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Cloud Quantum Computing of an Atomic Nucleus

E. F. Dumitrescu, A. J. McCaskey, G. Hagen, G. R. Jansen, T. D. Morris, T. Papenbrock, R. C. Pooser, D. J. Dean, P. Lougovski

arXiv:1801.03897v1quant-phnucl-th

TL;DR

The paper addresses whether cloud-accessed quantum processors can simulate a nuclear bound state despite limited qubits, connectivity, circuit depth, measurements, and intermittent access. It maps the deuteron to a pionless-EFT Hamiltonian, uses a low-depth unitary coupled-cluster ansatz with VQE, and obtains binding energies within a few percent of exact results.

  • Problem

    Quantum simulation of nuclear systems is limited by present devices, which have few nonerror-corrected qubits and constraints on gates, measurements, connectivity, and access.

  • Method

    The deuteron is represented with a leading-order pionless-EFT Hamiltonian and simulated using a reduced-depth unitary coupled-cluster ansatz, VQE, and cloud quantum hardware.

  • Results

    The combined two-qubit energy is E2 = −1.74±0.03 MeV versus the exact −1.749 MeV, while infinite-space extrapolations are within 2%; the error-mitigated three-qubit result is E3 = −2.08 ± 0.03 MeV.

  • Takeaways & Limitations

    Cloud quantum computation reproduced the deuteron binding energy and provides a first step toward quantum computations of heavier nuclei via cloud access.

  • Takeaways & Limitations

    The model uses a harmonic-oscillator basis with an ultraviolet cutoff Λ ≈152 MeV, separated from the bound-state momentum Q ≈46 MeV.

Abstract

from arXiv · show

We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.

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