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February 26, 20260 citationsOpen Access

From Protons to Planets: Deconstructing the Stochastic Illusion through Scalar Determinism

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SGShantanu S. Goel

Key Points

  • The aim is to challenge the idea that randomness is a fundamental property of nature by introducing deterministic principles.
  • Introduced the Causal Vacuum Postulate to define true stochastic events.
  • Synthesized evidence from Large Hadron Collider data, evolutionary biology, and algorithmic information theory.
  • Analyzed the implications of randomness on artificial intelligence and economic dynamics.
  • Argued that true randomness is physically prohibited by universal fields.
  • Proposed scalar inheritance as a key principle linking subatomic behavior to macroscopic outcomes.
  • Demonstrated that probabilistic approaches may obscure causal relationships in complex systems.

Abstract

The prevailing ontological framework of contemporary science posits "randomness" as a fundamental, irreducible property of the physical universe. This paper challenges that assumption, contending that randomness is an epistemic placeholder—a linguistic and mathematical heuristic for unresolved causal complexity. I introduce the Causal Vacuum Postulate, asserting that for an event to be truly stochastic (ontically random), it must occur in a state of absolute suspension from all universal fields—a state physically prohibited by the ubiquity of the Higgs, Gravitational, and Zero-Point fields. By synthesizing evidence from the Large Hadron Collider (LHC), Evolutionary Biology, and Algorithmic Information Theory, I argue for the Principle of Scalar Inheritance: the mechanism by which deterministic subatomic laws scale up to dictate macroscopic outcomes in complex systems. Finally, I argue that ontological randomness raises conceptual difficulties when examined under causal closure—a state that is unavoidable within the manifest universe. Furthermore, I apply this framework to the epistemology of artificial intelligence and macroeconomic market dynamics, illustrating how probabilistic smoothing destroys causal data. Finally, I address the biological paradox of measurement independence, arguing that human cognition itself is deterministically channelled by evolutionary constraints.

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Cite This Study

Shantanu S. Goel (2026) studied this question.

synapsesocial.com/papers/699fe33695ddcd3a253e6e1dhttps://doi.org/10.5281/zenodo.18757307
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