Orchestrating multi-level magic state distillation: a dynamic pipeline architecture

2025-09-29

AI Summary

Multi-level magic state distillation in fault-tolerant quantum computing incurs substantial resource overhead and suffers from low utilization of static pipelined architectures. Method: This paper proposes a dynamic pipelining architecture that identifies and models the bursty temporal pattern of magic state demand, enabling a factory-level dynamic scheduling mechanism and adaptive resource allocation strategy to jointly optimize multi-level distillation workflows. Contribution/Results: Compared to conventional static approaches, the proposed method reduces qubit overhead by 16%–70% for large-scale quantum applications and achieves an average 26%–37% reduction in qubit-time product on distillation benchmarks. It significantly improves magic state supply efficiency and hardware resource utilization while preserving fidelity and fault tolerance requirements.

Technology Category

• Machine Learning: Quantum Machine Learning
• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

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.

Problem

• Optimizing resource usage in multi-level magic state distillation
• Reducing qubit cost for large-scale quantum applications
• Improving efficiency of fault-tolerant quantum computing pipelines

Innovation

• Dynamic pipeline architecture for magic state distillation
• Dynamic factory scheduling and resource allocation techniques
• Reducing qubit cost and qubit-time volume significantly