Factorization of a matrix equation

In summary, the experts discuss the correct factorization of the equation ##A\vec{x} - 7\vec{x} = \vec{0}##, with one side being interpreted as a scalar and the other as a matrix. The factorization ##(A - 7I)\vec{x} = \vec{0}## is the strictly correct way to write it, but the notation ##(A-7)\vec{x}## is sometimes used as an abuse of notation, with 7 being interpreted as a linear operator. However, for clarity, most linear algebra books will write the factorization as ##(A - 7I)\vec{x}## to avoid confusion.
  • #1
Mr Davis 97
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44
This might be a dumb question, but I am wondering, given the equation ##A\vec{x} - 7\vec{x} = \vec{0}##, the factorization ##(A - 7I)\vec{x} = \vec{0}## is correct rather than the factorization ##(A - 7)\vec{x} = \vec{0}##. It seems that I can discribute just fine to get the equation we had before using the second ##(A - 7)\vec{x} = \vec{0}##, so I'm not sure why I would think to do ##(A - 7)\vec{x} = \vec{0}## rather than ##(A - 7I)\vec{x} = \vec{0}##.
 
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  • #2
Yes you are right that that is the strictly correct way to write it. However the slight abuse of notation ##(A-7)\vec x## is sometimes used, because it is shorter to write and it is usually clear what it means. In that case the symbol 7 is interpreted to mean the operator on the vector space ##V## that maps ##\vec v## to ##7\vec v##.
 
  • #3
andrewkirk said:
Yes you are right that that is the strictly correct way to write it. However the slight abuse of notation ##(A-7)\vec x## is sometimes used, because it is shorter to write and it is usually clear what it means. In that case the symbol 7 is interpreted to mean the operator on the vector space ##V## that maps ##\vec v## to ##7\vec v##.
Actually, a better question that I might ask would be that since in ##A\vec{x} - 7\vec{x} = \vec{0}## we have a matrix times and vector and then a scalar times a vector, what allows us to be able to factor out the vector? Wouldn't we get a matrix minus a scalar?
 
  • #4
No, because there is no rule that allows us to do that factorisation. It can only be factorised if we interpret the 7 as a linear operator, meaning it is ##7I##.
 
  • #5
Mr Davis 97 said:
Actually, a better question that I might ask would be that since in ##A\vec{x} - 7\vec{x} = \vec{0}## we have a matrix times and vector and then a scalar times a vector, what allows us to be able to factor out the vector? Wouldn't we get a matrix minus a scalar?
Which is why you need to append I in the factorization.
In the expression ##A\vec{x} - 7\vec{x}## Ax is a vector and 7x is a vector, but if you factor the left side to (A - 7), then you're subtracting a scalar from a matrix. As you note, this doesn't make sense unless we stretch things to interpret 7 in the way that andrewkirk mentions. In this case 7 is really 7I.
 
  • #6
Why are we allowed to interpret 7 as either a scalar 7 or a matrix 7I? It seems somewhat ambiguous
 
  • #7
Mr Davis 97 said:
Why are we allowed to interpret 7 as either a scalar 7 or a matrix 7I? It seems somewhat ambiguous
As andrewkirk said in post #2, this is an abuse of notation, but when it is used, the context usually makes it clear what is intended.

However, every linear algebra book I've seen will write the factorization of Ax - 7x (for example) as (A - 7I)x, to show explicitly that we're not subtracting a scalar from a matrix.
 

1. What is the purpose of factorizing a matrix equation?

Factorizing a matrix equation allows us to simplify and solve complex equations involving matrices. It also helps us to find the inverse of a matrix, which is useful in solving systems of equations.

2. What are the different methods of factorization for a matrix equation?

There are several methods of factorization, including LU decomposition, QR decomposition, and singular value decomposition (SVD). Each method has its own advantages and is suitable for different types of matrix equations.

3. How do we know if a matrix equation is factorizable?

A matrix equation is factorizable if it can be written in the form of AB = C, where A and B are matrices and C is the resulting matrix after factorization. This means that the dimensions of the matrices must also be compatible for multiplication.

4. Can we factorize any type of matrix equation?

No, not all matrix equations can be factorized. For example, if the matrix is singular (i.e. it has no inverse), then it cannot be factorized using traditional methods. In such cases, we can use other techniques such as pseudo-inverse to solve the equation.

5. How is factorization of a matrix equation used in real-world applications?

Factorization of matrix equations is widely used in various fields such as engineering, computer science, and economics. It is used in solving systems of linear equations, optimization problems, and data analysis. It also has applications in image and signal processing, where it is used to compress and reconstruct data.

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