article · Zenodo (CERN European Organization for Nuclear Research) · 2026
Is Randomness an Ontological Constant or a Persistent Observational Error?
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Abstract
While the current cryptographic landscape relies on ’Certified Randomness’ as an absolute safeguard, this paper argues that such entropy is merely an illusion born of dimensional blindness. We present Structural Unification Theory (SUT), which moves beyond the probabilistic models of the last decade to reveal a deterministic universe. By applying the Master Identity i = c +γ, we demonstrate that so-called ’Quantum Noise’ is the measurable high frequency vibration of a 26-dimensional rigid manifold. Anchored by a −1/12 substrate, this manifold suggests that what we perceive as ’randomity’ is actually a high-order geometric signal that is fully predictable within a unified framework.
Cite this paper
AHMAD, W. A. W. (2026). Is Randomness an Ontological Constant or a Persistent Observational Error? Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18252887
AHMAD, WAN AZHAR WAN. “Is Randomness an Ontological Constant or a Persistent Observational Error?” Zenodo (CERN European Organization for Nuclear Research), 2026, https://doi.org/10.5281/zenodo.18252887.
AHMAD, WAN AZHAR WAN. 2026. “Is Randomness an Ontological Constant or a Persistent Observational Error?” Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.18252887.
AHMAD, W.A.W. (2026) ‘Is Randomness an Ontological Constant or a Persistent Observational Error?’, Zenodo (CERN European Organization for Nuclear Research). Available at: https://doi.org/10.5281/zenodo.18252887.
@article{ahmad2026randomness,
title = {{Is Randomness an Ontological Constant or a Persistent Observational Error?}},
author = {AHMAD, WAN AZHAR WAN},
journal = {Zenodo (CERN European Organization for Nuclear Research)},
year = {2026},
doi = {10.5281/zenodo.18252887}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.