aiqbench analysis
This article presents Qomet, a novel compiler that optimizes fault-tolerant quantum execution by leveraging C-Phase gate commutativity to maximize instruction-level parallelism within lattice surgery architectures. By addressing fine-grained microarchitectural constraints like routing contention, the approach achieves significant speedups over traditional slice-based compilation methods. This work directly advances the efficiency of mapping logical algorithms onto physical quantum hardware, a critical step toward practical quantum advantage.
C-Phase-Aware Compilation for Efficient Fault-Tolerant Quantum Execution
arXiv:2605.14042v2 Announce Type: replace Abstract: Achieving practical quantum advantage on fault-tolerant quantum computers (FTQC) is fundamentally constrained by the substantial spatial and temporal overheads required to map logical operations onto physical hardware. Existing compilation approaches typically adopt coarse-grained, slice-based abstractions that overlook fine-grained microarchitectural effects, such as routing contention, leading to inefficient resource utilization and limited alignment between algorithm structure and hardware capabilities. We introduce Qomet, a microarchitecture-aware compiler that tightly couples algorithmic properties with lattice surgery (LS) execution. By exploiting C-Phase gate commutativity, Qomet translates sequential operations into simultaneous multi-target interactions, natively leveraging LS to eliminate false dependencies and expose instruction-level parallelism. To support this, Qomet employs an adaptive, event-driven scheduler that captures precise spatial and routing constraints to overlap instructions temporally. By minimizing grid idling and routing contention, Qomet achieves a geometric-mean execution speedup of 4.29$\times$ and a maximum speedup of 59.7$\times$ across realistic workloads.
Abstract:Achieving practical quantum advantage on fault-tolerant quantum computers (FTQC) is fundamentally constrained by the substantial spatial and temporal overheads required to map logical operations onto physical hardware. Existing compilation approaches typically adopt coarse-grained, slice-based abstractions that overlook fine-grained microarchitectural effects, such as routing contention, leading to inefficient resource utilization and limited alignment between algorithm structure and hardware capabilities. We introduce Qomet, a microarchitecture-aware compiler that tightly couples algorithmic properties with lattice surgery (LS) execution. By exploiting C-Phase gate commutativity, Qomet translates sequential operations into simultaneous multi-target interactions, natively leveraging LS to eliminate false dependencies and expose instruction-level parallelism. To support this, Qomet employs an adaptive, event-driven scheduler that captures precise spatial and routing constraints to overlap instructions temporally. By minimizing grid idling and routing contention, Qomet achieves a geometric-mean execution speedup of 4.29$\times$ and a maximum speedup of 59.7$\times$ across realistic workloads.
arXiv:2605.14042 [quant-ph]
(or arXiv:2605.14042v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2605.14042 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 231 words
