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To get the correct answer one must ask the correct question. In the field of Quantum Gravity the question has been how do we quantize General Relativity or derive a quantum theory which becomes General Relativity at low energies. Observing that Quantum Field Theory was the result of making Quantum Mechanics into a relativistic theory, I asked myself why not make QFT obey the principles of GR? I answered this question with a model I call Relativization. In a series of three papers I presented an answer to this alternative question which gives finite results for everything from black holes to particle physics.
Presented at the April meeting of the American Physical Society
El presengte trabajo tiene como objetivo dar a conocer las bondades de los modelos Logit y probit dentro del campo de la estimación de modelos con variable endógena discreta dicotómica.
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Muons compose the penetrating component of Cosmic Rays. At sea level, they constitute the largest part of Secondary Cosmic Rays, giving an average flux of ≈ 100 m−2s−1sr−1. The aim of our experiment is to estimate, from muon decay, the mean lifetime and the mass of invisible products. Our experimental setup includes four detectors: three of them are plastic scintillators and compose the trigger system, while the last one is a liquid scintillator which measures the particles energy. All these scintillators are read by photomultipliers. Trigger and pulse thresholds are computed by logical and temporal modules in a VME crate. The Data Acquisition System has been verified to work properly. It is composed of two fADCs modules, one I/O Register, one Motorola computer and a Farm. The liquid scintillator has been calibrated in energy using both passing muons and 60CO gamma source. Thanks to the charge-energy conversion factor we estimated electron energy spectrum. In particular we selected a sample of decay events by estimating muon mean lifetime τμ = 2.19 ± 0.34 μs; then we finally extrapolated an upper limit for invisible products mass mν < 5.99 ± 0.73 MeV/c2.
SVD-разложение и его практические приложения с исходным кодом на языке Matlab.
(SVD - decomposition and its practical applications with source code in the language Matlab.
Various geometrical shapes are described, for which the numerical value of the perimeter is the same as that of the area. Cases of one or two parameters are explored.