TU$^2$FRG -- a scalable approach for truncated unity functional renormalization group in generic fermionic models

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Hauptverfasser: Profe, Jonas B., Kennes, Dante M.
Format: Preprint
Veröffentlicht: 2022
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author Profe, Jonas B.
Kennes, Dante M.
author_facet Profe, Jonas B.
Kennes, Dante M.
contents Describing the emergence of phases of condensed matter is one of the central challenges in physics. For this purpose many numerical and analytical methods have been developed, each with their own strengths and limitations. The functional renormalization group is one of these methods bridging between efficiency and accuracy. In this paper we derive a new truncated unity (TU) approach unifying real- and momentum space TU, called TU$^2$FRG. This formalism significantly improves the scaling compared to conventional momentum (TU)FRG when applied to large unit-cell models and models where the translational symmetry is broken.
format Preprint
id arxiv_https___arxiv_org_abs_2201_06299
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle TU$^2$FRG -- a scalable approach for truncated unity functional renormalization group in generic fermionic models
Profe, Jonas B.
Kennes, Dante M.
Strongly Correlated Electrons
Disordered Systems and Neural Networks
Describing the emergence of phases of condensed matter is one of the central challenges in physics. For this purpose many numerical and analytical methods have been developed, each with their own strengths and limitations. The functional renormalization group is one of these methods bridging between efficiency and accuracy. In this paper we derive a new truncated unity (TU) approach unifying real- and momentum space TU, called TU$^2$FRG. This formalism significantly improves the scaling compared to conventional momentum (TU)FRG when applied to large unit-cell models and models where the translational symmetry is broken.
title TU$^2$FRG -- a scalable approach for truncated unity functional renormalization group in generic fermionic models
topic Strongly Correlated Electrons
Disordered Systems and Neural Networks
url https://arxiv.org/abs/2201.06299