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This research proposes a novel Intermediate Representation (IR) that treats quantum gates as dynamic values rather than fixed sequences, enabling classical logic to steer quantum behavior in hybrid applications. By supporting adaptive error correction and measurement-driven computation within a unified framework, this approach overcomes the limitations of traditional circuit-model compilers for complex, data-dependent workflows. The study demonstrates that this representation facilitates significant compiler optimizations previously impossible under static models.
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A Dynamic Intermediate Representation for Hybrid Quantum-Classical Programs

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arXiv:2609.01037v1 Announce Type: cross Abstract: Quantum compilers typically follow the circuit model, representing programs as fixed sequences of gates. This static view breaks down in hybrid quantum-classical applications, where gate choices depend on runtime data or measurement results. We introduce a new Intermediate Representation (IR) that elevates gates to first-class values, enabling their dynamic creation, composition, and control. This unified representation allows classical computation to steer quantum behaviour, capturing phenomena including stochastic gate selection, adaptive error correction, and measurement-driven computation within a single framework. Case studies in noise modelling, randomised compilation, error correction, and measurement-based quantum computing show that our IR expresses these programs compactly and supports optimisations that were not possible in the circuit model. Evaluation on a benchmark suite of hybrid quantum-classical programs indicates that our IR represents programs compactly and facilitates compiler analysis and transformation.

Abstract:Quantum compilers typically follow the circuit model, representing programs as fixed sequences of gates. This static view breaks down in hybrid quantum-classical applications, where gate choices depend on runtime data or measurement results. We introduce a new Intermediate Representation (IR) that elevates gates to first-class values, enabling their dynamic creation, composition, and control. This unified representation allows classical computation to steer quantum behaviour, capturing phenomena including stochastic gate selection, adaptive error correction, and measurement-driven computation within a single framework. Case studies in noise modelling, randomised compilation, error correction, and measurement-based quantum computing show that our IR expresses these programs compactly and supports optimisations that were not possible in the circuit model. Evaluation on a benchmark suite of hybrid quantum-classical programs indicates that our IR represents programs compactly and facilitates compiler analysis and transformation.

Programming Languages (cs.PL); Quantum Physics (quant-ph)

arXiv:2609.01037 [cs.PL]

(or arXiv:2609.01037v1 [cs.PL] for this version)

https://doi.org/10.48550/arXiv.2609.01037 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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