Jul 2026· 2026 IEEE International Conference on Quantum Software (QSW)· pp. 12-24· 0 citations· 69 references
Abstract
Quantum internet applications coordinate classical control, local quantum operations, and entanglement/communication across independent nodes under strict protocol ordering constraints. While Qoala and QNodeOS provide programming and execution abstractions for such applications, there is no compiler infrastructure that systematically lowers Qoala programs to executable node-level code while enabling optimization. We present the first multi-level compiler pipeline for Qoala quantum internet programs. The compiler lowers programs through three MLIR-based IRs that progressively expose hybrid control flow, explicit quantum memory, and Qoala block structure. On top of this pipeline, we implement (i) local peephole rewrites, and (ii) a block-reordering pass formulated as a MILP to reduce qubit lifetimes under precedence and resource constraints. We also provide static analyses for gate counts, qubit lifetimes, fidelity estimation, and quantum-memory efficiency. We evaluate on rotation-merging and blind quantum computing benchmarks using density-matrix simulation and IRderived estimates, showing that block reordering improves fidelity and memory reuse in latency-dominated regimes with modest compilation overhead.
This survey presents a full-stack view of compiler design for QEC-protected quantum computation, and identifies open challenges in cross-layer optimization, qLDPC compilation, compiler-decoder co-design, runtime adaptivity, and the development of integrated and benchmarkable FTQC compilation stacks.
Cheng-Hong Zhu, Jia-Han Chen, Ke-Ming He et al.· 0 citations
An economic order quantity model from perishable inventory theory is proposed to optimize the trade-off between entanglement distribution latency and the time cost of decoherence, offering a dual application for the hardware-software co-design of high-performance DQC.
Raymond P. H. Wu, Chathurika Ranaweera, Sutharshan Rajasegarar et al.· arXiv.org· 0 citations
A low-overhead fidelity-aware scheduling framework for multi-QPU systems based on a Graph Neural Network that estimates, before compilation, the expected fidelity of each circuit on each available QPU, and a tunable scheduler uses these estimates to control the trade-off between execution fidelity and parallelism.
Innocenzo Fulginiti, Antonio Tudisco, Salvatore Zammuto et al.· 0 citations
LLQM (Low-Level Quantum Machine), a profiling-driven meta-framework for quantum-classical pipelines that decomposes pipelines into fine-grained tasks and continuously profiles their CPU/GPU, memory, QPU, and queue dependencies alongside real-time hardware states, is presented.
Ayush Bansal, Owen Cochell, Santiago Núñez-Corrales et al.· 0 citations
An architecture-aware reinforcement-learning framework that formulates distributed quantum compilation as a constrained Markov Decision Process (MDP), where compiler-level communication actions dynamically update logical-qubit placement and enable subsequent gate execution.
Chien-Tung Kuo, Felix Burt, Samuel Yen-Chi Chen et al.· 1 citation
It is shown that the best-performing compilation strategy varies across the tested circuits and network configurations, and that both network topology and intra-QPU connectivity substantially affect the entanglement cost of execution.
Luke Andreesen, Shobhit Gupta, Sean E. Sullivan et al.· 0 citations
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