We prove the required Hahn-Banach theorem for a seminorm directly. First suppose the vector space is real. At an intermediate extension stage, let be a linear functional with , and let . Extending to amounts to choosing . The upper domination requires
The interval is nonempty: for all ,
Its endpoints are finite since inserting zero gives bounds and , while every lower candidate is below every upper candidate. Choose in the interval and put . For , the upper bound with proves . For , writing and applying the lower bound with proves the same inequality. The case is already known. Applying this domination to and using gives .
Partially order all dominated linear functional extensions of the original by extension of their domains and values. They form a nonempty set. The union along any chain is a well-defined dominated linear functional on a vector subspace, so every chain has an upper bound. The Zorn lemma gives a maximal extension. If its domain were not , the preceding one-dimensional construction would enlarge it, a contradiction. Thus the required extension exists on .
For a complex vector space, apply the proved real result to on the underlying real vector subspace. Let be the resulting real linear functional, with , and set
It is additive and real-linear, and , so it is complex-linear. On , the identity proves . Choose with and when . Then
The bound is immediate if . This proves the real and complex seminorm forms of Hahn-Banach theorem without invoking any version of that theorem.
For the distance to a set assertion, let . Define on the linear functional . The decomposition is unique because , and for ,
For the bound is immediate. Apply the just-proved Hahn-Banach theorem with to get , , , and . Choose with . Since
and , passage to the limit gives . Thus . This version of the Hahn-Banach distance formula needs neither a closed nor an attained distance to a set.
For the Banach limit construction below, take the real l-infinity sequence space, let be its left shift on bounded sequences, put , and let . This is a vector subspace and its distance to a set from determines the construction.
There is a genuine conflict in the printed coefficient assumptions: no uniformly positive coefficient in a zero-boundary Sobolev space exists. A function cannot also obey almost everywhere. Indeed, the Lipschitz truncation has , so Lipschitz truncation preserves zero-boundary Sobolev spaces, giving . But would be the nonzero constant . Its zero gradient contradicts the Poincaré inequality in the zero-boundary Sobolev space. Thus the literal coefficient class is empty.
For the meaningful uniformly elliptic problem, take with , and impose the Dirichlet boundary condition on the unknown and test functions: . Additional regularity of is harmless, but a zero trace for must be removed. The divergence-form elliptic operator is . Integration by parts defines the symmetric bounded bilinear form
In particular,
Here is the first Dirichlet Laplacian eigenvalue on the unit square; the Poincaré inequality follows, for example, by applying the one-dimensional inequality in each coordinate and adding. Thus is coercive in the gradient norm on , and the Dirichlet realization of is a positive definite symmetric operator. On its operator domain, .
The required functional and weak equation are
Because , the right side is a bounded linear functional by the Cauchy-Schwarz inequality and Poincaré inequality. The Lax-Milgram theorem gives a unique weak solution, and part (b) proves that it uniquely minimizes . These formulas prove the intended conclusion under the repaired coefficient hypothesis; under the literal hypothesis there is no coefficient to which the conclusion can be applied.
To prove that trace is the unique normalized cyclic linear functional, let be the matrix units. For , whereas , so the assumed identity for the linear functional gives . Also, and , giving . Write this common value as . Since the matrix units form a basis,
For the same conclusion follows immediately from the one-dimensional basis . Finally, ; if this equals , then over either specified field. The normalization makes exactly the trace.
Over the complex numbers, every finite-dimensional representation of a solvable Lie algebra has a basis in which every representing matrix is upper triangular. The Lie theorem is often stated first as the existence of a common eigenvector in every nonzero finite-dimensional Lie algebra representation of a solvable Lie algebra. Applying that assertion successively to quotient representations gives an invariant complete flag, and hence the upper triangular form. The same proof works over any algebraically closed field of characteristic zero.
We prove the common eigenvector assertion by induction on , writing the action as . The zero Lie algebra is immediate. If is solvable, its derived series of a Lie algebra shows that . Choose a codimension-one ideal of a Lie algebra containing , and choose . By induction there are and a linear functional such that for all .
