- They give explicit formulas for the inverse of a matrix
or the solution x of Ax=b.
These are not effective methods to compute the inverse
or the solution but if we want to do an error analysis
with parameters, then explicit formulas are great.
- Determinants are very natural objects.
Every real valued function on square matrices which satisfies
f(AB)=f(A) f(B), f(1)=1, f(k A) = kn A
is the determinant.
- Determinants are useful also in multilinear algebra and
differential geometry.
- Determinants allow to define an orientation of a basis,
if det(A) is positive, then the basis has a positive orientation,
if det(A) is negative, then the orientation is negative.
They have a geometric meaning of a signed volume.
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- Determinants provide a clean way to define the characteristic
polynomial det(x 1 - A) =0. It gives an immediate link between
the eigenvalue and the existence of a kernel of A-x 1.
- Determinants are important in many aspects of physics. This
reason alone would make an omission foolish.
- The computation of determinants is one of the most fun topics
in linear algebra. Finding the best way to crack a determinant
has aspects of puzzles. Cracking a large determinant can be as
fun as solving a crossword puzzle or Sudoku.
- Determinants are a fantastic tool to teach algorithms and the
effectiveness of the method. While the recursive definiton of
the determinant needs n! steps, the best method is a polyonomial.
Determinants give lesson in complexity theory.
Nobody knows whether one can compute permanents effectively,
which are determinants where the signs in the recursive
Laplace definition are not alternating +,-,+, but everywhere +.
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