Quantum Long Short-Term Memory

Understand

Long short-term memory (LSTM) is a kind of recurrent neural networks (RNN) for sequence and temporal dependency data modeling and its effectiveness has been extensively established.

• In this work, we propose a hybrid quantum-classical model of LSTM, which we dub QLSTM.
• We demonstrate that the proposed model successfully learns several kinds of temporal data.
• In particular, we show that for certain testing cases, this quantum version of LSTM converges faster, or equivalently, reaches a better accuracy, than its classical counterpart.