Let be the span of . If , the first of these vectors form a basis, and is -invariant. We claim that for each ,
For this is the definition of . For the induction step, use and . Applying the induction hypothesis to both and proves the claim. Consequently is -invariant, and every acts on by an upper triangular matrix with all diagonal entries .
Since both and preserve , the matrix trace of their commutator on is zero. The claim applied to gives
Here characteristic zero is essential: in the field, so . Now the common weight space
is nonzero and -invariant. Indeed, for ,
An endomorphism of a nonzero finite-dimensional complex vector space has an eigenvector, so choose an eigenvector of in . It is a common eigenvector for . This proves the Lie theorem.
For the printed matrices in characteristic , , and there is no common eigenvector. Index the standard basis by . The cyclic entry in the PDF gives
The diagonal eigenvalues of are distinct in . Thus every eigenvector of is a scalar multiple of a single . Since , is never a scalar multiple of , proving the assertion even when is not an algebraically closed field.
For ,
At the cyclic boundary,
Hence . The two-dimensional Lie subalgebra has derived algebra , whose own derived algebra is zero, so it is solvable. It nevertheless has no common eigenvector, including after extending to its algebraic closure. This is a failure of Lie theorem in positive characteristic. In the proof above, the obstruction is precisely that can vanish as a scalar in .
The derived algebra of a complex solvable Lie algebra is nilpotent. First suppose . By the Lie theorem, put every element of in upper triangular form. The diagonal of a commutator of upper triangular matrices is zero, so consists of strictly upper triangular matrices. The Lie algebra of all such matrices is a nilpotent Lie algebra: if consists of matrices whose entries vanish whenever , then
Therefore the lower central series of a Lie algebra of reaches zero. Alternatively, every element of is a nilpotent linear map, and the Engel theorem states that a finite-dimensional Lie subalgebra consisting of nilpotent linear maps is a nilpotent Lie algebra.
For an abstract complex solvable Lie algebra , apply the preceding result to its Adjoint representation. The Lie algebra is nilpotent. Since is central in , some term of the lower central series of a Lie algebra of lies in that central ideal; the next term is zero. Thus itself is nilpotent.
Conversely, every nilpotent Lie algebra is solvable, since its derived series of a Lie algebra is contained term by term in its lower central series of a Lie algebra. If is nilpotent, it is therefore solvable, and is Abelian. More directly, the derived series of a Lie algebra of , after its first term, is the derived series of a Lie algebra of . Consequently the derived algebra nilpotence criterion is
Schur's lemma says that a nonzero intertwiner between irreducible representations is an isomorphism; over , every endomorphism of a finite-dimensional irreducible representation is scalar. To prove the Schur lemma, let be a intertwining operator between irreducible representations. Its kernel and image of a linear map are invariant. If , irreducibility forces and . This proves the first assertion over any field. In particular the endomorphisms of an irreducible representation form a division ring.
When is finite-dimensional over an algebraically closed field, an endomorphism has an eigenvalue . The endomorphism has nonzero kernel. By the first assertion it must be zero, so . Consequently, for complex finite-dimensional irreducible representations, the space of intertwining operators has dimension zero for nonisomorphic representations and dimension one for isomorphic representations.
Every finite-dimensional representation of a complex semisimple Lie algebra is completely reducible. We prove the Weyl complete reducibility theorem using the allowed Casimir operator facts, without assuming a splitting in advance. For dual bases with respect to the Killing form, the Casimir element
is central in the universal enveloping algebra. Hence its Casimir operator commutes with the action on every Lie algebra representation and is compatible with subrepresentations, quotient representations, and intertwining operators. On the trivial Lie algebra representation it acts by zero. On every nontrivial finite-dimensional Irreducible Lie algebra representation it acts by a nonzero scalar.
