Quantum Brain
← Back to papers

Bloch Vector Assertions for Debugging Quantum Programs

Noah Oldfield, Christoph Laaber, Shaukat Ali·June 23, 2025·DOI: 10.48550/arXiv.2506.18458
PhysicsComputer Science

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

Abstract

Quantum programs must be reliable to ensure trustworthy results, yet debugging them is notoriously challenging due to quantum-specific faults like gate misimplementations and hardware noise, as well as their inherently probabilistic nature. Assertion-based debugging provides a promising solution by enabling localized correctness checks during execution. However, current approaches face challenges including manual assertion generation, reliance on mid-circuit-measurements, and poor scalability. In this paper, we present Bloq, a scalable, automated fault localization approach introducing Bloch-vector-based assertions utilizing expectation value measurements of Pauli operators, enabling low-overhead fault localization without mid-circuit measurements. In addition, we introduce AutoBloq, a component of Bloq for automatically generating assertion schemes from quantum algorithms. An experimental evaluation over 684432 programs using two algorithms (Quantum Fourier Transform (QFT) and Grover) shows that Bloq consistently outperforms the state-of-the-art approach Proq, notably as circuit depth and noise increase. For Grover, Bloq achieves a mean F1 score across all experimental instances of 0.74 versus 0.38 for Proq under ideal conditions, and maintains performance under noise (0.43 versus 0.06). Bloq also reduces Proq's runtime by a factor of 5 and circuit depth overhead by a factor of 23. These results underline Bloq's potential to make assertion-based debugging scalable and effective for near-term quantum devices.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.