Proving Non-Trivial Solutions of Ax = b

In summary, the conversation discusses the claim that if the equation Ax=b has a non-trivial solution, then b is in the span of the column vectors of A. The proof for this involves understanding the definition of span and using the components of x in the equation Av to show that the columns of A span the range of A, and form a basis for it if A is invertible.
  • #1
HaLAA
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As I study today, I read through my textbook that says if Ax=b has non-trival solution, then b span in A.

I want to know how can I prove it.
 
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  • #2
I don't understand what you mean by "b span in A". Can you post the exact claim you came across? You should also tell us where you found it. What book? What page number?
 
  • #3
Sounds like it should be b is in THE span OF (the column vectors of) A. The proof would just be knowing the definition of span, plus multiplying A times x and writing it out in terms of the components of x.
 
  • #4
The "range" of A, the set of all vector of the form Av for some v in the domain of A, is sometimes called the "span" of A. Since we can take, in succession, v= <1, 0, 0, ..., 0>, v= <0, 1, 0, ..., 0>, v= <0, 0, 1, ..., 0>, to v= <0, 0, 0, ..., 1> and applying A to each of those gives a column of A, it can be shown that the columns of A span the range of A. And, if A is invertible, form a basis for it.
 
  • #5


To prove that if Ax=b has a non-trivial solution, then b spans in A, we can use the definition of spanning set. A set of vectors spans a space if every vector in that space can be written as a linear combination of the vectors in the set. In this case, A is a set of vectors and b is a vector in the space.

Now, if Ax=b has a non-trivial solution, it means that there exists a non-zero vector x such that Ax=b. This can also be written as x being a linear combination of the columns of A, since x is a vector and A is a matrix. Therefore, b can be expressed as a linear combination of the columns of A, meaning that b is in the span of the columns of A.

In other words, b can be written as a linear combination of the vectors in A, which is the definition of a spanning set. Therefore, we can conclude that if Ax=b has a non-trivial solution, then b spans in A.
 

FAQ: Proving Non-Trivial Solutions of Ax = b

What is the definition of a non-trivial solution for Ax=b?

A non-trivial solution for Ax=b is a solution that is not equal to the zero vector. In other words, it is a solution where at least one variable is non-zero.

How can you prove the existence of a non-trivial solution for Ax=b?

In order to prove the existence of a non-trivial solution for Ax=b, you can use techniques such as row reduction, Gaussian elimination, or substitution to solve for the variables in the equation. If the solution results in at least one non-zero variable, then a non-trivial solution exists.

Can a non-trivial solution exist for every matrix equation Ax=b?

No, a non-trivial solution does not always exist for every matrix equation Ax=b. It depends on the properties of the matrix A and the vector b. For example, if the matrix A is invertible, then a non-trivial solution will exist. However, if the matrix A is singular (has no inverse), then a non-trivial solution may not exist.

How do you determine the uniqueness of a non-trivial solution for Ax=b?

The uniqueness of a non-trivial solution for Ax=b can be determined by examining the number of free variables in the solution. If there are no free variables, then the solution is unique. However, if there are one or more free variables, then there can be infinitely many solutions.

What are some real-world applications of proving non-trivial solutions of Ax=b?

Proving non-trivial solutions of Ax=b is important in many fields of science and engineering, such as physics, economics, and computer science. It is used to solve systems of linear equations, which have applications in modeling and predicting real-world phenomena such as population growth, chemical reactions, and financial trends.

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