, The Hubbard Model, New York: Pienum Press, 1995

[6]

J. R. Schrieffer and P. A. Wolff, Phys. Rev., 1966, 149: 491

[7]

L. Z. Zheng, Solid State Theory, Beijing: Higher Education Press, 2002 (in Chinese)

[8]

I. Antoniou, Y. Melnikov, and Q. Bi, Physica A, 1997, 246: 97

[9]

Q. Bi, H. E. Ruda, M. S. Zhang, and X. H. Zeng, Physica A, 2003, 322: 345

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg

AI Summary AI Mindmap
PDF (452KB)

917

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/