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Tensor Fields Exterior Algebra and Differential Forms
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Determinants of Matrices over a Commutative Ring
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Hereditary and Productive Behaviour of the Separation Axioms
- Limits of Real Functions
- limsup, liminf, and Subsequential Limits
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Properties of the Integral and the Working FTC
- Rank Theorems and Embedded Submanifolds
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Smooth Manifolds and Smooth Maps
- Smooth Vector Bundles and Sections
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- Tangent Cotangent and the Differential
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Fundamental Theorems of Calculus
- The Inverse and Implicit Function Theorems
- The Inverse Function Theorem Completed
- The Riemann Integral: Definition and Integrability
- The Topology of Euclidean Space
- The Total Derivative in ℝᵐ → ℝⁿ
- The ZFC Axioms and the Basic Set Constructions
- Topological Spaces and Continuity
- Topology of ℝ
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
This page defines tensors intrinsically as multilinear maps, builds the finite-dimensional exterior algebra from alternating covectors and duality, and then globalizes the constructions to tensor bundles, tensor fields, and differential forms. It stops before exterior derivative, Lie derivative, Cartan calculus, and de Rham theory.
3 · Logical flowchart
4 · Definitions, theorems and proofs
A type tensor on a finite-dimensional vector space
Definition
Let be a finite-dimensional real vector space, and let . A type tensor on is a multilinear map
With this convention, vectors are type tensors and covectors are type tensors.
The tensor product of multilinear tensors
Definition
Let be a type tensor and a type tensor on the same finite-dimensional vector space . Their tensor product is the type tensor defined by
Tensor product of multilinear tensors is associative and bilinear
Statement
On a finite-dimensional real vector space, the tensor product of multilinear tensors is associative and bilinear in each factor.
Facts & Assumptions
Given: Tensors on the same finite-dimensional real vector space and scalars .
The tensor product is defined by multiplying the two factor values on concatenated arguments (The tensor product of multilinear tensors).
Proof
Fix a list of arguments of the right total type. By [F1], evaluates on that list as the product of the three separate values .
The same formula [F1] gives exactly the same scalar for on the same list of arguments. Hence .
Again by [F1], , and the same computation in the second slot gives bilinearity there as well.
Therefore the tensor product is associative and bilinear in each factor.
The permutation action on covariant tensors
Definition
Let be a finite-dimensional real vector space, let , and let . If is covariant of degree , define by
Symmetrization and alternation operators
Definition
Let be covariant of degree . Its symmetrization and alternation are
Symmetrization and alternation are projections
Statement
For each , the operators and on covariant -tensors satisfy
Their images are exactly the symmetric and alternating covariant tensors.
Facts & Assumptions
Given: A covariant -tensor .
Symmetrization and alternation are the normalized averages over , with and without the sign factor (Symmetrization and alternation operators).
Proof
Applying twice gives a double average over . Reindex by the product permutation ; each occurs exactly times, so the second averaging changes nothing. Thus .
The same reindexing works for , and the sign factors multiply to . Hence .
If is symmetric, every summand in [F1] equals , so . Conversely, is fixed by every permutation because averaging over the whole group is permutation-invariant. The alternating case is identical, with the sign picked up under permutation.
Therefore and are projections onto the symmetric and alternating tensors.
The contraction of a mixed tensor
Definition
Let be a type tensor on with . Contracting the first contravariant slot against the first covariant slot gives the type tensor defined intrinsically by
where is any basis of and its dual basis. The next lemma shows that this formula is basis-independent.
Contraction is independent of the basis formula
Statement
The contraction formula
has the same value for every basis and its dual basis .
Facts & Assumptions
Given: A type tensor with , fixed arguments , and two bases and with dual families and .
Contraction is given by the displayed dual-basis sum (The contraction of a mixed tensor).
Every vector and every covector expand in a basis and its dual family (The dual family associated to a Hamel basis , defined by ).
Proof
Define the bilinear map by . Then the two contraction sums are and .
