Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:1004.0724 · Physical Review B

Bold-line diagrammatic Monte Carlo method: General formulation and application to expansion around the noncrossing approximation

Emanuel Gull, David R. Reichman, Andrew J. Millis

Published Aug 6, 2010• 81 citations
arXivHTMLPDF

Abstract

We present a general framework for performing ``bold-line'' diagrammatic Monte Carlo calculations using an analytical partial resummation as a starting point for a stochastic summation of all diagrams. As a stringent test case we assess the accuracy of the method by solving the equations of single-site dynamical mean-field theory, using the noncrossing approximation as a starting point. We establish the validity of the starting approximations and show that the bold method provides a very accurate treatment of the Mott-insulating phase.

DOI
10.1103/physrevb.82.075109

Related papers

Incorporating dynamic mean-field theory into diagrammatic Monte Carlo

Lode Pollet, Nikolay V. Prokof'ev, Boris V. Svistunov

The bold diagrammatic Monte Carlo (BDMC) method performs an unbiased sampling of Feynman's diagrammatic series using skeleton diagrams. For lattice models the efficiency of BDMC can be dramatically improved by incorporating dynamical mean-field theory (DMFT) solutions into renormalized propagators. From the DMFT perspective, combining it with BDMC leads to an unbiased method with well-defined accuracy. We illustrate the power of this approach by computing the single-particle propagator (and thus the density of states) in the non-perturbative regime of the Anderson localization problem, where a gain of the order of ${10}^{4}$ is achieved with respect to conventional BDMC in terms of convergence to the exact answer.

arXiv:1012.5808•Physical Review B•Apr 20, 2011•14 citations

The Bold-Thin-Bold Diagrammatic Monte Carlo Method for Open Quantum Systems

Zhenning Cai, Geshuo Wang, Siyao Yang

Abstract. We present two diagrammatic Monte Carlo methods for quantum systems coupled with harmonic baths, whose dynamics are described by integro-differential equations. The first approach can be considered as a reformulation of the Dyson series, and the second one, called “bold-thin-bold diagrammatic Monte Carlo,” is based on resummation of the diagrams in the Dyson series to accelerate its convergence. The underlying mechanism of the governing equations associated with the two methods lies in the recurrence relation of the path integrals, which is the most costly part in the numerical methods. The proposed algorithms give an extension to the work of Cai, Lu, and Yang [ Comput. Phys. Commun. 278 (2022), 108417], where the algorithms are designed based on reusing the previous calculations of bath influence functionals. Compared with the algorithms therein, our methods further include the reuse of system-associated functionals and show better performance in terms of computational efficiency and memory cost. We demonstrate the two methods in the framework of spin-boson model, and numerical experiments are carried out to verify the validity of the methods.

arXiv:2205.10896•SIAM Journal on Scientific Computing•Jul 19, 2023•8 citations

Integrating dynamical mean-field theory and diagrammatic Monte Carlo

Johan Carlström

Dynamical mean-field theory (DMFT) is one of the most widely used theoretical methods for electronic structure calculations, providing self-consistent solutions even in low-temperature regimes, which are exact in the limit of infinite dimension. The principal limitation of this method is that it neglects spatial fluctuations, which become important in finite dimensions. Diagrammatic Monte Carlo (diagMC), by contrast, provides results that are asymptotically exact for a convergent or resummable series, but are typically limited to high temperature as they depend on the analytic structure of the expansion. In this work, we present a framework for integrating these two methods so that the diagrammatic expansion is conducted around the DMFT solution. This results in a series expansion conducted only in terms that explicitly depend on nonlocal correlations, and which is asymptotically exact.

