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February 23, 20260 citationsOpen Access

The Metric and Fundamental Dimensions of Order

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QGQilin Guo

Key Points

  • To define the dimensional structure of order in Order Mechanics and its physical implications.
  • Specified the physical realization of the order equation's core parameter—generalized uncertainty.
  • Derived the fundamental dimensional structure of order utilizing positional uncertainty.
  • Performed dimensional analysis to establish a coherent framework for quantifying order.
  • Identified order density as having the dimension of a volume density.
  • Established that integrated total order becomes dimensionless.
  • Provided a quantitative foundation for Order Mechanics aligned with physical theories.

Abstract

Order Mechanics (OM) introduces a dynamical framework in which order functions as a fundamental state variable. System evolution is governed by the competition between causal forces, which promote structural aggregation, and entropic forces, which drive structural dispersal 【1,2】. While prior work established a conceptual formulation of order, its fundamental dimensional structure has remained unspecified, limiting formal correspondence with established physical theories. This work proceeds in two steps. We first specify the explicit physical realization of the core parameter in the order equation—the generalized uncertainty . We then derive the fundamental dimensional structure of order. We show that once microscopic uncertainty is concretized as positional uncertainty Δx 【3】, order density acquires, in a natural and internally consistent manner, the dimension of a volume density. Consequently, the integrated total order becomes dimensionless. This dimensional closure establishes a coherent quantitative foundation for the formal development of Order Mechanics. Keywords: Order Mechanics, Generalized Uncertainty, Dimensional Analysis, Order Density, Geometric Curvature, Dimensionless Order Parameter, Uncertainty principle, Quantum mechanics, Particle physics, Entropy.

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Cite This Study

Qilin Guo (2026) studied this question.

synapsesocial.com/papers/699ba08472792ae9fd8702eahttps://doi.org/10.5281/zenodo.18723821
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