This text reviews, hopefully in a pedagogical manner, a series of work on the automatic calculations of Feynman diagrams in the context of quantum nanoelectronics (Keldysh formalism) with an application to the Kondo effect in the out-of-equilibrium single impurity Anderson model. It includes a discussion of (A) how to deal with the proliferation of diagrams, (B) how to calculate them using the Tensor Cross Interpolation algorithm instead of Monte-Carlo and (C) how to resum the obtained series. These notes correspond to a lecture given at the Autumn School on Correlated Electrons 2025 in Jullich, Germany. The book with all the lectures of the school (edited by Eva Pavarini, Erik Koch, Alexander Lichtenstein, and Dieter Vollhardt) is available in open access.
This text reviews, hopefully in a pedagogical manner, a series of work on the automatic calculations of Feynman diagrams in the context of quantum nanoelectronics (Keldysh formalism) with an application to the Kondo effect in the out-of-equilibrium single impurity Anderson model. It includes a discussion of (A) how to deal with the proliferation of diagrams, (B) how to calculate them using the Tensor Cross Interpolation algorithm instead of Monte-Carlo and (C) how to resum the obtained series. These notes correspond to a lecture given at the Autumn School on Correlated Electrons 2025 in Jullich, Germany. The book with all the lectures of the school (edited by Eva Pavarini, Erik Koch, Alexander Lichtenstein, and Dieter Vollhardt) is available in open access.
The physics of N-body quantum systems reveals the emergence of numerous unexpected collective phenomena, such as the 0.7 anomaly, the Kondo effect, and high critical temperature superconductivity. From a theoretical perspective, describing these systems is challenging due to the exponential growth of the state space as the number of particles increases. For instance, the quantitative understanding of the Kondo effect required the development of new concepts and mathematical tools, including the (numerical) renormalization group. This pioneering work, which earned Wilson the Nobel Prize in 1978, laid the foundation for many subsequent advances.In this thesis, we focus on the physics of quantum dots, described by the Anderson model. This model exhibits rich phenomenology, both in the charge domain (Coulomb blockade) and the spin domain (Kondo effect). While this model is well understood in equilibrium, we propose an innovative technique to study its properties in the non-equilibrium regime—a historically challenging area to address. Our approach enables exact calculations with controlled errors.This method builds on the "Diagrammatic Monte Carlo" technique, which systematically computes a large number of Feynman diagrams. Traditionally, this technique stochastically samples the space of diagrams. In our work, we replaced this approach with a machine learning method based on tensor networks and the cross-interpolation algorithm. The latter identifies and leverages the specific structure of the diagram space, greatly accelerating the calculations. A key advantage of this method is its insensitivity to the sign problem that limits stochastic approaches.Using this new technique, we were able to compute diagrams up to much higher orders than previously possible (<30), enabling us to explore the physics of non-equilibrium quantum dots with unprecedented precision.
1. Eva Pavarini: Dynamical Mean-Field Theory for Materials, 2. Xavier Gonze: Constrained Density-Functional Theory: Formalism, Algorithms and Applications, 3. Robert Eder: Green Functions and Self-Energy Functionals, 4. Erik Koch: Exact Diagonalization and Lanczos Method, 5. Ulrich Schollwöck: DMRG as Impurity Solver, 6. Riccardo Rossi: Diagrammatic Monte Carlo for the Hubbard Model, 7. Walter Metzner: Mean-Field Theory of Spin and Charge Order in the Two-Dimensional Hubbard Model, 8. Cécile Repellin: Introduction to Topological Phases in Condensed Matter, 9. Carsten Timm: Ginzburg-Landau Theory of Superconductivity, 10. Anna Böhmer: Experimental Characterization of Phase Transitions, 11. Markus Grüninger: From Mott to Cluster Mott: Probing Correlations with RIXS, 12. Matteo Mitrano: Light Control of Many-Body Phases, 13. Luca Tocchio: Variational Monte Carlo for the Hubbard Model, 14. Annabelle Bohrdt: Neural Quantum States for Strongly Correlated Systems, 15. Benedikt Fauseweh: Quantum Many-Body Simulations on Digital Quantum Computers
Lecture notes of the Autumn School on Correlated Electrons 2018:Dieter Vollhardt: From Infinite Dimensions to Real Materials; Ole Andersen: From Materials to Models: Deriving Insight from Bands; Ferdi Aryasetiawan: Effective Electron-Electron Interaction in Many-Electron Systems; Marcus Kollar: The Foundations of Dynamical Mean-Field Theory; Michael Potthoff: Cluster Extensions of Dynamical Mean-Field Theory; Frank Lechermann: Charge Self-Consistency in Correlated Electronic Structure Calculations; Eva Pavarini: LDA+DMFT: Multi-Orbital Hubbard Models; Hao Tjeng: Determining Orbital Wavefunctions using Core-Level Non-Resonant Inelastic X-Ray Scattering; Hans Gerd Evertz: DMRG for Multiband Impurity Solvers; Fakher Assaad: Quantum Monte Carlo Methods for Fermion-Boson Problems; Erik Koch: Analytic Continuation of Quantum Monte Carlo Data; Hartmut Hafermann: Introduction to Diagrammatic Approaches; Thomas Maier: Dynamical Mean-Field and Dynamical Cluster Approximation Based Theory of Superconductivity; Karsten Held: Quantum Criticality and Superconductivity in Diagrammatic Extensions of DMFT; Martin Eckstein: Correlated Electrons out of Equilibrium: Non-Equilibrium DMFT
The Kondo effect is a hallmark of strongly-correlated systems, where an impurity's local degrees of freedom are screened by conduction electrons, forming a many-body singlet. With increasing degrees of freedom in the impurity, theoretical studies face significant challenges in accurately identifying and characterizing the underlying mechanisms that screen the impurity. In this work, we introduce a straightforward yet powerful methodology for identifying the formation of Kondo singlets and their screening mechanisms, by utilizing the numerical renormalization group (NRG) combined with the matrix product states (MPS) technique. We demonstrate the effectiveness of our method on the single and two-level Anderson impurity models (AIM). Furthermore, we discuss potential generalizations of the method to multichannel and multiorbital Kondo impurities. Harnessing advanced tensor network techniques, our approach extends to complex impurity systems, offering a robust and versatile framework for studying Kondo physics.