arXiv:2309.00674•Sep 1, 2023•0 citations

Numerically exact long-time behavior of nonequilibrium quantum impurity models

Emanuel Gull, David R. Reichman, Andrew J. Millis

A Monte Carlo sampling of diagrammatic corrections to the noncrossing approximation is shown to provide numerically exact estimates of the long-time dynamics and steady-state properties of nonequilibrium quantum impurity models. This ``bold'' expansion converges uniformly in time and significantly ameliorates the sign problem that has heretofore limited the power of real-time Monte Carlo approaches to strongly interacting real-time quantum problems. The approach enables the study of previously intractable problems ranging from generic long-time nonequilibrium transport characteristics in systems with large on-site repulsion to the direct description of spectral functions on the real frequency axis in dynamical mean field theory.

arXiv:1105.1175•Physical Review B•Aug 29, 2011•75 citations

Bold Diagrammatic Monte Carlo Technique: When the Sign Problem Is Welcome

Nikolay V. Prokof'ev, Boris V. Svistunov

We introduce a Monte Carlo scheme for sampling a bold-line diagrammatic series specifying an unknown function in terms of itself. The range of convergence of this bold(-line) diagrammatic Monte Carlo (BMC) technique is significantly broader than that of a simple iterative scheme for solving integral equations. With the BMC technique, a moderate "sign problem" turns out to be an advantage in terms of the convergence of the process. For an illustrative purpose, we solve the one-particle s-scattering problem. As an important application, we obtain the T matrix for a Fermi polaron (one spin-down particle interacting with the spin-up fermionic sea).

arXiv:cond-mat/0702555•Physical Review Letters•Dec 18, 2007•147 citations

Diagrammatic Monte Carlo approach for diagrammatic extensions of dynamical mean-field theory: Convergence analysis of the dual fermion technique

Jan Gukelberger, Evgeny Kozik, Hartmut Hafermann

The dual fermion approach provides a formally exact prescription for calculating properties of a correlated electron system in terms of a diagrammatic expansion around dynamical mean-field theory (DMFT). Most practical implementations, however, neglect higher-order interaction vertices beyond two-particle scattering in the dual effective action and further truncate the diagrammatic expansion in the two-particle scattering vertex to a leading-order or ladder-type approximation. In this work, we compute the dual fermion expansion for the two-dimensional Hubbard model including all diagram topologies with two-particle interactions to high orders by means of a stochastic diagrammatic Monte Carlo algorithm. We benchmark the obtained self-energy against numerically exact diagrammatic determinant Monte Carlo simulations to systematically assess convergence of the dual fermion series and the validity of these approximations. We observe that, from high temperatures down to the vicinity of the DMFT N\'eel transition, the dual fermion series converges very quickly to the exact solution in the whole range of Hubbard interactions considered ($4\ensuremath{\le}U/t\ensuremath{\le}12$), implying that contributions from higher-order vertices are small. As the temperature is lowered further, we observe slower series convergence, convergence to incorrect solutions, and ultimately divergence. This happens in a regime where magnetic correlations become significant. We find, however, that the self-consistent particle-hole ladder approximation yields reasonable and often even highly accurate results in this regime.

