Is result of vector inner product retained after matrix multiplication?

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SUMMARY

The discussion centers on the behavior of the inner product of two vectors, ## \vec{a} ## and ## \vec{b} ##, after they are transformed by a matrix ## W ## with real entries. It is established that if ## \vec{a} ## and ## \vec{b} ## are parallel, the inner product remains non-negative due to the positive semi-definiteness of ## W^T W ##. However, when ## \vec{a} ## and ## \vec{b} ## are linearly independent, the outcome of the transformed inner product can be negative, as demonstrated by counterexamples involving specific vectors and transformations. The discussion highlights the importance of the linear transformation's properties in determining the inner product's sign.

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Master1022
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Homework Statement
Let us imagine that we have two vectors ## \vec{a} ## and ## \vec{b} ## and they point in similar directions, such that the inner-product is evaluated to be a +ve number. If we now multiply both of the vectors by a matrix ## W ## which has real entries, will the inner product of the 'transformed' vectors also be positive?
Relevant Equations
Inner product
Hi,

I was thinking about the following problem, but I couldn't think of any conclusive reasons to support my idea.

Question:
Let us imagine that we have two vectors ## \vec{a} ## and ## \vec{b} ## and they point in similar directions, such that the inner-product is evaluated to be a +ve number. If we now multiply both of the vectors by a matrix ## W ## which has real entries, will the inner product of the 'transformed' vectors also be positive?

Attempt:

Intuitively I think along the lines of: if we imagine the operation as transforming a vector in some way, then the two vectors ## \vec{a}## and ## \vec{b}##, which were similar, should be transformed to similar vectors?

Mathematically, I can write the following:
<W \vec{a} , W \vec{b} > = (W \vec{a}) \cdot (W \vec{b}) = (W \vec{a})^{T} (W \vec{b}) = \vec{a}^{T} W^{T} W \vec{b}

- ## W^{T} W ## is positive semi-definite.
- I suppose if ## \vec{a} ## and ## \vec{b} ##, then if/how positive the outcome will depend on some type of sensitivity of ## W ##? That is, we could view ## \vec{b} = \vec{a} + \vec{\epsilon} ## and think about that?

Any help is greatly appreciated.
 
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If ##\vec a## and ##\vec b## are parallel, then the assertion follows directly from ##W^T W## being positive semi-definite (as long as you change the statement to be non-negative instead of positive - it should be pretty obvious that the result can be zero if ##W^T W## happens to have eigenvalues that are zero, such as when ##W = 0##).

However, consider what happens when you let ##\vec a## and ##\vec b## be linearly independent and ask yourself the following questions:
  • Taking any set of two vectors ##\vec c## and ##\vec d##, can you find a linear transformation ##W## such that ##W\vec a = \vec c## and ##W \vec b = \vec d##?
  • What does this mean for your assertion?
 
Thanks for the reply @Orodruin !
Orodruin said:
If ##\vec a## and ##\vec b## are parallel, then the assertion follows directly from ##W^T W## being positive semi-definite (as long as you change the statement to be non-negative instead of positive - it should be pretty obvious that the result can be zero if ##W^T W## happens to have eigenvalues that are zero, such as when ##W = 0##).
Agreed

Orodruin said:
However, consider what happens when you let ##\vec a## and ##\vec b## be linearly independent and ask yourself the following questions:
  • Taking any set of two vectors ##\vec c## and ##\vec d##, can you find a linear transformation ##W## such that ##W\vec a = \vec c## and ##W \vec b = \vec d##?
I think so... I could imagine forming some matrix equation like:
W [ \vec{a} \quad \vec{b}] = [\vec{c} \quad \vec{d}]
and if ## \vec{a} ## and ## \vec{b} ## are linearly independent, then the matrix is full-rank and that can be inverted to find ## W ##.

Orodruin said:
  • What does this mean for your assertion?
That might suggest that the outcome of the transformed inner product is still positive? This doesn't necessarily seem correct, but I am confused still...
 
Master1022 said:
That might suggest that the outcome of the transformed inner product is still positive? This doesn't necessarily seem correct, but I am confused still...
It took me about 30 seconds to find a counterexample. Hint. Let the vectors be ##(1,0)## and ##(1, 1)##. Look for a 2 x 2 matrix that maps ##(1, 0)## to itself and ##(1, 1)## to something in approximately the opposite direction.
 
Master1022 said:
That might suggest that the outcome of the transformed inner product is still positive? This doesn't necessarily seem correct, but I am confused still...
So you are free to choose any ##\vec c## and ##\vec d##. Are there any such pairs with a negative inner product?
 
PeroK said:
It took me about 30 seconds to find a counterexample. Hint. Let the vectors be ##(1,0)## and ##(1, 1)##. Look for a 2 x 2 matrix that maps ##(1, 0)## to itself and ##(1, 1)## to something in approximately the opposite direction.
Okay thanks @PeroK ! That makes sense, and yes I can see how the answer to my question was 'not necessarily'.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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