Compressing local vertex functions from the multipoint numerical renormalization group using quantics tensor cross interpolation

The multipoint numerical renormalization group (mpNRG) is a powerful impurity solver that provides accurate spectral data useful for computing local, dynamic correlation functions in imaginary or real frequencies nonperturbatively across a wide range of interactions and temperatures. It gives access to a local, nonperturbative four-point vertex in imaginary and real frequencies, which can be used as input for subsequent computations such as diagrammatic extensions of dynamical mean-field theory. However, computing and manipulating the real-frequency four-point vertex on large, dense grids quickly becomes numerically challenging when the density and/or the extent of the frequency grid is increased. In this paper, we compute four-point vertices in a strongly compressed quantics tensor train format using quantics tensor cross interpolation, starting from discrete partial spectral functions obtained from mpNRG. This enables evaluations of the vertex on frequency grids with resolutions far beyond the reach of previous implementations. We benchmark this approach on the four-point vertex of the single-impurity Anderson model across a wide range of physical parameters, both in its full form and in its asymptotic decomposition. For imaginary frequencies, the full vertex can be represented to an accuracy on the order of <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mn>2</a:mn><a:mspace width="0.16em"/><a:mo>×</a:mo><a:msup><a:mn>10</a:mn><a:mrow><a:mo>−</a:mo><a:mn>3</a:mn></a:mrow></a:msup></a:mrow></a:math> with maximum bond dimensions not exceeding 120. The more complex full real-frequency vertex requires maximum bond dimensions not exceeding 170 for an accuracy of <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"><c:mrow><c:mo>≲</c:mo><c:mn>2</c:mn><c:mo>%</c:mo></c:mrow></c:math>. Our work marks another step toward tensor-train-based diagrammatic calculations for correlated electronic lattice models starting from a local, nonperturbative mpNRG vertex.

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Journal
Physical Review Research
Published
2025-10-08
DOI
https://doi.org/10.1103/jx7h-lsqk
Citations
1
Primary Topic
Tensor decomposition and applications
Type
article
Field-Weighted Citation Impact
1.53
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article

Compressing local vertex functions from the multipoint numerical renormalization group using quantics tensor cross interpolation

Anxiang Ge, Jan von Delft, Marc K. Ritter, Mathias Pelz et al.
1 citations
Physical Review Research
Tensor decomposition and applications
1.53
article

Compressing local vertex functions from the multipoint numerical renormalization group using quantics tensor cross interpolation

Anxiang Ge, Jan von Delft, Marc K. Ritter, Mathias Pelz, Nepomuk Ritz, Markus Frankenbach
article en
1 citations

Abstract

The multipoint numerical renormalization group (mpNRG) is a powerful impurity solver that provides accurate spectral data useful for computing local, dynamic correlation functions in imaginary or real frequencies nonperturbatively across a wide range of interactions and temperatures. It gives access to a local, nonperturbative four-point vertex in imaginary and real frequencies, which can be used as input for subsequent computations such as diagrammatic extensions of dynamical mean-field theory. However, computing and manipulating the real-frequency four-point vertex on large, dense grids quickly becomes numerically challenging when the density and/or the extent of the frequency grid is increased. In this paper, we compute four-point vertices in a strongly compressed quantics tensor train format using quantics tensor cross interpolation, starting from discrete partial spectral functions obtained from mpNRG. This enables evaluations of the vertex on frequency grids with resolutions far beyond the reach of previous implementations. We benchmark this approach on the four-point vertex of the single-impurity Anderson model across a wide range of physical parameters, both in its full form and in its asymptotic decomposition. For imaginary frequencies, the full vertex can be represented to an accuracy on the order of <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mn>2</a:mn><a:mspace width="0.16em"/><a:mo>×</a:mo><a:msup><a:mn>10</a:mn><a:mrow><a:mo>−</a:mo><a:mn>3</a:mn></a:mrow></a:msup></a:mrow></a:math> with maximum bond dimensions not exceeding 120. The more complex full real-frequency vertex requires maximum bond dimensions not exceeding 170 for an accuracy of <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"><c:mrow><c:mo>≲</c:mo><c:mn>2</c:mn><c:mo>%</c:mo></c:mrow></c:math>. Our work marks another step toward tensor-train-based diagrammatic calculations for correlated electronic lattice models starting from a local, nonperturbative mpNRG vertex.

Physical Review ResearchVol. 7(4)
Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 15%
Tensor decomposition and applications
1.53
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