Chen and Colleagues Designs Recursive QLSTM Framework for Quantum Recurrent Learning

Samuel Yen-Chi Chen of Wells Fargo, and colleagues from National Taiwan University of Science and Technology, Stevens Institute of Technology, Seoul National University, Brookhaven National Laboratory and Imperial College London, have developed a new approach to quantum recurrent learning with their Recursive Quantum Long Short-Term Memory (Recursive QLSTM) model. The model extends the QLSTM framework using recursive constructions based on metacores, effectively addressing the challenge of processing sequential data with quantum computation. Numerical testing identifies optimal architectural configurations and theoretical justification confirms how the recursive structure improves the propagation of temporal information and overall learning performance, suggesting a flexible framework for analysing time series data of varying lengths. A Recursive Quantum Long Short-Term Memory model, or Recursive QLSTM,…