For
define its action on the projective line by the Möbius transformation
with the usual conventions when the denominator vanishes or . Matrix multiplication agrees with composition, so this is a group action. If fixes every projective point, then it fixes and , forcing , and fixing then gives . Thus the kernel consists exactly of the nonzero scalar matrices . The induced group homomorphism
is therefore injective. This is the projective general linear group action on the projective line.
For ,
The scalar subgroup has order , so
The four classes represented by
form a subgroup of order four, hence a Sylow subgroup for the prime two. Its action is translation on and fixes . For , characteristic two makes this permutation a product of two disjoint transpositions on the four finite points. It is therefore even, and
This realizes the Sylow 2-subgroup of PGL2 over F4.
A function on a convex set is convex when
for all and .
If is once differentiable, this is equivalent to monotonicity of its gradient:
Equivalently, every tangent hyperplane supports the graph:
If is twice differentiable, convexity is equivalent to the Hessian matrix being positive semidefinite throughout .
For
the Hessian is
A real symmetric two-by-two matrix is positive semidefinite exactly when its two diagonal entries and its determinant are nonnegative. Thus
The largest convexity domain is therefore
For , its boundary is the hyperbola in the first quadrant and the domain lies above it. For , it is the closed first quadrant. This is the convexity domain of x cubed plus y cubed plus Axy.
A linear operator on a real inner-product space is self-adjoint when
for all .
To prove the finite-dimensional spectral theorem, first note that the continuous quadratic function has a maximum on the unit sphere. The Lagrange multiplier equation at a maximizing vector gives , so has a real unit eigenvector. Its orthogonal complement is invariant because
Induction on the dimension supplies an orthonormal eigenbasis of that complement and hence of .
For ,
while symmetry and bilinearity are immediate, so the displayed formula defines an inner product on . Since
integration by parts gives
The boundary term vanishes for polynomials, proving that is self-adjoint.
On the monomial ,
Thus the matrix of in the monomial basis is triangular with diagonal
These are therefore its eigenvalues. For , corresponding eigenvectors are
for eigenvalues , respectively. They are the first Laguerre polynomials up to normalization, as described by the Laguerre differential operator on polynomials.
For a nonzero real vector , the Rayleigh quotient of the matrix is
The Rayleigh quotient iteration starts from a unit vector . Given , compute the shift
solve the linear system
and normalize in the Euclidean norm:
The next eigenvalue estimate is . The process stops when the eigenpair residual is sufficiently small.
Since , it suffices to map the two edge vectors. Let the columns of the required matrix be . The condition gives
The condition then gives
and hence
These are orthonormal. Taking produces the orthogonal matrix
Its columns are orthonormal, and direct substitution verifies , , and .
The matrix trace is
Using matrix multiplication and interchanging dummy indices,
The proposed noncyclic interchange is false. With matrix units,
one has
Trace is invariant under cyclic permutations, but an arbitrary swap need not be cyclic.
Write the complex similarity matrix as
with real. From we obtain , and equating real and imaginary parts gives
Therefore
for every real .
Now is a real polynomial and
Thus some real has . Taking , we have a real invertible matrix satisfying , or
This proves real similarity from complex similarity.
Eigenvectors belonging to distinct eigenvalues are linearly independent. Indeed, suppose
is a shortest nontrivial relation, where and the are distinct. Applying gives
a shorter nontrivial relation, a contradiction.
Thus distinct eigenvalues provide a basis of eigenvectors, proving that is diagonalizable over . If is real and all its eigenvalues are real, each real singular matrix has a nonzero real null vector. Choosing one for each eigenvalue gives a real eigenbasis. Hence the real matrix is diagonalizable over . This is the distinct eigenvalues imply diagonalizability criterion.
Suppose is diagonalized by a unitary matrix:
where is diagonal. Then
Since the diagonal matrices and commute,
Thus is a normal matrix.
A complex matrix is unitary matrix when
If with , unitarity preserves norms, so
Therefore every eigenvalue satisfies
Let
This permutation matrix is unitary. The actions
give
which is upper triangular.
Both sides are alternating in and in . If either triple repeats an index, both sides vanish. Otherwise each triple is a permutation of ; the determinant of the corresponding permutation matrix is exactly the product of the two permutation signs. Hence
There are nonzero components of , each equal to , so
The special orthogonal group is
If
its first column is a unit vector, say . The second column is the unique unit vector perpendicular to it that gives positive determinant, namely . Thus
so is rotation through about the origin.
For , its real characteristic polynomial of odd degree has a real eigenvalue. Every eigenvalue of an orthogonal matrix has modulus one, so every real eigenvalue is . Nonreal eigenvalues occur in conjugate pairs whose product is one, while ; if all eigenvalues are real, their product likewise forces at least one to be . Hence fixes a nonzero vector . The plane is -invariant, and the restriction to it is an orientation-preserving orthogonal map. By the result it is a planar rotation. Therefore is a rotation about the axis .
For , let be its permutation matrix and define the sign of a permutation by
Since ,
so this is a homomorphism. A transposition interchanges two columns of the identity matrix and therefore has determinant . If is expressed as a product of transpositions, then ; because the determinant depends only on , the parity of is independent of the chosen expression.
There are four main diagonals and the action is transitive, so the stabilizer of one has order
For the diagonal spanned by , the stabilizing signed permutation matrices are and with a permutation matrix. Hence
The action is not faithful: both and the central inversion fix every main diagonal setwise. In fact its kernel is exactly .
A Givens rotation is the identity except in rows and columns , where it has the block
For and , choose
when . Then
If both entries vanish, any angle works.
For the given matrix, first use
It gives
Then use
Thus is
All leading row entries are positive. The resulting QR decomposition by Givens rotations is
where
and is the matrix above. Since it is a product of transposed rotations, is orthogonal.
For a linear map , its rank is and its nullity is . The rank-nullity theorem states that, when is finite-dimensional,
To prove it, take a basis of and extend it to a basis
of . The vectors span . They are also linearly independent: if , then , and independence of the chosen basis forces every to vanish. Thus the rank is and the nullity is .
For the given subspace, row reduction of the coefficient matrix gives
Taking and therefore gives
Hence
is a basis of .
The characteristic polynomial is
To prove triangularizability, use induction on . The result is immediate for . Over , has a root , so has an eigenvector . Extend it to a basis. In this basis,
By induction, a change among the remaining basis vectors makes upper triangular. Thus the triangularization over an algebraically closed field gives
The minimal polynomial is the monic polynomial of least degree satisfying . To establish existence without quoting the Cayley-Hamilton theorem, let be an upper-triangular matrix similar to , with diagonal entries , and put
Then
The factors commute, so applying all of them successively lowers the invariant flag to zero:
Similarity gives the same polynomial identity for . Hence a nonzero monic annihilating polynomial of degree exists, and a least-degree one exists.
If and were two monic annihilating polynomials of the same least degree, then would be an annihilating polynomial of smaller degree unless it were zero. Thus the minimal polynomial is unique, and the minimal polynomial bound from a triangular invariant flag gives
Integer row and column operations give
Thus the Smith normal form is
The two relation vectors are the columns of the displayed matrix, so its cokernel is the presented module. Consequently
The Smith normal form of an integer matrix is a diagonal matrix
for which
with and . It exists and is unique.
The structure theorem for finitely generated modules over a principal ideal domain, specialized to , says that every finitely generated abelian group has a unique invariant-factor decomposition
Equivalently, its finite part is a direct sum of cyclic groups of prime-power order.