Improved multi-variable variational Monte Carlo method examined by high-precision calculations of one-dimensional Hubbard model

Ryui Kaneko, Satoshi Morita, Masatoshi Imada

Research output: Contribution to journalConference article

4 Citations (Scopus)

Abstract

We revisit the accuracy of the variational Monte Carlo (VMC) method by taking an example of ground state properties for the one-dimensional Hubbard model. We start from the variational wave functions with the Gutzwiller and long-range Jastrow factor introduced by Capello et al. [Phys. Rev. B 72, 085121 (2005)] and further improve it by considering several quantum-number projections and a generalized one-body wave function. We find that the quantum spin projection and total momentum projection greatly improve the accuracy of the ground state energy within 0.5% error, for both small and large systems at half filling. Besides, the momentum distribution function n(k) at quarter filling calculated up to 196 sites allows us direct estimate of the critical exponents of the charge correlations from the power-law behavior of n(k) near the Fermi wave vector. Estimated critical exponents well reproduce those predicted by the Tomonaga-Luttinger theory.

Original languageEnglish
Article number012046
JournalJournal of Physics: Conference Series
Volume454
Issue number1
DOIs
Publication statusPublished - 2013 Jan 1
Externally publishedYes
Event24th IUPAP Conference on Computational Physics, IUPAP-CCP 2012 - Kobe, Japan
Duration: 2012 Oct 142012 Oct 18

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Monte Carlo method
projection
wave functions
exponents
momentum
ground state
quantum numbers
distribution functions
estimates
energy

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Improved multi-variable variational Monte Carlo method examined by high-precision calculations of one-dimensional Hubbard model. / Kaneko, Ryui; Morita, Satoshi; Imada, Masatoshi.

In: Journal of Physics: Conference Series, Vol. 454, No. 1, 012046, 01.01.2013.

Research output: Contribution to journalConference article

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