Write , a monic primitive polynomial. If with , grouping terms gives a factorization in the polynomial ring :
Both factors have positive degree, so is not an irreducible polynomial.
Conversely, if is a prime number, change variables by . The binomial theorem gives
Every coefficient except the leading one is divisible by , because for , whereas the constant coefficient is not divisible by . The Eisenstein criterion makes this polynomial irreducible over . The substitution is an invertible ring homomorphism, so is also irreducible over ; the Gauss lemma for polynomials transfers this to . Hence
With , the weighted inner product for the Chebyshev polynomials becomes
The identity and the vanishing of for positive integers give zero when , when , and when . Thus
For Gaussian quadrature, choose the distinct nodes as the zeros of the degree- orthogonal polynomial for the weight, here , and choose the weights as the weighted integrals of their Lagrange interpolation basis functions. If a polynomial has degree at most , divide it as , where both and have degree at most . Orthogonality makes the integral of zero, while its quadrature sum also vanishes; interpolation integrates exactly. This proves degree exactness. It is optimal because the squared nodal polynomial, of degree , has zero quadrature sum and strictly positive integral.
For , , so the nodes are . Their interpolation basis functions are
The weighted zeroth and second moments are and , and the first moment is zero. Integrating these three basis functions gives equal weights , hence the Chebyshev–Gauss quadrature rule
which is exact for every polynomial of degree at most .
Take a nonzero complex unital Banach algebra, with identity . The spectrum of an element is
The standard Banach algebra spectrum theorem states that it is a nonempty compact subset of , contained in the disk . Conversely, every nonempty compact set occurs: in the Banach algebra , the coordinate function has Banach algebra spectrum exactly , since has a continuous reciprocal precisely when . Thus the possible Banach algebra spectra are exactly the nonempty compact subsets of the complex plane.
For a nonconstant polynomial , factor over . Substitution gives
These factors commute. A finite commuting product is invertible exactly when every factor is invertible: if is invertible, its inverse commutes with each , and is a two-sided inverse. Hence belongs to the Banach algebra spectrum of exactly when some root belongs to , which is equivalent to . Constant polynomials give the same result directly, since . This proves the polynomial spectral mapping theorem:
For a closed unital Banach subalgebra , use the common identity . An inverse in is an inverse in , so . Let . Choose tending to . Then , and . If were outside , continuity of inversion in would give
where membership follows from closedness. This would make , contrary to the closed Banach algebra spectrum having its boundary inside it. Therefore and is approached by points outside that Banach algebra spectrum, proving
Continuity of inversion here follows, for example, by writing a nearby element as an invertible element times a norm-small perturbation and using the Neumann series. This is spectrum in a closed unital subalgebra.
To retain the original Banach algebra spectrum in a commutative subalgebra, take the resolvent-generated commutative algebra
Every generator commutes with and with every other generator: commuting invertible elements have commuting inverses, and their inverses commute with all elements commuting with them. commutativity persists on the algebra they generate and on its norm closure. For every , the required inverse is in by construction, so . The inclusion for unital subalgebras gives the reverse containment. Hence .
Finally, the Banach subalgebra generated by one element is , and it is commutative. Put and suppose its complement has a bounded connected component . The boundary of lies in . For , the maximum modulus principle on a bounded domain applied to any polynomial gives
Here is the spectral radius, and the equality uses the already proved polynomial spectral mapping theorem. Define . The displayed bound makes this well defined, even when two polynomials represent the same algebra element, and bounded on the dense polynomial algebra. Its continuous extension to remains linear and multiplicative, with and , so it is a character of an algebra. If were invertible in , applying to its inverse equation would give . Thus , contradicting .
There are therefore no bounded complementary components. A compact subset of the plane has exactly one unbounded complementary component: everything outside a sufficiently large disk is connected, and every unbounded component meets it. Consequently
Write the rational function in reduced form. We first exclude a finite pole in its dependent variable at a generic point . If this pole has order , the inverse equation
has a holomorphic right-hand side near , with a zero of order in at . Choosing a generic point avoids collisions of pole branches and zeros of the reduced numerator. The unique inverse solution has
To justify the leading order, first note ; if the first nonzero term has order , substitution in the inverse equation makes the right-hand side start at order , since the change caused by has order at least . Thus . Inverting produces an algebraic branch point of order . Away from the fixed coefficient exceptions, can be chosen throughout an open set on the pole curve; inverse solutions based at these different give different initial values at a nearby ordinary point. These are movable singularities of a complex differential equation, contradicting the hypothesis. Hence the denominator has no genuine -dependent factor: is a polynomial in , with rational functions of as coefficients.
