2025/09/29 by Wang, Junshi, Prakash Murali, Murali, Prakash
Computer Science · #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Physical sciences #Neural Networks and Applications #Parallel Computing and Optimization Techniques #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2509.24402
openalex publication_date 2025/09/29 · openalex created_date 2025/10/19 · openalex updated_date 2026/07/28
Practical quantum computation requires high-fidelity instruction executions on qubits. Among them, Clifford instructions are relatively easy to perform, while non-Clifford instructions require the use of magic states. This makes magic state distillation a central procedure in fault-tolerant quantum computing. A magic state distillation factory consumes many low-fidelity input magic states and produces fewer, higher-fidelity states. To reach high fidelities, multiple distillation factories are typically chained together into a multi-level pipeline, consuming significant quantum computational resources. Our work optimizes the resource usage of distillation pipelines by introducing a novel dynamic pipeline architecture. Observing that distillation pipelines consume magic states in a burst-then-steady pattern, we develop dynamic factory scheduling and resource allocation techniques that go beyond existing static pipeline organizations. Dynamic pipelines reduce the qubit cost by 16%-70% for large-scale quantum applications and achieve average reductions of 26%-37% in qubit-time volume on generated distillation benchmarks compared to state-of-the-art static architectures. By significantly reducing the resource overhead of this building block, our work accelerates progress towards the practical realization of fault-tolerant quantum computers.