Proving (My) = (M*x).y | Complex Vectors and Matrices

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In summary, the conversation discusses finding the correct solution to a question on a recent exam. The question asks for a proof regarding complex vectors and matrices. The conversation includes an attempt at a solution and a discussion about defining inner products. Ultimately, it is determined that the solution provided is correct.
  • #1
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Homework Statement


This was a question in a recent exam and I would like to know if the answer I gave is correct since I not 100% sure...

If [itex]\mathbf{x}[/itex] and [itex]\mathbf{y}[/itex] are complex vectors in C^n (complex) and [itex]M[/itex] is a square (n x n)-matrix (also in C^n), prove that:
[tex]\mathbf{x} \cdot (M \mathbf{y}) = (M^* \mathbf{x}) \cdot \mathbf{y}[/tex]
(where M* denotes the complex conjugate + the transpose of M: [itex]M^* = \overline{M}^T[/itex]
(The dot denotes the standard complex dot-product)


The Attempt at a Solution


I did the following:

[tex]\mathbf{x} \cdot \mathbf{y} = \mathbf{x}^T \mathbf{\overline{y}}[/tex]
So
[tex]\mathbf{x} \cdot (M \mathbf{y}) = \mathbf{x}^T \overline{M \mathbf{y}} = \mathbf{x}^T \overline{M} \overline{\mathbf{y}}[/tex]

Now:
[tex]\mathbf{x}^T \overline{M} = (M^* \mathbf{x})^T[/tex] because [tex](M^* \mathbf{x})^T = \mathbf{x}^T (M^*)^T = \mathbf{x}^T \overline{M}[/tex]

So, now we have:
[tex]\mathbf{x} \cdot (M \mathbf{y}) = (M^* \mathbf{x})^T \overline{\mathbf{y}} = (M^* \mathbf{x}) \cdot \mathbf{y}[/tex]


Is this solution correct? Or did I make an error somewhere? (I'm not entirely sure of the very first statement for example...)

Thanks.
 
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  • #2
Yes, that's basically correct. But if you aren't sure of the first statement, look up how you defined the inner product. You could also have written your definition x.y=(y*)x. An equally valid definition of inner product is x.y=(x*)y. The first inner product is antilinear in y and the second one is antilinear in x. The choice of one or the other is a matter of convention.
 
  • #3
Well that was really the problem. The book we are using first defines inner products on the real numbers, it defines the standard dot product as:
[tex]\vec{x} \cdot \vec{y} = \sum_{i=1}^n x_i y_i[/tex]
and it is then shown that x.y = x^T y.

Then it goes on later about the complex numbers. It does define the standard dot product as:
[tex]\vec{x} \cdot \vec{y} = \sum_{i=1}^n x_i \overline{y_i}[/tex]
but it does NOT explicitly show that the dotproduct can also be written as [tex]\mathbf{x}^T \overline{\mathbf{y}}[/tex].
I can easily verify that this works but I wasn't sure whether it is true for every condition...

So it is correct? Yay :)
 
  • #4
That's the same as (y*)x, yes. Which is the same as your expression.
 

1. What is "Proof x.(My) = (M*x).y"?

"Proof x.(My) = (M*x).y" is a mathematical expression that represents the commutative property of multiplication. It states that when multiplying two numbers, the order of the factors does not affect the result.

2. What is the significance of this property?

The commutative property of multiplication is important in simplifying and solving mathematical equations. It allows us to rearrange the order of the numbers being multiplied without changing the final result.

3. Can you provide an example of this property in action?

Sure! For example, if we have the equation 2 x 3 = 3 x 2, we can see that the order of the numbers has been switched, but the result is still 6. This is because of the commutative property of multiplication.

4. Does this property apply to all numbers?

Yes, the commutative property of multiplication applies to all real numbers. It is a fundamental property of multiplication and is true for any two numbers, regardless of their value.

5. How is this property different from the associative property of multiplication?

The associative property states that when multiplying three or more numbers, the grouping of the factors does not affect the result. This is different from the commutative property, which only applies to two numbers being multiplied. However, both properties are important in simplifying and solving mathematical equations.

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