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Published values of G derived from high-precision measurements since the 1950s have remained compatible with Heyl (1930), but within the relative uncertainty of about 0.1% (or 1000 ppm) have varied rather broadly, and it is not entirely clear if the uncertainty has been reduced at all since the 1942 measurement. Some measurements published in ...
For example, an experimental uncertainty analysis of an undergraduate physics lab experiment in which a pendulum can estimate the value of the local gravitational acceleration constant g. The relevant equation [ 1 ] for an idealized simple pendulum is, approximately,
The numeric value adopted for ɡ 0 was, in accordance with the 1887 CIPM declaration, obtained by dividing Defforges's result – 980.991 cm⋅s −2 in the cgs system then en vogue – by 1.0003322 while not taking more digits than are warranted considering the uncertainty in the result.
In statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, ... (e.g., instrument precision) ...
The standard gravitational parameter μ of a celestial body is the product of the gravitational constant G and the mass M of that body. For two bodies, the parameter may be expressed as G ( m 1 + m 2 ) , or as GM when one body is much larger than the other: μ = G ( M + m ) ≈ G M . {\displaystyle \mu =G(M+m)\approx GM.}
The Generalized Uncertainty Principle (GUP) represents a pivotal extension of the Heisenberg Uncertainty Principle, incorporating the effects of gravitational forces to refine the limits of measurement precision within quantum mechanics. Rooted in advanced theories of quantum gravity, including string theory and loop quantum gravity, the GUP ...
The uncertainty principle, also known as Heisenberg's indeterminacy principle, is a fundamental concept in quantum mechanics. It states that there is a limit to the precision with which certain pairs of physical properties, such as position and momentum , can be simultaneously known.
Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.