Proof
Prerequisite proofs used below
The theorem and its prerequisites
Every nonconstant polynomial has a complex root; consequently every degree- complex polynomial is a product of linear factors, counted with multiplicity. We prove this conclusion through Goursat, the Cauchy estimate and Liouville, with the prerequisites given below.
Holomorphic means complex differentiable at every point of an open set; entire means holomorphic on all of . The elementary foundations used below are real one-variable integration and its chain rule, continuity and differentiation of polynomials, the complex modulus laws, and compactness in the Euclidean plane (including shrinking compact triangles, uniform continuity and a Lebesgue number for a compact cover). These real-analysis and topology foundations are explicitly prerequisites. No complex polynomial-root theorem, maximum-modulus theorem, analytic power-series representation, identity theorem, residue theorem or argument principle is assumed.
Complex differentiability implies continuity, since . Expanding a product difference quotient gives . Where ,
Thus products and nonvanishing quotients of holomorphic functions are holomorphic. In particular is holomorphic away from , and a root-free polynomial has an entire reciprocal. These facts use difference quotients, not a polynomial-root or regularity theorem.
1. An integral records both a path and its orientation
A piecewise curve is a continuous map that is continuously differentiable on finitely many subintervals, with one-sided derivatives at the joins. It is closed when . Its length is . A contour integral of continuous along it is
with real and imaginary parts integrated separately. The differential includes the direction of motion; replacing it by would define a different integral.
A piecewise increasing change of parameter preserving endpoints leaves the integral unchanged by substitution. Reversal changes its sign. Concatenating two compatible curves adds their integrals. These statements also allow zero-speed pieces. They do not require the curve to be injective.
Estimation lemma. If on the curve, then
Indeed, the modulus of a real-parameter integral is at most the integral of the modulus, and . This simple inequality is the main tool for showing that auxiliary arcs contribute nothing in a limit.
Worked example. On the positively oriented circle , , with ,
For the integrand times is . Otherwise it is , whose integral vanishes. The answer for is independent of radius, but changes sign if orientation is reversed.
2. Primitives turn path integrals into endpoint differences
A primitive of on an open set is a holomorphic function there with . The real chain rule applied on each smooth piece gives
for every contour in . Hence a function with a primitive has zero integral around every closed contour in .
Conversely, on a domain , suppose continuous has zero integral around every closed contour. Open connected subsets of the plane are polygonally connected. Fix and define as the integral from to along any polygonal path in . Closed-path cancellation makes it path independent. For sufficiently small , the final straight segment from to stays in , and
by continuity. Thus . The same construction works if polygonal closed paths alone have zero integrals; the resulting primitive then handles all contours.
3. Goursat's triangle argument: no continuity of the derivative assumed
Theorem. If is holomorphic on an open set containing a closed triangle , then its integral around the positively oriented boundary of is zero.
Proof. Subdivide by joining side midpoints into four triangles. Interior edge integrals cancel, so the outer integral is the sum of four child integrals. At least one child has integral modulus at least . Repeat inside such a child, obtaining nested closed triangles , diameter , perimeter , and
Compactness and shrinking diameters give one common point . Differentiability at says
The constant and linear terms have primitives, so contribute zero on the triangle boundary. For any , eventually throughout . Since , the estimation lemma gives
Thus . As is arbitrary, . No continuity of was used. ∎
Corollary: a primitive on each disk. If is holomorphic on a disk , fix its centre and set . For sufficiently close, the triangle with vertices lies in . The triangle theorem gives . The limit calculation of §2 yields . Consequently all closed-contour integrals in the disk vanish. The same argument works on any open convex set.
4. Homotopy and what “no hole” actually means
A fixed-endpoint homotopy between paths is a continuous map with , , and constant in . It deforms one path into the other without leaving . A domain is simply connected if every closed path can be contracted to its basepoint by such a homotopy.
Homotopy invariance. If is holomorphic on , and two piecewise paths in are fixed-endpoint homotopic there, their integrals agree.
Proof using only local primitives. The compact image of is covered by finitely many disks on which has primitives. By the Lebesgue-number property and uniform continuity, subdivide the parameter square into a fine rectangular grid so that the image of each closed cell lies in one such disk. Join the images of adjacent grid vertices by straight segments. For each cell these segments lie in its disk because disks are convex. Its polygonal boundary integral is zero by its primitive. Sum over cells: internal segments cancel with their reversals. On the bottom and top edges, each original path subarc and its replacing straight segment lie in the same disk and have the same endpoints, hence the same integral by the local primitive. The side segments vanish because endpoints were fixed. What remains is the bottom integral minus the top integral. This proves the claim even if the homotopy's intermediate paths are not differentiable. ∎
The open set for the circular deformation
In the Cauchy proof, let be the original open holomorphy neighbourhood of , and let . Choose . The correct holomorphy set for is , including the outer circle; the open disk alone would exclude that circle. This open set includes the boundary circle, and the following inequalities justify the deformation inside it.
