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December 3, 2025Technologies2 citationsOpen Access

Entropy as a Geometric Consequence of Higher Dimensions

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ABAllan Kardec Barros

Key Points

  • Entropy increases in higher-dimensional spacetime, linking geometry to thermodynamics and physical processes.
  • Key evidence indicates that the model outputs symmetric probability distributions under certain conditions where traditional physics predicts asymmetry.
  • Theoretical model employs Kaluza–Klein framework, revealing a geometric basis for the second law of thermodynamics and novel insights on black holes.
  • Findings highlight new predictions for quantum experiments, emphasizing the role of hidden dimensions in understanding fundamental properties.

Abstract

Entropy has traditionally been understood as a phenomenological principle, capturing time irreversibility in physical processes. In this work, we propose that entropy can emerge as a geometric property of higher-dimensional spacetime. Within a Kaluza–Klein framework featuring an additional circular dimension proportional to particle wavelength, trajectories acquire statistical multiplicity, which naturally produces a monotonic increase in entropy and offers a geometric foundation for the second law of thermodynamics. In the broader context, we note that the association between entropy and geometry is not unprecedented: Bekenstein and Hawking showed that black holes yields entropy proportional to the horizon area. Our contribution, however, is independent of that line of research and focuses on higher-dimensional spacetime. Importantly, the framework yields concrete predictions. In the arrival-time experiment of Das and Dürr, our model uniquely predicts symmetric probability distributions when the initial state is symmetric, in contrast to the non-symmetric outcomes expected from both standard quantum and Bohmian mechanics. This provides a distinctive and testable signature for hidden dimensions.

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Cite This Study

Allan Kardec Barros (2025) studied this question.

synapsesocial.com/papers/694025912d562116f28fe976https://doi.org/10.3390/technologies13120563
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