Laplace equation derivation, where does the potential go

In summary, the potential field only depends on position, so the derivative with respect to generalized coordinate, g_{j}, disappears when speed is involved.
  • #1
Uku
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0

Homework Statement


Since the potential field is only a function of position, not velocity, Lagrange's equations are as follows:
592afce1200ba232f3ce737cb32f2e25.png


(Wikipedia, image 1)

Homework Equations


6aa558a2b076e81bd4c97d6d5f168838.png


(Wikipedia, image 2)

The Attempt at a Solution



Now, [itex]-\frac{\partial{V}}{\partial{q_{j}}}[/itex]

How is speed involved in this derivative of potential by generalized coordinate (upper left, image 1)? Potential only depends on the position, we are assuming a conservative field, and that is what we are doing, how does this term disappear?
Feels like saying [itex]F=-\nabla V=0[/itex].
I mean, I can understand eg. generalized impulse depending on speed: [itex]p_{j}=\frac{\partial{L}}{\partial{\dot q_{j}}}[/itex], but not the potential-evaporating transition:
[itex]\frac{d}{dt}\left(\frac{\partial{L}}{\partial{\dot q_{j}}}\right)-\frac{\partial{L}}{\partial{q_{j}}}=0[/itex]
 
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  • #2
So what is your question exactly? Cant quite follow.
 
  • #3
My problem is in the sentence:
Since the potential field is only a function of position, not velocity, Lagrange's equations are as follows:
And in:
[itex]\frac{\partial{V}}{\partial{g_{j}}}[/itex] disappearing from the very first statement.
So - where does it go, [itex]g_{j}[/itex] is a generalized coordinate, not generalized velocity..?
 
  • #4
For a conservative field, which is only dependent on position, the lagrangian is defined as: ##\mathcal{L} = \mathcal{L}(\dot q_j, q_j, t) = T(\dot q_j, q_j, t) - V(q_j)##.

In particular, this means that:
$${\partial \mathcal{L}\over \partial \dot q_i} = {\partial \over \partial \dot q_i}(T(\dot q_j, q_j, t) - V(q_j))
= {\partial \over \partial \dot q_i}T(\dot q_j, q_j, t) - {\partial \over \partial \dot q_i}V(q_j)
= {\partial \over \partial \dot q_i}T(\dot q_j, q_j, t) - 0$$
 
  • #5
Thanks! That makes perfect sense, but it means that there is an error in:
592afce1200ba232f3ce737cb32f2e25.png


since here, very literally, [itex]\frac{\partial V}{\partial q_{j}}=0[/itex]
 
  • #6
Well, what is the following?
$${\partial \mathcal{L}\over \partial q_i} = {\partial \over \partial q_i}(T(\dot q_j, q_j, t) - V(q_j)) $$
Uku said:
since here, very literally, [itex]\frac{\partial V}{\partial q_{j}}=0[/itex]
Uhh :confused:
How do you get that?
 
  • #7
I think I mixed up, the potentials subtract. Thanks!
 

FAQ: Laplace equation derivation, where does the potential go

What is the Laplace equation and why is it important?

The Laplace equation is a second-order partial differential equation that describes the behavior of a scalar field in three-dimensional space. It is important because it is used to model a wide range of physical phenomena, including electric and gravitational potential, fluid flow, and heat transfer.

How is the Laplace equation derived?

The Laplace equation can be derived from the more general Poisson equation by setting the source term to zero. It can also be derived from the fundamental equation of electrostatics, which states that the electric field is equal to the negative gradient of the electric potential.

Where does the potential go in the Laplace equation?

In the Laplace equation, the potential is the dependent variable and is represented by the function Φ. It describes the scalar field that is being studied and how it changes in space.

What are the boundary conditions for the Laplace equation?

The boundary conditions for the Laplace equation are necessary to solve for the potential Φ. They are typically specified as either Dirichlet boundary conditions, where the potential is known at the boundary, or Neumann boundary conditions, where the normal derivative of the potential is known at the boundary.

How is the Laplace equation used in practical applications?

The Laplace equation is used in a variety of practical applications, including modeling the electric potential in electronic circuits, predicting the flow of fluids in pipes and channels, and determining the temperature distribution in heat transfer problems. It is also used in image processing and computer vision to smooth out images and remove noise.

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