Multi-Variable Calculus: Cancellation of dot products

In summary, the dot product of two vectors can be determined if the vectors are orthogonal and the scalar k is introduced. If the vectors are not orthogonal, then the dot product is undefined.
  • #1
Dembadon
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Homework Statement



In real-number multiplication, if uv1 = uv2 and u ≠ 0, then we can cancel the u and conclude that v1 = v2. Does the same rule hold for the dot product: If uv1 = uv2 and u ≠ 0, can you conclude that v1 = v2? Give reasons for your answer.

Homework Equations





The Attempt at a Solution



If we let u = k<u1, u2> with u2 = 0 and scalar k, then the dot product of u with any other vector v = k<v1, v2> will simply be the component kv1 because u2 will make the ku2kv2 product always zero regardless of its value. Thus, v can be infinitely many different vectors and still have the same dot product with u.
 
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  • #2
The hint is can you compute an inverse of [itex]\vec{u}[/itex] ? and thus multiply both by that inverse in order that both vectors v1 and v2 are equal.
 
  • #3
also a counter example might be good here, how about considering when
u • v1 = u • v2 = 0

what does this mean geometrically? using that it should be easy to find a counter example in 3D space
 
  • #4
Dembadon said:
If we let u = k<u1, u2> with u2 = 0 and scalar k, then the dot product of u with any other vector v = k<v1, v2> will simply be the component kv1 because u2 will make the ku2kv2 product always zero regardless of its value. Thus, v can be infinitely many different vectors and still have the same dot product with u.
Just out of curiosity, why do you introduce the scalar k? Doesn't your argument work without the k's?
 
  • #5
Pyrrhus said:
The hint is can you compute an inverse of [itex]\vec{u}[/itex] ? and thus multiply both by that inverse in order that both vectors v1 and v2 are equal.

Interesting! I hadn't thought of that. I'll have to play around with it.

lanedance said:
also a counter example might be good here, how about considering when
u • v1 = u • v2 = 0

what does this mean geometrically? using that it should be easy to find a counter example in 3D space

It would mean that both v1 and v2 are orthogonal to u, or that u is orthogonal to v1 and v2, right?

vela said:
Just out of curiosity, why do you introduce the scalar k? Doesn't your argument work without the k's?

You're absolutely right. Thank you for pointing that out. :smile:

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Thanks for the input, everyone. I appreciate your time.
 

1. What is Multi-Variable Calculus?

Multi-Variable Calculus is a branch of mathematics that deals with the study of functions of multiple variables. It involves the use of derivatives and integrals to analyze and solve problems involving functions with more than one independent variable.

2. What is a dot product in Multi-Variable Calculus?

A dot product, also known as a scalar product, is a mathematical operation that takes two vectors and returns a scalar quantity. In Multi-Variable Calculus, dot products are used to calculate the angle between two vectors and to determine the projection of one vector onto another.

3. How does cancellation of dot products work in Multi-Variable Calculus?

Cancellation of dot products refers to the process of simplifying or reducing a dot product expression to a simpler form. This is done by using properties of dot products, such as the commutative and distributive properties, to expand or factor out terms.

4. Why is cancellation of dot products important in Multi-Variable Calculus?

The cancellation of dot products is important in Multi-Variable Calculus because it allows us to simplify complex expressions and make them easier to work with. This can help us to solve problems more efficiently and accurately, as well as gain a better understanding of the underlying concepts.

5. What are some common applications of Multi-Variable Calculus and cancellation of dot products?

Multi-Variable Calculus and cancellation of dot products are used in various fields such as physics, engineering, economics, and computer graphics. They are used to model and analyze complex systems, optimize functions, and find solutions to problems involving multiple variables and vectors.

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