linear map

a linear map from to is a function with the following properties.
  • additivity. for all .
  • homogeneity. for all and all .
[cite:;taken from @algebra_axler_2024 chapter 3 linear maps; definition 3.1 linear map]
  1. any matrix defines a linear transformation by matrix multiplication: 2. every linear transformation is given by multiplication by the matrix : where the th column of is .
[cite:;taken from @calc_hubbard_2015 theorem 1.3.4]

some stuff from college

let be vector spaces over the field , and let be a function which would be called a linear map if:
  1. for every ,
  2. for every and ,
let be a linear transformation,
consider the transformation of the 2d plane :
where
this transformation maps the line , where or to the line
use the lines parametric form to find the image of an arbitrary point on the original line, then convert the obtained parametric coordinates of the image into an implicit equation
is a linear map?
we need to prove
i should be writing not
we need to prove

check whether this represents a linear map:
it isnt, a counter example:

if is a linear map then
if is a function such that then isnt a linear map

if is a linear map then:
  1. the kernel of is
  2. the image of is , which means all the values that can be returned by , which is also the column space of its corresponding transformation matrix (if it has one)

given the linear operator defined by
find the matrix of in the basis
on the left columns of the matrix lies the basis and on the right 4 columns lies the image
src_sage{A=matrix(QQ, [[1,1,0,0, 2,0,1,0], [1,-1,1,0, 2,-1,0,1], [1,0,-1,1, 2,0,-1,0], [1,0,0,-1, 2,1,0,-1]]); fm(r'')} {{{results()}}}
and so the matrix is:
src_sage{fm(r'')} {{{results()}}}

find the bases of
finding the basis of

to find the basis of we reduce the matrix:
and so the basis of is and
we apply a simple check:

given the linear operator defined by such that
find the matrix of in the basis

find the bases of

given the function defined by
prove is a linear transformation
's domain is a vector space of polynomials of the second degree at most,
assume , need to prove

let , need to prove
therefore, indeed is a linear transformation

find the matrix of in standard basis form

find the bases of