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

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.

Objective Model Selection in Physics: Exploring the Finite Information Quantity Approach

“…The study argues that this information can play a critical role in assessing the attainable accuracy of representing a modeled phenomenon. The method also addresses the concept of comparative uncertainty, which is a fundamental aspect for evaluating the accuracy limit of a model [1].…”

Informational Restrictions in the Formulation of Physical Laws by Researchers

“…The purpose of this research article is to provide a theoretically substantiated application of the phenomenon of random choice of a variable observed when formulating a model of any physical process. The article is based on the use of the basic element-the finite information quantity (FIQ) [2]-and the implementation of the information method described in [3,4]. Examples are introduced.…”