By [L1], any vector satisfies , and any covector satisfies . Bilinearity of therefore gives
The displayed sum is therefore basis-independent, so contraction is intrinsically defined.
The pullback of a covariant tensor by a linear map
Definition
Let and be finite-dimensional real vector spaces, let be an integer, let be linear, and let be a covariant tensor of degree . Its pullback is the covariant tensor on defined by
Linear pullback respects tensor products and permutations
Statement
Let and be finite-dimensional real vector spaces, let be linear, let and be covariant tensors on of degrees and , respectively, and let . Then
Facts & Assumptions
Given: Finite-dimensional real vector spaces , a linear map , covariant tensors on of degrees , and a permutation .
Pullback of a covariant tensor substitutes into every slot (The pullback of a covariant tensor by a linear map).
Tensor product multiplies the factor values on concatenated arguments, and the permutation action reorders the arguments (The tensor product of multilinear tensors, The permutation action on covariant tensors).
Proof
Evaluating on and using [F1] and [F2], which is exactly .
Likewise, which equals .
Therefore linear pullback respects tensor products and permutations.
Alternating -covectors
Definition
Let be a finite-dimensional real vector space. For , let be the vector space of alternating -linear maps . By convention,
The wedge product of alternating covectors
Definition
If and , their wedge product is
Equivalently,
where is the set of -shuffles.
The wedge product is alternating and bilinear
Statement
If and , then is alternating of degree , and the wedge product is bilinear in .
Facts & Assumptions
Given: Alternating covectors , , and scalars .
The wedge product is the normalized alternation of the tensor product, equivalently the signed shuffle sum (The wedge product of alternating covectors).
Proof
By [F1], is obtained by applying the alternation operator to . Alternation produces an alternating multilinear form, so .
Both tensor product and alternation are linear in each argument, so [F1] gives and similarly in the second slot.
Therefore the wedge product is alternating and bilinear.
The wedge product is associative and graded commutative
Statement
For alternating covectors , , and ,
and
Facts & Assumptions
Given: Alternating covectors of degrees .
The wedge product is the normalized alternation of the tensor product, equivalently the signed shuffle sum (The wedge product of alternating covectors).
The wedge product is alternating and bilinear (The wedge product is alternating and bilinear).
Proof
Using [F1] twice and bilinearity from [L1], both and are the full alternation of the multilinear tensor with the same normalization factor. Hence they are equal.
In the shuffle formula of [F1], swapping the inputs destined for with the inputs destined for contributes the sign of the block permutation, namely . Therefore every term of matches the corresponding term of .
Therefore the wedge product is associative and graded commutative.
The exterior algebra of covectors
Definition
Let be finite-dimensional. Its exterior algebra of covectors is the graded vector space
equipped with the wedge product of The wedge product of alternating covectors.
Wedge monomials in a dual basis form a basis
Statement
Let be a basis of , with dual basis . Then the wedges
form a basis of .
Facts & Assumptions
Given: A basis of and its dual basis .
The degree- part of the exterior algebra is , with wedge product given by alternating tensor multiplication (The exterior algebra of covectors).
Every covector expands in the dual basis, and (The dual family associated to a Hamel basis , defined by ).
Proof
Let . Expanding each input vector in the basis and using multilinearity shows that is determined by its values on basis -tuples. Because is alternating, every tuple with a repeated index vanishes and every tuple with distinct indices reduces, up to sign, to one with increasing indices. Thus is a linear combination of the displayed wedges from [F1].
Suppose , where and . Evaluating at with , [L1] gives when and otherwise. Hence every .
Therefore the displayed wedges form a basis of .
Dimension of the th exterior power is binomial
Statement
If is a finite-dimensional real vector space with and , then
In particular, for .
Facts & Assumptions
Given: A finite-dimensional real vector space with and .
The wedges with form a basis of (Wedge monomials in a dual basis form a basis).
The binomial coefficient counts the -element subsets of an -element set (The set of -element subsets and the binomial coefficient ).
