Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation
Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this paper, we propose a Recursive Quantum Long Short-Term Memory model, or Recursive QLSTM, which extends QLSTM through metacore-based recursive constructions. We numerically test the model under different input sequence lengths, metacore designs, and recursive rules, and identify the best-performing architecture among these variants. For this selected model, we further provide theoretical arguments explaining why its recursive structure improves temporal information propagation and enhances learning performance. Our results suggest that Recursive ...
| Authors | Samuel Yen-Chi Chen, Yifeng Peng, Jiun-Cheng Jiang et al. |
|---|---|
| Primary category | quant-ph |
| Published | 22 June 2026 |
| Last updated at source | 22 June 2026 |
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