OneAdapt: Adaptive Compilation for Resource-Constrained Photonic One-Way Quantum Computing
Hezi Zhang, Jixuan Ruan, Dean Tullsen, Yufei Ding, Ang Li, Travis S. Humble
TL;DR
The paper tackles resource-constrained photonic one-way quantum computing by designing a novel intermediate representation (IR) tailored to hardware limits. It introduces dynamic refreshing and 2D-bounded temporal routing as optimization passes to bound temporal-edge lengths while reducing 1D depth and 2D footprint, and demonstrates compatibility with quantum error correction for fault-tolerant operation. Compared with prior IRs, the approach achieves up to $3.68\\times$ reduction in 1D depth and, in FTQC settings with surface code, about $2.87\\times$ depth reduction, while maintaining bounded fusion-resource requirements. This work advances practical photonic MBQC by balancing hardware constraints with compile-time optimization and QEC integration, enabling scalable, low-latency quantum computation on photonic platforms.
Abstract
Measurement-based quantum computing (MBQC), a.k.a. one-way quantum computing (1WQC), is a universal quantum computing model, which is particularly well-suited for photonic platforms. In this model, computation is driven by measurements on an entangled state, which serves as an intermediate representation (IR) between program and hardware. However, compilers on previous IRs lacks the adaptability to the resource constraint in photonic quantum computers. In this work, we propose a novel IR with new optimization passes. Based on this, it realizes a resource-adaptive compiler that minimizes the required hardware size and execution time while restricting the requirement for fusion devices within an adaptive limit. Moreover, our optimization can be integrated with Quantum Error Correction (QEC) to improve the efficiency of photonic fault-tolerant quantum computing (FTQC).