Forward-mode automatic differentiation for the tensor renormalization group and its relation to the impurity method

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Auteur principal: Sugimoto, Yuto
Format: Preprint
Publié: 2026
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author Sugimoto, Yuto
author_facet Sugimoto, Yuto
contents We propose a forward-mode automatic differentiation (AD) framework for tensor renormalization group (TRG) methods. In this approach, evaluating the derivatives of the partition function up to order $k$ increases the matrix-multiplication cost by a factor of $(k+1)(k+2)/2$ compared to computing the free energy alone, and the memory footprint is only $k+1$ times that of the original calculation. In the limit where the derivatives of the SVD are neglected, we establish a theoretical correspondence between our forward-mode AD and conventional impurity methods. Numerically, we find that the proposed AD algorithm can calculate internal energy and specific heat significantly higher accuracy than the impurity method at comparable computational cost. We also provide a practical procedure to extract critical exponents from derivatives of the renormalized tensor in TRG calculations in both two and three dimensions. In addition, we discuss how to efficiently differentiate an arbitrary tensor network.
format Preprint
id arxiv_https___arxiv_org_abs_2602_08987
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Forward-mode automatic differentiation for the tensor renormalization group and its relation to the impurity method
Sugimoto, Yuto
High Energy Physics - Lattice
We propose a forward-mode automatic differentiation (AD) framework for tensor renormalization group (TRG) methods. In this approach, evaluating the derivatives of the partition function up to order $k$ increases the matrix-multiplication cost by a factor of $(k+1)(k+2)/2$ compared to computing the free energy alone, and the memory footprint is only $k+1$ times that of the original calculation. In the limit where the derivatives of the SVD are neglected, we establish a theoretical correspondence between our forward-mode AD and conventional impurity methods. Numerically, we find that the proposed AD algorithm can calculate internal energy and specific heat significantly higher accuracy than the impurity method at comparable computational cost. We also provide a practical procedure to extract critical exponents from derivatives of the renormalized tensor in TRG calculations in both two and three dimensions. In addition, we discuss how to efficiently differentiate an arbitrary tensor network.
title Forward-mode automatic differentiation for the tensor renormalization group and its relation to the impurity method
topic High Energy Physics - Lattice
url https://arxiv.org/abs/2602.08987