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Quantum Machine Learning
OpenQudit: Extensible and Accelerated Numerical Quantum Compilation via a JIT-Compiled DSL
arXiv
Authors: Ed Younis
Year
2025
Paper ID
16862
Status
Preprint
Abstract Read
~2 min
Abstract Words
122
Citations
N/A
Abstract
High-performance numerical quantum compilers rely on classical optimization, but are limited by slow numerical evaluations and a design that makes extending them with new instructions a difficult, error-prone task for domain experts. This paper introduces OpenQudit, a compilation framework that solves these problems by allowing users to define quantum operations symbolically in the Qudit Gate Language (QGL), a mathematically natural DSL. OpenQudit's ahead-of-time compiler uses a tensor network representation and an e-graph-based pass for symbolic simplification before a runtime tensor network virtual machine (TNVM) JIT-compiles the expressions into high-performance native code. The evaluation shows that this symbolic approach is highly effective, accelerating the core instantiation task by up to mathtt{sim}20times on common quantum circuit synthesis problems compared to state-of-the-art tools.
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- High-performance numerical quantum compilers rely on classical optimization, but are limited by slow numerical evaluations and a design that makes extending them with new...
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