Getting a solution from a system of PDEs

In summary, The conversation discusses finding a potential function for a given vector function. The first function can be written as the curl of a vector function and the second as the gradient of a scalar function. However, finding a solution for the second function requires additional argumentation and constraints. By setting a constraint, a potential function can be found that satisfies the original function. However, the uniqueness of the solution is not guaranteed.
  • #1
CrosisBH
27
4
Homework Statement
From Griffith's E&M 1.50b
Show that [tex]\vec{F}_3=yz\hat{x}+zx\hat{y}+xy\hat{z}[/tex] can be written both as the gradient of a scalar and as the curl of a vector. Find scalar and vector potentials for this function.
Relevant Equations
None specifically (I think), all I need is the definition of the gradient of a scalar function, and the curl of a vector function.
I want to start off here saying I took the problem has finding a potential function, and not a general solution, so I worked to only find one function that works.

I already confirmed that this function can be written as a curl of a vector function and the gradient of a scalar function.

Since it can:

[tex]\vec{F}_3 = \nabla v[/tex]
and so
[tex]yz = \frac{\partial v}{\partial x}[/tex]
[tex]zx = \frac{\partial v}{\partial y}[/tex]
[tex]xy = \frac{\partial v}{\partial z}[/tex]

Here's where the physicist rigor comes in. I only took the first function and integrated it with respect with x (treating the partial derivitive as a normal derivitive) and got that v = xyz + C(y,z), and I just set the constant = 0 and got a solution of v = xyz.

The second part is what's tripping me. Where I have to write this as a curl of a vector function.
[tex] \vec{F}_3 = \nabla \times \vec{C} [/tex]

I expanded the right hand side out to vector components and got this system:
[tex] yz = \frac{\partial C_z}{\partial y} - \frac{\partial C_y}{\partial z} [/tex]
[tex] xz = \frac{\partial C_x}{\partial z} - \frac{\partial C_z}{\partial x} [/tex]
[tex] xy = \frac{\partial C_y}{\partial x} - \frac{\partial C_x}{\partial y} [/tex]

I have no idea how to force a solution out of this, and I don't have the mathematical knowledge to solve this system of PDEs for a general solution. I'm kinda stuck. Any help is appreciated.
 
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  • #2
CrosisBH said:
I only took the first function and integrated it with respect with x (treating the partial derivitive as a normal derivitive) and got that v = xyz + C(y,z), and I just set the constant = 0 and got a solution of v = xyz.
The first part is fine, but you cannot do the second part without additional argumentation, i.e., inserting your v into the remaining differential equations and finding out that the partial derivatives of C(x,y) are both zero, actually making C a constant. It is otherwise somewhat confusing to call a function (which C(x.y) is) a constant.

For your remaining question, note that the vector potential is not going to be unique so you are going to need additional constraints in order to find it unambiguously. A common approach is to introduce an additional constraint, for example ##C_z = 0##, try it out and see where it gets you.
 
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  • #3
Orodruin said:
The first part is fine, but you cannot do the second part without additional argumentation, i.e., inserting your v into the remaining differential equations and finding out that the partial derivatives of C(x,y) are both zero, actually making C a constant. It is otherwise somewhat confusing to call a function (which C(x.y) is) a constant.

For your remaining question, note that the vector potential is not going to be unique so you are going to need additional constraints in order to find it unambiguously. A common approach is to introduce an additional constraint, for example ##C_z = 0##, try it out and see where it gets you.

I did your suggestion, and worked out the system and got a vector of [itex]\vec{C} = \left(\frac{1}{2}xz^2 - \frac{1}{2}xy^2\right)\hat{x} - \frac{1}{2} yz^2 \hat{y}[/itex] as a potential function and worked it out and the curl of the function is the original function. So for these types of problems that demand a solution but not a specific one, I can keep imposing reasonable constrants until a solution pops up? (By the way, thanks a bunch)
 
  • #4
CrosisBH said:
So for these types of problems that demand a solution but not a specific one, I can keep imposing reasonable constrants until a solution pops up?
If by ”reasonable” you mean that they are not so stringent that they rule out all solutions. Otherwise there is nothing ”physically reasonable” in a particular choice of constraint other than that it might make it easier to find a solution.
 
  • #5
For a vector [itex] \vec{B} = \vec{\nabla} \times \vec{A} [/itex], isn't the solution [itex] \vec{A} = \frac{1}{2} \vec{B} \times \vec{r}[/itex]?
 
  • #6
Dr Transport said:
For a vector [itex] \vec{B} = \vec{\nabla} \times \vec{A} [/itex], isn't the solution [itex] \vec{A} = \frac{1}{2} \vec{B} \times \vec{r}[/itex]?
No, this is true if ##\vec B## is constant, which is not the case here. Furthermore the solution is not unique neither for the scalar nor for the vector potential.
 
Last edited:

What is a system of PDEs?

A system of PDEs, or partial differential equations, is a set of equations that involve multiple unknown functions and their partial derivatives with respect to multiple independent variables. These equations are used to model and solve problems in various fields such as physics, engineering, and mathematics.

Why is it important to get a solution from a system of PDEs?

Solving a system of PDEs allows us to understand and predict the behavior of complex systems and phenomena. This can help us make informed decisions, design more efficient systems, and advance our understanding of the world around us.

What are the steps involved in getting a solution from a system of PDEs?

The general steps for solving a system of PDEs include: 1) identifying the type of PDEs involved, 2) transforming the equations into a standard form, 3) applying appropriate boundary and initial conditions, 4) using analytical or numerical methods to solve the equations, and 5) interpreting and analyzing the solution.

What are some common analytical methods used to solve a system of PDEs?

Some common analytical methods include separation of variables, method of characteristics, and Fourier/Laplace transforms. These methods involve manipulating the equations to reduce them to simpler forms that can be solved using known techniques, such as integration or algebraic manipulation.

What is the role of computer simulations in getting a solution from a system of PDEs?

Computer simulations play a crucial role in solving complex systems of PDEs. They allow for faster and more accurate solutions, especially for systems with many variables and nonlinear equations. Simulations also allow for visualizing and analyzing the behavior of the system in different scenarios, providing valuable insights and understanding.

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