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作 者:Boris Menin
机构地区:[1]Refrigeration Consultancy Ltd., Beer-Sheba, Israel
出 处:《Journal of Applied Mathematics and Physics》2017年第2期365-385,共21页应用数学与应用物理(英文)
摘 要:In this paper, we aim to verify the numerical magnitude of the relative uncertainty in the measurement of fundamental physical constants. For this purpose, we use a metric called comparative uncertainty with which an a priori mismatch between the selected model and the observed physical object is checked. The comparative uncertainty is caused by the finite number of dimensional variables of the applied model. We show a comparison of the achieved values of the relative and comparative uncertainties of the gravitational constant, Planck’s constant, Boltzmann’s constant, and fine structure constant, according to data published in the scientific literature over the last 7 - 15 years. The results generally agree well with CODATA recommendations. We show that the comparative uncertainty as a universal metric can be used for the identification of recommended target values of the relative uncertainty in the field experiments.In this paper, we aim to verify the numerical magnitude of the relative uncertainty in the measurement of fundamental physical constants. For this purpose, we use a metric called comparative uncertainty with which an a priori mismatch between the selected model and the observed physical object is checked. The comparative uncertainty is caused by the finite number of dimensional variables of the applied model. We show a comparison of the achieved values of the relative and comparative uncertainties of the gravitational constant, Planck’s constant, Boltzmann’s constant, and fine structure constant, according to data published in the scientific literature over the last 7 - 15 years. The results generally agree well with CODATA recommendations. We show that the comparative uncertainty as a universal metric can be used for the identification of recommended target values of the relative uncertainty in the field experiments.
关 键 词:FUNDAMENTAL Physical CONSTANTS Information THEORY Mathematical Modeling SIMILARITY THEORY UNCERTAINTY
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