For a vector subspace of , its codimension is the dimension of the quotient vector space . This definition also applies when is infinite-dimensional. If is a direct sum, the map is a linear isomorphism from to , so . In particular, the kernel of a nonzero linear functional has codimension one: normalize and write .
Cokernel Created 2026-09-29 Updated 2026-10-14
The cokernel records output information that a linear map cannot produce. For , it is the quotient vector space
Its elements are cosets . Two vectors represent the same class exactly when is in the image of a linear map. The zero class is the whole image of a linear map, so
Changing by an attainable output does not change its obstruction. This is useful because one can test compatibility before trying to find an input. The quotient vector space construction is described in Axler's §3E. [ref]
For the linear map given by , the image of a linear map is the horizontal line. All outputs with the same second coordinate have the same cokernel class, because their difference is horizontal. Thus this cokernel is isomorphic to via . In particular, has zero class and is attainable, while has nonzero class and is unattainable.
Figure 1.
The second output coordinate is a cokernel obstruction to solving
. The horizontal axis is the image of a linear map . The class of is the parallel line , which never meets the image. The projection is attainable but has a different cokernel class. Details.
If is finite-dimensional, the dimension rule for a quotient vector space gives
Compare this with the rank-nullity theorem, . The kernel counts invisible inputs; the cokernel counts missing output directions. They need not have the same dimension: has a two-dimensional kernel and a one-dimensional cokernel. A linear map is surjective exactly when its cokernel is zero.
The cokernel is a quotient, rather than a chosen perpendicular vector subspace. With a finite-dimensional inner product space as output, one may represent each class by its unique component in the orthogonal complement of the image of a linear map. That representation depends on the chosen inner product. For matrices over the complex numbers, this complement is , leading to the cokernel compatibility equations.
The same quotient definition applies to a group homomorphism of abelian groups. For given by , the cokernel is . The equation is solvable exactly when is an even integer; the two cosets record integer parity. A quotient captures the obstruction here just as it captures a missing output coordinate for a linear map.
Exterior power Created 2026-09-28 Updated 2026-10-14
The th exterior power is the quotient vector space of the tensor power that makes every elementary tensor with two equal factors zero. More precisely, take the quotient vector space by the linear span of all such tensors. Its elementary products turn alternating multilinear maps into linear maps: every alternating -linear map on factors uniquely through .[ref]
If is an ordered basis, the increasing products
form a basis of . There is one for each -element choice of basis directions, so
Repeated directions vanish; products with a different order can be sorted using their sign. Coordinate determinants distinguish the remaining increasing products, establishing linear independence.[ref]
For , a basis of is . This explains the three bivector components in the worked example. The top exterior power has one basis element, , while : four independent directions cannot fit into that vector space. By convention is the scalar field, even when has dimension zero.
Hermitian inner product Created 2026-10-14 Updated 2026-10-20
A Hermitian inner product is a Hermitian form on a complex vector space which has positive definiteness: for every nonzero vector . It is precisely a complex inner product. Only with this definiteness condition does
define a norm rather than a seminorm or an expression that may not be real. The standard Hermitian inner product on is ; positive weights give , with squared norm .[ref]
A Hermitian inner product need not have a real matrix. For instance, with the linear-first coordinate convention,
The last expression proves positive definiteness without a lengthy calculation of eigenvalues. For it gives , while for it gives . These unequal values expose why a silent switch to would change this particular Hermitian inner product: with these same entries it gives at . All entries must keep their roles from the matrix of a Hermitian form.
The Cauchy-Schwarz inequality for a Hermitian inner product states
Equality holds exactly when are linearly dependent, including when either is zero. For a nonzero , outline the proof by setting and . Then , and the Pythagorean theorem gives
Nonnegativity proves the inequality, while positive definiteness makes equality equivalent to . The scalar has no extra conjugate because the first argument is linear.[ref]
The Cauchy-Schwarz inequality also holds for a positive semidefinite Hermitian form, but equality need not imply linear dependence: for , the independent vectors and give . Equality then describes dependence after passing to the quotient vector space by the radical of a Hermitian form. The indefinite Hermitian form in Hermitian form shows that conjugate symmetry alone does not even guarantee the inequality.
For a worked orthogonal projection, take , and . Then , and , with and for the squared norms. The residual is perpendicular in this Hermitian inner product even though its ordinary real dot product with is . For complex , the same orthogonal projection uses ; rotating multiplies by , while rotating multiplies by . This combines geometric decomposition with sensitivity to the relative complex arguments of the multipliers.
Figure 1.
Analytical illustration: weighted orthogonal projection on a real slice and opposite changes of complex argument of its projection coefficient
. Details.
