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Constant Rank, Submersions, Immersions and Regular Level Sets
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Compactness in Metric Spaces
- Completeness, Completion, and Uniform Continuity
- Connectedness
- 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
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Determinants of Matrices over a Commutative Ring
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- 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
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- 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
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Properties of the Integral and the Working FTC
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Simple Field Extensions and the Construction of the Complex Numbers
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- 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
The Euclidean inverse function theorem turns an invertible derivative into local coordinates, while higher inverse regularity preserves the class. Rank, nullity, kernels, images, matrix rank, and finite-dimensional orthogonal decomposition describe which derivative coordinates can be inverted and which remain free. These results supply the algebraic and analytic inputs for rank persistence, coordinate normal forms, and tangent kernels.
Differential rank, rectangular minors, submersions, immersions, regular values, level sets, and their tangent spaces are defined first. Nonzero minors make rank lower semicontinuous and provide source coordinates for the constant-rank normal form. Its maximal-rank cases yield local projection and inclusion theorems, openness of submersions, and local graph descriptions of regular levels. Curve velocities identify the tangent kernel intrinsically, after which a finite-dimensional factorization argument proves the vector-valued Lagrange multiplier theorem and its scalar-constraint form.
3 · Logical flowchart
4 · Definitions, theorems and proofs
The rank of a derivative and constant-rank Euclidean maps
Definition
Let , let be open, and let be ( Euclidean maps and diffeomorphisms). The rank of at is where rank is the dimension of the image (Rank and nullity of a linear map with finite-dimensional domain). In the standard bases, this is also the rank of the Jacobian matrix (The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case).
For and , the map has constant rank on when for every . On the empty set this condition is vacuous, so it may hold for more than one ; every assertion that needs a determined rank will assume is nonempty or specify .
Submatrices and minors of a rectangular matrix
Definition
Let be a matrix over a commutative ring (Finite rectangular matrices over a commutative ring, their entries, rows and columns). For increasing lists of distinct row indices and column indices , the submatrix is the matrix whose entry is .
When , the -minor is (For , the determinant over a commutative ring by the Leibniz formula, and for a real matrix), and it is called an -rowed minor. The positive-size condition is part of the terminology here: no determinant of an empty matrix is introduced.
A matrix has rank at least exactly when it has a nonzero -rowed minor
Statement
Let and let . Then if and only if some -rowed minor of is nonzero (Submatrices and minors of a rectangular matrix). Equivalently, the rank of is the largest positive size of a nonzero minor when , and it is when every entry is zero (The rank of a matrix equals the rank of the linear map ).
Facts & Assumptions
Given: A real matrix and a natural with .
The rank of a matrix is the dimension of its column space, because row rank equals column rank (Row space, column space, nullspace, row rank, column rank and matrix rank, Row rank equals column rank, and both equal the number of pivots); a list is independent exactly when only the zero coefficient list has zero linear combination (Linear independence: a finite list is independent when forces every , and a subset is independent when every injective finite list into is independent).
A real matrix has rank exactly when it is invertible, and it is invertible exactly when its determinant is nonzero (Invertible matrix theorem: invertibility, full pivot rank, RREF , trivial nullspace and unique solvability are equivalent, A finite square real matrix is invertible if and only if its determinant is nonzero).
Proof
Suppose first that the -minor is nonzero, and write for the corresponding submatrix.
Conversely, suppose . Choose independent columns and form the resulting matrix . Its column rank and hence its row rank are , so its rows span and contain independent rows.
By [L2], is invertible. If a linear combination of the columns of indexed by vanishes, restricting that equality to the rows in gives , hence . Those columns are independent, so .
The submatrix determined by those columns and rows has rank , so [L2] makes its determinant nonzero. This is an -rowed minor of , proving the converse and the equivalence.
Differential rank is lower semicontinuous
Statement
Let be on an open set. For every natural , the locus is open. Thus is lower semicontinuous. In particular the submersion locus, the immersion locus, and every locus on which the derivative has the largest possible rank are open.
Facts & Assumptions
Given: A map and a natural number .
For , a matrix has rank at least exactly when it has a nonzero -rowed minor (A matrix has rank at least exactly when it has a nonzero -rowed minor, The rank of a derivative and constant-rank Euclidean maps, The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case).
Each fixed-size determinant is a polynomial in the matrix entries, while the first partial derivatives of a map are continuous; sums, products, and composites of continuous Euclidean maps are continuous, and the empty set and whole metric space are open (For every fixed finite size at least one, the determinant of a real square matrix is a polynomial in its matrix entries, Euclidean maps and diffeomorphisms, Euclidean maps are closed under componentwise algebra and composition, The metric topology: a set is open when every one of its points has a ball around it inside the set; closed means open complement).
Proof
If , then ; if , then . Both sets are open.
Assume and fix . By [L1], one -rowed minor of is nonzero.
