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May 17, 20260 citationsOpen Access

Phase Summary and Engineering Application Conjectures Based on Status-Relational Entropy (SRE) Dynamics

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YLYue Lu

Key Points

  • The study aims to reveal that physical constants are emergent properties rather than fixed values and explore implications for engineering.
  • Examines the theoretical implications of universal constants derived from causal-chain networks.
  • Analyzes empirical applications in semiconductor transistors, biological ion channels, and topological insulators.
  • Discusses the role of macro-observational statistics in engineering design and implementation.
  • Physical constants, rather than being fixed, are influenced by larger causal factors and emergent properties.
  • Successful engineering requires integration of macro-observational statistics with underlying principles of physical systems.
  • Specific topologies can exploit causal-chain mechanisms to extend beyond conventional limits in engineering applications.

Abstract

Core Concept:This study demonstrates that fundamental physical constants (such as fine-structure constant and G) are not hard-coded base parameters, but evolutionary macroscopic rigidities emergent from global causal-chain networks. Expecting to precisely deduce universal constants locally through structural mathematical formulas is logically impossible, as scaling limits always induce mathematical truncation and distortion. Engineering Implementation:Genuine underlying principles cannot be comprehensively applied to practical engineering once decoupled from real-world empirical inputs. Humanity must rely on macro-observational statistics to execute localized probability-domain hedging. In specific isomorphic topologies—such as semiconductor transistors, biological membrane ion channels, and topological insulator edge states—we can utilize endogenous causal-chain strain mechanisms to actively break through the parameters and limits constraints manifested by large-number statistical convergence.

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Cite This Study

Yue Lu (2026) studied this question.

synapsesocial.com/papers/6a095c2c7880e6d24efe233ahttps://doi.org/10.5281/zenodo.20204412
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