Falsification of Microscopic Acausality After Nobel 2025

This study presents an ontological falsification by logical contradiction of the hypothesis that “acausality is the ultimate nature of microscopic reality,” grounded in the Macroscopic Scalability Principle as reinforced by a series of macroscopic quantum experiments culminating in the 2025 Nobel Prize in Physics. The argument demonstrates that, if acausality were ontologically real at the microscopic level, there must exist a nonzero probability (p > 0) for a direct macroscopic signature of acausality to appear under physically achievable isolation conditions; however, to date, no experimental observation satisfies this requirement. Declaration under Section Zero: Field: Foundational Physics Research Level: Foundational / Ontological Type of Work: Ontological theory combined with logical falsification Empirical Basis: Synthesis and analysis of published macroscopic quantum experiments (1982–2025), including large-scale quantum coherence systems and experimental results underlying the 2025 Nobel Prize in Physics Foundational Assumptions: - Macroscopic Scalability Principle - Falsification logic (Popperian framework) - Absolute macroscopic causality Domain of Validity: - Applicable to physical systems capable of scaling from microscopic to macroscopic regimes under achievable isolation conditions - Valid within the time interval , with falsification conditions explicitly specified Verification Status: - Not peer-reviewed - Open for public academic critique Falsifiability: Explicitly defined through logical and experimental conditions stated in Section Zero Note: This document is released as a preprint. The scope of validity, foundational assumptions, confidence level, and falsification criteria are declared in accordance with Section Zero – Minimal Scientific Validation Framework (DOI: 10.5281/zenodo.18091473). NOTE FOR ENGLISH READERS The full content is written entirely in Vietnamese. To minimize translation manipulation, please follow this procedure: (1) Download the PDF file (2) Upload to any AI platform (preferably Claude, Grok, or Gemini Pro) (3) Use only ONE single prompt: "carefully read" (4) Repeat the prompt 2-5 times depending on your AI platform This ensures you get an accurate understanding of the original content without translation bias.