A complex square matrix is a normal matrix if it commutes with its conjugate transpose:
By unitary diagonalization of a normal matrix, there are a unitary matrix and a diagonal matrix such that
The matrix 2-norm is invariant under multiplication by unitary matrices, so
For a diagonal matrix,
with equality on a coordinate vector belonging to an eigenvalue of greatest modulus. Hence
the matrix 2-norm of a normal matrix.
Let be the Toeplitz antisymmetric tridiagonal matrix with , , and zero diagonal. Fixed homogeneous endpoint values give the homogeneous update
The hint gives the eigenvalues
Because each is purely imaginary, for every real , so the left matrix is invertible. The two matrices are polynomials in and therefore have the same orthonormal eigenvectors. The amplification matrix
has eigenvalues
The numerator and denominator are complex conjugates, so . Moreover, the common orthonormal eigenbasis makes a normal matrix. By the matrix 2-norm of a normal matrix,
for every . Thus the Crank-Nicolson centered-advection scheme on a finite interval is unconditionally stable:
Insert the Fourier mode
into the leapfrog advection scheme. This gives
and hence the amplification polynomial
Its roots are
If , the square root is real for every , and
If , choosing makes the roots non-real multiples of with reciprocal moduli, one of which exceeds one, so the method is unstable.
The endpoint requires care. At the polynomial is
so a generic mode has the form and grows linearly. It satisfies the weaker test often quoted in elementary Fourier analysis, but it violates the root condition for a multistep method because the unit-modulus root is repeated. Therefore the rigorous uniform stability range for arbitrary two-level initial data is
If “stable” is being used only for the non-amplification condition on root moduli, the conventionally quoted range is , with a defective marginal endpoint rather than a uniformly stable case.

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