Gradient of a dot product identity proof?

In summary, the conversation discusses the difficulty of proving the vector identity ∇(A\bulletB) = A×(∇×B)+B×(∇×A)+(A\bullet∇)B+(B\bullet∇)A and suggests using the identity A×(B×C) = B(A\bulletC)-C(A\bulletB) and the use of Levi-Cevita symbols and the Kronecker Delta to simplify the proof. The conversation also mentions the importance of being careful with the ∇ operator in vector identities.
  • #1
Libohove90
41
0
Gradient of a dot product identity proof?

Homework Statement


I have been given a E&M homework assignment to prove all the vector identities in the front cover of Griffith's E&M textbook. I have trouble proving:

(1) ∇(A[itex]\bullet[/itex]B) = A×(∇×B)+B×(∇×A)+(A[itex]\bullet[/itex]∇)B+(B[itex]\bullet[/itex]∇)A

Homework Equations


(2) A×(B×C) = B(A[itex]\bullet[/itex]C)-C(A[itex]\bullet[/itex]B)


The Attempt at a Solution


I applied the identity in equation (2) to the first two terms on the right hand side of equation (1), and that allowed me to cancel out 4 terms. Yet, I end up with:

∇(A[itex]\bullet[/itex]B) = ∇(A[itex]\bullet[/itex]B)+∇(B[itex]\bullet[/itex]A)

...which I know cannot be correct. How can I prove this identity in a relatively straightforward way? I have seen other pages asking this yet they all involved the use of Levi-Cevita symbols and the Kronecker Delta, which I am trying not to use because we haven't learned them. I would gladly appreciate anyone's effort to help me out.
 
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  • #2


The only sensible way I can see is to do it by hand for let's say the <x> component in both sides and show they are the same.
 
  • #3


I was hoping I can get around the long calculations lol
 
  • #4


You have to be careful with the ∇ operator in vector identities, as it is not commutative. I think this caused the problem here.
The long calculation will work, and it is sufficient to consider one component.
 
  • #5


Libohove90 said:
I was hoping I can get around the long calculations lol
I know you wanted avoid them, but it's definitely worth learning about the Kronecker delta and Levi-Civita symbol. Using them makes verifying the identity much easier.
 

FAQ: Gradient of a dot product identity proof?

What is the gradient of a dot product?

The gradient of a dot product is a mathematical operation that calculates the rate of change of a dot product with respect to its variables. It is represented by the symbol ∇ (del) and is also known as a vector of partial derivatives.

What is the identity proof for the gradient of a dot product?

The identity proof for the gradient of a dot product is a mathematical proof that shows the relationship between the gradient of a dot product and its variables. It is used to derive the formula for the gradient of a dot product.

Why is the gradient of a dot product important?

The gradient of a dot product is important because it allows us to find the direction of steepest ascent or descent for a given function. This is useful in optimization problems and can also be used in vector calculus to find the directional derivative of a function.

How is the gradient of a dot product calculated?

The gradient of a dot product is calculated by taking the partial derivatives of the dot product with respect to each variable. These partial derivatives are then combined to form the gradient vector ∇f.

What are some real-life applications of the gradient of a dot product?

The gradient of a dot product has many applications in physics, engineering, and economics. It is used to calculate the force acting on a point particle in a vector field, to find the direction of maximum heat transfer in thermodynamics, and to optimize functions in economics and machine learning.

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