QUASI-REPRODUCIBLE EXPERIMENTS: UNIVERSAL ADJUSTMENT FUNCTION FOR A QUANTITATIVE DESCRIPTION OF COMPLEX SYSTEMS DATA

Abstract

This paper outlines the foundations of the original theory of quasi-reproducible experiments (QRE), based on the testable hypothesis of the existence of a significant correlation (memory) between successive measurements. Based on this hypothesis, which the authors refer to for brevity as the verified partial correlation principle (VPCP), it can be proven that there is a universal fitting function (UPF) for quasi-periodic (QP) and quasi-reproducible (QR) measurements. In other words, there is a certain common platform or “bridge” on which, figuratively speaking, there meet a true theory (claiming to describe data from first principles or verifiable models) and an experiment that proposes this theory to test measured data, as much as possible “cleansed” of influence uncontrollable factors and hardware functions of the measuring device. The proposed theory was tested on space data representing temperature fluctuations and measured by European satellites in space for the early stages of the evolution of the Universe. As a result of processing these data, the frequency response corresponding to these cumulative/integral data was obtained and the necessary quantitative characteristics corresponding to the “ideal” experiment were calculated within the framework of the QE. The authors want to point out that this theory can be applied to a wide class of complex systems whose response can be measured repeatedly.