Definition
Null space of a linear map is defined as: Basically the kernel, or the part of the function that maps to 0.
Null space is a subspace
Suppose , then is a subspace of
Proof:
- Identity: As every linear map sends to , we know thus 0 is in the null space
- Additive closure: Let some . That means . Then:
- Scaler Multiplicative Closure Let some and . then
Straight from kernels in abstract algebra
Injective or one-to-one
A function is called injective if
This also means that
This also just means that distinct inputs map to distinct outputs. A function only needs each input to map to one output, but allows for multiple inputs to map to the same output. So if you read the definition, if two inputs are not the same then their outputs are also not the same.
Check for Injective:
A function is injective
Proof:
-
- Assume a function is injective. That means .
- By the same logic, we know has to map to for any linear map. Thus, only can map to as the function is injective, as if any other then
-
- Assume
- We have to show that .
- If then we know
- Thus
- As the only thing in the null space is , we know or .
Range
Definition
For a function , the range is a subset of equal to for all
This is just a collection of the outputs of the function
Range is a subspace
For , we have it so is a subspace of
Proof:
- 0
- and
- Additive Closure
- Let . this means there exists
- Scaler Multiplicative closure
- Let . Then
Surjective or onto
A function is surjective if
todo look at example
Fundamental Theorem of linear maps
Suppose is a finite-dimensional and . Then range is finite dimensional and
todo take a look at this proof
By the proof above we get some important results, that you should rewrite and prove:
Proof:
- We just need to show that the null space of a function is not
- Dim V = Dim null T + Dim range T
- Dim null T = Dim V - Dim range T
- Dim null T >= Dim V - Dim range W (as range is a subspace which always has a lower dimension)
- Dim null T > 0
similar proof with iniqualities.