Scalable Quantum Simulations of Scattering in Scalar Field Theory on 120 Qubits

Simulations of collisions of fundamental particles on a quantum computer are expected to have an exponential advantage over classical methods and promise to enhance searches for new physics. Furthermore, scattering in scalar field theory has been shown to be BQP-complete, making it a representative problem for which quantum computation is efficient. As a step toward large-scale quantum simulations of collision processes, scattering of wavepackets in one-dimensional scalar field theory is simulated using 120 qubits of IBM’s Heron superconducting quantum computer ibm_fez. Variational circuits compressing vacuum preparation, wavepacket initialization, and time evolution are determined using classical resources. By leveraging physical properties of states in the theory, such as symmetries and locality, the variational quantum algorithm constructs scalable circuits that can be used to simulate arbitrarily-large system sizes. A new strategy is introduced to mitigate errors in quantum simulations, which enables the extraction of meaningful results from circuits with up to 4924 two-qubit gates and two-qubit gate depths of 103. The effect of interactions is clearly seen, and is found to be in agreement with classical Matrix Product State simulations. The developments that will be necessary to simulate high-energy inelastic collisions on a quantum computer are discussed.

The author thanks Roland Farrell, Marc Illa, Zhiyao Li, Henry Froland, Anthony Ciavarella, and Martin Savage for helpful discussions and insightful comments. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, InQubator for Quantum Simulation (IQuS) under Award Number DOE (NP) Award DE-SC0020970 via the program on Quantum Horizons: QIS Research and Innovation for Nuclear Science. This work was also supported, in part, through the Department of Physics and the College of Arts and Sciences at the University of Washington. This work has made extensive use of Wolfram Mathematica, python, julia, jupyter notebooks in the conda environment, IBM’s quantum programming environment qiskit, and iTensor in this work. This work was enabled, in part, by the use of advanced computational, storage and networking infrastructure provided by the Hyak supercomputer system at the University of Washington. This research was done using services provided by the OSG Consortium, which is supported by the National Science Foundation awards #2030508 and #1836650. The author acknowledges the use of IBM Quantum Credits for this work. The views expressed are those of the author, and do not reflect the official policy or position of IBM or the IBM Quantum team.