First work over a field of characteristic different from two. If a nonzero symmetric bilinear form had for every vector, polarization would give
a contradiction. Hence choose with . Every decomposes uniquely as
with the second summand orthogonal to . Induct on the orthogonal complement to obtain a diagonal basis. If the restricted form becomes zero, any basis of that remaining space completes the diagonalization. In this basis the rank of a quadratic form is exactly the number of nonzero diagonal coefficients; the remaining basis vectors span its radical of a bilinear form.
Over the reals, rescale the nonzero basis vectors so the diagonal entries are copies of , copies of and zeros. Define the signature of a quadratic form by , so . To prove it is basis independent, note that is the largest dimension of a linear subspace on which the form is positive-definite. The positive coordinate linear subspace attains dimension ; on any other positive linear subspace, projection to those positive coordinates is injective, since its kernel has nonpositive quadratic value. Thus its dimension is at most . The same argument for the negative form characterizes . This proves Sylvester's law of inertia and that the signature is well-defined.
Let and be positive and negative normalized basis vectors, and let be the radical of a bilinear form. The span of and for is a totally isotropic subspace: all mutual bilinear pairings vanish. Its dimension is . Conversely, project any totally isotropic subspace to the nondegenerate positive-plus-negative quotient. The projected linear subspace is still null, and its projections to both the positive and negative coordinate spaces are injective: a vector with one component zero would have strictly signed quadratic value unless it vanished. Its dimension is therefore at most , while the kernel of the quotient map on has dimension at most . Hence
This proves both construction and sharpness of the maximum dimension of a totally isotropic subspace.
For the five-variable example, the symmetric coefficient matrix is
Its cyclic structure makes the vectors , , eigenvectors with eigenvalues . Thus the eigenvalues are
Their product is , and three are positive and two negative. Therefore
The real and imaginary parts of each conjugate pair of eigenvectors give the corresponding real two-dimensional eigenspaces, consistent with the real inertia calculation.
Associate to the symmetric bilinear form . If is identically zero, every basis is diagonal. Otherwise choose with . Every has the decomposition
whose second term lies in . Thus , with no cross term in . Induction on dimension gives a diagonal basis. Rescaling its nonzero entries reduces the form to
with additional zero coordinates. Define the rank of a quadratic form and its signature . Rank is intrinsic, since it is the rank of , equivalently . Also is the greatest dimension of a subspace on which the restriction of is a positive-definite quadratic form: any such subspace intersects the negative-plus-zero coordinate space only at zero, so its dimension is at most , while the positive coordinate space attains . The corresponding negative statement identifies . This proves the basis independence of and , the Sylvester's law of inertia conclusion.
For a totally isotropic subspace on which vanishes, polarization identity also makes vanish on . Quotient by the radical of a bilinear form. In the resulting nondegenerate form, projection of an isotropic subspace to either the positive or negative coordinate space is injective, so its dimension is at most . Consequently . The radical of a bilinear form together with the vectors , , attains this bound. The maximum dimension of a totally isotropic subspace is therefore
The criterion for membership in a diagonal basis follows similarly: a nonzero vector can belong to a diagonal basis if it has nonzero quadratic value, by the same orthogonal splitting, or if it lies in the radical of a bilinear form, by choosing a radical basis containing it. An isotropic vector in a diagonal basis must be orthogonal to every basis vector, and hence must lie in that radical. For the specified form, its radical is the -axis, giving exactly
The zero vector never belongs to a basis.