For clarity, the last fact can be expressed by the Casimir eigenvalue formula: on an irreducible with dominant integral weight , the scalar is , with the inner product induced by the Killing form and the half-sum of positive roots. On the real span of the weights this inner product is positive definite, and the scalar is positive for . For a semisimple Lie algebra with several simple factors the scalars add, so a nontrivial representation still gives a nonzero scalar. These are properties of the Casimir operator being used here.
First establish Casimir splitting of a trivial quotient. Suppose
is a short exact sequence of finite-dimensional Lie algebra representations, with trivial quotient. The generalized eigenspaces of are invariant, so
Each with maps to zero under : applying a sufficiently large power of and using gives . Thus .
Take a composition series of a module of . The Casimir operator is nilpotent on , so its scalar on every irreducible composition factor is zero. The stated Casimir operator property makes every such factor trivial. In a basis adapted to the composition series of a module, the image of on therefore consists of strictly upper triangular matrices, so that image is solvable. The allowed fact that a semisimple Lie algebra acts trivially on every one-dimensional representation implies that is a perfect Lie algebra: otherwise a nonzero linear functional on would define a nontrivial one-dimensional Lie algebra representation. Thus , and its image is consequently a perfect Lie algebra too. A perfect Lie algebra that is also a solvable Lie algebra is zero, since its derived series of a Lie algebra is constant until it vanishes. Hence acts trivially on . Choose with . The map is an invariant section, proving the split short exact sequence assertion.
Now let be any nonzero subrepresentation. On the Hom representation the action is
Consider the invariant subspace
Restriction produces a short exact sequence
Surjectivity follows by extending to a linear map on . The quotient is trivial, because commutes with the action on . The preceding Casimir splitting of a trivial quotient yields an invariant with . Thus
and is invariant. The zero subrepresentation also has a complement. Repeatedly splitting off an irreducible subrepresentation now gives a direct sum of irreducibles, proving the Weyl complete reducibility theorem.
A derivation of a Lie algebra is a linear map satisfying the Leibniz rule
The space is a vector subspace of . Equip it with the commutator . Expanding the Leibniz rule twice gives
Subtracting proves that is again a derivation of a Lie algebra. Antisymmetry and the Jacobi identity hold for the commutator in every associative endomorphism algebra, so this defines the derivation Lie algebra.
The Jacobi identity says that is a derivation of a Lie algebra. Moreover, for ,
so
This makes an ideal of a Lie algebra in .
Finally suppose is semisimple. Let act on by . The Weyl complete reducibility theorem supplies an invariant complement to . For , invariance gives , while the ideal identity above gives . Their intersection is zero, so for every . The center of a Lie algebra of a semisimple Lie algebra is zero, hence for every , and . Therefore
Every derivation of a Lie algebra is inner, and the element giving it is unique because the center of a Lie algebra vanishes.
Invertibility is stable under sufficiently small perturbations, and inversion is continuous. Let be the identity of the complex unital Banach algebra , with its submultiplicative algebra norm. For , completeness makes the Neumann series
converge in . Multiplying either side of the partial sums by gives , which tends to , proving that the sum is a two-sided inverse.
Fix , the group of invertible elements of a Banach algebra. If , then
so the Neumann series makes invertible. This proves that is open. It also gives a local bound
We retain here so the estimate does not silently assume a normalized identity. The inverse identity
then implies
This proves continuity of inversion in a Banach algebra.
For a unital Banach algebra, the spectrum of an element is
For a nonunital Banach algebra, use its unitization of an algebra with multiplication and norm
It is a unital Banach algebra, with identity , and define . In this nonunital convention, belongs to the spectrum: the scalar coordinate of is zero, so it cannot be invertible in .
The spectrum is nonempty and compact. It suffices to work in a nonzero unital Banach algebra, since unitization reduces the other case to this one. The group of invertible elements of a Banach algebra is open, so the complement of the spectrum of an element is open. For , the Neumann series gives
Thus is closed and lies in , hence is compact.
