Quantum Brain
← Back to papers

Erasure Minesweeper: Exploring Hybrid-Erasure Surface Code Architectures for Efficient Quantum Error Correction

Jason Chadwick, Mariesa Teo, Joshua Viszlai, Willers Yang, Frederic T. Chong·April 30, 2025·DOI: 10.1109/QCE65121.2025.00077
Physics

AI Breakdown

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

Abstract

Dual-rail erasure qubits can substantially improve the efficiency of quantum error correction, allowing lower error rates to be achieved with fewer qubits, but each erasure qubit requires $3 \times$ more transmons to implement compared to standard qubits. In this work, we introduce a hybrid-erasure architecture for surface code error correction where a carefully chosen subset of qubits is designated as erasure qubits while the rest remain standard. Through code-capacity analysis and circuitlevel simulations, we show that a hybrid-erasure architecture can boost the performance of the surface code-much like how a game of Minesweeper becomes easier once a few squares are revealed-while using fewer resources than a full-erasure architecture. We study strategies for the allocation and placement of erasure qubits through analysis and simulations. We then use the hybrid-erasure architecture to explore the trade-offs between per-qubit cost and key logical performance metrics such as threshold and effective distance in surface code error correction. Our results show that the strategic introduction of dual-rail erasure qubits in a transmon architecture can enhance the logical performance of surface codes for a fixed transmon budget, particularly for near-term-relevant transmon counts and logical error rates.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.