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TRIXEL Framework

Reference implementation of the TRIXEL calibrator system (SD, VD, VS) — minimum for maximum. TRIXEL Framework https://doi.org/10.5281/zenodo.20721811

T = (V, D, S) — a mathematical framework describing any system through three dimensions:

V (Existence) — what the system is

D (Dynamics) — how it changes

S (Structure) — the scale or form in which it exists

From these, three calibrators measure their mutual relationships.

What this is TRIXEL is an independent research project by Milan Takáč (Košice, Slovakia), developed collaboratively with AI assistance. The framework is not affiliated with any academic institution.

Latest preprint (v3.0): https://doi.org/10.5281/zenodo.20721811

Previous version (v1.0): https://doi.org/10.5281/zenodo.20610880

Installation bash pip install numpy scipy

Quick start python

import numpy as np from calibrators import compute_all, dominant_calibrator, check_algebraic_identity

S = np.linspace(0, 10, 500) V = np.exp(-0.5 * ((S-5)/1.5)**2) D = -np.gradient(V, S)

c = compute_all(V, D, S) print(f"VS range: {c['VS'].min():.4f} to {c['VS'].max():.4f}")

err, holds = check_algebraic_identity(V, D, S) print(f"Identity VD/VS = SD holds: {holds} (error: {err:.2e})")

dom = dominant_calibrator(c['SD'], c['n']) Example notebook: examples/basic_usage.ipynb

The three calibrators

Calibrator Formula Meaning
SD |dD/dS| How fast dynamics change with structure
VS 1/|dV/dS| Sensitivity of existence to structural change
VD SD/n Bridge between dynamics and existence

Exact identity: VD / VS = SD

Dominance map In (log SD, log n) space, one calibrator always dominates:

VS dominant — existence highly sensitive to structure

SD dominant — dynamics change rapidly with structure

VD dominant — intermediate regime

Verified at 99.99% accuracy on a 600×600 grid.

Verified results Algebraic identity VD/VS = SD — exact

Dominance partition theorem — 99.99% accuracy

VS early warning — Burgers turbulence (90/90 runs, FP=0%, FN=0%)

Cross-domain validation — Lotka–Volterra ecology

Real tokamak data — VS identifies stable plasma phases in GOLEM (5 shots, metadata + raw oscilloscope data).

Not yet verified VS as disruption precursor on real tokamak data

VS early warning in 2D Navier–Stokes

VS on EEG seizure data

Rogowski coil calibration for GOLEM

Physical interpretation VS = 1/|dV/dS| drops when the system’s existence becomes rapidly sensitive to structural changes. This happens before global energy or amplitude changes become visible.

The mapping (choice of V, D, S) must be physically motivated.

How to apply TRIXEL Choose S (time, wavenumber, radius, position…)

Choose V(S) (energy spectrum, current, population…)

Choose D(S) (dE/dt, dI/dt, dN/dt…)

Run compute_all(V, D, S) and examine VS

Repository structure Kód trixel/ ├── calibrators.py ├── README.md ├── requirements.txt ├── tests/ │ └── test_identity.py └── examples/ └── basic_usage.ipynb Citation bibtex @misc{takac2026trixel, author = {Takáč, Milan}, title = {TRIXEL 3.0 — Scale-Adaptive Metric Framework}, year = {2026}, doi = {10.5281/zenodo.20721811}, url = {https://doi.org/10.5281/zenodo.20721811} } License MIT License.

Contact Milan Takáč, Košice, Slovakia https://doi.org/10.5281/zenodo.20721811

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Reference implementation of the TRIXEL calibrator system (SD, VD, VS) — minimum for maximum.

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