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Universal language model with the intervention of quantum theory

D. -F. Qin

TL;DR

The paper proposes a quantum-inspired framework for natural language, modeling linguistic elements as density-matrix quantum states in a semantic Hilbert space to capture symbol-meaning duality and context. It formalizes semantic representation via density matrices, introduces the concept of a common semantic substrate, and uses Von Neumann entropy and infonergy to study linguistic evolution and information dynamics. Empirical evaluation compares quantum-density embeddings to classical vectors, showing feasible performance and clearer interpretability of polysemy, while outlining two paths to a Universal Quantum Language Model: purely quantum-format representations and hybrid quantum-classical encoders. The work aims to ground NLP in quantum theory, offering theoretical explanations for word embeddings and proposing potential quantum-computing applications, including Q-drive memories and circuit-based implementations. Overall, it lays a groundwork for quantum-statistical linguistics with implications for both theory and future quantum-enhanced NLP systems.

Abstract

This paper examines language modeling based on the theory of quantum mechanics. It focuses on the introduction of quantum mechanics into the symbol-meaning pairs of language in order to build a representation model of natural language. At the same time, it is realized that word embedding, which is widely used as a basic technique for statistical language modeling, can be explained and improved by the mathematical framework of quantum mechanics. On this basis, this paper continues to try to use quantum statistics and other related theories to study the mathematical representation, natural evolution and statistical properties of natural language. It is also assumed that the source of such quantum properties is the physicality of information. The feasibility of using quantum theory to model natural language is pointed out through the construction of a experimental code. The paper discusses, in terms of applications, the possible help of the theory in constructing generative models that are popular nowadays. A preliminary discussion of future applications of the theory to quantum computers is also presented.

Universal language model with the intervention of quantum theory

TL;DR

The paper proposes a quantum-inspired framework for natural language, modeling linguistic elements as density-matrix quantum states in a semantic Hilbert space to capture symbol-meaning duality and context. It formalizes semantic representation via density matrices, introduces the concept of a common semantic substrate, and uses Von Neumann entropy and infonergy to study linguistic evolution and information dynamics. Empirical evaluation compares quantum-density embeddings to classical vectors, showing feasible performance and clearer interpretability of polysemy, while outlining two paths to a Universal Quantum Language Model: purely quantum-format representations and hybrid quantum-classical encoders. The work aims to ground NLP in quantum theory, offering theoretical explanations for word embeddings and proposing potential quantum-computing applications, including Q-drive memories and circuit-based implementations. Overall, it lays a groundwork for quantum-statistical linguistics with implications for both theory and future quantum-enhanced NLP systems.

Abstract

This paper examines language modeling based on the theory of quantum mechanics. It focuses on the introduction of quantum mechanics into the symbol-meaning pairs of language in order to build a representation model of natural language. At the same time, it is realized that word embedding, which is widely used as a basic technique for statistical language modeling, can be explained and improved by the mathematical framework of quantum mechanics. On this basis, this paper continues to try to use quantum statistics and other related theories to study the mathematical representation, natural evolution and statistical properties of natural language. It is also assumed that the source of such quantum properties is the physicality of information. The feasibility of using quantum theory to model natural language is pointed out through the construction of a experimental code. The paper discusses, in terms of applications, the possible help of the theory in constructing generative models that are popular nowadays. A preliminary discussion of future applications of the theory to quantum computers is also presented.
Paper Structure (25 sections, 12 equations, 5 figures, 3 tables)

This paper contains 25 sections, 12 equations, 5 figures, 3 tables.

Table of Contents

  1. I.Introduction
  2. II.Related Work
  3. 2.1 Mainstream Approaches to NLP
  4. 2.2 An Attempt on QLM
  5. III.Intervention of Quantum Theory
  6. 3.1 Quantum Language Model
  7. 3.2 Semantic Representation
  8. 3.2.1 Basic Example
  9. 3.2.2 Common Semantic Substrate
  10. 3.2.3 Advantages of Quantum State Embedding
  11. IV.INTERACTION OF LINGUISTIC ELEMENTS
  12. 4.1 Structured linguistic Elements
  13. 4.1.1 Linguistic Composition
  14. 4.1.2 Linguistic Context
  15. 4.1.3 Numerical Approximation of Composition
  16. ...and 10 more sections

Figures (5)

  • Figure 1: NLP development lineage
  • Figure 2: Example4-1
  • Figure 3: Example4-2
  • Figure 4: V.N Entropy of Histories of Various Dynasties
  • Figure 5: Quantum circuits for encoding triqubit density matrix