Put , , and . For ,
Thus the whole compact homotopy image lies in . The grid/local-primitive proof works for this free homotopy of closed loops: , so the two polygonal side tracks are identical, have opposite boundary orientations and cancel. They need not be constant. The top and bottom circles are piecewise ; no differentiability of the intervening homotopy is needed. This supplies exactly the domain and moving-basepoint step used next.
1. A boundary integral determines an interior value
For and , orient the circle counterclockwise. Suppose is holomorphic on an open neighbourhood of the closed disk . For every with ,
The denominator is never zero on . The formula is an interior-value theorem; it does not assert this value for an exterior point or a point on the contour.
Proof. Choose with . The outer circle deforms to the small circle without passing through : use centres and radii . Each moving circle encloses and stays in the original disk. Apply the grid/local-primitive proof of C02 to on the punctured disk. Although the moving basepoint is not fixed, its two side tracks are identical and cancel, so closed-loop integrals are unchanged. Hence
The final term has modulus at most , which tends to zero by continuity at . This proves the formula. ∎
This proof does not presume that has a holomorphic extension at ; that fact is a consequence of the regularity obtained below.
The first derivative, with a uniform bound
Only the first Cauchy derivative estimate is needed for Liouville. For an interior point of a fixed circle , set . When , subtraction of the two Cauchy formulas gives the difference quotient kernel
Its difference from is
If and , the estimation lemma bounds the error after division by and integration by , which tends to zero. Hence . For a circle of radius centred at , this gives . Repeating the same argument gives the higher-order formula below; Liouville uses only the first-order estimate.
2. All higher derivatives and their bounds
For in the open disk the distance from to the contour is positive. On a sufficiently small disk around , difference quotients of the kernel converge uniformly in to . The estimation lemma permits passing that limit under the contour integral. Repeating this argument yields
The uniform kernel argument proves the existence of these derivatives; it does not assume was initially . The same formula shows they are continuous locally because the denominators stay uniformly separated from zero.
On a circle centred at of radius , put . Length estimation gives the Cauchy estimates
The radius must belong to a disk on which the function is holomorphic up to a neighbourhood of its boundary. Taking a larger radius through a singularity is invalid.
Liouville and the polynomial-root theorem
For an entire function, the preceding estimate is available at every radius. Applying it to a bounded entire function gives Liouville; applying Liouville to a polynomial reciprocal proves root existence.
Liouville's theorem. A bounded entire function is constant. If on , apply the estimate on a disk of arbitrary radius about any : . Sending gives , so the function is constant on the connected plane.
Fundamental theorem of algebra. Every nonconstant complex polynomial has a complex root. If had no root, would be entire. Its leading term implies as , so is bounded outside a large disk; continuity gives boundedness on the remaining compact disk. Liouville makes constant, contradicting the degree of . Repeated division by linear factors then factors every degree- polynomial into exactly linear factors counted with multiplicity.
Elementary details of the polynomial contradiction
For completeness, a function with on is constant: along the real and imaginary parts of have derivative zero, so the real mean-value theorem gives .
Write with , , and . For ,
If had no root, its reciprocal would be continuous everywhere and holomorphic, since
The displayed growth bound makes bounded outside the radius- disk. It is bounded on the remaining closed disk by compactness and continuity. Liouville makes a constant, which is nonzero, forcing to be constant, a contradiction. Thus a root exists.
Finally gives , where has degree and leading coefficient . Apply the root theorem to if it is nonconstant and induct on degree. After exactly divisions the remaining factor is the nonzero constant . Degree and the product identity give exactly linear factors with multiplicity. This also proves the complex splitting assertion needed by finite-dimensional spectral or Jordan arguments; it does not assert splitting over an arbitrary real or other ground field.
All spaces are finite-dimensional over or .
1. A metric adds structure not present in an abstract basis
An inner product satisfies , linearity in the first variable, and for . The norm is , and orthogonality means . Over the conjugation has no effect. In standard complex coordinates, , where means conjugate transpose.
For , put . Expanding yields the Cauchy–Schwarz inequality
with equality exactly when are dependent. The triangle inequality follows by expanding and applying this bound to the cross term. Positive definiteness, not mere symmetry, is essential here.
Gram–Schmidt converts an independent list to an orthonormal list spanning the same successive subspaces:
Each is orthogonal to previous and is nonzero because otherwise would lie in the span of its predecessors. A zero or dependent input requires omitting a vector rather than dividing by zero.
For a subspace with orthonormal basis , define
Then and , so and the projection is independent of the chosen orthonormal basis. For every ,
proving is the unique closest point. Orthogonality gives both existence and optimality.
2. Algebraic dual versus Hermitian adjoint
Every linear functional can be written uniquely as for a vector . In an orthonormal basis , take and check on basis vectors. This representation depends on the inner product. Over the correspondence is conjugate-linear, not a complex-linear identification with the algebraic dual.
For , its adjoint is uniquely defined by
Functional representation proves existence and uniqueness for each ; conjugations in the convention show is linear. In orthonormal bases its matrix is . By contrast, the algebraic dual map of C01 has ordinary transpose in dual bases and goes . These are related constructions, not identical definitions.
Evaluation in the defining identity gives
Moreover
The first follows because is perpendicular to every exactly when . Apply the first to and take orthogonal complements to obtain the second in finite dimensions.
