Digital-analog quantum genetic algorithm using Rydberg-atom arrays

Abstract

Digital-analog quantum computing (DAQC) combines digital gates with analog operations, offering an alternative paradigm for universal quantum computation. This approach leverages the higher fidelities of analog operations and the flexibility of local single-qubit gates. In this paper, we propose a quantum genetic algorithm within the DAQC framework using a Rydberg-atom emulator. The algorithm employs single-qubit operations in the digital domain and a global driving interaction based on the Rydberg Hamiltonian in the analog domain. We evaluate the algorithm performance by estimating the ground-state energy of Hamiltonians, with a focus on molecules such as ${\mathrm{H}}_2$, $\mathrm{LiH}$, and $\mathrm{Be}{\mathrm{H}}_2$. Our results show energy estimations with less than 1% error and state overlaps nearing 1, with computation times ranging from a few minutes for ${\mathrm{H}}_2$ (2-qubit circuits) to one to two days for $\mathrm{LiH}$ and $\mathrm{Be}{\mathrm{H}}_2$ (6-qubit circuits). The gate fidelities of global analog operations further underscore DAQC as a promising quantum computing strategy in the noisy intermediate-scale quantum era.

13 pages, 14 figures

References in corpus (5)

• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Quantum phase transition from a superfluid to a Mott insulator in a gas of ultracold atoms
• Simulated Quantum Computation of Molecular Energies
• Quantum computing with neutral atoms
• Coherent and dissipative dynamics of entangled few-body systems of Rydberg atoms

Cited by in corpus (1)

• Digital-Analog Quantum Machine Learning