Grover's Algorithm for Question Answering

TL;DR

This paper adapts Grover's quantum search algorithm to natural language question answering by representing words as quantum states and constructing a superposition of possible answers, enabling efficient search for correct answers.

Contribution

It introduces a quantum NLP framework that uses tensor contractions and superpositions to represent text and questions, applying Grover's algorithm for answer search.

Findings

Quantum superposition captures multiple meanings of ambiguous phrases.

The framework constructs an oracle for correct answer detection.

Potential quadratic speedup in quantum question answering processes.

Abstract

Grover's algorithm, a well-know quantum search algorithm, allows one to find the correct item in a database, with quadratic speedup. In this paper we adapt Grover's algorithm to the problem of finding a correct answer to a natural language question in English, thus contributing to the growing field of Quantum Natural Language Processing. Using a grammar that can be interpreted as tensor contractions, each word is represented as a quantum state that serves as input to the quantum circuit. We here introduce a quantum measurement to contract the representations of words, resulting in the representation of larger text fragments. Using this framework, a representation for the question is found that contains all the possible answers in equal quantum superposition, and allows for the building of an oracle that can detect a correct answer, being agnostic to the specific question. Furthermore, we show that our construction can deal with certain types of ambiguous phrases by keeping the various different meanings in quantum superposition.