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We develop a continuous-time quantum Monte Carlo (CTQMC) method for quantum impurities coupled to interacting quantum wires described by a Tomonaga-Luttinger liquid. The method is negative-sign free for any values of the Tomonaga-Luttinger…

Strongly Correlated Electrons · Physics 2015-06-19 K. Hattori , A. Rosch

We have developed a multi-orbital approach to compute the electronic structure of a quantum impurity using the non-crossing approximation. The calculation starts with a mean-field evaluation of the system's electronic structure using a…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 Richard Korytár , Nicolás Lorente

We present an efficient ab initio dynamical mean-field theory (DMFT) implementation for quantitative simulations in solids. Our DMFT scheme employs ab initio Hamiltonians defined for impurities comprising the full unit cell or a supercell…

Strongly Correlated Electrons · Physics 2020-03-05 Tianyu Zhu , Zhi-Hao Cui , Garnet Kin-Lic Chan

We study the problem of an impurity in fully polarized (spin-up) low density neutron matter with the help of an accurate quantum Monte Carlo method in conjunction with a realistic nucleon-nucleon interaction derived from chiral effective…

Nuclear Theory · Physics 2015-11-18 Alessandro Roggero , Abhishek Mukherjee , Francesco Pederiva

The accurate theoretical description of materials with strongly correlated electrons is a formidable challenge in condensed matter physics and computational chemistry. Dynamical Mean Field Theory (DMFT) is a successful approach that…

Quantum cluster theories are a set of approaches for the theory of correlated and disordered lattice systems, which treat correlations within the cluster explicitly, and correlations at longer length scales either perturbatively or within a…

Superconductivity · Physics 2009-11-11 T. A. Maier , M. S. Jarrell , D. J. Scalapino

Quantum computers (QC) could harbor the potential to significantly advance materials simulations, particularly at the atomistic scale involving strongly correlated fermionic systems where an accurate description of quantum many-body effects…

We present a novel, generally applicable Monte Carlo algorithm for the simulation of fluid systems. Geometric transformations are used to identify clusters of particles in such a manner that every cluster move is accepted, irrespective of…

Statistical Mechanics · Physics 2016-08-31 Jiwen Liu , Erik Luijten

The multichannel Kondo model with SU(N) spin symmetry and SU(K) channel symmetry is considered. The impurity spin is chosen to transform as an antisymmetric representation of SU(N), corresponding to a fixed number of Abrikosov fermions…

Strongly Correlated Electrons · Physics 2009-10-30 Olivier Parcollet , Antoine Georges , Gabriel Kotliar , Anirvan Sengupta

We study theoretically a triangular cluster of three magnetic impurities, hybridizing locally with conduction electrons of a metallic host. Such a cluster is the simplest to exhibit frustration - an important generic feature of many complex…

Strongly Correlated Electrons · Physics 2014-03-18 Andrew K. Mitchell , Thomas F. Jarrold , Martin R. Galpin , David E. Logan

We introduce a quantum Monte Carlo technique to calculate exactly at finite temperatures the Green function of a fermionic quantum impurity coupled to a bosonic field. While the algorithm is general, we focus on the single impurity Anderson…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 Liliana Arrachea , Marcelo J. Rozenberg

We present a novel approach for finding and evaluating structural models of small metallic nanoparticles. Rather than fitting a single model with many degrees of freedom, the approach algorithmically builds libraries of nanoparticle…

The Kondo scale TK for impurity systems is expected to guarantee universal scaling of physical quantities. However, in practice, not every definition of TK necessarily supports this notion away from the strict scaling limit. Specifically,…

Strongly Correlated Electrons · Physics 2014-02-26 Markus Hanl , Andreas Weichselbaum

Here we present a quantum algorithm for clustering data based on a variational quantum circuit. The algorithm allows to classify data into many clusters, and can easily be implemented in few-qubit Noisy Intermediate-Scale Quantum (NISQ)…

Quantum Physics · Physics 2024-01-08 Pablo Bermejo , Roman Orus

We outline how the coupled cluster method of microscopic quantum many-body theory can be utilized in practice to give highly accurate results for the ground-state properties of a wide variety of highly frustrated and strongly correlated…

Strongly Correlated Electrons · Physics 2014-10-24 R. F. Bishop , P. H. Y. Li , C. E. Campbell

Unconventional quantum criticality in heavy-fermion systems has been extensively analyzed in terms of a critical destruction of the Kondo effect. Motivated by a recent demonstration of quantum criticality in a mixed-valent heavy-fermion…

Strongly Correlated Electrons · Physics 2012-08-24 J. H. Pixley , Stefan Kirchner , Kevin Ingersent , Qimiao Si

We investigate the boundary phenomena that arise in a finite-size $XX$ spin chain interacting through an $XX$ interaction with a spin$-\frac{1}{2}$ impurity located at its edge. Upon Jordan-Wigner transformation, the model is described by a…

Strongly Correlated Electrons · Physics 2025-07-17 Pradip Kattel , Yicheng Tang , J. H. Pixley , Natan Andrei

The single impurity Kondo model at zero temperature in a magnetic field is solved by a semi-analytical approach based on the flow equation method. The resulting problem is shown to be equivalent to a resonant level model with a non-constant…

Strongly Correlated Electrons · Physics 2009-11-07 C. Slezak , S. Kehrein , Th. Pruschke , M. Jarrell

We present the algorithmic details of the dynamical cluster approximation (DCA), with a quantum Monte Carlo (QMC) method used to solve the effective cluster problem. The DCA is a fully-causal approach which systematically restores non-local…

Strongly Correlated Electrons · Physics 2009-11-07 M. Jarrell , Th. Maier , C. Huscroft , S. Moukouri

Fitting geometric models onto outlier contaminated data is provably intractable. Many computer vision systems rely on random sampling heuristics to solve robust fitting, which do not provide optimality guarantees and error bounds. It is…

Computer Vision and Pattern Recognition · Computer Science 2022-06-28 Anh-Dzung Doan , Michele Sasdelli , David Suter , Tat-Jun Chin
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