What question did this study set out to answer?

This research aims to empirically validate scalar causal attractor frameworks using gravitational strain data from LIGO-Virgo.

April 28, 2026Open Access

Longitudinal Analysis of Scalar Causal Attractors in LIGO-Virgo Data (2015–2024): Empirical Validation of UAT/UPC Frameworks through 219 Gravitational Events

Key Points

This research aims to empirically validate scalar causal attractor frameworks using gravitational strain data from LIGO-Virgo.
Utilized the Resonant Hunter v8.4 protocol to analyze LIGO-Virgo gravitational strain data from 2015 to 2024.
Conducted a longitudinal study covering 219 gravitational events to track scalar causal attractors.
Employed Global SVD optimization for analysis and contrasted results against synthetic noise control.
Identified a resonance limit at RMS≈0.7071, consistent with quantum-rotational coherence.
Documented a temporal drift of attractor frequency, indicating asymmetric time flow (α).
Detected a systematic signal degradation in O4 data, validating the theoretical torsion limit (κ crit ≈4.978).

Abstract

This dataset and technical report provide a comprehensive longitudinal study of gravitational strain data from the LIGO-Virgo collaboration, spanning from the first detection (GW150914) to the current fourth observing run (O4). The research utilizes the Resonant Hunter v8. 4 protocol to identify and track a predicted scalar causal attractor—a "Bit-0" informational node—governed by the Universal Applied Time (UAT) and Unified Causal Principle (UPC) frameworks. Key Findings: Scalar Saturation: Systematic identification of a normalized resonance limit at RMS≈0. 7071, consistent with the theoretical 1/ 2 saturation threshold of quantum-rotational coherence. Inflationary Drift (α): Documentation of the temporal drift of the attractor frequency, providing empirical evidence for an asymmetric time flow (TAU). Phase Fracture in O4: Detection of a systematic signal degradation and "phase jump" in recent O4 data, validating the theoretical torsion limit (κ crit ≈4. 978) as the system approaches a state of thermodynamic overdrive. Statistical Robustness: Results derived from a Global SVD (Singular Value Decomposition) optimization across 219 events, contrasted against a synthetic-noise control group (which yielded 0. 0% correlation). Contents: EventLogMaster. csv: Detailed analysis of 219 GW events including attractor values and detector resonance percentages (H1, L1, V1). GlobalAitoffMap. png: ICRS sky localization of the causal attractor using robust multi-event triangulation. ResonantHunterᵥ8. 4. py: The core Python processing engine used for the extraction of scalar signatures from LIGO strain data. Authorship & Context: This work is the result of independent research by Miguel Ángel Percudani, establishing a new calibration milestone for the detection of non-linear gravitational signatures and the construction of future scalar-sensitive observational frameworks.

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