Lagrangian visualisation and Uncertainty Principle

In summary, quantum theory (QT) is based on the principle of uncertainty (HUP) and the Fourier transformation of wave functions in phase space. The Lagrangian and Action principle are also important in quantum mechanics, as seen in Feynman's book "QED: The Strange Theory of Light and Matter" and Wharton's work on classical particles and fields. The use of Fourier analysis and commutators, such as [x,p_x], are also key in the derivation of HUP. Further visualization and explanation of \frac{\partial}{\partial t} \pi_i = \frac{\partial {\mathcal L}}{\partial x_i} is needed for a better understanding.
  • #1
exponent137
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Probably, the essence of quantum theory (QT) is principle of uncertainty (HUP).

The essence of QT is also the fact that Fourier transformation of wave function in phase(?) space gives wave function in momentum space. If one wave function is Gaussian (and so both ones) this gives HUP.

Very useful function in quantum mechanics are also Lagrangian and Action principle. Feynman used them in visualization of QED in his book "QED: The Strange Theory of Light and Matter".

But Lagrangian cannot be so easily visualized as Hamiltonian, for instance.

Wharton also find Lagrangian useful in QT:

Indeed, for classical particles and fields, there's a perfect match between the initial data one
uses to constrain the Lagrangian and the amount of classical data one is permitted under the HUP. In Fermat's principle, if you know the initial light ray position, the HUP says you can't know the initial angle.

http://fqxi.org/data/essay-contest-files/Wharton_FQX4.pdf

Above Fourier analysis is used in derivation of HUP. Another aspect in derivation of HUP is use of commutator [x,p_x]. Can Lagrangian be another aspect?
 
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  • #2
Now I succeded to find something:
[tex]\frac{\partial}{\partial t} \pi_i = \frac{\partial {\mathcal L}}{\partial x_i}.[/tex]
The canonical commutation relations then amount to
[tex] [x_i,\pi_j] = i\hbar\delta_{ij}, \, [/tex]
http://en.wikipedia.org/wiki/Canonical_commutation_relation

If [tex]\pi_i=p_i[/tex] this is the most simple version, what I searched. But I please for visualization and explanation of this?
 

1. What is Lagrangian visualization?

Lagrangian visualization is a technique used in fluid dynamics to track the movement of individual particles in a fluid. This is achieved by creating a grid of particles and following their trajectories over time, providing a visual representation of the flow field.

2. How does the Uncertainty Principle relate to Lagrangian visualization?

The Uncertainty Principle, also known as Heisenberg's uncertainty principle, states that it is impossible to simultaneously know the precise position and momentum of a particle. In Lagrangian visualization, the particles being tracked are subject to this principle, as their exact position and momentum cannot be known at the same time.

3. Can Lagrangian visualization be used for any type of fluid?

Yes, Lagrangian visualization can be used for any type of fluid, whether it is a gas or a liquid. It is particularly useful for studying turbulent flow, as it allows for tracking of individual particles in the chaotic nature of turbulent motion.

4. How does uncertainty affect the accuracy of Lagrangian visualization?

Uncertainty can have a significant impact on the accuracy of Lagrangian visualization. As the particles being tracked are subject to the Uncertainty Principle, there will always be some level of uncertainty in their position and momentum, which can affect the accuracy of the overall visualization.

5. Are there any limitations to using Lagrangian visualization?

There are a few limitations to using Lagrangian visualization. One is that it can be computationally intensive, as it requires tracking the movement of a large number of individual particles. Additionally, it may not be suitable for studying certain types of flows, such as those with very low Reynolds numbers.

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