Variational quantum transduction

Quantum transducers are critical for quantum interconnect, enabling coherent signal transfer across disparate frequency domains. Beyond material and device advances, protocol design has become a powerful means to improve transduction. We introduce a variational quantum transduction (VQT) framework that employs variational tools from near-term quantum computing to systematically optimize protocol performance. As a variational quantum circuit, the existence of barren plateau does not prevent VQT from providing substantial advantage, as a small-scale problem is sufficient for quantum transduction and training only needs to be done once to configure a VQT system. Maximizing the quantum information rate within this framework yields protocols that surpass the benchmark schemes considered in their respective classes within the finite-energy regimes under consideration. For non-adaptive protocols, VQT exceeds the performance envelopes of Gottesman-Kitaev-Preskill (GKP)-based and entanglement-assisted approaches. In the adaptive setting, VQT provides only a marginal improvement over Gaussian feedforward strategies, indicating that Gaussian adaptive transduction is already close to optimal for the parameter regimes that we studied. With increasingly universal quantum control, VQT provides a systematic path toward optimized quantum transduction.