Proof
Choose a basis of . By [L1], has one basis vector for each strictly increasing -tuple from .
Such tuples are the same thing as -element subsets of an -element set, so [F1] counts them by . Therefore . If , there are no such tuples, so the basis is empty and .
This is exactly the claimed dimension formula and vanishing statement.
The finite-dimensional exterior power of vectors
Definition
Let be a finite-dimensional real vector space and let . The th exterior power of is the dual vector space
For , the decomposable -vector is the functional
Universal property of the finite-dimensional exterior power
Statement
Let be an alternating -linear map into a real vector space . Then there is a unique linear map
such that
for all .
Facts & Assumptions
Given: An alternating -linear map .
The th exterior power is the dual space , and is the evaluation functional (The finite-dimensional exterior power of vectors).
The wedges of a basis form a basis of , so the corresponding decomposable -vectors span by duality (Wedge monomials in a dual basis form a basis).
Proof
Choose a basis of . Define on the spanning set of decomposable wedges by for , and extend linearly. This is possible because [L1] gives a basis indexed by those increasing tuples.
For arbitrary , expand each in the chosen basis. Multilinearity of and of the wedge, together with alternation on both sides, reduce both expressions to the same signed sum over increasing -tuples. Hence .
If is another linear map with the same property, then and agree on every decomposable basis wedge, hence on all of by linearity and [L1]. So is unique.
Therefore every alternating -linear map factors uniquely through .
Functoriality of finite-dimensional exterior powers
Statement
Let be finite-dimensional real vector spaces and let . Every linear map induces a linear map
characterized by
Moreover,
Facts & Assumptions
Given: Finite-dimensional real vector spaces , an integer , and linear maps and .
Every alternating -linear map factors uniquely through (Universal property of the finite-dimensional exterior power).
Proof
The map is alternating and -linear in . By [L1], it therefore factors uniquely through a linear map with the stated action on decomposable wedges.
The identity map and the composite have the expected values on every decomposable wedge: and The same formula holds for .
By uniqueness in [L1], the maps in step 2.1 must agree. Therefore exterior powers preserve identities and composition.
Hence and define a functor.
Exterior-power duality pairing
Statement
The canonical pairing
extends to a nondegenerate bilinear pairing
and for decomposable elements one has
Facts & Assumptions
Given: Covectors and vectors in a finite-dimensional real vector space .
A decomposable -vector is the functional on alternating -covectors (The finite-dimensional exterior power of vectors).
The wedge product is the signed shuffle sum on alternating covectors (The wedge product of alternating covectors).
Wedges of a basis and of its dual basis give dual coordinate systems on exterior powers (Wedge monomials in a dual basis form a basis).
Proof
By [F2], is the alternating sum over permutations of , which is exactly the determinant of the matrix . By [F1], this is the value of the pairing on the displayed decomposable elements.
Choose a basis of with dual basis . By [L1], the wedges form a basis of and the wedges form a basis of , and step 1.1 shows . Therefore the pairing matrix in these bases is the identity, so the pairing is nondegenerate.
Thus the canonical exterior-power pairing is bilinear, has the determinant formula on decomposables, and is nondegenerate.
The top exterior power is one-dimensional
Statement
If is a finite-dimensional real vector space with , then and are one-dimensional.
Facts & Assumptions
Given: A finite-dimensional real vector space with .
The dimension formula gives (Dimension of the th exterior power is binomial).
The pairing between and is nondegenerate (Exterior-power duality pairing).
Proof
By [L1], the space is one-dimensional.
Since is the dual of by definition, or equivalently because [L2] identifies it with the dual through a nondegenerate pairing, it has the same dimension. Hence .
Therefore both top exterior powers are one-dimensional.
Interior product on alternating covectors
Definition
Let be a finite-dimensional real vector space, let , and let with . The interior product is defined by
For , adopt the formal convention and set .
