1988
DOI: 10.1103/physrevb.38.433
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Monte Carlo study of the symmetric Anderson-impurity model

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Cited by 89 publications
(69 citation statements)
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“…We did not observe any major difference in the characteristics of the DQMC algorithm in simulating the dynamic Hubbard model: Autocorrelation times remain short, as is typically the case with DQMC, and there was no major change in the numerical stability 3,23,24,25 . The key issue in DQMC is the 'sign problem' which we will discuss in the following sections.…”
Section: Methodsmentioning
confidence: 86%
“…We did not observe any major difference in the characteristics of the DQMC algorithm in simulating the dynamic Hubbard model: Autocorrelation times remain short, as is typically the case with DQMC, and there was no major change in the numerical stability 3,23,24,25 . The key issue in DQMC is the 'sign problem' which we will discuss in the following sections.…”
Section: Methodsmentioning
confidence: 86%
“…In the determinantal Monte Carlo (the Hirsch and Fye algorithm) the impurity susceptibility is very difficult to calculate due to statistical noises in the simulation [21]. The problem is that one has to calculate the total susceptibility for the Anderson Hamiltonian and then subtract the susceptibility for the free case from it.…”
Section: Observablesmentioning
confidence: 99%
“…Finally, some observables are difficult to evaluate. One famous example is the impurity susceptibility which is known to contain large fluctuations [21].…”
Section: Introductionmentioning
confidence: 99%
“…Numerical efforts, which are necessary for the existing numerical methods (e.g., numerical renormalization group (NRG) [39], quantum Monte Carlo [40,41], continuous-time quantum Monte Carlo [42], exact diagonalization [43][44][45], nano-DMFT [46][47][48][49][50][51], and nano-DΓA [48,52]) grow fast with increasing system size or asymmetry, such that the comprehensive analysis of complex quantum dot systems (especially the conductance) is rather difficult for purely numerical methods. Therefore, developing and using semi-analytical techniques is important for description of such systems.…”
Section: Introductionmentioning
confidence: 99%