arXiv:1611.07523•Physical review. B./Physical review. B•Jul 28, 2017•55 citations
We present a general framework for performing ``bold-line'' diagrammatic Monte Carlo calculations using an analytical partial resummation as a starting point for a stochastic summation of all diagrams. As a stringent test case we assess the accuracy of the method by solving the equations of single-site dynamical mean-field theory, using the noncrossing approximation as a starting point. We establish the validity of the starting approximations and show that the bold method provides a very accurate treatment of the Mott-insulating phase.
The bold diagrammatic Monte Carlo (BDMC) method performs an unbiased sampling of Feynman's diagrammatic series using skeleton diagrams. For lattice models the efficiency of BDMC can be dramatically improved by incorporating dynamical mean-field theory (DMFT) solutions into renormalized propagators. From the DMFT perspective, combining it with BDMC leads to an unbiased method with well-defined accuracy. We illustrate the power of this approach by computing the single-particle propagator (and thus the density of states) in the non-perturbative regime of the Anderson localization problem, where a gain of the order of 104{10}^{4}104 is achieved with respect to conventional BDMC in terms of convergence to the exact answer.
Abstract. We present two diagrammatic Monte Carlo methods for quantum systems coupled with harmonic baths, whose dynamics are described by integro-differential equations. The first approach can be considered as a reformulation of the Dyson series, and the second one, called “bold-thin-bold diagrammatic Monte Carlo,” is based on resummation of the diagrams in the Dyson series to accelerate its convergence. The underlying mechanism of the governing equations associated with the two methods lies in the recurrence relation of the path integrals, which is the most costly part in the numerical methods. The proposed algorithms give an extension to the work of Cai, Lu, and Yang [ Comput. Phys. Commun. 278 (2022), 108417], where the algorithms are designed based on reusing the previous calculations of bath influence functionals. Compared with the algorithms therein, our methods further include the reuse of system-associated functionals and show better performance in terms of computational efficiency and memory cost. We demonstrate the two methods in the framework of spin-boson model, and numerical experiments are carried out to verify the validity of the methods.
Dynamical mean-field theory (DMFT) is one of the most widely used theoretical methods for electronic structure calculations, providing self-consistent solutions even in low-temperature regimes, which are exact in the limit of infinite dimension. The principal limitation of this method is that it neglects spatial fluctuations, which become important in finite dimensions. Diagrammatic Monte Carlo (diagMC), by contrast, provides results that are asymptotically exact for a convergent or resummable series, but are typically limited to high temperature as they depend on the analytic structure of the expansion. In this work, we present a framework for integrating these two methods so that the diagrammatic expansion is conducted around the DMFT solution. This results in a series expansion conducted only in terms that explicitly depend on nonlocal correlations, and which is asymptotically exact.
A Monte Carlo sampling of diagrammatic corrections to the noncrossing approximation is shown to provide numerically exact estimates of the long-time dynamics and steady-state properties of nonequilibrium quantum impurity models. This ``bold'' expansion converges uniformly in time and significantly ameliorates the sign problem that has heretofore limited the power of real-time Monte Carlo approaches to strongly interacting real-time quantum problems. The approach enables the study of previously intractable problems ranging from generic long-time nonequilibrium transport characteristics in systems with large on-site repulsion to the direct description of spectral functions on the real frequency axis in dynamical mean field theory.
We introduce a Monte Carlo scheme for sampling a bold-line diagrammatic series specifying an unknown function in terms of itself. The range of convergence of this bold(-line) diagrammatic Monte Carlo (BMC) technique is significantly broader than that of a simple iterative scheme for solving integral equations. With the BMC technique, a moderate "sign problem" turns out to be an advantage in terms of the convergence of the process. For an illustrative purpose, we solve the one-particle s-scattering problem. As an important application, we obtain the T matrix for a Fermi polaron (one spin-down particle interacting with the spin-up fermionic sea).
The dual fermion approach provides a formally exact prescription for calculating properties of a correlated electron system in terms of a diagrammatic expansion around dynamical mean-field theory (DMFT). Most practical implementations, however, neglect higher-order interaction vertices beyond two-particle scattering in the dual effective action and further truncate the diagrammatic expansion in the two-particle scattering vertex to a leading-order or ladder-type approximation. In this work, we compute the dual fermion expansion for the two-dimensional Hubbard model including all diagram topologies with two-particle interactions to high orders by means of a stochastic diagrammatic Monte Carlo algorithm. We benchmark the obtained self-energy against numerically exact diagrammatic determinant Monte Carlo simulations to systematically assess convergence of the dual fermion series and the validity of these approximations. We observe that, from high temperatures down to the vicinity of the DMFT N\'eel transition, the dual fermion series converges very quickly to the exact solution in the whole range of Hubbard interactions considered ($4\ensuremath{\le}U/t\ensuremath{\le}12$), implying that contributions from higher-order vertices are small. As the temperature is lowered further, we observe slower series convergence, convergence to incorrect solutions, and ultimately divergence. This happens in a regime where magnetic correlations become significant. We find, however, that the self-consistent particle-hole ladder approximation yields reasonable and often even highly accurate results in this regime.