Interior product is a graded antiderivation
Statement
If , , and , then
Facts & Assumptions
Given: Alternating covectors of degrees and a vector .
Interior product inserts into the first slot (Interior product on alternating covectors).
The wedge product is the signed shuffle sum (The wedge product of alternating covectors).
Proof
Evaluate both sides on . By [F2], the terms in split into two groups: those where lands among the arguments sent to , and those where it lands among the arguments sent to .
The first group is exactly by [F1]. To move into the first slot of in the second group, it must cross the slots occupied by , which contributes the sign ; that group is therefore .
Summing the two groups gives the claimed formula, so interior product is a graded antiderivation.
The type tensor bundle
Definition
Let be a smooth manifold, and let . The type tensor bundle of is the fibrewise assignment
that is, the fibre over consists of the type tensors on in the multilinear-map sense. The next theorem equips this disjoint union with its smooth vector-bundle structure.
Tensor transition laws define a smooth vector bundle
Statement
For every smooth manifold and integers , the tensor-coordinate change rules define a smooth vector bundle whose fibre over is the space of type tensors on .
Facts & Assumptions
Given: A smooth manifold with overlapping charts and .
The fibre of at is the space of type tensors on (The type tensor bundle).
Tangent bases transform by the Jacobian, and cotangent bases transform by the inverse transpose Jacobian (Change-of-coordinate formula for tangent bases, Cotangent coordinate changes use the inverse transpose Jacobian).
A smooth cocycle of fibrewise linear transition maps defines a smooth vector bundle (Construction of a vector bundle from a smooth cocycle).
Proof
On a chart domain , the coordinate bases and [F1, given, construct] identify each fibre in [F1] with the fixed finite-dimensional vector space of type tensors on . This gives local trivializations
On an overlap, [L1] shows that each contravariant slot picks up one inverse [L1, step 1.1, algebra] Jacobian factor and each covariant slot picks up one Jacobian factor. Hence the tensor-coordinate change map is fibrewise linear, smooth in the base point, and satisfies the cocycle law because Jacobians and inverse Jacobians do.
Therefore [L2] applies to these local transition maps and produces a smooth [F1, L2, step 2.1] vector bundle. By construction its fibre over is the tensor space from [F1].
Thus the tensor transition laws define the smooth tensor bundle . [step 3.1]
A smooth tensor field
Definition
Let be a smooth manifold. A smooth tensor field of type on is a smooth section of the tensor bundle .
Smoothness of a tensor field is equivalent to smooth coordinate components
Statement
A type tensor field is smooth if and only if, in every smooth chart, its coordinate component functions are smooth.
Facts & Assumptions
Given: A type tensor field on a smooth manifold .
A smooth tensor field is a smooth section of the tensor bundle (A smooth tensor field).
The tensor bundle is a smooth vector bundle with the standard tensor-coordinate trivializations (Tensor transition laws define a smooth vector bundle).
Smoothness of a section is equivalent to smoothness of its local component functions (Smoothness of a section is equivalent to smooth local components).
Proof
By [F1] and [L1], a tensor field is a section of a smooth vector bundle whose local bundle coordinates are exactly the tensor coefficients relative to the chart bases and .
Applying [L2] to those trivializations shows that the section is smooth exactly when each local coefficient function is smooth.
Therefore smoothness of a tensor field is equivalent to smoothness of its coordinate components.
Tensor products and contractions of smooth tensor fields are smooth
Statement
The tensor product of smooth tensor fields is smooth. If a smooth mixed tensor field has at least one contravariant and one covariant slot, then contracting its first contravariant slot against its first covariant slot is smooth.
Facts & Assumptions
Given: Smooth tensor fields and , and a smooth mixed tensor field with at least one covariant and one contravariant slot.
Tensor-field smoothness is equivalent to smoothness of the local coefficient functions (Smoothness of a tensor field is equivalent to smooth coordinate components).
Tensor product is bilinear, and contraction is basis-independent (Tensor product of multilinear tensors is associative and bilinear, Contraction is independent of the basis formula).