Calcul numérique exact des diagrammes de Feynman pour la physique de Kondo hors équilibre en utilisant l'Interpolation de Tenseur par produit de Croix La physique des systèmes quantiques à N-corps révèle l’émergence de nombreux phénomènes collectifs inattendus, tels que l'anomalie 0.7, l'effet Kondo ou la supraconductivité à haute température critique. D'un point de vue théorique, la description de ces systèmes est complexe en raison de l’augmentation exponentielle de la taille de l’espace des états en fonction du nombre de particules. Par exemple, la compréhension quantitative de l’effet Kondo a nécessité le développement de nouveaux concepts et outils mathématiques, dont le groupe de renormalisation (numérique). Ce travail pionnier, qui valut à Wilson le prix Nobel en 1978, a ouvert la voie à de nombreuses avancées.Dans cette thèse, nous nous intéressons à la physique des boîtes quantiques, décrites par le modèle d’Anderson. Ce modèle présente une riche phénoménologie, tant dans le domaine de la charge (blocage de Coulomb) que dans celui du spin (effet Kondo). Si ce modèle est bien compris en régime d'équilibre, nous proposons ici une technique novatrice pour étudier ses propriétés dans le régime hors équilibre, un domaine historiquement difficile à traiter. Notre approche permet un calcul exact avec des erreurs contrôlées.Cette méthode est une évolution du « Monte Carlo diagrammatique », qui permet de calculer de manière systématique un très grand nombre de diagrammes de Feynman. Traditionnellement, cette technique échantillonne l’espace des diagrammes de façon stochastique. Dans notre travail, nous avons remplacé cette approche par une méthode d’apprentissage machine, basée sur les réseaux de tenseurs et l'algorithme d'interpolation par produit de croix. Ce dernier détecte et exploite la structure spécifique de l’espace des diagrammes, accélérant ainsi considérablement les calculs. Il présente l’avantage majeur d’être insensible au problème de signe qui limite les approches stochastiques.Grâce à cette nouvelle technique, nous avons pu calculer l’ensemble des diagrammes jusqu’à des ordres bien plus élevés qu’auparavant (<30), ce qui nous a permis de dévoiler la physique des boîtes quantiques hors équilibre avec une précision inégalée.
1. Dieter Vollhardt: Understanding Correlated Materials with Lattice Fermions in Infinite Dimensions, 2. Robert Jones: Density Functional Theory for the Sceptical, 3. Eva Pavarini: Dynamical Mean-Field Theory for Materials, 4. Luca de' Medici: Hund's Metal Physics in the Iron-Based Superconductors, 5. Tim Wehling: DMFT for Moiré Systems, 6. Claude Ederer: Effect of Charge Self-Consistency in Calculations for Transition-Metal Oxides, 7. Jan Tomczak: A Perspective on Screened Coulomb Interactions from the constrained Random Phase Approximation, 8. Krzysztof Byczuk: Dynamical Mean-Field Theory for Correlated Electrons with Disorder, 9. Xavier Waintal: Learning Feynman Diagrams with Tensor Trains, 10. Philipp Werner: QMC for Nonequilibrium Systems, 11. Erik Koch: Analytic Continuation of Quantum Monte Carlo Data, 12. Walter Metzner: Functional Renormalization of Strongly Correlated Electrons: DMFT as a Booster Rocket, 13. Alexander Lichtenstein: Path Integrals and Reference Systems, 14. Karsten Held: Unconventional Superconductivity in the Dynamical Vertex Approximation, 15. Thomas Ayral: Dynamical Mean-Field Theory with Quantum Computing