3. Normality supplies an orthonormal eigenbasis
An endomorphism is self-adjoint if , unitary (orthogonal over ) if , and normal if . Self-adjoint and unitary maps are normal. A normal map need be neither.
If is normal, then , because the squares are determined by . For normal , the operator is also normal. Thus
If is an eigenvector, its orthogonal complement is invariant under both and by the adjoint identity. Their restrictions to that complement remain adjoints and commute, hence are normal.
Complex spectral theorem. A complex endomorphism is normal exactly when it admits an orthonormal eigenbasis.
Proof. In nonzero dimension the characteristic polynomial has a complex root, so choose and normalize an eigenvector. The preceding orthogonal-complement argument reduces to a normal operator on a space of one less dimension. Induction gives the orthonormal eigenbasis. Conversely a diagonal matrix in an orthonormal basis commutes with its conjugate transpose, so is normal. ∎
A self-adjoint eigenvalue is real: gives . A unitary eigenvalue has modulus one because norms are preserved. These are necessary spectral properties, not sufficient conditions for an arbitrary matrix to be self-adjoint or unitary.
Real symmetric spectral theorem. A real self-adjoint map has an orthonormal real eigenbasis. For existence of a real eigenvalue, complexify its real symmetric matrix. Any complex eigenvalue is real by the previous calculation. For a complex eigenvector, at least one of its real and imaginary parts is a nonzero real eigenvector for that real eigenvalue. Normalize it and induct on its invariant real orthogonal complement. A real normal operator need not have real eigenvalues: a plane rotation is the standard counterexample.
4. Positivity and the singular value decomposition
A self-adjoint is positive semidefinite when for all , and positive definite when the inequality is strict for nonzero . In an orthonormal eigenbasis these conditions are equivalent to all eigenvalues being nonnegative or positive, respectively. This proves existence and uniqueness of a positive semidefinite square root: replace each nonnegative eigenvalue by its nonnegative square root. For uniqueness, any positive semidefinite with commutes with and preserves each -eigenspace; on that eigenspace its nonnegative eigenvalues must all equal the selected square root, so the restriction is that scalar times the identity.
For , is self-adjoint and nonnegative because
Choose an orthonormal eigenbasis with eigenvalues , putting the positive ones first. For , set . The adjoint identity shows these are orthonormal. Extend them to an orthonormal basis of . If , the norm identity gives . Therefore in these bases is rectangular diagonal, and in standard coordinates
This is the singular value decomposition. The positive are singular values, their number is the rank, and zero singular values encode the kernel. The definition is compatible with unequal domain and codomain dimensions.
Worked example. For over , has orthonormal eigenvectors and , with eigenvalues two and zero. The singular values are ; the image direction is . The eigenvalues of itself, one and zero, are not its singular values.
5. Exercises
P01 — Foundation. Orthonormalize in .
P02 — Core. Project onto and compute the squared distance.
P03 — Core. For , find the algebraic transpose and Hermitian adjoint. Decide whether is self-adjoint.
P04 — Core. Orthogonally diagonalize and construct its positive definite square root.
P05 — Diagnosis. Does having real eigenvalues imply a real matrix is symmetric? Give a counterexample.
P06 — Proof. Prove that an orthogonal projection satisfies . Conversely prove that a self-adjoint idempotent is the orthogonal projection onto its image.
P07 — Core. Find singular values and rank of .
P08 — Proof. Show that a normal nilpotent operator on a complex inner-product space is zero.
P09 — Extension. For an invertible map with , prove its induced Euclidean operator norm is its largest singular value, and that .
6. Full solutions
P01. First . Subtracting the projection from gives of norm , hence . Their dot product is zero and each norm is one.
P02. The projection is . The residual is , orthogonal to , and the squared distance is three.
P03. , while . Neither equals , and it is not self-adjoint. Complex conjugation distinguishes the adjoint from the algebraic dual matrix.
P04. Unit eigenvectors , have eigenvalues three and one. With , . Its positive square root is .
P05. has real eigenvalues one and two but is not symmetric. An arbitrary eigenbasis need not be orthonormal; real spectrum alone is insufficient.
P06. Orthogonal decomposition gives . For , with in the image and in its orthogonal complement, , so . Conversely an idempotent gives . If is self-adjoint, for . Thus the sum is orthogonal and is the orthogonal projection.
P07. , so the singular values, in decreasing order, are four and three. Both are positive, so rank is two. The extra codomain direction does not add a third domain singular value in this convention.
P08. By the complex spectral theorem, is unitarily diagonalizable. A nilpotent eigenvalue satisfies , hence . Its diagonal matrix is zero, so .
P09. Write , so and . The largest ratio on unit vectors is , attained at a corresponding right singular vector. Invertibility makes all singular values positive; the inverse SVD has singular values , so its norm is .
7. Summary
Inner products give canonical orthogonal complements and adjoints relative to the chosen metric. Normality is exactly orthonormal diagonalizability over ; real self-adjointness gives the real symmetric theorem. Applying it to yields singular values for every rectangular map. Bilinear forms use a different basis-change law, developed next.