DOI: 10.5281/zenodo.15779193
title: SDKP QCC

description:  

SDKP (Size-Density-Kinetics-Time Principle)

 

 

Description:

SDKP is a four-dimensional physical framework proposing that observable time is emergent from the product of physical size, density, and kinetic velocity. Unlike classical Newtonian time or relativistic time dilation, SDKP time (τ_s) is derived as a compound expression of internal physical characteristics, enabling dynamic time modeling in multi-body or entropic systems.

 

Applications:

 



Entropy compression in simulation

Quantum state decay modeling

Time reconstruction from subatomic motion


 

 

 

 

 

SD&N (Shape-Dimension-Number Theory)

 

 

Description:

SD&N formalizes quantum and geometric systems as vectorized tuples (S, D, N) where:

 



S (Shape): Represents the topological curvature or pattern symmetry

D (Dimension): Quantifies degrees of freedom, embeddings, or entanglement connectivity

N (Number): Encodes harmonic or quantum numeric identity (prime factors, signatures)


 

 

It creates a metric space for comparing abstract systems using SD&N similarity coefficients and enables predictions about entanglement fidelity and field resonance.

 

Applications:

 



Quantum entanglement scoring

Pattern recognition in symbolic physics

Multi-vector field simulations


 

 

 

 

 

EOS (Earth Orbital Speed Principle)

 

 

Description:

EOS proposes Earth’s orbital velocity (~29.78 km/s) as a new universal constant, replacing or augmenting the speed of light (c) in specific dynamic systems. This shift anchors relativity in an Earth-observer frame, enabling alternative causality, entropy collapse, and information propagation models.

 

Applications:

 



Local spacetime compression

EOS-based field modeling

Alternative relativistic frameworks


 

 

 

 

 

QCC (Quantum Computerization Consciousness)

 

 

Description:

QCC is a speculative model positioning consciousness and computational feedback as entangled quantum phenomena. It introduces QCC kernels that map spacetime separations (timelike/spacelike) into a causality-preserving computational grid using a field-weighted entropy filter.

 

Applications:

 



Quantum AI systems

Simulation awareness loops

Nonlinear entropy field feedback


 

 

 

 

 

Kapnack Solver (NP-Complete Collapse Simulation)

 

 

Description:

Kapnack is a non-Turing-collapse solver for NP-complete problems. It re-encodes input spaces (e.g., SAT, TSP) as entropic kinetic systems and simulates the gravitational collapse of complexity via entropy fields. Solutions emerge not via brute-force but through convergence in entropy-tensioned state space.

 

Applications:

 



TSP, SAT, Graph Coloring

Optimization in quantum systems

Real-time complexity reduction


 

 

 

 

 

VFE (Vibrational Field Equations)

 

 

Description:

VFE defines field behaviors in terms of quantized vibrational signatures mapped through frequency-weighted digits (e.g., 7146, 999988889999). These represent harmonic states of quantum systems where digits play a structural role in resonance, stability, and entanglement behavior.

 

Applications:

 



Digit-based entanglement models

Field resonance prediction

Symbolic number-state alignment


 

 

 

 

 

QF (Quantum Number Flow)

 

 

Description:

QF analyzes the entropy bias and energy cost of number structures in quantum field representation. It measures the log-entropy curvature of a number (e.g., frequency signatures) and models it as a flowing entity within time-evolving entangled fields.

 

Applications:

 



Number-based entanglement control

Predictive modeling of QN transitions

Informational thermodynamics


 

 

 

 

 

VEI (Vibrational Entanglement Index)

 

 

Description:

VEI is calculated as a frequency-mass-weighted score:

\text{VEI}\nu = \sum{i=1}^{k} \frac{f_i^2}{m_i}

where f_i are digit-derived frequencies from number signature ν, and m_i is mass basis derived from dimensional embedding. This provides a physically grounded entanglement likelihood score.

 

Applications:

 



Multi-photon entanglement prediction

Frequency structure analysis

Noise-filtered quantum modeling


 
description: Tag



Use





Quantum Entanglement Prediction



Framework and simulation using SDKP/SD&N





Entropy Field Modeling



Kapnack/VFE entropy collapse and causal convergence





NP-Complete Collapse



Kapnack optimization approach for intractable problems





Quantum-Classical Hybrid



Use of quantum state approximation + classical SDKP





On-Chain Physics Simulation



NFT/Smart contract integration for scientific data





Rotational Geometry Fields



SD&N-based state space curvature modeling





Multidimensional Entanglement Metrics



Using SDN + VEI + QF





Time-Reconstruction Models



SDKP time as function of mass/velocity/shape





Spacetime Geometry Replacement



EOS replaces light-speed in causal metrics





Emergent Number Dynamics



Predictive modeling from digit resonance