Single-Layer Digitized-Counterdiabatic Quantum Optimization for $p$-spin Models

• URL: http://arxiv.org/abs/2311.06682v1
• Date: Sat, 11 Nov 2023 22:49:16 GMT
• Title: Single-Layer Digitized-Counterdiabatic Quantum Optimization for $p$-spin Models
• Authors: Huijie Guan, Fei Zhou, Francisco Albarr\'an-Arriagada, Xi Chen, Enrique Solano, Narendra N. Hegade, He-Liang Huang
• Abstract summary: We take advantage of a digitized-counterdiabatic quantum optimization (DCQO) algorithm to find an optimal solution of the $p$-spin model up to 4-local interactions. By further optimizing parameters using variational methods, we solve with unit accuracy 2-spin, 3-spin, and 4-spin problems for $100%$, $93%$, and $83%$ of instances, respectively.
• Score: 8.463477025989542
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum computing holds the potential for quantum advantage in optimization problems, which requires advances in quantum algorithms and hardware specifications. Adiabatic quantum optimization is conceptually a valid solution that suffers from limited hardware coherence times. In this sense, counterdiabatic quantum protocols provide a shortcut to this process, steering the system along its ground state with fast-changing Hamiltonian. In this work, we take full advantage of a digitized-counterdiabatic quantum optimization (DCQO) algorithm to find an optimal solution of the $p$-spin model up to 4-local interactions. We choose a suitable scheduling function and initial Hamiltonian such that a single-layer quantum circuit suffices to produce a good ground-state overlap. By further optimizing parameters using variational methods, we solve with unit accuracy 2-spin, 3-spin, and 4-spin problems for $100\%$, $93\%$, and $83\%$ of instances, respectively. As a particular case of the latter, we also solve factorization problems involving 5, 9, and 12 qubits. Due to the low computational overhead, our compact approach may become a valuable tool towards quantum advantage in the NISQ era.

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