Information Content of the Model for Calculating the Finite Precision of Measurements

Boris Menin *

Mechanical and Refrigeration Consultation Expert, 9 Yakov Efrat St., Beer-Sheba 8464209, Israel.

*Author to whom correspondence should be addressed.


Abstract

Aims: We argue that the choice of a specific qualitative–quantitative set of variables in a model by a conscious observer fundamentally limits the achievable accuracy of the measurement process.

Place and Duration of Study: Mechanical & Refrigeration Consultation Expert, between January 2020 and July 2020.

Methodology: Using the concept of “finite information quantities” introduced by Gisin, we try to present it as a practical tool in science and engineering in calculating the proximity indicator of a model to the phenomenon being studied.

Results: The formulated metric (comparative uncertainty) allows us to set the optimal achievable uncertainty of the model and to confirm the impossibility of implementing the principle of infinite precision.

Conclusion: Any attempt to search for a universal physical theory must consider the uncertainty caused by the observer’s vision and the working of the human brain.

Keywords: Information entropy, measurement uncertainty, measurement units, mathematical model, observability, precision engineering, modeling, random variables


How to Cite

Menin, Boris. 2020. “Information Content of the Model for Calculating the Finite Precision of Measurements”. Physical Science International Journal 24 (7):33-46. https://doi.org/10.9734/psij/2020/v24i730201.