A Hermitian inner product therefore supplies more than a positive diagonal: orthogonality, orthogonal projection onto a span, and the triangle inequality for its norm make approximation and distance meaningful. For the function space of complex continuous functions on , has positive definiteness, because a nonzero continuous function has positive modulus on a small interval. The same construction turns overlap under integration into lengths and best approximation in finite-dimensional vector subspaces.
For a linear map and an invariant subspace , the rule defines a linear map on the quotient vector space . Indeed, two representatives differ by an element of , so their images also differ by an element of . Conversely, this rule is well-defined only if , by comparing every with zero.
Kernel of a seminorm 2026-10-14
The kernel of a seminorm is its zero set, a linear subspace by absolute homogeneity and the triangle inequality. The estimate shows that adding an element of does not change . Hence defines a norm on the quotient vector space .
On itself, is a pseudometric; it is a metric exactly when is a norm. In particular, zero distance in one pseudometric need not mean equality of vectors. A separating family of seminorms removes the common zero-distance ambiguity.
Parallel lines as a quotient vector space Created 2026-10-14 Updated 2026-10-25
For fixed , the parallel affine lines are precisely the cosets of the indicated quotient vector space. Changing representatives adds a multiple of , so and are well-defined. The zero is the whole line , not a single point. If is a basis, the two line classes form a basis of the quotient by spanning and independence modulo .
Since is proper, is a nonzero linear functional. Choose with , by rescaling any vector outside its kernel. For every ,
If , applying gives . Consequently this is a direct sum, and the quotient vector space has dimension one. This computes the codimension of a vector subspace:
To prove boundedness without assuming completeness, use the linear functional with closed kernel criterion directly. Since is a closed set and , the distance
is positive. If , then , so
For the resulting estimate is immediate. Therefore
Here denotes the continuous dual space.
Write , where and . These kernels satisfy . Also and : for example, when . Thus the proposed linear map between quotient vector spaces is well-defined and has the formula
If belongs to its kernel, then . Therefore , so and is zero. We have proved
These are the injections between successive kernel quotients. In finite dimension, they imply .
Surjectivity need not hold. Take a nonzero vector space and the zero linear map . At , we have and , so
No. Over any field , take , let be the identity operator, and choose the vector subspace
Both and the quotient vector space have dimension one. A one-dimensional vector space has no nonzero proper vector subspace, so neither can have a nonzero proper invariant subspace. The induced linear map on a quotient vector space is again the identity operator.
However, is another nonzero proper vector subspace of , and . Hence
The hypotheses do not prevent a direct sum whose two summands are invariant subspaces.
The quotient vector space identifies two vectors precisely when . Since is an invariant subspace, . Thus
Consequently : the output does not depend on the chosen representative. This proves that the induced linear map on a quotient vector space
is well-defined. It is a linear map because, for scalars ,
The line through the origin is , containing zero and closed under addition and scalar multiplication, so it is a vector subspace. If , then and for some real . Conversely that equality gives the same set after shifting the line parameter. Thus
Changing representatives to , changes their sum by and a scalar multiple by . The line classes therefore do not change, proving both operations well-defined. Associativity follows from . The zero vector of this quotient vector space is the entire line , because .
For a basis of , every vector is , so . If this combination equals , then ; independence of the three original basis vectors forces . Hence is a basis of the space of parallel lines as a quotient vector space.
For the specified direction, add to to obtain the representative . Thus its coordinates in the two standard line classes are . The two supplied image classes have coordinates and , while their input coordinates are and . If are the matrix columns, then and . Solving gives
Call the four given column vectors . Direct componentwise calculation gives
The first two vectors are independent: their first two components give the determinant . They form a basis of , so .
Choose columns . This gives the matrix
Its image is exactly , since all its columns belong to and its first two span . Its column sum is zero, so belongs to its kernel.
All linear maps with the stated kernel condition and image contained in factor uniquely through the quotient vector space . This quotient has dimension four. A linear map from it to the two-dimensional is specified by eight independent real coordinates, so the requested space has dimension . Requiring the image to equal , instead of being contained in , would not define a vector space; the printed containment is essential.
The zero-composition subspaces of a linear map are subspaces because the defining equations are homogeneous linear equations in : they hold for the zero map and are preserved by addition and scalar multiplication. A map with vanishes on , so it factors uniquely through the quotient vector space . Conversely every map from that quotient to gives such a . Therefore
The condition says exactly that the image of lies in . Consequently
Both dimension formulas use the fact that the space of maps between spaces of dimensions has dimension : matrix units in any chosen bases supply a basis.