For nonemptiness of the Banach-algebra spectrum, suppose that were defined on all of . At any , factoring gives a locally convergent power series
For every bounded linear functional , the scalar function is therefore entire. The bound at infinity makes it bounded outside a disk, while continuity makes it bounded on the disk. By the Liouville theorem, it is constant; since it tends to zero at infinity, it is identically zero. The version of the Hahn-Banach theorem used here says that bounded linear functionals separate points of a normed vector space: if , there is with . Consequently for every , contradicting . This proves the assertion.
Every nonzero complex unital normed division algebra is algebraically and topologically isomorphic to . This is the Gelfand-Mazur theorem; completeness is not needed in its statement. Let be a normed division algebra, and take its completion of a normed space using the algebra norm to obtain a unital Banach algebra . Submultiplicativity extends multiplication continuously to the completion, and the original identity remains its identity.
For , the spectrum of an element of in contains some . If in , the division-algebra assumption supplies an inverse in , which is still an inverse in . This contradicts . Therefore . The map is a bijective complex algebra homomorphism, and
It and its inverse are continuous; when , it is an isometry.
A complete algebra norm on a function algebra dominates the supremum norm, even before continuity of point evaluations is known. Let be the given algebra of functions. Form the same artificial unitization even if already has an identity. For each , the algebraic map
is a unital multiplicative complex linear functional. No continuity has been assumed. Since , the element cannot be invertible: applying to an inverse equation would give . Hence , and the spectrum bound already proved yields
Taking the supremum proves the supremum bound for a complete function-algebra norm:
In particular every is bounded, and every point evaluation is a bounded linear functional of norm at most . This is an instance of automatic continuity of characters: a character of an algebra on a Banach algebra is bounded because its value at any element belongs to that element's spectrum.
A useful comodule natural transformation formula determines from a single linear functional. Define
using the regular right comodule . For any vector space , the cofree right comodule has coaction . Naturality with respect to all maps gives
The coaction is itself a morphism of right comodules. Its naturality equation, followed by , therefore gives
This derivation works for all comodules, not merely finite-dimensional ones.
The monoidal equation , evaluated on the two regular comodules and followed by their counits, implies
The unit equation gives . Thus is a unital algebra homomorphism over a field . In addition, the -colinearity of gives the useful intertwining relation
This fixes the orientation of relative to .
For the convolution product for coalgebra maps, define . Multiplicativity of and the two antipode identities show
Consequently
Coassociativity and the two convolution identities verify both composites directly. Since was a -comodule morphism, its linear inverse is also a -comodule morphism. Inverting the naturality and monoidal equations shows that the inverses form a monoidal natural transformation . Every such monoidal transformation is therefore invertible, without requiring a bijective antipode.
Use right comodules with coaction . Fix the convention that is induced by and by . We classify lax monoidal structures first; the strong case is identified at the end.
Every natural transformation of the indicated tensor bifunctors is determined by a linear functional , and its components have the comodule tensor transformation formula
To prove the assertion, set . On the cofree comodules , naturality with respect to forces the component to act as on the two factors. Apply naturality to the pair of coactions , , then apply their counits. This yields the formula. Conversely the formula is plainly natural with respect to comodule morphisms, and recovers from the regular comodules.
It remains to impose exactly three kinds of equations. First, the component must be -colinear from the tensor with product to the tensor with product . Expanding its two coactions gives (C), the multiplication compatibility for a comodule tensor transformation
Necessity follows by taking and applying the two counits; sufficiency follows by substituting the identity into the coaction formula for arbitrary .
Second, the two unit triangles in the preceding part are exactly (U):
Here is the common algebra unit. These identities are forced by the regular comodule and sufficient by the counit law.
Third, expand the associativity diagram on three right comodules. The two scalar factors, after their counits are removed, are (A):
The product in this expression is , because the intermediate arguments and are source-tensor objects. Necessity follows from the three regular comodules; sufficiency is the same substitution for arbitrary coactions. Using (C), the same condition can equivalently be written with the target product :
This is the normalized bialgebra scalar cocycle equation for that convention.
