Prove this Vector Operation

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In summary: This is because vectors in R^3 are defined by their components in the x, y, and z directions, and the cross product of two vectors is just their vector product in these directions. However, in order for a vector to have a direction in space, it needs to have a magnitude (or length). This means that the vectors in your problem have a negative magnitude, which means that the cross product of them won't have a direction.In summary, you're trying to solve for the magnitude of a vector which has the opposite direction of its original vector. You're missing some crucial information, such as the fact that vectors in R^3 need to have a magnitude in order to have a direction in space. Once you have
  • #1
BioBabe91
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Homework Statement


if vectors [tex]\vec{a}[/tex] and [tex]\vec{b}[/tex] have opposite directions, how to show that |[tex]\vec{a}[/tex]| + |[tex]\vec{b}[/tex]| = |[tex]\vec{a}[/tex] - [tex]\vec{b}[/tex]|?

Homework Equations


quadratic equation, definition of absolute value

The Attempt at a Solution


[tex]|\vec{a}-\vec{b}| = \sqrt{\vec{a}^{2}-2\vec{a}\bullet\vec{b}+\vec{b}^{2}}[/tex]
and then I got
[tex]|\vec{a}-\vec{b}| = \sqrt{\vec{a}^{2}-2|\vec{a}||\vec{b}|cos\Phi+\vec{b}^{2}}[/tex]
So then cosine of the angle is equal to -1, and I don't know how to go from there.
 
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  • #2
Looks like a notation issue.

[tex]
\begin{align}
\vec{a}^2 &= a^2\notag\\

|\vec{a}|&=a\notag
\end{align}
[/tex]

Everything under the radical is a scalar.
 
  • #3
bigplanet401 said:
Looks like a notation issue.

[tex]
\begin{align}
\vec{a}^2 &= a^2\notag\\

|\vec{a}|&=a\notag
\end{align}
[/tex]

Everything under the radical is a scalar.

This makes no sense. In the first equation you have the square of a vector, which implies multiplication of some kind. The only kinds of multiplication that are available are 1) multiplication by a scalar, 2) the dot product, and 3) (for vectors in R^3) the cross product.

In the second equation, you claim that the magnitude of a vector is equal to the vector itself.
 
  • #4
BioBabe91 said:

Homework Statement


if vectors [tex]\vec{a}[/tex] and [tex]\vec{b}[/tex] have opposite directions, how to show that |[tex]\vec{a}[/tex]| + |[tex]\vec{b}[/tex]| = |[tex]\vec{a}[/tex] - [tex]\vec{b}[/tex]|?


Homework Equations


quadratic equation, definition of absolute value


The Attempt at a Solution


[tex]|\vec{a}-\vec{b}| = \sqrt{\vec{a}^{2}-2\vec{a}\bullet\vec{b}+\vec{b}^{2}}[/tex]
and then I got
[tex]|\vec{a}-\vec{b}| = \sqrt{\vec{a}^{2}-2|\vec{a}||\vec{b}|cos\Phi+\vec{b}^{2}}[/tex]
So then cosine of the angle is equal to -1, and I don't know how to go from there.

You're given that the vectors have the opposite directions, which means that a = -kb for some positive scalar k. Also, since a.b = |a||b|cos(theta), and theta = pi, you have a.b = -|a||b|.

Put both of these ideas together, and the result you want should fall out pretty readily.
 
  • #5
This makes no sense. In the first equation you have the square of a vector, which implies multiplication of some kind. The only kinds of multiplication that are available are 1) multiplication by a scalar, 2) the dot product, and 3) (for vectors in R^3) the cross product.

In the second equation, you claim that the magnitude of a vector is equal to the vector itself.

Again, I think it's a notation issue. You'll often see shorthands like this in the literature. Since you're using boldface:
[tex]
\begin{align}
\mathbf{a}^2 &= \mathbf{a} \cdot \mathbf{a} = a^2 = |\mathbf{a}|^2
\intertext{and}
|\mathbf{a}| &= a.
\end{align}
[/tex]

I can see where there might be problems, if instead we did something like
[tex]
\mathbf{a}^2 = \mathbf{aa} = \mathbf{a} \otimes \mathbf{a}
[/tex]
and instead ended up with a dyadic (an outer product).

Notice that the arrows are missing on the RHS of each equation in my previous post.
 

What is a vector operation?

A vector operation is a mathematical operation that is performed on vectors, which are quantities that have both magnitude and direction. Examples of vector operations include addition, subtraction, multiplication, and division.

Why is it important to prove vector operations?

Proving vector operations is important because it allows us to ensure that the mathematical operations we are performing on vectors are accurate and consistent. By proving these operations, we can have confidence in the results and use them to make accurate predictions and solve real-world problems.

How do you prove a vector operation?

The method for proving a vector operation will depend on the specific operation being performed. Generally, it involves using mathematical properties and principles to manipulate the vectors and show that the result is consistent with the expected outcome. This can also involve using vector diagrams and geometric proofs.

What are some common mistakes when proving vector operations?

One common mistake when proving vector operations is forgetting to consider the direction of the vectors. Since vectors have both magnitude and direction, it is important to ensure that the direction is taken into account when performing operations. Another mistake is not using the correct mathematical properties and principles, which can lead to incorrect results.

What are some applications of vector operations in science?

Vector operations have many applications in science, including physics, engineering, and computer science. They are used to describe and analyze the motion of objects, calculate forces and velocities, and model complex systems. In computer science, vector operations are used in data analysis, image processing, and machine learning algorithms.

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