Parametrized Quantum Circuits of Synonymous Sentences in Quantum Natural Language Processing
Mina Abbaszadeh, S. Shahin Mousavi, Vahid Salari
TL;DR
This paper develops a quantum natural language processing approach for Persian, translating sentence semantics into quantum circuits using DisCoCat diagrams and ZX-calculus, enabling comparison of synonymous sentences across English and Persian.
Contribution
It introduces a novel method for representing and comparing the semantics of transitive sentences in Persian and English using parametrized quantum circuits and diagrammatic calculus.
Findings
Successful translation of sentence semantics into quantum circuits
Comparison of synonymous sentences across languages using quantum models
Application of ZX-calculus to linguistic diagram rewriting
Abstract
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.
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Computational Physics and Python Applications · Neural Networks and Applications