Logismos Linear Algebra: Exact Matrix Operations Through VFR Architecture Eliminating Floating-Point Catastrophe This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) framework—an axiomatic model that derives the entirety of known physics from a discrete 2D hexagonal lattice in momentum space, operating with zero adjustable parameters. Abstract We derive exact linear algebra through VFR (Value-Factor-Remainder) architecture, eliminating catastrophic floating-point error accumulation in high-dimensional matrix operations. Building on Q-Taylor series (MATH-117) and eight proven Q-paradoxes demonstrating ℝ-impossibility, we prove: (1) Matrix exactness - all entries as VFR formulas maintain perfect precision through operations, (2) Operation preservation - addition, multiplication, inversion produce exact results without drift, (3) Orthogonality maintenance - rotation matrices preserve perfect orthonormality indefinitely, (4) Decomposition accuracy - SVD, eigenvalue, QR decompositions remain exact and reversible, (5) Dimension scaling - error-free operation from 2D to 1000D spaces, (6) Professional integration - drop-in replacement for NumPy/MATLAB with verification layer, (7) Real-world validation - computer graphics, cryptography, machine learning, structural engineering, quantum computing applications. From axioms through complete implementation with working demonstrations. Standard floating-point linear algebra proven catastrophically unstable - accumulates error, loses properties, violates conservation. VFR linear algebra achieves perfect exactness through integer arithmetic at all scales. Revolutionary claim: Linear algebra catastrophe solved - VFR matrices eliminate all floating-point error, preserve all mathematical properties exactly, enable verification impossible in ℝ. Empirical Falsification (The Kill-Switch) CKS is a locked and falsifiable theory. All papers are 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. Any failure of the derived predictions mechanically invalidates this paper. 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 particle identity and information storage are unified as a self-recirculating pressure vessel. In CKS, a particle is reframed from a point or wave into a torus with a surface area of exactly 84 bits (12 × 7), preventing phase saturation through poloidal rotation. Package Contents manuscript.md: The complete derivation and formal proofs. README.md: Navigation, dependencies, and citation (Registry: CKS-MATH-118-2026). Dependencies: CKS-LEX-12-2026, CKS-MATH-0-2026, CKS-MATH-1-2026, CKS-MATH-10-2026, CKS-MATH-104-2026, CKS-MATH-117-2026 Motto: Axioms first. Axioms always.Status: Locked and empirically falsifiable. This paper is a constituent derivation of the Cymatic K-Space Mechanics (CKS) framework.