Fisher Information Geometry and the Thermodynamic Cost of Self-Referential Calibration
Fisher Information Geometry and the Thermodynamic Cost of Self-Referential Calibration
Version 2 adds a new Section 8: Numerical Demonstration, a self-contained 20-dimensional linear-prediction simulation confirming the three core predictions (delusion-correction separation, detectable staleness, optimal calibration budget) under continuous drift. Changes from v1: - New Section 8 with three figures and reproducible Python code - Abstract: corrected ln 2 factoring to match Theorem 5 - Detectability proof: fixed θ₀ linearisation - Additivity proof: added separable-DOF qualifier - Discussion: updated summary table to reference numerical results - Editorial: minor wording improvements throughout Supplementary material: tdome_demo.py (self-contained, requires only NumPy + Matplotlib), three figure PDFs, and alpha_opt_curve.csv.
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!