This package provides the complete operational software, detailed construction manual, and precision technical notes for the **Puan Station 36+1 Coil Rotational Detector** – a tabletop instrument designed to detect scalar torsion fields predicted by the Universal Applicable Time (UAT) and Unified Principle of Causality (UPC) frameworks. **Key Features: **- **Dynamic Frequency Calibration: ** The operating frequency is automatically calculated for the current date using the UAT Inflationary Drift (α = 0. 046 Hz/day, reference epoch 2023-05-27, f₀ = 84. 4 Hz). Leap years are correctly handled. - **Operational Scripts: ** - `puan₃6chgenerator. py`: Generates 36 phase-synchronized sinusoidal signals with 7% table rotation asymmetry and logarithmic torsion (τ = 0. 3697). - `puanᵣmsₘonitor. py`: Captures and displays the live RMS value from the central observer coil. - **Complete Construction Manual (PDF): ** Includes coil specifications, mechanical layout, wiring diagrams, battery power supply design, and star-grounding scheme. - **Precision Technical Note (PDF): ** Detailed instructions for INA128 instrumentation amplifier implementation, shielding, and grounding – essential for achieving the target noise floor. - **Digital Twin Simulation: ** A self-contained simulation script (`simulation/puancombineddemo. py`) validates the phase equations and demonstrates the expected RMS saturation (~0. 7050, target 0. 7071) in an ideal environment. **Hardware Requirements (for operational use): **- 5 × 8-channel audio interfaces with Word Clock synchronization (e. g. , Behringer UMC1820) - 36 identical air-core peripheral coils + 1 central observer coil- INA128 instrumentation amplifier with precision 51 kΩ gain resistor (G = 1. 9694) - Battery power supply (±12 V, ±5 V) for low-noise operation **Intended Audience: ** Experimental physicists, independent researchers, and engineers interested in replicating or validating the UAT/UPC scalar torsion detection methodology. **Related DOIs: **- UAT Framework: 10. 5281/zenodo. 17729221 (https: //doi. org/10. 5281/zenodo. 17729221) - UPC Framework: 10. 5281/zenodo. 18210808 (https: //doi. org/10. 5281/zenodo. 18210808) **Author: ** Miguel Ángel Percudani (ORCID: 0009-0007-1748-3212)
Building similarity graph...
Analyzing shared references across papers
Loading...
Miguel Angel Percudani
Building similarity graph...
Analyzing shared references across papers
Loading...
Miguel Angel Percudani (Thu,) studied this question.
www.synapsesocial.com/papers/69ec5b3d88ba6daa22dacd3f — DOI: https://doi.org/10.5281/zenodo.19704791