Proof
In any chart, [L1] identifies , , and with families of smooth coefficient functions. By [L2], the coefficients of are finite sums of products of the coefficients of and . Those are smooth.
In the same chart, [L2] writes each contracted coefficient of as a finite sum of coordinate coefficients of . Because the contraction formula is basis-independent, these chartwise definitions glue. The resulting coefficient functions are smooth by [L1].
Therefore tensor products and the contraction defined above preserve smoothness.
The pullback of a covariant tensor field
Definition
Let be smooth, and let be a covariant -tensor field on . Its pullback is the covariant -tensor field on defined by
Pullback of covariant tensors is smooth and functorial
Statement
If is smooth and is a smooth covariant tensor field on , then is a smooth covariant tensor field on . Moreover,
for every composable smooth map .
Facts & Assumptions
Given: Smooth maps and , and a smooth covariant tensor field on the target.
Pullback of a covariant tensor field is defined by inserting the differential into every slot (The pullback of a covariant tensor field).
Tensor pullback commutes with the corresponding fibrewise linear operations, and tensor products and contractions of smooth tensor fields are smooth (Linear pullback respects tensor products and permutations, Tensor products and contractions of smooth tensor fields are smooth).
Differentials satisfy the chain rule (The chain rule for differentials of smooth maps).
Proof
In local coordinates, [F1] expresses each coefficient of as a finite sum of the coefficients of multiplied by partial derivatives of . Those are smooth, so [L1] implies that is smooth.
The identity map has identity differential, so [F1] gives .
For , [F1] and [L2] give which is exactly .
Therefore pullback of covariant tensors is smooth and functorial.
A general mixed tensor field does not have a pullback by every smooth map
Statement
False claim: for every smooth map and every vector field on , there is a vector field on satisfying
Such an would be the natural candidate for a pullback of along .
Facts & Assumptions
Given: The smooth map , , and the constant vector field on .
Covariant tensor fields do admit functorial pullbacks (Pullback of covariant tensors is smooth and functorial).
Refutation
The field is a type tensor field, so the false claim requires a vector field on with for every .
The differential of the constant map is zero at every point, so for every possible , whereas . Thus the required equality is impossible.
Thus a general mixed tensor field does not have a pullback by every smooth map, even though [L1] shows that purely covariant tensors do.
Symmetric and alternating covariant tensor subbundles
Definition
Let be a smooth manifold. For , let be the covariant tensor bundle. Its symmetric subbundle and alternating subbundle are the fibrewise subsets
where the right-hand sides use the fibrewise symmetrization and alternation operators.
Symmetric and alternating images are smooth subbundles
Statement
For each , the symmetric and alternating fibrewise parts of form smooth vector subbundles of the covariant tensor bundle.
Facts & Assumptions
Given: A smooth manifold and an integer .
The symmetric and alternating parts are defined fibrewise inside the covariant tensor bundle (Symmetric and alternating covariant tensor subbundles).
The covariant tensor bundle is a smooth vector bundle, and the fibrewise symmetrization and alternation operators are projections (Tensor transition laws define a smooth vector bundle, Symmetrization and alternation are projections).
The image of a constant-rank bundle map over one base is a smooth vector subbundle (Constant-rank kernels and images of bundle maps over one base are subbundles).
Proof
By [L1], symmetrization and alternation act fibrewise on as smooth bundle endomorphisms over . Their fibres are the usual linear projections onto the symmetric and alternating tensors.
Because a projection has constant rank equal to the dimension of its image, the fibre ranks of these bundle maps are constant on . Therefore [L2] shows that their images are smooth vector subbundles.
Those images are exactly the symmetric and alternating bundles from [F1]. Hence both are smooth vector subbundles of .
The exterior power bundle of the cotangent bundle
Definition
Let be a smooth manifold and . The th exterior-power bundle of the cotangent bundle is the fibrewise assignment
The next theorem provides its smooth vector-bundle structure.
