Need help with combination of dot product and cross product question

In summary, the conversation discusses a problem related to vectors and the dot product and cross product. The goal is to show that the dot product between one vector and the cross product of two other vectors is equal to the dot product between one of those vectors and the cross product of the other two. The conversation mentions using algebraic properties and index notation to solve the problem, but the person ultimately solves it using brute force.
  • #1
warfreak131
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Homework Statement



Let [tex]\vec{A}[/tex], [tex]\vec{B}[/tex], and [tex]\vec{C}[/tex] be three vectors which are all not in the same plane. Show that [tex]\vec{A}{\cdot}(\vec{B}{\times}\vec{C})=\vec{B}{\cdot}(\vec{C}{\times}\vec{A})=\vec{C}{\cdot}(\vec{A}{\times}\vec{B})[/tex]

Homework Equations



Don't know :(

The Attempt at a Solution



Well I looked up some algebraic properties of dot products and cross products, but nothing that relates the two. I tried working it out, but it's getting extremely messy.
 
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  • #2
  • #3
thank you, but that link is really complicated and i don't understand it.

as for brute force, that would be so long and tedious, and the probability of making a minor error which results in an incorrect answer is so high

is there any easier way to do it?

EDIT:

nevermind, I got it, brute force worked, thanks
 
Last edited:

1. What is the difference between dot product and cross product?

The dot product is a mathematical operation that takes two vectors as input and returns a scalar value. It is calculated by multiplying the magnitudes of the two vectors and then multiplying it by the cosine of the angle between them. The result of a dot product is a single number. On the other hand, the cross product is a vector operation that takes two vectors as input and returns a vector that is perpendicular to both input vectors. It is calculated by multiplying the magnitudes of the two vectors and then multiplying it by the sine of the angle between them. The result of a cross product is a vector.

2. How do I calculate the dot product and cross product of two vectors?

To calculate the dot product of two vectors, you need to first find the magnitudes of the two vectors. Then, multiply the magnitudes and the cosine of the angle between them. The formula for dot product is: A · B = |A| * |B| * cos(θ). To calculate the cross product, you also need to find the magnitudes of the two vectors. Then, multiply the magnitudes, the sine of the angle between them, and the unit vector perpendicular to the plane formed by the two vectors. The formula for cross product is: A x B = |A| * |B| * sin(θ) * u.

3. What is the geometric interpretation of dot product and cross product?

The dot product has a geometric interpretation as the projection of one vector onto another. It represents the component of one vector in the same direction as the other vector. The cross product has a geometric interpretation as the area of the parallelogram formed by the two vectors. It represents the direction perpendicular to the plane formed by the two vectors.

4. When is it appropriate to use dot product and cross product?

Dot product is commonly used in physics and engineering to calculate work, energy, and angles between vectors. It is also used in computer graphics and deep learning algorithms. Cross product is commonly used in physics and engineering to calculate torque, angular momentum, and the direction of magnetic fields. It is also used in computer graphics and 3D geometry calculations.

5. What are some real-world applications of dot product and cross product?

The dot product has applications in physics, engineering, computer graphics, and deep learning. It is used to calculate the work done by a force, the angle between two vectors, and the similarity between two vectors in machine learning algorithms. The cross product has applications in physics, engineering, computer graphics, and 3D geometry calculations. It is used to calculate torque, magnetic fields, and the orientation of objects in 3D space.

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