What is the Proof for Matrix Multiplication with Invertible Matrices?

In summary, the conversation discusses a proof involving matrices A, X, V, and Y, where AX = 0, AVX = 0, and AVY = 0 are given. The conversation also brings up the use of the inverse of matrix V and questions about the specifics of the matrices involved. Two examples are given to demonstrate the potential complexity of the proof.
  • #1
jumbogala
423
4

Homework Statement


I'm doing a proof in which I need to show:
given that AX = 0, AVX=0 where V is invertible.

Also, given that AVY = 0, then AY = 0.


Homework Equations





The Attempt at a Solution


I can't remember from the previous course I took how to do this. I know that I can multiply from the left or right by V-1, but seeing as V is in the middle that won't work.

This is part of a larger proof, if it would make more sense to have the entire question let me know.
 
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  • #2
I'm assuming A,X,V,Y are matrices, but I'm not sure (EDIT: I see you stated in the title that they are matrices). Also do X and Y need to be vectors or are they general matrices. Do we require some matrices to be square or non-zero? Any other assumptions?

The information you have given is not sufficient. Consider:
[tex]A = \left[\begin{array}{cc} 1 & 0 \\ 0 & 0 \end{array} \right][/tex]
[tex]X = \left[\begin{array}{cc} 0 \\ 0 \end{array} \right][/tex]
[tex]V = \left[\begin{array}{cc} 0 & 1 \\ 1 & 0 \end{array} \right][/tex]
[tex]Y = \left[\begin{array}{cc} 1 \\ 0 \end{array} \right][/tex]
Then [itex]V^2=I[/itex] so V is invertible. AX = AVX = AVY = 0, but,
[tex]AY = \left[\begin{array}{cc} 1 \\ 0 \end{array} \right][/tex]
 
  • #3
A slightly more interesting example where all matrices are non-zero:
[tex]A = \left[\begin{array}{ccc} 1 & 0 & 0 \\ 0 & 0 &0 \\ 0 &0 & 0 \end{array} \right][/tex]
[tex]X = \left[\begin{array}{c} 0 \\ 0 \\ 1 \end{array} \right][/tex]
[tex]V = \left[\begin{array}{ccc} 0 & 1 & 0 \\ 0 & 0 & 1 \\ 1&0&0 \end{array} \right][/tex]
[tex]Y = \left[\begin{array}{c} 1 \\ 0 \\ 0 \end{array} \right][/tex]
Then [itex]V^3=I[/itex] so V is invertible. AX = AVX = AVY = 0, but,
[tex]AY = \left[\begin{array}{c} 1 \\ 0 \\ 0 \end{array} \right][/tex]
 

FAQ: What is the Proof for Matrix Multiplication with Invertible Matrices?

1. What is matrix multiplication?

Matrix multiplication is a mathematical operation that involves multiplying two matrices to produce a new matrix. It is commonly used in linear algebra and has many practical applications in fields such as engineering, physics, and computer science.

2. Why is it important to prove matrix multiplication?

Proving the validity of matrix multiplication is important because it ensures that the mathematical operations being performed are accurate and reliable. It also allows for the development of more complex algorithms and formulas based on the properties of matrix multiplication.

3. What are the steps to prove matrix multiplication?

The steps to prove matrix multiplication involve first defining the properties and rules of matrix multiplication, such as the number of rows and columns in each matrix and the order in which the matrices are multiplied. Then, the proof involves using these properties and rules to demonstrate that the resulting matrix from the multiplication is correct according to these rules.

4. Can matrix multiplication be proved using different methods?

Yes, there are multiple ways to prove matrix multiplication. Some common methods include using mathematical induction, using the properties of determinants, and using the properties of matrix inverses. Each method may have its own advantages and may be more suitable for certain types of matrices.

5. How is matrix multiplication used in real-world applications?

Matrix multiplication has many practical applications, such as in computer graphics, where it is used to transform and manipulate images. It is also used in data analysis and machine learning to process and analyze large datasets. In engineering, it is used to model and solve complex systems. Additionally, matrix multiplication is used in coding and cryptography to encrypt and decrypt data.

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