Measurement-Based Analysis of Communication phenomena under Physical Constraints

This work presents a measurement-based framework for the empirical analysis of communication phenomena, with a focus on distinguishing structured signals from noise, artifacts, and misclassification. The approach is explicitly non-speculative and restricts itself to quantities that are directly measurable or operationally constrained. Communication is treated here as a physical process subject to measurement limits, uncertainty propagation, and cross-validation across independent observables. The work emphasizes classification regimes defined by convergence or inconsistency between independent measurements, rather than inference about intent, origin, or meaning. To support this analysis, an Independent-Constraint Framework (ICF) is employed as a methodological tool. The ICF is not the subject of this work, but a means to ensure reproducibility, falsifiability, and controlled interpretation when assessing communication-related measurements across different physical and observational domains. Applications discussed in this record span astrophysical, planetary, and technosignature-relevant contexts, with the goal of establishing a rigorous measurement-first standard for communication studies that minimizes false positives and avoids narrative or model-driven bias. This record is intended as a stable methodological reference for empirical communication studies and may be updated through versioned releases as measurement techniques and datasets evolve. Measurement-Based Analysis of Communication phenomena under Physical Constraints Previous research has extensively explored signal detection and classification in noisy environments, including information-theoretic criteria for distinguishing structured signals from noise and machine learning approaches for modulation recognition. However, these works typically rely on model inference or pattern recognition frameworks. In contrast, the present study adopts a measurement-first methodology, emphasizing independent physical constraints and explicit falsifiability to classify communication phenomena without speculative interpretation. 1/ Methodology is measurement-first and non-speculative 2/ Empirical reliability and falsifiability 3/ Domain-agnostic (communication broadly, including potential technosignatures), not just communication in engineered systems. Summary of a rigorous physical measurement perspective combined with falsifiability and constraint independence.