Let be the -uniform hypergraph and use strong saturation of a uniform hypergraph in its immediate-completion sense: each missing edge lies in an -set whose other -subsets are already edges of . The argument allows existing hypergraph cliques. Take , the usual parameter range; if , strong saturation forces every possible edge to be present, and the inequality is immediate whenever its binomial terms are defined. The case has the trivial lower bound zero.
For , choose distinct real numbers and form the Vandermonde matrix whose th column is . Every columns are linearly independent by the Vandermonde determinant. Set , so , and work in the quotient vector space
Here the inclusion of is injective: extend a basis of to a basis of and use the resulting wedge bases of the exterior powers. Write for the image in of the coordinate wedge indexed by an -set . All these images span .
For any -set , let be its coordinate subspace. The restriction of has rank , so has dimension . Wedge a basis of this intersection to obtain a nonzero element
Every coefficient is nonzero. Indeed, projection of onto the coordinates is an isomorphism: a vector in its kernel is supported on , whose columns of are independent. The coefficient is the determinant of that projection in the chosen bases. Passing to therefore gives a linear dependence
If is missing from , take its strong-saturation witness . The dependence expresses in the span of the for the other edges , all of which are present. Thus the vectors indexed by the present edges span all of . The exterior-power quotient bound for strong hypergraph saturation follows:
The bound is sharp: include precisely the -sets meeting one fixed -set . A missing edge is disjoint from , and every other -subset of meets , so adding immediately completes a hypergraph clique of order . The number of included edges is exactly the displayed bound.
An -uniform hypergraph is strongly saturated with respect to a complete uniform hypergraph of order if adding any missing edge creates a new complete uniform hypergraph on vertices containing that edge. Equivalently, for every missing -set , there is an -set for which all other -subsets are edges. Existing complete subhypergraphs are allowed in this strong-saturation definition.
We prove the bound by an exterior-power quotient bound for strong hypergraph saturation. Assume and . Let with basis . Choose distinct real numbers and let be the kernel of the matrix whose column is
Every columns are linearly independent by the Vandermonde determinant, so . Form the quotient vector space
For each -set , let be the image in of the exterior product . These images span .
For an -set , let be its coordinate subspace. The matrix restricted to has rank , so has dimension . The wedge of a basis of this intersection is a nonzero vector
Every coefficient is nonzero. Indeed, projection from onto the coordinates in is an isomorphism: a vector in its kernel would be supported on , where the columns are independent, and hence would be zero. That projection's determinant is precisely the corresponding wedge coefficient. Thus, in the quotient vector space,
For a missing edge, choose its strong-saturation witness . All other vectors in this relation come from present edges, so the missing edge's vector is in their span. Consequently the present-edge vectors already span all of . Their number is at least its dimension:
This is sharp. Take all -sets that meet a fixed -set . A missing edge is disjoint from , and on every other -set meets ; adding completes the required clique. The number of edges is exactly the boxed difference. If , no missing edge could have a witness, so a strongly saturated hypergraph must be complete; the substantive construction above is for the usual range .
For the set-pair problem, write and choose . If , the cross-disjointness implies that is in neither nor . In particular, the witnesses are distinct. Let ; each and contains exactly its own witness from .
Choose two different indices . The sets and are disjoint, lie outside , and have sizes and . Hence
For equality, partition the ground set into disjoint sets with sizes , respectively, and enumerate as . Set
Then is for and empty otherwise. This realizes equality whenever the bound permits . The argument is a diagonal-intersection set-pair bound, with no additional assumptions on intersections among the or among the .
The endomorphisms of the finite-dimensional vector space over the complex numbers form the general linear Lie algebra with the usual addition and scalar multiplication and Lie bracket . This commutator is bilinear and antisymmetric, and expanding the six products verifies the Jacobi identity.
For a Lie subalgebra , being an abelian Lie algebra means . A nilpotent Lie algebra has , eventually zero; a solvable Lie algebra has , eventually zero. These are the lower central series of a Lie algebra and derived series of a Lie algebra, respectively. Nilpotence is a condition on the Lie bracket, and does not require every member to be a nilpotent endomorphism: a nonzero scalar multiple of the identity spans an abelian Lie algebra.
A flag of a vector space is an increasing chain of vector subspaces. The flag we construct is a complete flag, , where , and each is an invariant subspace for . We first prove the common-eigenvector assertion in the Lie theorem, by induction on ; the zero algebra is immediate. For nonzero solvable , its derived algebra is proper, so there is a codimension-one ideal of a Lie algebra containing . Write . By induction there are and a linear functional on such that for every .
