In this paper, we introduce HamilToniQ, an open-source, and application-oriented benchmarking toolkit for the comprehensive evaluation of Quantum Processing Units (QPUs). Designed to navigate the complexities of quantum computations, HamilToniQ incorporates a methodological framework assessing QPU types, topologies, and multi-QPU systems. The toolkit facilitates the evaluation of QPUs' performance through multiple steps including quantum circuit compilation and quantum error mitigation (QEM), integrating strategies that are unique to each stage. HamilToniQ's standardized score, H-Score, quantifies the fidelity and reliability of QPUs, providing a multidimensional perspective of QPU performance. With a focus on the Quantum Approximate Optimization Algorithm (QAOA), the toolkit enables direct, comparable analysis of QPUs, enhancing transparency and equity in benchmarking. Demonstrated in this paper, HamilToniQ has been validated on various IBM QPUs, affirming its effectiveness and robustness. Overall, HamilToniQ significantly contributes to the advancement of the quantum computing field by offering precise and equitable benchmarking metrics.

翻译：本文介绍HamilToniQ——一种面向应用的开源基准测试工具包，用于全面评估量子处理单元（QPU）。为应对量子计算的复杂性，HamilToniQ构建了涵盖QPU类型、拓扑结构及多QPU系统评估的方法论框架。该工具包通过量子电路编译与量子错误缓解（QEM）等多个步骤实现QPU性能评估，整合了各阶段特有的策略。通过标准化评分H-Score，HamilToniQ量化了QPU的保真度与可靠性，从多维度呈现QPU性能。该工具包以量子近似优化算法（QAOA）为核心，支持QPU的直接可比较分析，提升了基准测试的透明度与公平性。本文在多种IBM QPU上验证了HamilToniQ的有效性与鲁棒性。总体而言，HamilToniQ通过提供精确且公平的基准测试指标，显著推动了量子计算领域的发展。