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:2010.08482 · Computer Physics Communications

Accelerated impurity solver for DMFT and its diagrammatic extensions

Corey Melnick, P. Sémon, Kwangmin Yu, Nicholas D’Imperio, A.–M. S. Tremblay, Gabriel Kotliar

Published Jun 18, 2021• 14 citations
arXivHTMLPDF
DOI
10.1016/j.cpc.2021.108075

Related papers

DMFT Impurity Solvers

Volodymyr Turkowski

Springer eBooks•Jan 1, 2021•0 citations

A real-time impurity solver for DMFT

HyungWon Kim, Camille Aron, Jong E. Han +1 more

Bulletin of the American Physical Society•Mar 18, 2016•0 citations

Cluster Impurity Solver for LDA+DMFT Calculations

Quan Yin, Sergey Yu. Savrasov

Bulletin of the American Physical Society•Mar 15, 2006•0 citations

Development of a DFT+++DMFT method using multi-orbital impurity solver

Mancheon Han, Hyungju Oh, Choong‐Ki Lee +1 more

Bulletin of the American Physical Society•Mar 5, 2015•0 citations

A non-equilibrium DMFT impurity solver based on the Lindblad equation

Antonius Dorda

•Jan 1, 2013•0 citations

Accelerating a Strong-Coupling Non-Equilibrium Steady-State Impurity Solver using (Quantics) Tensor Trains

Bastian Schindler, Martin Eckstein

Including higher order diagrammatic corrections to the strong-coupling expansion is mainly limited by the evaluation of high-dimensional, time-ordered integrals. In this work we present and compare four different parametrizations of the integrands in order to obtain a low-rank (quantics) tensor-train representation using tensor cross interpolation. Particular emphasis is placed on a quantics time-difference formulation in which the required retarded convolutions are performed directly in quantics tensor-train form. Using controlled Gaussian benchmarks, we analyze the accuracy, bond dimensions, and computational scaling of the different approaches. We then validate the most promising formulations in self-consistent equilibrium and nonequilibrium DMFT calculations and demonstrate calculations up to the third order in the strong-coupling expansion. Finally, we extend the solver to impurity models with retarded density-density interactions and apply it within nonequilibrium extended DMFT. Our results show that tensor cross interpolation substantially reduces the cost of evaluating higher-order diagrams and provides a controlled, systematically improvable framework for nonequilibrium quantum impurity calculations.

arXiv:2608.13146•Aug 13, 2026•0 citations
Including higher order diagrammatic corrections to the strong-coupling expansion is mainly limited by the evaluation of high-dimensional, time-ordered integrals. In this work we present and compare four different parametrizations of the integrands in order to obtain a low-rank (quantics) tensor-train representation using tensor cross interpolation. Particular emphasis is placed on a quantics time-difference formulation in which the required retarded convolutions are performed directly in quantics tensor-train form. Using controlled Gaussian benchmarks, we analyze the accuracy, bond dimensions, and computational scaling of the different approaches. We then validate the most promising formulations in self-consistent equilibrium and nonequilibrium DMFT calculations and demonstrate calculations up to the third order in the strong-coupling expansion. Finally, we extend the solver to impurity models with retarded density-density interactions and apply it within nonequilibrium extended DMFT. Our results show that tensor cross interpolation substantially reduces the cost of evaluating higher-order diagrams and provides a controlled, systematically improvable framework for nonequilibrium quantum impurity calculations.