Exterior-power transition laws define a smooth vector bundle
Statement
For every smooth manifold and , the bundle is a smooth vector bundle.
Facts & Assumptions
Given: A smooth manifold and an integer .
The bundle is the fibrewise bundle of alternating -covectors (The exterior power bundle of the cotangent bundle).
The alternating fibrewise part of the covariant tensor bundle is a smooth vector subbundle (Symmetric and alternating images are smooth subbundles).
Proof
The bundle is the covariant -tensor bundle, and its alternating fibrewise image is the collection of alternating -covectors at each point.
By [L1], that alternating fibrewise image is a smooth vector subbundle of . By step 1.1, this subbundle is exactly .
Therefore the exterior-power transition laws define a smooth vector bundle.
A smooth differential -form
Definition
Let be a smooth manifold and . A smooth differential -form on is a smooth section of . The space of such forms is denoted , and .
Local coordinate expression for a differential form
Statement
On a chart , every smooth differential -form has a unique expression
with smooth coefficient functions on .
Facts & Assumptions
Given: A smooth -form on a chart domain with coordinates .
A smooth -form is a smooth section of (A smooth differential -form).
The coordinate differentials form the dual basis of the cotangent fibres, and their increasing wedges form a basis of the alternating -covectors (Coordinate differentials form the dual cotangent basis, Wedge monomials in a dual basis form a basis).
Smoothness of a section is equivalent to smoothness of its local components (Smoothness of a section is equivalent to smooth local components).
Proof
At each point , [L1] gives a basis of , so has a unique expansion over increasing multi-indices .
The coefficient functions are exactly the local components of the section in the bundle frame from [L1]. Therefore [L2] makes them smooth on .
This gives the unique local coordinate expression for .
The wedge product of differential forms
Definition
Let and . Their wedge product is the differential form defined pointwise by
The next proposition verifies that this pointwise field is smooth.
Differential forms form a graded commutative algebra
Statement
The graded vector space
with the wedge product is an associative graded-commutative algebra.
Facts & Assumptions
Given: Differential forms of homogeneous degrees .
The wedge product of forms is defined pointwise from the wedge product of alternating covectors (The wedge product of differential forms).
The fibrewise wedge product is associative and graded commutative (The wedge product is associative and graded commutative).
Tensor-field smoothness can be checked on coordinate components (Smoothness of a tensor field is equivalent to smooth coordinate components).
Proof
At each point , [F1] and [L1] give and
The local coefficient functions of are polynomial expressions in the local coefficients of and , so [L2] shows that wedge products remain smooth.
Therefore is closed under wedge and inherits associativity and graded commutativity pointwise from [L1].
Interior product of a form by a vector field
Definition
Let be a smooth section of the tangent bundle, that is, a smooth vector field on , and let . The interior product is defined pointwise by
For , adopt the formal convention and set .
This pointwise field is smooth. Indeed, in local coordinates write and expand in the smooth frame as in Local coordinate expression for a differential form. The coefficients of are signed finite sums of products , and are therefore smooth.
Interior product on forms is a graded antiderivation
Statement
If is a smooth vector field and , , then
Facts & Assumptions
Given: A smooth vector field and forms of degrees .
Interior product of a form is defined pointwise from the fibrewise interior product (Interior product of a form by a vector field).
Fibrewise interior product is a graded antiderivation (Interior product is a graded antiderivation).
Proof
At each point , [F1] identifies with .
Applying [L1] in the vector space gives Using [F1] again identifies this with the fibre at of the claimed form identity.
Since the two forms agree at every point, the displayed identity holds on .
The pullback of a differential form
Definition
Let be smooth, and let . The pullback is the pullback of viewed as an alternating covariant -tensor field:
Pullback of forms is smooth functorial and preserves wedges
Statement
For a smooth map , pullback sends smooth differential forms on to smooth differential forms on , is functorial, and satisfies
Facts & Assumptions
Given: A smooth map , a smooth map , and forms on the target.
