Tensor Networks for Lattice Gauge Theories beyond one dimension: a Roadmap
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arXiv
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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866909777188093952 |
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| author | Magnifico, Giuseppe Cataldi, Giovanni Rigobello, Marco Majcen, Peter Jaschke, Daniel Silvi, Pietro Montangero, Simone |
| author_facet | Magnifico, Giuseppe Cataldi, Giovanni Rigobello, Marco Majcen, Peter Jaschke, Daniel Silvi, Pietro Montangero, Simone |
| contents | Tensor network methods are a class of numerical tools and algorithms to study many-body quantum systems in and out of equilibrium, based on tailored variational wave functions. They have found significant applications in simulating lattice gauge theories approaching relevant problems in high-energy physics. Compared to Monte Carlo methods, they do not suffer from the sign problem, allowing them to explore challenging regimes such as finite chemical potentials and real-time dynamics. Further development is required to tackle fundamental challenges, such as accessing continuum limits or computations of large-scale quantum chromodynamics. In this work, we review the state-of-the-art of Tensor Network methods and discuss a possible roadmap for algorithmic development and strategies to enhance their capabilities and extend their applicability to open high-energy problems. We provide tailored estimates of the theoretical and computational resource scaling for attacking large-scale lattice gauge theories. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_03058 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Tensor Networks for Lattice Gauge Theories beyond one dimension: a Roadmap Magnifico, Giuseppe Cataldi, Giovanni Rigobello, Marco Majcen, Peter Jaschke, Daniel Silvi, Pietro Montangero, Simone High Energy Physics - Lattice Strongly Correlated Electrons High Energy Physics - Theory Computational Physics Quantum Physics Tensor network methods are a class of numerical tools and algorithms to study many-body quantum systems in and out of equilibrium, based on tailored variational wave functions. They have found significant applications in simulating lattice gauge theories approaching relevant problems in high-energy physics. Compared to Monte Carlo methods, they do not suffer from the sign problem, allowing them to explore challenging regimes such as finite chemical potentials and real-time dynamics. Further development is required to tackle fundamental challenges, such as accessing continuum limits or computations of large-scale quantum chromodynamics. In this work, we review the state-of-the-art of Tensor Network methods and discuss a possible roadmap for algorithmic development and strategies to enhance their capabilities and extend their applicability to open high-energy problems. We provide tailored estimates of the theoretical and computational resource scaling for attacking large-scale lattice gauge theories. |
| title | Tensor Networks for Lattice Gauge Theories beyond one dimension: a Roadmap |
| topic | High Energy Physics - Lattice Strongly Correlated Electrons High Energy Physics - Theory Computational Physics Quantum Physics |
| url | https://arxiv.org/abs/2407.03058 |