A Multi-Level Integrity Evaluation Framework for Quantum Circuits under Controlled Anomaly Injection

2026-04-29

AI Summary

This study addresses the integrity challenges faced by quantum circuits in the NISQ era, including compilation-induced transformations, hardware constraints, and potential malicious tampering. Existing approaches fall short due to their reliance solely on structural or behavioral analysis, limiting comprehensive integrity assessment. To overcome this, the work proposes the first three-tier evaluation framework that jointly characterizes circuit integrity across structural, behavioral, and gate-interaction dimensions through a Structural Integrity Score (SIS), an Operational Integrity Score (OIS), and an Interaction Graph Semantic logic Score (IGS). The method innovatively employs Jensen–Shannon divergence to quantify behavioral deviations, constructs an interaction graph to capture pre-execution dependencies, and validates efficacy via controlled anomaly injection. Experiments demonstrate that, in structurally ambiguous cases, OIS and IGS achieve detection rates of 93.85% and 72.58%, respectively, significantly outperforming single-metric approaches.

Abstract

Ensuring the integrity of quantum circuits is a significant challenge in the Noisy Intermediate-Scale Quantum (NISQ) era, where circuits are subject to compilation transformations, hardware constraints, and potential adversarial modifications. Existing validation approaches typically rely on either structural analysis or behavioral evaluation, leading to incomplete assessment of circuit correctness. In this work, we investigate the relationship between structural, interaction-level, and behavioral perspectives of circuit integrity, demonstrating that a single aspect of integrity is insufficient to guarantee circuit integrity; structural similarity alone does not ensure behavioral equivalence. To address this problem, we use a three-layer metric framework that combines the Structural Integrity Score (SIS), the Operational Integrity Score (OIS), and the Interaction Graph Semantic-Logical Score (IGS). SIS captures global structural properties, OIS quantifies behavioral divergence using Jensen-Shannon distance, and IGS models interaction patterns and dependencies in a pre-execution setting. Through controlled anomaly injection on benchmark quantum circuits, we demonstrate that each metric captures a different aspect of circuit deviation. In particular, structural blind-spot cases (SIS >= 0.95) reveal a clear limitation of structural analysis, where OIS detects anomalies in 93.85% of instances, while IGS detects 72.58%. These results highlight that the metrics provide complementary insights and that a single metric is insufficient for reliable circuit validation.

Problem

• quantum circuits
• integrity evaluation
• NISQ
• anomaly detection
• circuit validation

Innovation

• quantum circuit integrity
• multi-level evaluation
• anomaly injection
• structural-behavioral divergence
• interaction graph semantics