2006
DOI: 10.1103/physrevlett.97.076405
|View full text |Cite
|
Sign up to set email alerts
|

Continuous-Time Solver for Quantum Impurity Models

Abstract: We present a new continuous-time solver for quantum impurity models such as those relevant to dynamical mean field theory. It is based on a stochastic sampling of a perturbation expansion in the impurity-bath hybridization parameter. Comparisons with Monte Carlo and exact diagonalization calculations confirm the accuracy of the new approach, which allows very efficient simulations even at low temperatures and for strong interactions. As examples of the power of the method we present results for the temperature… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

10
1,232
0

Year Published

2007
2007
2017
2017

Publication Types

Select...
4
2
1

Relationship

0
7

Authors

Journals

citations
Cited by 1,054 publications
(1,242 citation statements)
references
References 15 publications
(25 reference statements)
10
1,232
0
Order By: Relevance
“…To solve the self-consistency equations different techniques ("impurity solvers") have been developed which are either fully numerical and "numerically exact", or semi-analytic and approximate. The numerical solvers can be divided into renormalization group techniques such as the numerical renormalization group (NRG) [37,38] and the density-matrix renormalization group (DMRG) [39], exact diagonalization (ED) [40][41][42], and methods based on the stochastic sampling of quantum and thermal averages, i.e., quantum Monte-Carlo (QMC) techniques such as the Hirsch-Fye QMC algorithm [32,43,44,33] and continuous-time (CT) QMC [45][46][47].…”
Section: Solution Of the Self-consistency Equations Of The Dmftmentioning
confidence: 99%
“…To solve the self-consistency equations different techniques ("impurity solvers") have been developed which are either fully numerical and "numerically exact", or semi-analytic and approximate. The numerical solvers can be divided into renormalization group techniques such as the numerical renormalization group (NRG) [37,38] and the density-matrix renormalization group (DMRG) [39], exact diagonalization (ED) [40][41][42], and methods based on the stochastic sampling of quantum and thermal averages, i.e., quantum Monte-Carlo (QMC) techniques such as the Hirsch-Fye QMC algorithm [32,43,44,33] and continuous-time (CT) QMC [45][46][47].…”
Section: Solution Of the Self-consistency Equations Of The Dmftmentioning
confidence: 99%
“…Since the occupation number n f of the f state is conserved by H c + H f , the "segment picture" 22 can be used for evaluation of the trace for f operators. The f state |f (τ ) fluctuates between the empty state |0 and the occupied state |1 by the hybridization term H hyb as shown in Fig.…”
Section: A Treatment Of the Coulomb Interactionmentioning
confidence: 99%
“…(25). In order to fulfill ergodicity, we need to perform two types of updates: (i) the segment addition/removal as in the ordinary Anderson model 22 , and (ii) a U f c addition/removal update. For update (i), we perform random choice for a new segment in the same way as in Ref.…”
Section: B Monte Carlo Proceduresmentioning
confidence: 99%
See 2 more Smart Citations