Analysis of Ansatze Expressibility and Complexity and Their Impact on Classification Accuracy Using QNN and QLSTM Article

Tripathi, Sarvapriya M, Upadhyay, Himanshu, Soni, Jayesh. (2025). Analysis of Ansatze Expressibility and Complexity and Their Impact on Classification Accuracy Using QNN and QLSTM . IEEE ACCESS, 13 152412-152429. 10.1109/ACCESS.2025.3604721

Open Access

cited authors

  • Tripathi, Sarvapriya M; Upadhyay, Himanshu; Soni, Jayesh

authors

publication date

  • January 1, 2025

published in

keywords

  • Accuracy
  • Ans & auml;tz
  • Complexity theory
  • Computational modeling
  • Computer Science
  • Computer Science, Information Systems
  • Cost function
  • Engineering
  • Engineering, Electrical & Electronic
  • Integrated circuit modeling
  • Logic gates
  • Quantum circuit
  • Quantum entanglement
  • Quantum state
  • Qubit
  • Science & Technology
  • Technology
  • Telecommunications
  • deep learning
  • expressibility
  • machine learning
  • parameterized quantum circuit (PQC)
  • quantum LSTM (QLSTM)
  • quantum machine learning (QML)
  • quantum neural networks (QNN)

Digital Object Identifier (DOI)

publisher

  • IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

start page

  • 152412

end page

  • 152429

volume

  • 13