One-Dimensional Hubbard Model in High Temperatures Through Many-Body Perturbation Theory

Main Article Content

M.A. Tag
A. Hafdallah

Abstract

We present symbolic algorithms designed to investigate the perturbative expansions of the d-Hubbard model. These methods are part of recent developments in many-body perturbation theory that aim to reformulate Feynman diagrams in terms of divided differences. The direct application of this technique to the one-dimensional Hubbard model yields the coefficients of the grand potential up to the sixth order, expressed in terms of both the interacting potential (U expansions) and high-temperature expansions (β expansions). A key feature of this approach is the ability to merge the β expansions to any desired order. To verify our analytical results, we compare the derived magnetic susceptibility with the exact solution of the quantum transfer matrix method in the half-filled case.

Article Details

How to Cite
[1]
M. Tag and A. Hafdallah, “One-Dimensional Hubbard Model in High Temperatures Through Many-Body Perturbation Theory”, Acta Phys. Pol. A, vol. 147, no. 2, p. 79, Feb. 2025, doi: 10.12693/APhysPolA.147.79.
Section
Regular segment

References

H.Q. Lin, Phys. Rev. B 42, 6561 (1990)

A. Weiße, H. Fehske, in: Computational Many-Particle Physics, Lecture Notes in Physics, Vol. 739, Springer, 2008 p. 529

J.M. Zhang, R.X. Dong, Eur. J. Phys. 31, 591 (2010)

P. Sun, G. Kotliar, Phys. Rev. B 66, 085120 (2002)

K. Held, Adv. Phys. 56, 829 (2007)

H. Park, K. Haule, G. Kotliar, Phys. Rev. Lett. 101, 186403 (2008)

S.R. White, Phys. Rev. Lett. 69, 2863 (1992)

S.R. White, Phys. Rev. B 48, 10345 (1993)

Y.-F. Jiang, J. Zaanen, T.P. Devereaux, H.-C. Jiang, Phys. Rev. Res. 2, 033073 (2020)

H. Yokoyama, H. Shiba, J. Phys. Soc. Jpn. 56, 1490 (1987)

K. Ido, T. Ohgoe, M. Imada, Phys. Rev. B 97, 045138 (2018)

H. Shi, S. Zhang, Phys. Rev. B 88, 125132 (2013)

S. Zhang, in: Emergent Phenomena in Correlated Matter Modeling and Simulation, Vol. 3, Eds. E. Pavarini, E. Koch, U. Schollwöck, Verlag des Forschungszentrums Jülich, 2013 p. 1

M. Motta, S. Zhang, Wiley Interdiscip. Rev. Comput. Mol. Sci. 8, e1364 (2018)

F.D. Malone, S. Zhang, M.A. Morales, J. Chem. Theory Comput. 15, 256 (2019)

G. Knizia, G.K.L. Chan, Phys. Rev. Lett. 109, 186404 (2012)

G. Knizia, G.K.L. Chan, J. Chem. Theory Comput. 9, 1428 (2013)

B.-X. Zheng, G.K.-L. Chan, Phys. Rev. B 93, 035126 (2016)

N. V. Prokof'ev, B.V. Svistunov, Phys. Rev. Lett. 81, 2514 (1998)

K. Van Houcke, E. Kozik, N. Prokof'ev, B. Svistunov, Phys. Proc. 6, 95 (2010)

Y. Deng, E. Kozik, N.V. Prokof'ev, B.V. Svistunov, Europhys. Lett. 110, 57001 (2015)

M.A. Tag, A. Boudiar, M.E.H. Mansour, A. Hafdallah, C. Bendjeroudib, B. Zaidi, Phys. Scr. 99, 065993 (2024)

J. Hubbard, Proc. R. Soc. A 276, 238 (1963)

M.C. Gutzwiller, Phys. Rev. Lett. 10, 159 (1963)

M. Tag, M. Mansour, Int. J. Mod. Phys. C 30, 1950100 (2019)

M. Tag, S. Khéne, Int. J. Mod. Phys. C 28, 1750113 (2017)

T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, Introduction to Algorithms, 3rd ed., MIT Press, 2009, p. 41; p. 900; p. 990

I. Charret, E. Silva, S. de Souza, O. Santos, M.T. Thomaz, A.T. Costa Jr., Phys. Rev. B 64, 195127 (2001)

G. Jüttner, A. Klümper, J. Suzuki, Nucl. Phys. B 522, 471 (1998)

M.A. Tag, High Temperature Series Expansion of 1D Hubbard Model, 2025