Problem
Research questions and friction points this paper is trying to address.
fault-tolerant quantum computing
magic-state cultivation
classical runtime
latency constraints
MagiCFirm: A Runtime for Magic-State Cultivation with Algorithm-Hardware Co-Design
🤖 AI Summary
This study addresses the lack of open-source classical runtimes and the high protocol decision latency in magic state preparation for fault-tolerant quantum computing by proposing MagiCFirm, an algorithm-hardware co-designed runtime system. Methodologically, it introduces a two-stage early-escape decoding scheme that enables parallel execution of partial and full decoding. Architecturally, the system leverages offline-compiled microprograms, dedicated datapaths, and a configurable runtime framework to accelerate the preparation pipeline. Experimental results demonstrate that MagiCFirm reduces magic state preparation time by 39.3% and overall application execution time by 11%, providing an efficient, open-source classical control solution for fault-tolerant quantum computing.
📝 Abstract
Magic-state cultivation offers a promising alternative for lowering the cost of non-Clifford operations in fault-tolerant quantum computing (FTQC). However, realizing cultivation in practice exposes two challenges: (i) the lack of an open-source classical runtime layer between logical software and physical control, and (ii) the latency constraints on protocol-specific decisions that determine magic-state readiness. To address these challenges, we adopt an algorithm--hardware co-design approach. At the algorithm level, we develop a two-stage early-escape scheme that identifies an informative subset of detectors offline, constructs a compact decoding problem, and performs partial decoding in parallel with complete decoding at runtime, allowing high-confidence attempts to advance before full decoding completes. At the hardware level, we present MagiCFirm, a configurable runtime that combines offline-compiled microprograms with dedicated datapaths for detector construction, event processing, and protocol control, enabling end-to-end execution of magic-state cultivation. Across evaluated configurations, MagiCFirm reduces wall-clock magic-state preparation time by up to 39.3% at matched logical error rate. For a representative magic-state-bound workload, this translates to an estimated 11% reduction in overall application runtime.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Magic-state cultivation
Algorithm-hardware co-design
Early-escape decoding
Fault-tolerant quantum computing
Runtime system
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