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Linear Maps

Abstract

A brief overview of maps, the conditions for a map to be a linear maps and some of there properties.

Keywords:Linear MapsMatricesVector Spaces

A map from a vector space VV to a vector space VV' is a rule which assigns to every element of VV an elements in VV'.

Linear Map Conditions

A map L:FnFmL: \mathbb{F}^{n} \rightarrow \mathbb{F}^{m} is called a linear map if

Matrices and Linear Maps

Each linear map has an associated matrix. The linear map L:FnFmL: \mathbb{F}^{n} \rightarrow \mathbb{F}^{m} has an associated matrix ML  Mmn(F)M_{L}~\in~\mathbb{M}_{mn}(\mathbb{F}) with elements given by

mij=eimL(ejn),m_{ij} = e^{m}_{i} \cdot L(e^{n}_{j}),

where eine^{n}_{i} and ejme^{m}_{j} are the standard basis of Fn\mathbb{F}^{n} and Fm\mathbb{F}^{m} respectively.

The map LL can be applied to a vector xFn\bm{x} \in \mathbb{F}^{n} via its associated matrix as

L(x)=MLx  Fm.L(\bm{x}) = M_{L} \bm{x}~\in~\mathbb{F}^{m}.

Operations of Linear Maps

Scalar Multiplication
Addition
Concatenations
Image and Kernel

Let L:FnFmL: \mathbb{F}^{n} \rightarrow \mathbb{F}^{m} be a linear map with associated matrix ML  Mmn(F)M_{L}~\in~\mathbb{M}_{mn}(\mathbb{F}) and λ  F1\lambda~\in~\mathbb{F}^{1}

(λL)(x)=λL(x)(\lambda L)(\bm{x}) = \lambda L(\bm{x})

where λL\lambda L is also a linear map.

On the associated matrix MLM_{L} with elements mijm_{ij} this becomes

MλL=λML=λmij.M_{\lambda L} = \lambda M_{L} = \lambda m_{ij}.

Properties of Linear Maps

Surjective
Injective
Bijective
Nullity
Rank

Let L:FnFmL: \mathbb{F}^{n} \rightarrow \mathbb{F}^{m} be a linear map.

LL is surjective if and only if

ImL=Fm,\textrm{Im}L = \mathbb{F}^{m},

meaning the map can output all possible vectors in the output space.

Projections

A linear map L:VVL: V \rightarrow V is a projection if L2=LL^{2}=L.

This means applying the map twice gives the same results as applying the map once.

Properties of Projections

Let L:VVL: V \rightarrow V be a projection.