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Conference on Lasers and Electro-Optics

Subatomic Many-Body Physics Simulations on a Quantum Frequency Processor

Hsuan‐Hao Lu, Natalie Klco, Joseph M. Lukens, Titus Morris, Aaina Bansal, A. Ekström, G. Hagen, T. Papenbrock, Andrew M. Weiner, Martin J. Savage A, Pavel Lougovski

Published Jan 1, 2019• 4 citations
Publisher

Abstract

We demonstrate a photonic quantum simulation on a quantum frequency processor, computing the effective interaction potential between composite particles in the Schwinger model and determining the binding energies of three nuclei (3H, 3He, and 4He).
DOI
10.1364/cleo_qels.2019.fth3a.6

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Simulating complex many-body quantum phenomena is a major scientific impetus behind the development of quantum computing, and a range of technologies are being explored to address such systems. We present the results of the largest photonics-based simulation to date, applied in the context of subatomic physics. Using an all-optical quantum frequency processor, the ground-state energies of light nuclei including the triton (3H^{3}\mathrm{H}3H), 3He^{3}\mathrm{He}3He, and the alpha particle (4He^{4}\mathrm{He}4He) are computed. Complementing these calculations and utilizing a 68-dimensional Hilbert space, our photonic simulator is used to perform subnucleon calculations of the two- and three-body forces between heavy mesons in the Schwinger model. This work is a first step in simulating subatomic many-body physics on quantum frequency processors---augmenting classical computations that bridge scales from quarks to nuclei.
Gauge theories such as quantum electrodynamics, in principle, give us a precise understanding of the interactions between subatomic particles, but often the calculations involved are beyond current computational capabilities. Quantum simulators based on experimental many-body systems could be a solution to this problem. Scientists exploit the current state-of-the-art experimental technology for manipulating cold trapped ions and propose a simulator of the one-dimensional version of quantum electrodynamics.
To understand the properties and interactions of materials, and determining the ground state energies is one of the important challenges in quantum chemistry, materials science, and quantum mechanics, where quantum computing can play an important role for studying the properties of materials. In this study, we have explored the quantum processor application to compute the He molecule ground state energy which utilizes the Variational Quantum Eigensolver (VQE) algorithm. In here, we have implemented VQE on a state-of-the-art quantum processor, optimizing a parameterized quantum circuit to minimize the energy expectation value of the He molecule's Hamiltonian on the four qubits processor. The obtained results of this work show a significant improvement in accuracy compared to classical computational methods, such as Hartree-Fock and density functional theory, which demonstrate the compute potential of quantum algorithms in quantum many-body problems. Thus, these results demonstrate the advantages of quantum computing in achieving high accuracy in simulations of molecular and material properties, and pave the way for future applications in more complex systems. This work highlights the potential of quantum processors in the fields of quantum chemistry, computational physics, and data science.
Abstract To understand the properties and interactions of materials, and determining the ground state energies is one of the important challenges in quantum chemistry, materials science, and quantum mechanics, where quantum computing can play an important role for studying the properties of materials. In this study, we have explored the quantum processor application to compute the He molecule ground state energy which utilizes the Variational Quantum Eigensolver (VQE) algorithm. In here, we have implemented VQE on a state-of-the-art quantum processor, optimizing a parameterized quantum circuit to minimize the energy expectation value of the He molecule's Hamiltonian on the four qubits processor. The obtained results of this work show a significant improvement in accuracy compared to classical computational methods, such as Hartree-Fock and density functional theory, which demonstrate the compute potential of quantum algorithms in quantum many-body problems. Thus, these results demonstrate the advantages of quantum computing in achieving high accuracy in simulations of molecular and material properties, and pave the way for future applications in more complex systems. This work highlights the potential of quantum processors in the fields of quantum chemistry, computational physics, and data science.