Thus the required structures correspond bijectively to all linear maps satisfying (C), (U) and (A). No convolution invertibility has been imposed for a lax monoidal functor structure. If “monoidal” is required to mean strong, add precisely that is invertible under the convolution product for coalgebra maps on . Its convolution inverse supplies the inverse component by the same displayed formula; conversely natural inverse components recover a convolution inverse by the regular-comodule argument. In that case (C) is the explicit bialgebra cocycle twist relation
This also records which multiplication lies on each side of the twist. Interchanging the names of interchanges the two tensor conventions, rather than silently changing the equation.
For a concrete lax example, take the two-dimensional bialgebra with basis , product , and , . Set and , . Normalization and (C) hold, and (A) follows by checking the eight basis triples: triples involving reduce to normalization, and the triple has both sides zero. But the tensor component is zero, so this lax monoidal functor is not strong.
The dual space here is the algebraic dual space , consisting of every linear functional; no topology or boundedness is imposed. For a basis , define . These are linear functionals satisfying . Evaluating on each gives , proving linear independence. Conversely, for every ,
This proves spanning and hence proves, without assuming a dimension theorem, that the dual basis is a basis and .
The canonical bidual evaluation map is
Its definition makes no choice of basis and it is linear. If , one coordinate functional is nonzero on , so is injective. For any , choose . Expanding in the dual basis gives , proving surjection explicitly. Thus is an isomorphism.
If is any basis of , its dual basis in exists by the result just proved. Put . These vectors form a basis of , and . Every basis of the finite-dimensional dual is a dual basis, of a uniquely determined basis of .
For a separating subspace of an algebraic dual , choose a basis of . The linear map is injective because separates nonzero vectors. The rank-nullity theorem implies ; but implies . Hence
The zero-dimensional case also has this conclusion.
For , the monomials form an infinite basis, each polynomial using only finitely many of them. The map identifies with all real sequences, because any sequence defines . The linear subspace of finitely supported sequences is proper (it excludes ) and separating (one coefficient functional detects any nonzero polynomial). Thus
Using the usual zero-boundary Sobolev space convention,
where weak derivatives define and is the space of test functions. In the Gaussian free field convention, the same notation often denotes the Dirichlet energy space, the completion in the gradient norm alone. On bounded domains the Poincaré inequality makes the two definitions equivalent; on unbounded domains one must distinguish them. The following gradient-pairing argument applies in either setting whenever the energy completion is realized as weak functions.
Identify with a vector subspace of by zero extension of H01. Approximating by test functions in shows that this is an isometric embedding in the inhomogeneous Sobolev norm and also in the Dirichlet inner product norm. In particular, arbitrary irregularity of causes no additional boundary term.
Define
These are weakly harmonic Sobolev functions. For , integration by parts in the weak sense gives . If , choose converging to in , or in energy for the homogeneous convention. The Cauchy-Schwarz inequality gives
Hence the orthogonality of supported and harmonic Dirichlet functions is
Both are linear vector subspaces. In the inhomogeneous convention they are closed: the first is the isometric image of a complete space, and the second is the intersection of the kernels of the linear functionals . No spanning assertion is needed. The PDF contains this orthogonality statement; the TeX has badly corrupted it into an assertion about openness.
For multi-indices , define
These seminorms define the Fréchet space topology of the Schwartz space: exactly when every tends to zero. An equivalent increasing family is
A tempered distribution is a continuous linear functional on this space. Equivalently, for some . The usual weak convergence of tempered distributions means for every fixed Schwartz function. The strong dual topology instead requires uniform convergence on every subset of the Schwartz space that is a bounded set in a topological vector space; the Fourier maps below are continuous in both topologies.
Using , differentiation under the integral and integration by parts give
The omitted coefficient has modulus one. By the Leibniz rule, every integrand is a finite sum of a polynomial times a derivative of . Inserting the integrable weight bounds its L1 norm by finitely many Schwartz space seminorms. In particular . Thus the Fourier transform maps continuously into itself.
