Optimizing Quantum Algorithms on Bipotent Architectures

Abstract

Vigorous optimization of quantum gates has led to bipotent quantum architectures, where the optimized gates are available for some qubits but not for others. However, such gate-level improvements limit the application of user-side pulse-level optimizations, which have proven effective for quantum circuits with a high level of regularity, such as the ansatz circuit of the Quantum Approximate Optimization Algorithm (QAOA). In this paper, we investigate the trade-off between hardware-level and algorithm-level improvements on bipotent quantum architectures. Our results for various QAOA instances on two quantum computers offered by IBM indicate that the benefits of pulse-level optimizations currently outweigh the improvements due to vigorously optimized monolithic gates. Furthermore, our data indicate that the fidelity of circuit primitives is not always the best indicator for the overall algorithm performance; also their gate type and schedule duration should be taken into account. This effect is particularly pronounced for QAOA on dense portfolio optimization problems, since their transpilation requires many SWAP gates, for which efficient pulse-level optimization exists. Our findings provide practical guidance on optimal qubit selection on bipotent quantum architectures and suggest the need for improvements of those architectures, ultimately making pulse-level optimization available for all gate types.

References in corpus (23)

• Quantum Computing in the NISQ era and beyond
• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Mixed State Entanglement and Quantum Error Correction
• Variational Quantum Algorithms
• Photonic quantum technologies
• Dynamical suppression of decoherence in two-state quantum systems
• Error mitigation for short-depth quantum circuits
• Trapped-Ion Quantum Computing: Progress and Challenges
• Quantum computing with neutral atoms
• Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor
• ProjectQ: An Open Source Software Framework for Quantum Computing
• t$|$ket$⟩$ : A Retargetable Compiler for NISQ Devices
• Quantum Computing for Finance: State of the Art and Future Prospects
• A universal gate for fixed-frequency qubits via a tunable bus
• Realization of high-fidelity CZ and ZZ-free iSWAP gates with a tunable coupler
• Demonstration of fidelity improvement using dynamical decoupling with superconducting qubits
• Digitized-counterdiabatic quantum approximate optimization algorithm
• MAXCUT QAOA performance guarantees for p >1
• Benchmarking the performance of portfolio optimization with QAOA
• A Hardware-Aware Heuristic for the Qubit Mapping Problem in the NISQ Era
• Benchmarking the noise sensitivity of different parametric two-qubit gates in a single superconducting quantum computing platform
• staq -- A full-stack quantum processing toolkit
• Portfolio Optimization with Digitized-Counterdiabatic Quantum Algorithms

Cited by in corpus (7)

• A Review on Quantum Approximate Optimization Algorithm and its Variants
• Algorithm-Oriented Qubit Mapping for Variational Quantum Algorithms
• Synergistic Dynamical Decoupling and Circuit Design for Enhanced Algorithm Performance on Near-Term Quantum Devices
• Improving the Performance of Digitized Counterdiabatic Quantum Optimization via Algorithm-Oriented Qubit Mapping
• Exploring the Fidelity of Flux Qubit Measurement in Different Bases via the Quantum Flux Parametron
• Data-Efficient Quantum Noise Modeling via Machine Learning
• EmuPlat: A Framework-Agnostic Platform for Quantum Hardware Emulation with Validated Transpiler-to-Pulse Pipeline