Data assimilation into a numerical shallow water flow model: a stochastic optimal control approach

1995 ◽  
Vol 6 (1-2) ◽  
pp. 145-158 ◽  
Author(s):  
A.W. Heemink ◽  
I.D.M. Metzelaar
Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1533 ◽  
Author(s):  
Jussi Lindgren ◽  
Jukka Liukkonen

We provide a natural derivation and interpretation for the uncertainty principle in quantum mechanics from the stochastic optimal control approach. We show that, in particular, the stochastic approach to quantum mechanics allows one to understand the uncertainty principle through the “thermodynamic equilibrium”. A stochastic process with a gradient structure is key in terms of understanding the uncertainty principle and such a framework comes naturally from the stochastic optimal control approach to quantum mechanics. The symmetry of the system is manifested in certain non-vanishing and invariant covariances between the four-position and the four-momentum. In terms of interpretation, the results allow one to understand the uncertainty principle through the lens of scientific realism, in accordance with empirical evidence, contesting the original interpretation given by Heisenberg.


2011 ◽  
Vol 59 ◽  
pp. 15-26 ◽  
Author(s):  
Weiming Wu ◽  
Alejandro Sánchez ◽  
Mingliang Zhang

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