For completeness, the Fourier inversion theorem follows here by Gaussian regularization. The inverse transform of is . The Fourier transform of a Gaussian and Fubini's theorem show
As , the right side tends to by the approximate identity property, while the left side tends to the undamped inverse integral by dominated convergence theorem, since . Hence
The inverse is times reflection composed with the continuous Fourier transform, and is therefore continuous on the Schwartz space. This proves a continuous linear isomorphism with continuous inverse.
Define the Fourier transform of a tempered distribution by
The continuous map on Schwartz space makes this a tempered distribution; the transpose of supplies its inverse. Pointwise convergence of pairings proves weak continuity. For the strong dual topology, the transform of a bounded set of Schwartz functions is bounded, so uniform convergence of pairings on bounded sets proves continuity of both Fourier maps there too.
Now let be a rotation matrix in the special orthogonal group and write . A change of variables with unit Jacobian gives
The rotation equivariance of the Fourier transform on tempered distributions follows by duality:
Therefore . Applying this identity and the inverse Fourier transform gives the two directions:
This is precisely preservation of radial tempered distributions. For , acts transitively on spheres, so an invariant smooth function is an ordinary radial function.
Use the real Hilbert space , the zero-boundary Sobolev space, with norm . The Poincaré inequality makes this equivalent to its usual Sobolev space norm. Define the symmetric bilinear form and continuous linear functional
The Cauchy-Schwarz inequality and the sharp interval Poincaré inequality imply
Thus is a bounded bilinear form and a coercive bilinear form, and is bounded because is square-integrable. The Lax-Milgram theorem supplies a unique weak solution:
This is obtained from the differential equation by integration by parts; the test functions have zero boundary trace. Conversely, the weak solution satisfies in the sense of distributions. Since , it belongs to and solves the equation almost everywhere.
Equivalently, the Ritz method minimizes
over . Indeed , since the mixed term is . This proves existence and uniqueness of the minimizer directly from the weak solution, as well as its equivalence to the variational problem.
The continuous dual space consists of all bounded real linear functionals on , with operator norm . Let be Cauchy in this norm. For each , , so converges in ; define its limit to be .
Pointwise limits of the linear identities show that is linear. The sequence of norms is bounded, say by , so and . Given , choose so that for all . Holding fixed and taking the pointwise limit in gives for all . Thus , proving
Completeness of is not needed; completeness of the scalar field supplies the pointwise limit.
On the one-dimensional linear subspace , define . It is linear and obeys even for negative . The norm on is a sublinear functional, so the real Hahn-Banach theorem extends to a linear functional with for every .
Apply this also to to get . Hence , proving continuity and . At the extension satisfies , forcing the reverse norm inequality. Therefore
The exclusion of is what ensures that this particular construction attains norm one.
Take , which is a Banach space by the completeness of the dual just proved. The canonical embedding into the bidual is
For fixed this is a bounded linear functional on , since , and is linear in . This gives . For , the norming functional from the Hahn-Banach theorem has and , giving the reverse inequality. At zero equality is immediate. Thus
In particular is injective and isometric. If a dense isometric embedding is wanted, rather than merely the stated embedding, take the norm closure of in ; a closed subspace of a Banach space is complete and supplies a completion of a normed space.
The dual vector space is , the vector space of all linear functionals on . For a vector subspace , its annihilator of a vector subspace is
Given a basis , define by and extend linearly. If , evaluation at gives , so the are linearly independent. Every satisfies
so they also span and therefore form its dual basis.
Write . The condition is
Gaussian elimination gives and . Hence
Use the usual connected-manifold convention for this assertion. Suppose, for contradiction, that . The Dolbeault theorem gives , and the Hodge decomposition theorem for compact Kähler manifolds and its conjugation symmetry give . Hence every real class in has a real harmonic differential form of type as its representative.
