Abstract
Strongly coupled gauge theories far from equilibrium may exhibit unique features that could illuminate the physics of the early universe and of hadron and ion colliders. Studying real-time phenomena has proven challenging with classical-simulation methods, but is a natural application of quantum simulation. To demonstrate this prospect, we quantum compute nonequal-time correlation functions and perform entanglement tomography of nonequilibrium states of a simple lattice gauge theory, the Schwinger model, using a trapped-ion quantum computer by IonQ Inc. As an ideal target for near-term devices, a recently predicted [Zache et al., Phys. Rev. Lett. 122, 050403 (2019)] dynamical quantum phase transition in this model is studied by preparing, quenching, and tracking the subsequent nonequilibrium dynamics in three ways: (i) overlap echos signaling dynamical transitions, (ii) nonequal-time correlation functions with an underlying topological nature, and (iii) the entanglement structure of nonequilibrium states, including entanglement Hamiltonians. These results constitute the first observation of a dynamical quantum phase transition in a lattice gauge theory on a quantum computer, and are a first step toward investigating topological phenomena in nuclear and high-energy physics using quantum technologies.
| Original language | English |
|---|---|
| Article number | 030323 |
| Journal | PRX Quantum |
| Volume | 4 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 2023 |
Funding
This manuscript has been authored by UT-Battelle, LLC, under Contract No. DE-AC0500OR22725 with the U.S. Department of Energy (DOE). The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes. The DOE will provide public access to these results of federally sponsored research in accordance with the DOE’s Public Access Plan. We are grateful to Sonika Johri, Matthew Keesan, Denise Ruffner (IonQ), Anthony Tricario (Google Cloud), Robert Hugg, Samuel Porter, Sheila M. Zellner-Jenkins (Division of Information Technology, University of Maryland), Ansonia Saunders (Department of Procurement and Strategic Sourcing, University of Maryland), Franz Klein, John Sawyer (Mid-Atlantic Quantum Alliance, University of Maryland), Mark Heil (Burwood), Misha Dhar, Fabrice Frachon, Lorilyn Hall, George Moussa, Martin Roettler, and Tracy Woods (Microsoft) for their great help and efforts in enabling us, by providing the organizational, technological, and legal groundwork, to use IonQ’s quantum hardware through the Google Cloud and Microsoft Azure infrastructures, and for answering our many questions. We thank Torsten Zache for discussions and careful reading of this paper. Z.D. and N.M. acknowledge funding by the U.S. Department of Energy’s Office of Science, Office of Advanced Scientific Computing Research, Accelerated Research in Quantum Computing program Award No. DE-SC0020312 for algorithmic developments for fermionic simulations, and the U.S. Department of Energy’s Office of Science, Office of Nuclear Physics under Award No. DE-SC0021143 via the program on Quantum Horizons: QIS Research and Innovation for Nuclear Science for quantum simulation of gauge-theory dynamics on near-term quantum hardware. N.M. acknowledges funding by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, InQubator for Quantum Simulation (IQuS) Ref. under Award No. DOE (NP) Award DE-SC0020970. Z.D. is further supported by the U.S. Department of Energy, Office of Science, Early Career Award, under Award No. DESC0020271. K.Y.A. and E.D. were supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Science Center. K.Y.A. was also supported by MITRE Corporation TechHire and Quantum Horizon programs. The hardware-implementation results were produced using computing credits from IonQ, Google, and Microsoft.