particle model वाक्य
उदाहरण वाक्य
मोबाइल
- In a paper published in 2009, researchers from Iceland recounted their application of an interacting particle model to the capelin stock around Iceland, successfully predicting the spawning migration route for 2008.
- The quantum physicist postulates that a wave / particle model of energy and matter substructs universal cosmology and in this way quantum physicists and Omni artists are concerned with the same observable and intuited phenomenon.
- When \ epsilon = 0 the mean field particle model described above reduces to a simple mutation-selection genetic algorithm with fitness function " G " and mutation transition " M ".
- The Gladstone Dale relation requires a particle model of light because the continuous wave-front required by wave theory cannot be maintained if light encounters atoms or molecules that maintain a local electric structure with a characteristic refractivity.
- The Glauber detection theory differs from the Born probabilistic interpretation, in that it expresses the meaning of physical law in terms of relationships, counting signals in the detection processes, without assuming the particle model of matter.
- If G ( x ) = 1 is the unit function and \ epsilon = 1, the interaction between the particle vanishes and the particle model reduces to a sequence of independent copies of the Markov chain X _ n.
- The Glauber detection theory differs from the Born probabilistic interpretation, in that it expresses the meaning of physical law in terms of measured facts ( relationships ), counting events in the detection processes, without assuming the particle model of matter.
- New classes of mean field particle simulation techniques for Feynman-Kac path-integration problems includes genealogical tree based models, backward particle models, adaptive mean field particle models, island type particle models, and particle Markov chain Monte Carlo methods
- New classes of mean field particle simulation techniques for Feynman-Kac path-integration problems includes genealogical tree based models, backward particle models, adaptive mean field particle models, island type particle models, and particle Markov chain Monte Carlo methods
- New classes of mean field particle simulation techniques for Feynman-Kac path-integration problems includes genealogical tree based models, backward particle models, adaptive mean field particle models, island type particle models, and particle Markov chain Monte Carlo methods
- The particle models does have photons of finite size, so there would be a specific, very large, but not infinite, number of photons flying in any given room . talk ) 13 : 38, 27 April 2010 ( UTC)
- The first uniform convergence results with respect to the time parameter for mean field particle models were developed in the end of the 1990s by Pierre Del Moral and Alice Guionnet for interacting jump type processes, and by Florent Malrieu for nonlinear diffusion type processes.
- Despite making key advances in theoretical physics, including the exchange particle model of fundamental forces, causal S-matrix theory, and the renormalization group, his idiosyncratic style and publication in minor journals led to his work being unrecognized until the mid-1990s.
- The independent particle model and mean field theories ( we shall see that there exist several variants ) have a great success in describing the properties of the nucleus starting from an effective interaction or an effective potential, thus are a basic part of atomic nucleus theory.
- In 1922 Lorentz first examined Martin Knudsen's investigation on rarefied gases and in connection with that he discussed Le Sage's particle model, followed by a summary of his own electromagnetic Le Sage model-but he repeated his conclusion from 1900 : Without absorption no gravitational effect.
- It is important to remember that the virtual particle model is just an " interpretation " of what happens, and although it gives correct results under enough conditions to be useful, it is only one possible way of looking at it, and has its limitations . talk ) 18 : 27, 2 January 2013 ( UTC)
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