Submitted:
23 April 2025
Posted:
24 April 2025
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Abstract
Keywords:
1. Introduction
2. Theoretical and Ontological Foundations
2.1. The Orange as an Experimental Spheroidal Model
2.2. Vector Emergence and the Postulate of Dimensional Existence
2.3. Dimensional Structure Ontology
2.4. Experimental and Symbolic Implications
3. Mathematical Structure of the Mesh
3.1. Three-Dimensional Local Vector
3.2. Angular Thermal Modulation Function
- α\alphaα is the coefficient of angular expansion,
- ΔT\Delta TΔT is the local thermal variation of the cell.
3.3. Modulated Vector
3.4. Weighted Dimensional Result Vector
3.5. Dimensional Existence Criterion
3.6. Summary of Key Parameters

4. Computer Simulation and Results
4.1. Structure of the Simulation
- 3D spheroidal mesh with subdivision into up to 60 cells;
- Local three-dimensional vectors, oriented as a function of spherical coordinates (x,y,z)(x, y, z)(x,y,z);
- Thermal parameter ΔT with pseudo-random variation between 1K and 6K per cell;
- Coefficient of thermal expansion α=0.015\alpha = 0{,}015α=0.015;
- Vector weights εn\varepsilon_nεn ranging from -1.1 to -0.7;
- Constant angular frequency ω=1\omega = 1ω=1 to check the dimensional criterion.
4.2. Vector Processing
- Calculation of the angular thermal function:
- 2.
- Local vector modulation:
- 3.
- Resonant weighting:
- 4.
- Application of the dimensional postulate:
4.3. Graphic Visualization
- Green vectors represent valid dimensions (ω⋅εn≈-1\omega \cdot \varepsilon_n \approx -1ω⋅εn≈-1);
- Red vectors are unstable and do not generate dimensions;
- Translucent orange sphere represents the base spheroidal mesh (e.g. orange).
4.4. Simulation Results
- 30 vectors met the dimensional criterion (ω⋅εn≈-1\omega \cdot \varepsilon_n \approx -1ω⋅εn≈-1),
- The dimensional emergence index was 25%,
- The dimensions emerged distributed radially and angularly, validating the hypothesis that they are vectorial manifestations conditioned to thermal-angular stability.
4.5. Source Code Base (Summary)
4.6. Conclusions from the Simulation
5. Physical Experimental Protocol
5.1. Objective of the Experiment
5.2. Materials Required

5.3. Stages of the Experiment
-
Preparing the mesh
- ○
- Divide the spherical surface (orange or printed model) into 20 to 40 octagonal cells.
- ○
- Mark each cell with identifiers and insertion points for sensors.
-
Sensor positioning
- ○
- Insert a thermal sensor in the center of each cell.
- ○
- Connect all the sensors to the microcontroller with coordinate mapping (xi,yj,zk)(x_i, y_j, z_k)(xi,yj ,zk).
-
Controlled thermal application
- ○
- Use thermal actuators to selectively heat/cool each cell.
- ○
- Record the thermal variation ΔT\Delta TΔT in real time.
-
Local vector calculation
- ○
- Modify each vector M⃗ijk\vec{M}_{ijk}Mijk with:M′⃗ijk= M⃗ijk⋅(1+α⋅ΔT)\vec{M'}_{ijk} = \vec{M}_{ijk} \cdot (1 + \alpha \cdot \Delta T)M′ijk= Mijk⋅(1+α⋅ΔT)
- ○
- Weight with εn\varepsilon_nεn according to the cell's energy response.
-
Dimensional validation
- ○
- Apply the postulate:ω⋅εn≈-1\omega \cdot \varepsilon_n \approx -1ω⋅εn≈-1
- ○
- If true, the cell is considered an emerging dimensional zone.
-
Visualization and registration
- ○
- The system displays valid and unstable vectors on a 3D screen.
- ○
- Validated cells are highlighted with specific colors.
5.4. Verification Hypothesis
5.5. Prototype Applications
- Education: experimental teaching of dimensional physics;
- Research: reference model for vector resonance studies;
- Scientific validation: laboratory testing of theoretical concepts with measurable data;
- Engineering: development of resonant systems guided by vector geometry.
6. Comparative Analysis with Traditional Models
6.1. Comparative Table

