Lightweight Targeted Estimation of Layout Noise in a Quantum Computer using Quality Indicator Circuits

2025-09-23

AI Summary

Non-uniform and dynamically varying noise in quantum hardware degrades circuit mapping quality. Method: This paper proposes a lightweight, real-time layout evaluation technique centered on compact, structure-preserving Quality Indicator Circuits (QICs). It integrates isomorphic layout enumeration, non-overlapping joint-layout fusion, and distortion-threshold-based overlap control—enabling high-accuracy optimal region identification without reliance on outdated calibration data. Contribution/Results: Compared to Just-In-Time (JIT) mapping, the method reduces hardware resource overhead by 79%; relative to Mapomatic, it achieves significantly higher layout quality. Experimental evaluation on near-term quantum devices demonstrates both computational efficiency and robustness, enhancing the reliability and practicality of quantum circuit execution in the NISQ era.

Technology Category

• Machine Learning: Quantum Machine Learning
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

In the current era of quantum computing, minimizing noise is essential for reliably executing quantum circuits on hardware. A key factor affecting circuit performance is the mapping of the abstract quantum circuit to the physical layout of the quantum hardware. This mapping can significantly influence output quality, especially since hardware noise profiles are non-uniform and dynamic. Existing solutions such as Mapomatic and Just-In-Time (JIT) Transpilation attempt to address this issue but are limited either by relying on stale calibration data or high hardware usage, respectively. In this article, we propose Quality Indicator Circuits (QICs) as a lightweight, real-time method for assessing layout quality. A QIC is a small probe circuit that is designed to retain the basic structure of the user's circuit and whose ideal noiseless outcome is known. It is used to evaluate which region of the quantum hardware is best suited for executing the circuit of interest. We first propose a basic method where a QIC is executed for each isomorphic layout to detect the best among them. Although this requires several targeted circuit executions, we show that it still, in most cases, reduces the execution overheads as compared with JIT. To reduce the overheads further, we propose the union of multiple layouts with a Union QIC approach that has no overlaps, and a Distortion Threshold based approach allowing some overlap. Our results show that these outperform Mapomatic in the quality of layout selection while reducing the hardware overhead of JIT by 79 percent on average. This makes our proposed method lightweight and reliable, and a viable technique for layout selection in near-term quantum devices.

Problem

• Estimating layout noise in quantum computers
• Assessing hardware region suitability for circuits
• Reducing execution overhead in layout selection

Innovation

• Quality Indicator Circuits assess layout quality
• Union QIC reduces hardware execution overhead
• Distortion Threshold allows controlled layout overlap