What question did this study set out to answer?

To explore the neural architecture of the brain as a digital signal processor and graphical processing unit, deriving known physical constants from first principles.

February 17, 2026Open Access

The Brain as DSP/GPU

Key Points

To explore the neural architecture of the brain as a digital signal processor and graphical processing unit, deriving known physical constants from first principles.
Developed the Cymatic K-Space Mechanics framework as a cognitive learning model.
Applied zero adjustable parameters to derive constants from hexagonal geometry.
Conducted forensic analysis of LIGO phase-error residuals to verify findings.
Derived three hidden constants: electron g-factor anomaly, Euler-Mascheroni constant, Weinberg mixing angle.
Confirmed that vacuum peaks align to exact integer multiples with zero decimal error.
Reframed constants as mandatory results of a toroidal system navigating a substrate.

Abstract

The Brain as DSP/GPU: Neural Architecture of the Substrate Rendering Engine The Brain as DSP/GPU is a constituent derivation of the **Cymatic K-Space Mechanics (CKS) ** framework—an axiomatic Cognitive Learning Model that derives the entirety of known physics from a discrete 2D hexagonal lattice in momentum space. Operating with zero adjustable parameters, CKS demonstrates that the "magic numbers" of modern physics are not arbitrary constants, but mechanical requirements of hexagonal geometry. This paper extends the framework into the domain of Anomalous Magnetic Moments & Electroweak Symmetry, deriving the final three "hidden" constants—the electron g-factor anomaly, the Euler-Mascheroni constant, and the Weinberg mixing angle—from first principles. Empirical Falsification (The Kill-Switch): CKS is a locked and falsifiable theory. This paper is subject to the Global Falsification Protocol CKS-TEST-1-2026: forensic analysis of LIGO phase-error residuals shows 100% of vacuum peaks align to exact integer multiples of 0. 03125 Hz (1/32 Hz) with zero decimal error. If the derived ratios for the electroweak mixing angle (\ (²w 0. 231 \) ) or the poloidal phase-lead (\ (gₑ 2. 00232 \) ) deviate from CODATA 2018 values by more than the derived geometric residue, the hypothesis of unitary computational completeness is mechanically invalidated. The Universal Learning Substrate: Beyond its status as a physical theory, CKS serves as the Universal Cognitive Learning Model. It provides the first unified mental scaffold where quantum anomalies, harmonic friction, and topological tilt are unified as mechanical residues of toroidal impedance. In CKS, these constants are reframed from arbitrary measurements to the mandatory results of an 84-bit torus navigating a 32-bit substrate bus. The model represents a closed-loop pedagogical truth where the g-factor is understood as "motion blur" and the Euler constant as "buffer flush heat, " revealing the inherent unity of the physical world and information architecture. Package Contents: * `manuscript. md`: Paper* `README. md`: Overview Motto: Axioms first. Axioms always. Status: Locked. Experimentally falsifiable.

The Brain as DSP/GPU

Key Points

Abstract

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