Parametrized Quantum Circuits of Synonymous Sentences in Quantum Natural Language Processing
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Abstract (arXiv)
In this paper, we develop a compositional vector-based semantics of positive transitive sentences in quantum natural language processing for a non-English language, i.e. Persian, to compare the parametrized quantum circuits of two synonymous sentences in two languages, English and Persian. By considering grammar+meaning of a transitive sentence, we translate DisCoCat diagram via ZX-calculus into quantum circuit form. Also, we use a bigraph method to rewrite DisCoCat diagram and turn into quantum circuit in the semantic side.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 6 of its 15 references that are in the map. First posted on arXiv 2 Feb 2021.
Builds on
6 of 15 references.
References · 6
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2020Foundations for Near-Term Quantum Natural Language Processingcited by 51
- 2020Quantum Natural Language Processing on Near-Term Quantum Computerscited by 39
- 2014The Frobenius anatomy of word meanings I: subject and object relative pronounscited by 24
- 2020A hybrid classical-quantum workflow for natural language processingcited by 7
- 2018Applying Distributional Compositional Categorical Models of Meaning to Language Translationcited by 1
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Citing papers per year: 2022: 1; 2023: 1.
2 papers.