ECCentric: An Empirical Analysis of Quantum Error Correction Codes

TL;DR

The paper introduces ECCentric, an end-to-end benchmarking framework to systematically compare quantum error correction codes across hardware topologies, noise models, and compilation strategies, enabling practical, stack-wide analysis. Using ECCentric, the authors benchmark six codes from five families across four dimensions, revealing that intra-QPU execution often outperforms distributed approaches, that qubit connectivity dominates code-distance effects, and that compiler overhead can negate QEC benefits. They show that trapped-ion platforms with qubit shuttling are particularly promising for near-term fault tolerance and argue for selective QEC deployment on noisy devices. These findings offer concrete guidance to hardware designers and compiler developers for advancing toward fault-tolerant quantum computation.

Abstract

Quantum error correction (QEC) is essential for building scalable quantum computers, but a lack of systematic, end-to-end evaluation methods makes it difficult to assess how different QEC codes perform under realistic conditions. The vast diversity of codes, an expansive experimental search space, and the absence of a standardized framework prevent a thorough, holistic analysis. To address this, we introduce ECCentric, an end-to-end benchmarking framework designed to systematically evaluate QEC codes across the full quantum computing stack. ECCentric is designed to be modular, extensible, and general, allowing for a comprehensive analysis of QEC code families under varying hardware topologies, noise models, and compilation strategies. Using ECCentric, we conduct the first systematic benchmarking of major QEC code families against realistic, mid-term quantum device parameters. Our empirical analysis reveals that intra-QPU execution significantly outperforms distributed methods, that qubit connectivity is a far more critical factor for reducing logical errors than increasing code distance, and that compiler overhead remains a major source of error. Furthermore, our findings suggest that trapped-ion architectures with qubit shuttling are the most promising near-term platforms and that on noisy devices, a strategic and selective application of QEC is necessary to avoid introducing more errors than are corrected. This study provides crucial, actionable insights for both hardware designers and practitioners, guiding the development of fault-tolerant quantum systems.

Figures (28)

• Figure 1: Workflow of a quantum circuit protected with QEC, showing how mapping and routing, translation, and decoding are handled during execution.
• Figure 2: Our comprehensive framework provides a structured empirical analysis of QEC landscape. We examine the QEC field across four key dimensions, addressing eight critical research questions.
• Figure 3: Lifetime of a quantum circuit protected with QEC code. Our analysis covers the elements in green.
• Figure 4: Visualization of the six QEC codes explored in this work. White dots represent data qubits, yellow and purple dots indicate gauge qubits, and remaining dots correspond to additional ancilla qubits. $\hat{X}$, $\hat{Y}$, and $\hat{Z}$ symbolize logical operators, $G_x$ and $G_z$ gauge operators. Field colors indicate stabilizers $S^x$ and $S^z$.
• Figure 5: Architecture of the ECCentric framework. Our design of a fully modular and extensible setup, enabling systematic study of the different aspects of QEC realization.