The intersection form is . Its value on the Kähler class is positive: . Every real harmonic form splits uniquely as , with primitive and constant. Indeed, is a harmonic function, hence constant by connectedness, and ; subtracting kills , and part (b) makes primitive.
Part (c) gives , while . Thus
This proves the Hodge index theorem for compact Kähler surfaces in this case: has signature .
On the alleged two-dimensional totally isotropic subspace , the linear functional has a nonzero vector in its kernel. Its harmonic differential form representative is primitive, so the preceding negative-definiteness statement gives , contradicting the vanishing of on . Therefore
Connectedness is essential if one's definition of a manifold allows disconnected spaces. For , with , one has . Take on each component the pullback of the degree-two class from its first factor. Each class has square zero, and their mutual pairing is zero because their supports lie on different components. Their span is then a two-dimensional totally isotropic subspace, disproving the unqualified disconnected version.
Rado's criterion. Let be a matrix over the rational numbers, with columns . A partition regular matrix is one for which every finite coloring of the positive integers gives a monochromatic positive vector with ; repeated coordinates are allowed. The columns condition is the existence of an ordered set partition of into nonempty blocks such that
Rado's theorem states
Necessity. Clear denominators so the columns are integer vectors. For each pair of disjoint index sets , with , for which is outside the linear span of the -columns, choose an integer linear functional that vanishes on those columns and satisfies . Such a functional exists by extending a basis of the span to one also containing , defining a functional on that basis, and clearing its rational denominators.
There are only finitely many such pairs. Choose a prime number dividing none of these nonzero integer evaluations. If there are no such pairs, any prime will do. Use the last nonzero digit coloring: write , with , and color by . Since is a partition regular matrix, this coloring supplies a monochromatic positive solution, so all its unit parts have a common nonzero residue .
Group the coordinates by increasing P-adic valuation, obtaining blocks with valuations . Suppose for some the sum lay outside the linear span of the earlier columns, with earlier index set . Apply to . Earlier terms vanish exactly. Divide the remaining integer equation by and reduce modulo . Later terms vanish modulo , while the current block gives
contrary to the choice of . Thus every block sum lies in the earlier linear span, and for the first block this means it is zero. This proves the columns condition by the finite separating-functional proof of the columns condition.
Sufficiency. Suppose the columns condition holds. For , choose rational coefficients , indexed by earlier columns, such that
Take a positive integer clearing their denominators and bounding all . We use the allowed monochromatic m-p-c set theorem with levels. Its M-p-c set is the full set
where the generators make every displayed expression positive. Positivity is part of this convention, rather than a rule that discards nonpositive expressions. For , set
All these numbers lie in the monochromatic set . The coefficient of in is
with the first coefficient zero by . Hence . This Rado solution inside an m-p-c set proves sufficiency.
The equality-or-inequality dichotomy. If every finite coloring gives a monochromatic solution with , the first alternative holds. Otherwise fix a finite coloring admitting no such solution. Given any other finite coloring , use the refinement of a finite coloring . Since is a partition regular matrix, it supplies a solution monochromatic for both colorings. Its first two coordinates cannot be equal, by the defining property of , so it is the required unequal solution for . Thus one of the two universal alternatives always holds. This is the partition regularity dichotomy under an extra constraint; the alternatives are not asserted to be mutually exclusive.
Both restrictions can fail. The Schur matrix
is a partition regular matrix: blocks and satisfy the columns condition. Color by , using the 2-adic valuation. An equal-coordinate solution would have , and , so its coordinates cannot be monochromatic. This exhibits failure of the equality restriction.
Conversely, satisfies the columns condition in one block. Every solution has , so even the constant one-color finite coloring admits no unequal-coordinate solution. Consequently
Work in the real zero-boundary Sobolev space , whose members have square-integrable weak derivatives and zero endpoint trace. Define the bounded bilinear form and linear functional
The weak formulation is to find with for every . Integration by parts recovers the differential equation for a smooth solution; conversely, this identity is the definition of its weak solution.