Let be the cyclic subspace spanned by . The commutator derivation identity and show inductively that
Thus and all its initial cyclic spans are -invariant. If , the first cyclic vectors form a basis, is also -invariant, and . For , the trace of a matrix commutator gives
Hence , since the field has characteristic zero. The nonzero common weight space
is -invariant: . The restriction of to has an eigenvector, because is an algebraically closed field. This is a common eigenvector for . Its line is invariant, and repeating the argument on the quotient vector space gives the complete invariant flag. Equivalently, this proves simultaneous triangularization of a Lie algebra representation.
In a basis adapted to this complete flag, every member of is upper triangular, so every member of its derived algebra is strictly upper triangular. Products of strictly upper triangular matrices vanish, and each iterated Lie bracket of such matrices is a sum of these products. Consequently the derived algebra is a nilpotent Lie algebra. We may therefore take : it is an ideal, and the quotient Lie algebra is abelian. This also covers .
There is a small domain issue in the printed notation. If means a quotient vector space by the horizontal plane, the displayed formula does not descend to that quotient vector space: and represent the same class but give different values. The intended construction is stereographic projection, restricted to the unit sphere with the north pole removed. Interpreting the slash as removal of the plane also supplies a suitable ambient domain. The holomorphic stereographic atlas of the sphere is obtained as follows.
Write and . On use . Its inverse, with , is
These formulas give a smooth manifold chart from onto . On choose the second manifold chart
Its inverse is , and , so this is also a smooth manifold chart onto . The conjugation in this second stereographic projection is essential. On the overlap, , so
Both directions of this transition are holomorphic maps on , with nonzero derivative. The two manifold charts cover the sphere, hence define a holomorphic atlas, giving precisely the Riemann sphere. If one instead used in both manifold charts, the transition would be and would not be holomorphic.
Orient the sphere by this holomorphic atlas. The given volume form is smooth at infinity: replacing by in its exterior product gives the same expression
Moreover, , so the normalization of this volume form is
Thus the printed volume form has half the area of the standard round unit sphere; replacing its integral by would introduce an erroneous factor of two.
For , the holomorphic map extends over infinity, since the target reciprocal coordinate is when the source reciprocal coordinate is . Its pullback of a differential form is
Using gives
The degree of a map between oriented manifolds is therefore
For , the formula on the finite manifold chart is the constant . Its unique continuous extension is also at infinity, rather than an undefined expression . Its pullback of a differential form is zero and its degree of a map between oriented manifolds is zero.
For the preimage calculation when , choose a regular value . There are exactly distinct roots of . At each root the real Jacobian determinant is , so every local contribution to the degree of a map between oriented manifolds is . Their sum is , agreeing with the integral. The exceptional values and infinity are avoided because they are branch values when . For the constant map, any is a regular value with no preimages, giving the same answer zero. This establishes the degree of a power map of the Riemann sphere for every allowed .
Since the first basis vectors span the invariant subspace , their images have no components in the last coordinates. Thus
Here is the matrix of , is the matrix of the induced map on the quotient vector space , and is unrestricted. The chosen complementary span need not itself be invariant, so should not in general be called a restriction to that complement. The block-triangular determinant gives
The exterior derivative is an -linear map , agrees with the differential of a smooth function, satisfies the graded Leibniz rule for , and has . These properties determine it locally and hence globally. To see locality directly, if a differential form vanishes near , choose a smooth bump function equal to one near and supported where . The identity gives . Thus global forms can be computed using local extensions in a manifold chart.
In coordinates write . Since , the graded Leibniz rule forces
This is the uniqueness of the exterior derivative from its axioms. The coordinate formula also establishes existence: it has the stated properties, and the chain rule shows that coordinate changes give the same operator.
The de Rham cohomology is the real quotient vector space
Thus a cohomology class records a closed differential form modulo an exact differential form. In degree zero there are no exact forms; closed functions are locally constant. The Poincaré lemma says that every closed form of positive degree on a star-shaped open subset of is exact, and hence that positive-degree closed forms are locally exact on a smooth manifold.
For the first de Rham cohomology of the two-sphere, let and . Stereographic projection identifies each with , so a closed one-form has primitives . On the connected overlap , the derivative of is zero, so this difference is a constant. Subtracting that constant from makes the primitives agree. They glue to a global smooth primitive. Therefore .
Let be the double covering map and the antipodal map. The pullback of a differential form identifies forms downstairs with -invariant forms upstairs. Averaging commutes with . If an invariant form is exact upstairs, averaging its primitive proves it exact downstairs. Conversely an invariant cohomology class has an invariant representative by the same averaging. This proves the de Rham cohomology of a finite quotient identification . In degree zero the sphere is connected and fixes constants; degree one is zero; in degree two the granted action is multiplication by , whose invariant real subspace is zero. Forms of degree greater than two vanish. Hence
This is real de Rham cohomology; it does not detect the integral two-torsion of the real projective plane.