Bridge of $Ψ$'s: Quantum Circuit Optimization with Schrödinger Bridges
Quantum circuit optimization replaces a circuit with an equivalent one of fewer gates and lower depth, reducing execution cost and error rate. We ask whether a generative model can learn this transformation directly from examples, rather than selecting from a fixed rewrite library or rigid algebraic routines. We present Bridge of $Ψ$'s (BOPS), a generative model based on Schrödinger bridges, using a custom denoiser architecture, that learns a transformation from a source circuit into an equivalent optimized circuit. We train it on data constructed to be hard for existing optimizers, by applying rewrite rules backwards so that each input has a known lower-cost target. On held-out 8 qubits ...
| Authors | Lino S. Hofstetter, Lia Yeh, Prakash Murali |
|---|---|
| Primary category | quant-ph |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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