Let its degree in be . Use the dependent coordinate on the Riemann sphere. Its equation is
If , the right-hand side has a pole of order at for generic . The same inverse-equation argument gives a movable algebraic branch point of order . It follows that , so the equation is Riccati, including its linear and constant special cases:
The requirement about the whole dependent-variable Riemann sphere is essential: examining only finite values would miss the branching at for degree at least three.
The linearization of a Riccati equation is particularly symmetric in the system
On a simply connected domain where the coefficients are holomorphic, its solutions are holomorphic. Direct differentiation gives
A nonzero initial vector never becomes the zero vector, by uniqueness for the linear differential equation, so the quotient is meromorphic. Choosing initial vector represents every finite initial value, and represents infinity. At fixed coefficient singularities, a single globally holomorphic vector solution need not exist; the assertion is local on ordinary domains, or on their appropriate continuation surface.
Finally, for any two finite solutions of the Riccati equation,
Use this identity on the four differences in
The logarithmic derivative of this cross-ratio is
Thus is constant wherever the expression is initially defined, and the identity extends as an identity of meromorphic functions. Distinctness of is preserved at ordinary points by uniqueness, interpreted on the Riemann sphere. Solving the constant cross-ratio equation gives the Riccati cross-ratio superposition
For this means ; gives , and gives . The constant is selected by the initial value of , so the formula represents every solution, with its denominator zeros interpreted as poles.
Let , with the two copies of the graph vertex set distinguished. In , the diagonal pairs form an independent set of size : for , their adjacency cannot hold in both a graph and its complement graph. There is another such diagonal set in . These two types lie in different components of , so their set union is independent. Thus
which proves the printed bound.
A stronger complement-pair capacity gain will make the strict inequality transparent. In words of length , choose a pattern of coordinates from and from . Match the th coordinate of the first type with the th of the second type, and put the same graph vertex label in each pair. This gives independent words for each pattern: if two label tuples differ, their differing pair has a nonedge in one of the two complementary graphs. Codes belonging to distinct patterns are mutually nonadjacent, since some coordinate lies in different components of the disjoint set union. Consequently
The inequalities show that its th root tends to two. Therefore
This strengthens, rather than changes, the bound requested in the PDF.
For a polynomial representation of a graph over a field , choose points and polynomials , where is a finite-dimensional vector space, such that
No condition is imposed at adjacent pairs. To bound a strong power, put its polynomials in disjoint variable blocks:
They lie in a polynomial space canonically identified with , of dimension . For an independent set of words, evaluation of their polynomials at their associated point tuples is a diagonal matrix with nonzero diagonal: distinct words have a nonedge coordinate, which supplies a zero factor. The polynomials in that independent set are therefore linearly independent, since evaluating any linear relation at each tuple forces its corresponding coefficient to be zero. Hence
This is the polynomial form of the Haemers rank bound, proved here by evaluations and tensor products rather than assumed.
For an explicit counterexample, let the graph vertices of be the five-element subsets of . Join distinct exactly when is odd. There are graph vertices. Over , take and
At the diagonal in the field. At a distinct nonedge the set intersection is even, so . These polynomials lie in the twenty-dimensional space spanned by , proving .
Represent the complement graph over , using the same indicator vectors and
Its evaluation at is . The diagonal value is modulo three. Distinct nonedges of are edges of , so the set intersection size is one or three. Their evaluations are respectively zero and modulo three. The polynomials belong to the space spanned by the squarefree quadratic monomials , , of dimension . Therefore .
The graph capacity inequalities are real-number bounds regardless of which field supplies the polynomial representation of a graph. Combining them with the stronger set union lower bound gives
since . This proves nonadditivity of Shannon capacity for the graph just defined, with both individual upper bounds calculated explicitly.