Hardware transpilation of parameterized quantum circuits produces ansatz-dependent shifts in expressibility (up to 125%) and trainability (up to 25%), altering the expected trade-off between them.
Designing robust quantum neural networks via optimized circuit metrics,
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Beyond Logical Circuits: Hardware-Aware Analysis of Expressibility and Trainability in Variational Quantum Algorithms
Hardware transpilation of parameterized quantum circuits produces ansatz-dependent shifts in expressibility (up to 125%) and trainability (up to 25%), altering the expected trade-off between them.