User:IssaRice/Linear algebra/Equivalent statements for injectivity and surjectivity: Difference between revisions

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Let <math>A</math> be an <math>m \times n</math> matrix.
Let <math>A</math> be an <math>m \times n</math> matrix. That's a matrix with <math>m</math> rows and <math>n</math> columns, which you can also think of as a map <math>\mathbf R^n \to \mathbf R^m</math>.


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Latest revision as of 19:42, 30 August 2023

Let be an matrix. That's a matrix with rows and columns, which you can also think of as a map .

Injective Surjective Bijective
is injective is surjective is bijective
has a left inverse has a right inverse has both a left and right inverse (which turn out to be the same)
for each , the equation has at most one solution (in other words, a solution may not exist, but if it does, it is unique) for each , the equation has at least one solution (in other words, a solution always exists, but it may not be unique) for each , the equation has exactly one (in other words, a solution always exists, and it is unique)
the columns of are linearly independent the columns of span the columns of are a basis of
the rows of span the rows of are linearly independent the rows of are a basis of
has rank has rank has rank
in the row echelon form of , there is a pivot in every column in the row echelon form of , there is a pivot in every row in the row echelon form of , there is a pivot in every column and every row

Characterizations of injectivity

left inverse

Ax=b has at most one solution

linearly independent columns

spanning rows

rank n

pivot in every column

null space = {0}

zero-dimensional null space

dimension of range = n

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