Quantum natural language processing

Quantum natural language processing (QNLP) is the application of quantum computing to natural language processing (NLP). It computes word embeddings as parameterised quantum circuits that can solve NLP tasks faster than any classical computer.[1][2][3] It is inspired by categorical quantum mechanics and the DisCoCat framework, making use of string diagrams to translate from grammatical structure to quantum processes.[4][5][6]

  1. ^ Cite error: The named reference :0 was invoked but never defined (see the help page).
  2. ^ Cite error: The named reference :2 was invoked but never defined (see the help page).
  3. ^ Rai, Anshuman (2022-01-31). "A Review Article on Quantum Natural Language Processing". International Journal for Research in Applied Science and Engineering Technology. 10 (1): 1588–1594. doi:10.22214/ijraset.2022.40103. ISSN 2321-9653.
  4. ^ Rai, Anshuman (2022-01-31). "A Review Article on Quantum Natural Language Processing". International Journal for Research in Applied Science and Engineering Technology. 10 (1): 1588–1594. doi:10.22214/ijraset.2022.40103. ISSN 2321-9653.
  5. ^ Coecke, Bob; de Felice, Giovanni; Meichanetzidis, Konstantinos; Toumi, Alexis (2020-12-07). "Foundations for Near-Term Quantum Natural Language Processing". arXiv:2012.03755 [quant-ph].
  6. ^ Ganguly, Srinjoy; Morapakula, Sai Nandan; Bertel, Luis Gerardo Ayala, "An Introduction to Quantum Natural Language Processing (QNLP)", Coded Leadership, CRC Press, pp. 1–23, retrieved 2022-11-11