[Paper Review] Variational Quantum Transduction

Pengcheng Liao, Haowei Shi+1 more|arXiv (Cornell University)|Mar 4, 2026

Quantum Computing Algorithms and Architecture0 citations

TL;DR

The paper introduces Variational Quantum Transduction (VQT), a variational circuit framework to optimize quantum transduction protocols under realistic constraints, and shows it can outperform non-adaptive schemes while offering limited gains over Gaussian adaptive strategies in the adaptive setting.

ABSTRACT

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 framework, VQT is not plagued by known training issues such as barren plateau, because a small-scale problem is sufficient for substantial advantage 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 all known schemes in their respective classes. 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. With increasingly universal quantum control, VQT provides a systematic path toward optimal quantum transduction.

Motivation & Objective

• Motivate quantum transduction as a primitive for quantum networks and sensing.
• Develop a variational quantum circuit framework to optimize transduction protocols.
• Compare non-adaptive and adaptive transduction within a unified coherent-information metric.
• Demonstrate that VQT outperforms GKP-based and entanglement-assisted non-adaptive protocols, while adaptive Gaussian strategies remain highly effective.

Proposed method

• Model transduction as a beamsplitter interaction with efficiency η and use coherent information as the performance metric.
• Introduce a variational quantum circuit (VQC) framework with input state preparers for the optical signal S and microwave inputs (P,A) and a joint decoder.
• Employ an echoed conditional-displacement (ECD) gate as a hardware-native primitive in layered VQC architectures.
• Include an optional adaptive module to perform measurement-based feedforward, enabling adaptive transduction.
• Optimize input states and decoding operations under energy and resource constraints to maximize coherent information.
• Compare VQT to baseline protocols: intraband entanglement-assisted (EA) with two-mode squeezing, GKP environment-assisted schemes, and adaptive Gaussian transduction.

Experimental results

Research questions

• RQ1 Can VQT identify transduction protocols that maximize coherent information under fixed energy and resource constraints?
• RQ2 How do non-adaptive and adaptive transduction protocols compare under VQT optimization?
• RQ3 What roles do non-Gaussianity and entanglement play across transmissivity regimes in non-adaptive transduction?
• RQ4 Is Gaussian adaptive transduction near-optimal once feedforward is available?
• RQ5 How do VQT-optimized inputs evolve with transmissivity η (e.g., GKP-like at low η, Gaussian at high η)?

Key findings

• Fully variational entanglement-assisted non-adaptive transduction yields the highest coherent information across η.
• Optimal non-adaptive inputs transition from GKP-like at low η to Gaussian as η increases, with entanglement mainly helpful at higher η.
• Adaptive VQT provides only a modest improvement over Gaussian adaptive strategies, indicating Gaussian adaptivity is near-optimal.
• In adaptive settings, the optimized inputs become squeezed-thermal in S and squeezed-vacuum in P, with no detectable entanglement or non-Gaussianity in PA.
• VQT without EA approaches the QT channel capacity for η > ~0.6, showing limited added value from ancilla in high-transmissivity regimes.
• Overall, VQT outperforms baseline non-adaptive protocols and offers a systematic path toward optimal quantum transduction.