Late Breaking Results: Hardware-Aware Compilation Reshapes Trainability in Variational Quantum Circuits

• URL: http://arxiv.org/abs/2604.16527v1
• Date: Thu, 16 Apr 2026 14:08:02 GMT
• Title: Late Breaking Results: Hardware-Aware Compilation Reshapes Trainability in Variational Quantum Circuits
• Abstract summary: Execution on real quantum devices requires hardware-aware compilation (transpilation) to satisfy qubit connectivity and native gate-set constraints.<n>In this paper, we examine how transpilation can alter the gradient statistics.
• Score: 2.717526933594264
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Variational quantum circuits (VQCs) are typically evaluated at the logical design level when analyzing trainability. However, execution on real quantum devices requires hardware-aware compilation (transpilation) to satisfy qubit connectivity and native gate-set constraints. In this paper, we examine how transpilation can alter the gradient statistics. Using parameter-shift differentiation and gradient variance estimation, we compare logical and transpiled circuits across three representative ansatz families: EfficientSU2 (dense entanglement), TTN (tree tensor network), and RealAmplitudes (linear entanglement). We observe architecture-dependent trainability shifts where densely entangling circuits exhibit pronounced gradient reshaping in shallow regimes, structured tensor-network circuits remain comparatively robust, and linear architectures show mixed behavior. Deep circuits across all families display minimal sensitivity to hardware-aware compilation. These findings demonstrate that transpilation acts as an implicit structural transformation of the optimization landscape, motivating compilation-aware analysis and co-design for VQCs.

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