6.2. Highlights of the Vector Mesh Compared to Classical Theories
- Direct empiricism: unlike purely theoretical models, the Octagonal Mesh can be physically assembled (e.g. prototypes with sensors in oranges or printed models).
- Interactive simulation: thermal vector modeling can be carried out in real time with accessible computer tools.
- Measurable physical criterion of dimensional existence: the postulate ω⋅ε-=-1\omega \cdot \varepsilon_- = -1ω⋅ε-=-1 offers a clear and testable condition - something unheard of in previous hyperdimensional approaches.
- Experimental and philosophical unification: connects physics, topology, epistemology and ontology in a cohesive, vector-based structure.
6.3. Impact on Contemporary Physics
- Replace continuous geometries with discrete and modular vectors;
- Offer reproducible simulations with real data;
- Eliminate the need for hidden or compressed dimensions;
- Redefine the role of vacuum as an active stabilizing element;
- Propose an emerging vector reality, sensitive to thermal, density and intentional variations.
7. Practical and Scientific Applications
7.1. What is Existence?
7.2. Time as a Vector
- A tangential vector projected by the internal vector rotation of the mesh;
- Reversible or null in vector coherence zones;
- A dynamic ontological state, not a fixed background in which events occur.
7.3. The Observer as a co-Destructive Agent
- The theory of coemergence (Karen Barad),
- The relational ontology (Rovelli),
- Structural realism (Ladyman and French).
7.4. Vacuum as Active Resistance
- A stabilizing resonant field;
- Represented by the negative resistance ε-\varepsilon-ε-, which regulates dimensional emergence;
- An active factor in maintaining reality, not a neutral scenario.
7.5. Reality as Vector Coherence
8. Practical and Scientific Applications
8.1. Teaching Dimensional Physics and Vector Topology
- Applied vector physics,
- Topology and differential geometry,
- Cosmology and epistemology of science.
8.2. Empirically Based Cosmological Simulation
- Modeling black holes as vector collapse zones;
- Simulate the Big Bang as an initial angular explosion;
- Treating dark matter as unstabilized vectors;
- Evaluate the expansion of the universe as a thermal reorganization of the lattice.
8.3. Vector Computing: Vetobits
- It is a three-dimensional vector with orientation, modulus and thermal weighting;
- It can represent multiple simultaneous states, as in qubits;
- It depends on angular stabilization to be considered "active" (valid state).
8.4. Materials Engineering with Resonant Structure
- Self-sustaining structures that reconfigure themselves with thermal variation;
- Geometries based on octagons and vectors that respond to environmental stimuli;
- Materials that change their density, rigidity or shape according to internal vector patterns.
8.5. Ontology Applied to Psychology and Philosophy of Consciousness
- Energy and vibrational psychology;
- Modeling mental fields as vector topologies (see Dimension 11);
- Therapies based on emotional vector coherence (Dimension 12);
- Ethics applied to the structure of the field (Dimension 13).
8.6. Prototyping and Scientific Validation
- Thermo-vector devices to simulate the mesh on a reduced scale;
- Cryogenic environments with vector sensors to study stability zones;
- Physical simulations in particle accelerators to detect angular patterns predicted by theory;
- Tests with 3D printers and flexible materials to create dynamic physical meshes.
9. Conclusions
- A cohesive mathematical vector base (thermal modulation functions, dimensional weightings);
- A structured ontology where space, time and the observer are co-emergent and dynamic;
- An unprecedented practical and pedagogical application, allowing the experimental teaching of dimensional physics;
- A clear visualization of reality as a resonant, organizable, aesthetic and harmonious field.
- It redefines the concept of dimension as a stabilized vector, not as a topological abstraction.
- It proposes a relational reality, where the observer influences the dimensional mesh.
- It offers a reproducible and computationally validated physical model.
- It establishes a bridge between science, philosophy, symbolism and technology.
- New ways of simulating the universe with real vectors instead of continuous curves;
- Post-binary vector computing;
- Construction of devices with adaptive dimensional behavior;
- An epistemology of reality based on harmonic stability and vector emergencies, and not on absolute variables.
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