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https://dx.doi.org/10.48550/ar...
Article . 2020
License: CC BY
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Tensor lattice field theory with applications to the renormalization group and quantum computing

Authors: Meurice, Yannick; Sakai, Ryo; Unmuth-Yockey, Judah;

Tensor lattice field theory with applications to the renormalization group and quantum computing

Abstract

We discuss the successes and limitations of statistical sampling for a sequence of models studied in the context of lattice QCD and emphasize the need for new methods to deal with finite-density and real-time evolution. We show that these lattice models can be reformulated using tensorial methods where the field integrations in the path-integral formalism are replaced by discrete sums. These formulations involve various types of duality and provide exact coarse-graining formulas which can be combined with truncations to obtain practical implementations of the Wilson renormalization group program. Tensor reformulations are naturally discrete and provide manageable transfer matrices. Combining truncations with the time continuum limit, we derive Hamiltonians suitable to perform quantum simulation experiments, for instance using cold atoms, or to be programmed on existing quantum computers. We review recent progress concerning the tensor field theory treatment of non-compact scalar models, supersymmetric models, economical four-dimensional algorithms, noise-robust enforcement of Gauss's law, symmetry preserving truncations and topological considerations. We discuss connections with other tensor network approaches.

Review article, 71 pages, 47 figures, connections to other tensor network approaches and references added

Related Organizations
Keywords

High Energy Physics - Theory, Quantum Physics, High Energy Physics - Lattice, Statistical Mechanics (cond-mat.stat-mech), High Energy Physics - Theory (hep-th), High Energy Physics - Lattice (hep-lat), FOS: Physical sciences, Quantum Physics (quant-ph), Condensed Matter - Statistical Mechanics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green