Linear algebra, can A be one-to-one given a case

In summary, the question asks if a linear transformation can be one-to-one if there exists a b such that Ax = b has no solutions. This is equivalent to asking if a linear transformation can be one-to-one if it is not onto. The basic theorem in linear algebra states that for a nxn matrix A, either the equation Ax = b has a unique solution for any n-vector b, or it has no solution (for some b) or infinitely many solutions (for some other b).
  • #1
CookieSalesman
103
5

Homework Statement


Given an nxn matrix, if a b exists so Ax=b has no solutions, can A be one-to-one?

Homework Equations


I understand that as a linear transformation, you need things such as (to be one-to-one as a linear trans)
1. n pivots
2. Only the trivial solution exists to Ax=0

Ax=b having no solutions is a bit of an oddball for me.

The Attempt at a Solution


If I set up an augmented matrix such as [I | b] (Identity matrix | some vector b)
By removing one pivot from the Ident. matrix I can see that I've created an Ax=b where b has no solution. This is akin to a linearly independent set (which contains the zero vector). in Rn space.
It technically doesn't span Rn space nor Rm space fully... I think? As it will have a row of zeroes and a column of zeroes.
But does this truly affect its ability to be one-to-one?
I don't see how it does...

For instance, let's say you have a 3x3 ID matrix A, but one pivot is missing.
If that's put into an augmented matrix[A|b], if a row with zeroes has a number to the right of it, it means there's no solution for this b. So doesn't this mean the situation is just n/a?
 
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  • #2
CookieSalesman said:

Homework Statement


Given an nxn matrix, if a b exists so Ax=b has no solutions, can A be one-to-one?
<snip>

Hint: If Ax = b has no solution then the transformation is not onto. So the question could be rephrased as "Can a linear transformation that is 1-1 be not onto? Does that help? Think about ##R^2## and ##R^3##.

[Edit]: Never mind, I missed the nxn.
 
Last edited:
  • #3
CookieSalesman said:

Homework Statement


Given an nxn matrix, if a b exists so Ax=b has no solutions, can A be one-to-one?

Homework Equations


I understand that as a linear transformation, you need things such as (to be one-to-one as a linear trans)
1. n pivots
2. Only the trivial solution exists to Ax=0

Ax=b having no solutions is a bit of an oddball for me.

The Attempt at a Solution


If I set up an augmented matrix such as [I | b] (Identity matrix | some vector b)
By removing one pivot from the Ident. matrix I can see that I've created an Ax=b where b has no solution. This is akin to a linearly independent set (which contains the zero vector). in Rn space.
It technically doesn't span Rn space nor Rm space fully... I think? As it will have a row of zeroes and a column of zeroes.
But does this truly affect its ability to be one-to-one?
I don't see how it does...

For instance, let's say you have a 3x3 ID matrix A, but one pivot is missing.
If that's put into an augmented matrix[A|b], if a row with zeroes has a number to the right of it, it means there's no solution for this b. So doesn't this mean the situation is just n/a?

There is a very basic theorem in linear algebra: if A is nxn (which you say yours is), then either (1) the equation Ax = b has a unique solution for any n-vector b on the right; or (2) Ax = b has either no solution (for some b) or infinitely many solutions (for some other b).

Case (1) is the same as saying: Ax = 0 if and only if x = 0.
 
  • #4
Thanks everyone. I think that helped.
 

1. Can a linear transformation be one-to-one?

Yes, a linear transformation can be one-to-one if and only if the null space of the transformation is equal to {0}, meaning that the transformation maps distinct elements of the domain to distinct elements of the codomain.

2. What is the difference between one-to-one and onto in linear algebra?

In linear algebra, a one-to-one transformation is a function that maps distinct elements of the domain to distinct elements of the codomain. An onto transformation is a function that maps every element in the codomain to at least one element in the domain.

3. Can a matrix be one-to-one?

Yes, a matrix can be one-to-one if and only if its columns are linearly independent, meaning that the only solution to the equation Ax = 0 is x = 0, where A is the matrix and x is a vector of appropriate size. This condition is equivalent to the null space of the matrix being equal to {0}.

4. What is the importance of one-to-one transformations in linear algebra?

One-to-one transformations are important in linear algebra because they preserve the dimension of the vector space, meaning that the transformed space has the same number of basis vectors as the original space. This makes it easier to work with the transformed space and can simplify computations.

5. Is it possible for a linear transformation to be both one-to-one and onto?

Yes, a linear transformation can be both one-to-one and onto, in which case it is called an isomorphism. This means that the transformation is bijective, meaning that it maps every element in the domain to exactly one element in the codomain and vice versa. Isomorphisms are useful in linear algebra because they preserve not only the dimension, but also the structure of the vector space.

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