Editorial: Examining the Effects of T-Consciousness Fields on an In Silico Experiment; Impact on the Distribution of Random Numbers and Monte Carlo Calculations
Main Article Content
Keywords
T-Consciousness Fields, Random Numbers, Distribution, Monte Carlo, Computer Computations
Abstract
This research, considering the principles of Constant and Variable Consciousness defined in the TCF theory, was designed and conducted by selecting an appropriate problem in the world of computer computations where it is possible to examine the behavior of the system as a result of encountering variables that create uncertainty. Accordingly, the aim of the series of studies in this issue is to investigate the effect of TCFs on computations performed by computers using the Monte Carlo method and through the generation of random numbers with the general nature of statistical computations. For this purpose, the effects of TCFs One and Two were examined at two levels: first, the generation of random numbers by computer programs across various systems and operating systems; and second, computations related to a problem with a specific analytical solution, which includes three cases: one-dimensional calculation (integrals), two-dimensional calculation (surface), and three-dimensional calculation (volume). This research was conducted through comparisons between control and sample groups with a statistically significant and validated number of samples. Here, the dimensions refer to the number of different sets of random numbers used in the computations. According to the results obtained from the series of studies in this issue, as the complexity of the computational problem increased (from one-dimensional to three-dimensional), the system under study was gradually driven to accept more uncertainty in the calculations, or in other words, to accept greater error in estimation. This phenomenon caused the deterministic nature of random numbers, which depends on mathematical formulations and software subroutines, to become less pronounced, and the system's output to approach a more variable behavior. This made the observation of the influence of the TCFs under study more significant, in terms of statistically meaningful trends and changes. This level of influence of the TCFs can also be considered as the impact of information on information.