A form pullback is the covariant tensor pullback restricted to alternating tensors (The pullback of a differential form).
Covariant tensor pullback is smooth and functorial (Pullback of covariant tensors is smooth and functorial).
Fibrewise linear pullback respects tensor products and permutations, hence wedge products (Linear pullback respects tensor products and permutations).
Proof
By [F1], is obtained from the covariant tensor pullback. Because [L1] sends smooth covariant tensors to smooth covariant tensors and preserves composition, the same is true for forms.
At each point , [F1] and [L2] give which is exactly .
The identity and composition laws are inherited from [L1], and step 1.2 gives wedge preservation. Therefore pullback of forms is smooth, functorial, and wedge-preserving.
A diffeomorphism pulls back tensor fields and forms isomorphically
Statement
If is a diffeomorphism, then pullback by is an isomorphism on covariant tensor fields and on differential forms. Its inverse is pullback by .
Facts & Assumptions
Given: A diffeomorphism with inverse .
A diffeomorphism has a smooth inverse (Diffeomorphisms and local diffeomorphisms of manifolds).
Covariant tensor pullback and form pullback are functorial (Pullback of covariant tensors is smooth and functorial, Pullback of forms is smooth functorial and preserves wedges).
Proof
By [F1], both and are smooth, so [L1] gives pullback maps in both directions on covariant tensor fields and on forms.
Functoriality from [L1] yields The identity pullback is the identity map by the same functoriality statements.
Hence is an isomorphism with inverse on covariant tensor fields and on differential forms.
The wedge product is not commutative
Statement
False claim: the wedge product is commutative.
Facts & Assumptions
Given: The standard coordinate -forms on .
The wedge product is graded commutative, so for -forms one has (The wedge product is associative and graded commutative).
Refutation
Evaluating on gives , so .
By [L1], . Since step 1.1 shows is nonzero, it follows that .
Therefore the wedge product is not commutative.
A nonzero one-form need not have a nonzero square under the wedge product
Statement
False claim: every nonzero -form has nonzero wedge square.
Facts & Assumptions
Given: A nonzero -form .
The wedge product is graded commutative (The wedge product is associative and graded commutative).
Refutation
Since has degree , [L1] gives .
Over this implies , hence . So even a nonzero -form has zero square.
Therefore the claim is false.
A -form on an -manifold must vanish when
Statement
False claim: on an -manifold, a -form can be nonzero even when .
Facts & Assumptions
Given: An -manifold and an integer .
If and , then (Dimension of the th exterior power is binomial).
The bundle has fibre at each point (Exterior-power transition laws define a smooth vector bundle).
Refutation
For each , the tangent space has dimension . Hence [L1] gives .
By [L2], every fibre of is zero. Therefore every section of that bundle is the zero form.
So no nonzero -form exists when , and the claim is false.
Tensor components do not transform as independent scalar functions
Statement
False claim: tensor coordinate components transform as if each were an independent scalar function.
Facts & Assumptions
Given: The Euclidean metric on and the polar chart on .
Tensor-coordinate changes involve Jacobian factors on each slot (Tensor transition laws define a smooth vector bundle).
Refutation
In Cartesian coordinates, the coefficient matrix of is .
In polar coordinates, and , so Thus the coefficient matrix becomes , not the unchanged scalar pair from step 1.1. This is exactly the Jacobian action described in [L1].
Therefore tensor components do not transform as independent scalar functions.
A tensor is not determined by its values on diagonal tuples without symmetry
Statement
False claim: a tensor is determined by its values on diagonal tuples without any symmetry hypothesis.
Facts & Assumptions
Given: On , the bilinear forms and .
Bilinear forms are type tensors (A type tensor on a finite-dimensional vector space).
Refutation
By [F1], both and are tensors of the same type. They are distinct because while .
For every , one has . Thus the two tensors agree on every diagonal pair .
Therefore diagonal values alone do not determine a general tensor.
5 · Examples, counterexamples and false statements
None yet.