The origin of quantum mechanical statistics: some insights from research on human language

Identical systems, or 'entities', are 'indistinguishable' in quantum mechanics (QM), and the 'symmetrization postulate' rules the possible statistical distributions of a large number of identical quantum entities. However, a thorough analysis of the historical development of QM attributes the origin of quantum statistics, in particular, 'Bose-Einstein statistics', to a lack of statistical independence of the micro-states of identical quantum entities. We have recently identified Bose-Einstein statistics in the combination of words in large texts, as a consequence of the 'entanglement' created by the meaning carried by words when they combine in human language. Relying on this investigation, we put forward the hypothesis that entanglement, hence the lack of statistical independence, is due to a 'mechanism of contextual updating', which provides deeper reasons for the appearance of Bose-Einstein statistics in human language. However, this investigation also contributes to a better understanding of the origin of quantum mechanical statistics in physics. Finally, we provide new insights into the 'intrinsically random behaviour of microscopic entities' that is generally assumed within classical statistical mechanics.This article is part of the theme issue 'Newton, <i>Principia</i>, Newton Geneva Edition (17th-19th) and modern Newtonian mechanics: heritage, past & present'.

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Journal
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Published
2025-12-18
DOI
https://doi.org/10.1098/rsta.2023.0285
Primary Topic
Advanced Text Analysis Techniques
Type
article
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article

The origin of quantum mechanical statistics: some insights from research on human language

Jonito Aerts Arguëlles, Diederik Aerts, Massimiliano Sassoli de Bianchi, Sandro Sozzo et al.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
Advanced Text Analysis Techniques
article

The origin of quantum mechanical statistics: some insights from research on human language

Jonito Aerts Arguëlles, Diederik Aerts, Massimiliano Sassoli de Bianchi, Sandro Sozzo, Lester Beltran
article en

Abstract

Identical systems, or 'entities', are 'indistinguishable' in quantum mechanics (QM), and the 'symmetrization postulate' rules the possible statistical distributions of a large number of identical quantum entities. However, a thorough analysis of the historical development of QM attributes the origin of quantum statistics, in particular, 'Bose-Einstein statistics', to a lack of statistical independence of the micro-states of identical quantum entities. We have recently identified Bose-Einstein statistics in the combination of words in large texts, as a consequence of the 'entanglement' created by the meaning carried by words when they combine in human language. Relying on this investigation, we put forward the hypothesis that entanglement, hence the lack of statistical independence, is due to a 'mechanism of contextual updating', which provides deeper reasons for the appearance of Bose-Einstein statistics in human language. However, this investigation also contributes to a better understanding of the origin of quantum mechanical statistics in physics. Finally, we provide new insights into the 'intrinsically random behaviour of microscopic entities' that is generally assumed within classical statistical mechanics.This article is part of the theme issue 'Newton, <i>Principia</i>, Newton Geneva Edition (17th-19th) and modern Newtonian mechanics: heritage, past & present'.

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesVol. 383(2311)
University of Udine (IT), Vrije Universiteit Brussel (BE)
Openalex Percentile: Top 91%
Advanced Text Analysis Techniques
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The origin of quantum mechanical statistics: some insights from research on human language — Jonito Aerts Arguëlles, Diederik Aerts, et al. · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2025) | TGRS Research Map | TGRS