Least squares adjustment of the coupling constants in nuclear beta-decay

1974 ◽  
Vol 267 (2) ◽  
pp. 129-133 ◽  
Author(s):  
A. Kropf ◽  
H. Paul
Keyword(s):  
Least Squares ◽  
Beta Decay ◽  
Coupling Constants ◽  
Nuclear Beta Decay ◽  
Least Squares Adjustment

Controversy and Consensus: Nuclear Beta Decay 1911-1934

2000 ◽  
Vol 84 (500) ◽  
pp. 382
Author(s):  
Steve Abbott ◽  
Carsten Jensen ◽  
Finn Aaserud ◽  
Helge Kragh ◽  
Erik Rudinger ◽  
...  
Keyword(s):  
Beta Decay ◽  
Nuclear Beta Decay

scholarly journals Using Least-Squares Residuals to Assess the Stochasticity of Measurements—Example: Terrestrial Laser Scanner and Surface Modeling

2021 ◽  
Vol 5 (1) ◽  
pp. 59
Author(s):  
Gaël Kermarrec ◽  
Niklas Schild ◽  
Jan Hartmann
Keyword(s):  
Least Squares ◽  
Laser Scanner ◽  
Real Data ◽  
Point Clouds ◽  
Statistical Testing ◽  
Normal Vector ◽  
Engineering Structures ◽  
3D Point Clouds ◽  
Least Squares Adjustment ◽  
Correlation Parameters

Terrestrial laser scanners (TLS) capture a large number of 3D points rapidly, with high precision and spatial resolution. These scanners are used for applications as diverse as modeling architectural or engineering structures, but also high-resolution mapping of terrain. The noise of the observations cannot be assumed to be strictly corresponding to white noise: besides being heteroscedastic, correlations between observations are likely to appear due to the high scanning rate. Unfortunately, if the variance can sometimes be modeled based on physical or empirical considerations, the latter are more often neglected. Trustworthy knowledge is, however, mandatory to avoid the overestimation of the precision of the point cloud and, potentially, the non-detection of deformation between scans recorded at different epochs using statistical testing strategies. The TLS point clouds can be approximated with parametric surfaces, such as planes, using the Gauss–Helmert model, or the newly introduced T-splines surfaces. In both cases, the goal is to minimize the squared distance between the observations and the approximated surfaces in order to estimate parameters, such as normal vector or control points. In this contribution, we will show how the residuals of the surface approximation can be used to derive the correlation structure of the noise of the observations. We will estimate the correlation parameters using the Whittle maximum likelihood and use comparable simulations and real data to validate our methodology. Using the least-squares adjustment as a “filter of the geometry” paves the way for the determination of a correlation model for many sensors recording 3D point clouds.

An electromagnetic ion trap for studies in nuclear beta decay

1999 ◽  
Author(s):  
D. Beck ◽  
M. Beck ◽  
G. Bollen ◽  
J. Deutsch ◽  
J. Dilling ◽  
...  
Keyword(s):  
Beta Decay ◽  
Ion Trap ◽  
Nuclear Beta Decay
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