Hamiltonian learning in quantum field theories

被引：0

作者：

Ott, Robert ^{[1
,2
]}

Zache, Torsten V. ^{[1
,2
]}

Prüfer, Maximilian ^{[3
]}

Erne, Sebastian ^{[3
]}

Tajik, Mohammadamin ^{[3
,4
]}

Pichler, Hannes ^{[1
,2
]}

Schmiedmayer, Jörg ^{[3
]}

Zoller, Peter ^{[1
,2
]}

机构：

[1] Institute for Theoretical Physics, University of Innsbruck, Innsbruck,6020, Austria

[2] Institute for Quantum Optics and Quantum Information, The Austrian Academy of Sciences, Innsbruck,6020, Austria

[3] Vienna Center for Quantum Science and Technology, Atominstitut, TU Wien, Stadionallee 2, Vienna,1020, Austria

[4] Max Planck Institute of Molecular Cell Biology and Genetics, Dresden,01307, Germany

来源：

Physical Review Research | 2024年 / 6卷 / 04期

关键词：

Quantum field theories (QFTs) as relevant for condensed-matter or high-energy physics are formulated in continuous space and time; and typically emerge as effective low-energy descriptions. In atomic physics; an example is given by tunnel-coupled superfluids; which realize the paradigmatic sine-Gordon model; and can act as quantum simulators of continuous QFTs. To quantitatively characterize QFT simulators; or to discover the Hamiltonian governing the dynamics of a continuous many-body quantum system; we discuss Hamiltonian learning as a method to systematically extract the operator content and the coupling constants of Hamiltonians from experimental data. In contrast to Hamiltonian learning for lattice models with a given lattice scale; we learn QFT Hamiltonians on a resolution scale set by the experiment. Varying the resolution scale gives access to QFTs at different energy scales; and allows to learn a flow of Hamiltonians reminiscent of the renormalization group. Applying these techniques to available experimental data from a tunnel-coupled quantum gas experiment allows a definite distinction between a free quadratic theory from an interacting sine-Gordon model; as the underlying QFT description of the system. © 2024 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title; journal citation; and DOI;

D O I：

10.1103/PhysRevResearch.6.043284

中图分类号：

学科分类号：

摘要：

引用

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