Confinement in a Z2 lattice gauge theory on a quantum computer
Year: 2025
Authors: Mildenberger J., Mruczkiewicz W., Halimeh J.C., Jiang Z., Hauke P.
Autors Affiliation: Univ Trento, Pitaevskii BEC Ctr, CNR INO, Trento, Italy; Univ Trento, Dept Phys, Trento, Italy; Trento Inst Fundamental Phys & Applicat, INFN TIFPA, Trento, Italy; Google Quantum AI, Venice, CA 90291 USA; Ludwig Maximilians Univ Munchen, Dept Phys, D-80333 Munich, Germany; Ludwig Maximilians Univ Munchen, Sommerfeld Ctr Theoret Phys ASC, Munich, Germany; Munich Ctr Quantum Sci & Technol MCQST, Munich, Germany.
Abstract: Gauge theories describe the fundamental forces in the standard model of particle physics and play an important role in condensed-matter physics. The constituents of gauge theories, for example, charged matter and electric gauge field, are governed by local gauge constraints, which lead to key phenomena such as the confinement of particles that are not fully understood. In this context, quantum simulators may address questions that are challenging for classical methods. Although engineering gauge constraints is highly demanding, recent advances in quantum computing are beginning to enable digital quantum simulations of gauge theories. Here we simulate confinement dynamics in a Z(2) lattice gauge theory on a superconducting quantum processor. Tuning a term that couples only to the electric field produces confinement of charges, a manifestation of the tight bond that the gauge constraint generates between both. Moreover, we show how a modification of the gauge constraint from Z(2) towards U(1) symmetry freezes the system dynamics. Our work illustrates the restriction that the underlying gauge constraint imposes on the dynamics of a lattice gauge theory, showcases how gauge constraints can be modified and protected, and promotes the study of other models governed by multibody interactions.
Journal/Review: NATURE PHYSICS
More Information: We are grateful to the Google Quantum AI team, particularly E. Ostby and M. Hoffmann, for support and discussions. We also thank H. Lang for discussions. We acknowledge participation in the Google Quantum AI Early Access Program, within which all the quantum computations have been remotely performed between two continents, using Cirq75. Further numerical simulations have been performed with the help of qsim76. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 804305 (StrEnQTh)), within the QuantERA II Programme from the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 101017733), from the European Union’s Horizon Europe research and innovation programme (grant agreement no. 101080086 (NeQST)), the Italian Ministry of University and Research (MUR) through the FARE grant for the project DAVNE (grant no. R20PEX7Y3A), the Google Research Scholar Award ProGauge, Provincia Autonoma di Trento, and Q@TN, the joint lab between University of Trento, FBK-Fondazione Bruno Kessler, INFN-National Institute for Nuclear Physics and CNR-National Research Council. J.C.H. acknowledges funding by the Max Planck Society, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2111 – 390814868, and the European Research Council (ERC) under the European Union’s Horizon Europe research and innovation program (grant agreement no. 948141 (SimUcQuam) and 101165667 (QuSiGauge)). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.KeyWords: Invariance; DynamicsDOI: 10.1038/s41567-024-02723-6Citations: 1data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2025-03-30References taken from IsiWeb of Knowledge: (subscribers only)