Probability flow in multi-step reactions

Author(s):  
William A. Friedman
Keyword(s):  
1988 ◽  
Vol 55 (3) ◽  
pp. 702-705 ◽  
Author(s):  
Y. K. Lin ◽  
Guoqiang Cai

A systematic procedure is developed to obtain the stationary probability density for the response of a nonlinear system under parametric and external excitations of Gaussian white noises. The procedure is devised by separating the circulatory portion of the probability flow from the noncirculatory flow, thus obtaining two sets of equations that must be satisfied by the probability potential. It is shown that these equations are identical to two of the conditions established previously under the assumption of detailed balance; therefore, one remaining condition for detailed balance is superfluous. Three examples are given for illustration, one of which is capable of exhibiting limit cycle and bifurcation behaviors, while another is selected to show that two different systems under two differents sets of excitations may result in the same probability distribution for their responses.


2021 ◽  
Author(s):  
Wen-Xiang Chen

This article points out that when the boundary condition $\frac{T}{T_{c}}=z$ (when z is a complex number) is preset, bosons can produce Bose condensation without an energy layer. Under Bose condensation, incident waves may condense in various black holes in the theory of loop quantum gravity. This paper shows that under the gravitational subsystem composed of two bosons, the extreme value of the measurement uncertainty principle can be smaller because the probability flow density is related to the time parameter. This is a model to verify the existence of gravitons.


2019 ◽  
Vol 65 (3) ◽  
pp. 314-349
Author(s):  
Piotr Sulewski

This paper proposes scenarios of generating two-way and three way contingency tables (CTs). A concept of probability flow parameter (PFP) plays a crucial role in these scenarios. Additionally, measures of untruthfulness of H0 are defined. The power divergence statistics and the |X| statistics are used. This paper is a simple attempt to replace a nonparametric statistical inference from CTs by the parametric one. Maximum likelihood method is applied to estimate PFP and instructions of generating CTs according to scenarios in question are presented. The Monte Carlo method is used to carry out computer simulations.


2019 ◽  
pp. 215-223
Author(s):  
A. C. Fischer-Cripps
Keyword(s):  

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