HQPEF-Py: Metrics, Python Patterns, and Guidance for Evaluating Hybrid Quantum Programs

Fuente: arXiv
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Main Authors: Osei, Michael Adjei, Shapiro, Sidney
Format: Preprint
Published: 2025
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author Osei, Michael Adjei
Shapiro, Sidney
author_facet Osei, Michael Adjei
Shapiro, Sidney
contents We study how to evaluate hybrid quantum programs as end-to-end workflows rather than as isolated devices or algorithms. Building on the Hybrid Quantum Program Evaluation Framework (HQPEF), we formalize a workflow-aware Quantum Readiness Level (QRL) score; define a normalized speedup under quality constraints for the Utility of Quantumness (UQ); and provide a timing-and-drift audit for hybrid pipelines. We complement these definitions with concise Python reference implementations that illustrate how to instantiate the metrics and audit procedures with state-of-the-art classical and quantum solvers (e.g., via Qiskit or PennyLane), while preserving matched-budget discipline and reproducibility.
format Preprint
id arxiv_https___arxiv_org_abs_2511_18506
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle HQPEF-Py: Metrics, Python Patterns, and Guidance for Evaluating Hybrid Quantum Programs
Osei, Michael Adjei
Shapiro, Sidney
Software Engineering
We study how to evaluate hybrid quantum programs as end-to-end workflows rather than as isolated devices or algorithms. Building on the Hybrid Quantum Program Evaluation Framework (HQPEF), we formalize a workflow-aware Quantum Readiness Level (QRL) score; define a normalized speedup under quality constraints for the Utility of Quantumness (UQ); and provide a timing-and-drift audit for hybrid pipelines. We complement these definitions with concise Python reference implementations that illustrate how to instantiate the metrics and audit procedures with state-of-the-art classical and quantum solvers (e.g., via Qiskit or PennyLane), while preserving matched-budget discipline and reproducibility.
title HQPEF-Py: Metrics, Python Patterns, and Guidance for Evaluating Hybrid Quantum Programs
topic Software Engineering
url https://arxiv.org/abs/2511.18506