Assessing System Capabilities and Bottlenecks of an Early Fault-Tolerant Bicycle Architecture

TL;DR

This paper analyzes bottlenecks in early fault-tolerant quantum computers, focusing on inter-module communication, and proposes compiler optimizations to improve performance and reliability.

Contribution

It introduces new compiler techniques like synthesizing rotations at the factory, transvection-based Clifford deferral, and Clifford insertion, filling gaps in prior work.

Findings

Syn@fac reduces circuit failure probability by 9 times on average.

Transvection reduces Clifford deferral compile time by 77%.

Clifford insertion cuts circuit duration by 11.54% on average.

Abstract

Early modular fault tolerant quantum computers remain constrained by costly inter-module communication and limited magic state factory service. Understanding such bottlenecks and investigating compiler optimizations most close the gap between algorithm requirements and hardware capabilities is a concrete and practically urgent systems problem. We study the modular architectures based on Bivariate Bicycle codes and identify the dominant bottleneck: inter-module communication induced by non-Clifford operations. We build a compilation pipeline to fill the missing parts of prior works and propose compiler optimizations: synthesizing arbitrary-angle rotations at the factory (syn@fac), transvection based Clifford deferral, and Clifford insertion for critical path duration reduction. We extend the evaluation scope of the prior work to 40+ benchmark categories drawn from PennyLane and MQTBench, including quantum algorithms and Hamiltonian simulations with varying sizes. Under the present instruction cost, syn@fac reduces estimated circuit failure probability by a factor of 9.0 on average across non-Clifford benchmarks. The robustness persists across sweeps of instruction cost ratios, LPU count, and factory count. Besides, transvection reduces Clifford deferral compile time by 77.04\%, while Clifford insertion reduces end-to-end circuit duration by 11.54\% on average on MQTBench, with smaller gains on Hamiltonian simulations. We hope this work inspires the studies on compiler optimizations for early modular FTQC systems.