Use the full norm. The Cauchy-Schwarz inequality gives and . Also , so is a coercive bilinear form with constant one. The Lax-Milgram theorem states that a bounded, coercive bilinear form on a real Hilbert space determines a unique weak solution for every bounded linear functional. It therefore applies here.
The equivalent minimization problem is
If is the weak solution, symmetry and give
This is positive unless , proving a unique global minimizer. Conversely, differentiating at gives the weak identity. Thus the unique energy minimizer is exactly the unique weak solution. As a check, the classical representative is
It satisfies both endpoint conditions and .
The starting point of a conforming finite element method is a weak formulation in a Hilbert space . For example, a homogeneous Dirichlet boundary condition on a bounded Lipschitz domain gives . One seeks
where is a bounded bilinear form, , and is a bounded linear functional. A conforming finite element space is finite dimensional and is typically built from functions that are polynomial on each element of a finite element mesh. With a basis , the Galerkin method imposes the same identity only for , giving
The stiffness matrix is sparse when basis supports overlap only locally. Local element integrals assemble its entries; the mass matrix represents an term. This separates the choice of trial functions from the variational principle determining their coefficients.
The fundamental well-posedness theorem is the Lax-Milgram theorem: if for some , there is a unique solution for each , with . The same theorem on gives a unique discrete solution. The constants must be independent of the mesh for uniform stability of a numerical method. Boundary conditions are built into the trial space when they are essential constraints; flux conditions arise through boundary terms in integration by parts and are natural constraints in the weak formulation.
When is symmetric and a coercive bilinear form, the Ritz method minimizes
over . Its first variation is exactly the Galerkin method, so Ritz minimization and Galerkin testing coincide for symmetric coercive problems. The energy norm turns the approximation into an orthogonal projection. Indeed, subtracting the exact and discrete weak equations gives Galerkin orthogonality, . For every the Pythagorean identity becomes
so
This exact best-approximation property is the central advantage of the Ritz method.
Symmetry is unnecessary for the Galerkin method. For any bounded, coercive form, the Céa lemma gives
To prove it, put . Galerkin orthogonality yields , so coercivity and boundedness give . Divide when and take the infimum. Thus approximation capability plus uniform coercivity gives convergence. In contrast, minimizing for a nonsymmetric form differentiates its symmetric part and generally does not solve the original weak equation.
A concrete symmetric example is the one-dimensional reaction-diffusion problem from Question 5. Continuous piecewise-linear hat functions give the diffusion stiffness matrix with diagonal and neighbouring entries , and the mass matrix with diagonal and neighbouring entries . Therefore and . Its positive-definite matrix is the coordinate form of the continuous energy. The exact smooth solution makes this an explicit test of the method, not just an abstract existence result.
For a nonsymmetric example, take positive , constant real , and
Its form is . Since , it has coercivity constant in the full norm, although it is not symmetric when . The Galerkin method remains well posed. On the uniform hat basis, , where , and . The skew-symmetric matrix cancels from , proving nonsingularity. A Ritz energy would omit precisely this advection contribution. Small may nevertheless make the approximation constant large and produce poorly resolved layers; algebraic solvability is not an accuracy guarantee.
Quantitative convergence uses a finite element interpolation estimate. On a shape-regular mesh, for piecewise-linear conforming elements and in the usual low-dimensional setting,
The Céa lemma therefore gives an energy error. The Aubin–Nitsche duality argument improves the L2 norm error when the dual elliptic problem has regularity: solve and use
Consequently
with constants depending on the solution and regularity bounds. The second estimate is conditional on dual regularity; corners or insufficient data regularity can reduce the rate.
The same Galerkin method handles evolution equations. For the homogeneous heat equation, the semidiscrete finite element heat equation is . Because is a positive-definite matrix and is a positive semidefinite matrix,
The decreasing quadratic form is exactly the L2 norm squared of the finite-element function. This separates spatial stability of a numerical method from the subsequent time integrator, just as in the Schrödinger equation example. Conformity, coercivity and approximation estimates together explain convergence.