By [L2], the same minor is a continuous scalar function of . Its nonzero locus contains an open neighbourhood of , and [L1] gives .
Every point of therefore has an open neighbourhood inside it, and the two exceptional cases were settled in step 1.1. Hence is open for every , proving all stated consequences.
Submersions and immersions between Euclidean open sets
Definition
Let , let and be open, and let be .
- is an immersion at when is injective (The kernel and image are linear subspaces, and a linear map is injective if and only if its kernel is trivial), equivalently when (The rank of a derivative and constant-rank Euclidean maps). Thus an immersion point can exist only when .
- is a submersion at when is surjective (Injection, surjection, bijection), equivalently when . Thus a submersion point can exist only when .
The map is an immersion or submersion when the corresponding condition holds at every point of .
Regular and critical points, regular and critical values, and level sets
Definition
Let , let be open, and let be .
- A point is a regular point of when is a submersion at , and a critical point otherwise (Submersions and immersions between Euclidean open sets).
- A value is a regular value when every is a regular point. A value that is not regular is a critical value. In particular every value outside is regular by vacuous truth.
- The level set or fibre over is .
Regularity is a condition on the derivative at points of the fibre, not a claim that the fibre is nonempty.
The tangent space to a regular level set
Definition
Let be , let be a regular value, and let (Regular and critical points, regular and critical values, and level sets). For regular, . This kernel (Kernel and image of a linear map) is the tangent space to the regular level set at .
Since is surjective, rank-nullity gives (Rank-nullity: ). Thus the definition introduces an existing linear subspace of the asserted dimension; it makes no assignment when the fibre is empty because there is then no point .
A nonzero rank minor supplies the source coordinates for the constant-rank theorem
Statement
Let , let be , and suppose . After permuting source and target coordinates, if the leading minor of is nonzero and is a local diffeomorphism at . If , the same conclusion holds with equal to the identity map. Empty coordinate blocks are omitted.
Facts & Assumptions
Given: The map , the point , and .
Positive matrix rank is detected by a nonzero minor (A matrix has rank at least exactly when it has a nonzero -rowed minor, The rank of a derivative and constant-rank Euclidean maps).
A real square matrix is invertible exactly when its determinant is nonzero; a map between equal-dimensional Euclidean open sets with invertible derivative at a point is a local diffeomorphism there, and a map has a local inverse (A finite square real matrix is invertible if and only if its determinant is nonzero, The Euclidean inverse function theorem, A local inverse of a regular map is , Euclidean maps and diffeomorphisms).
Proof
If , take ; it is a diffeomorphism on every open neighbourhood of .
Suppose . By [L1], choose a nonzero -rowed minor and permute coordinates so it is the leading minor. The derivative is block triangular with that block and an identity block of size on its diagonal.
Its determinant is the nonzero leading minor, including the full-rank case where the identity block is empty. Thus [L2] makes invertible and a local diffeomorphism at .
Steps 1.1 and 2.1 cover every possible rank and give the asserted source coordinates.
In source rank coordinates, the remaining components depend only on the rank coordinates
Statement
Assume the hypotheses of A nonzero rank minor supplies the source coordinates for the constant-rank theorem and that has constant rank near . In the source coordinates , shrink to a rectangular neighbourhood and write Then is independent of . When , is locally constant; when , the block is empty; and when , the block is empty.
Facts & Assumptions
Given: A map of constant rank near and the local coordinates from the source-coordinate lemma.
The source-coordinate map is a local diffeomorphism, the chain rule computes the derivative of , and a nonzero -rowed minor forces rank at least (A nonzero rank minor supplies the source coordinates for the constant-rank theorem, The chain rule for total derivatives: , Euclidean maps are closed under componentwise algebra and composition, A matrix has rank at least exactly when it has a nonzero -rowed minor).
A differentiable map with zero derivative on a nonempty connected open Euclidean set is constant (A differentiable map on a connected open Euclidean set has zero derivative exactly when it is constant).
Proof
Shrink the coordinate image to a product of open rectangles around . By [L1], is , has constant rank , and its first components are the coordinates .
If and , any nonzero partial derivative would join the identity block of to form a nonzero -rowed minor, contradicting constant rank by [L1]. Hence all derivatives of vanish.
For each fixed , the rectangle is connected and [L2] makes constant. If , the same argument applies to all components on the connected rectangle; if or , the relevant block is empty and the conclusion is immediate.
Thus, after shrinking, in every rank regime.
The Euclidean constant-rank normal form
Statement
Let , let be , and suppose has constant rank on a neighbourhood of . There are local coordinate diffeomorphisms at and at , both sending the distinguished point to , such that for near . The final zero lies in ; every zero-dimensional block is omitted.
Facts & Assumptions
Given: The stated map, point, and constant rank .
Source rank coordinates make equal to after shrinking, and a differentiable map with zero derivative on a connected open set is constant (A nonzero rank minor supplies the source coordinates for the constant-rank theorem, In source rank coordinates, the remaining components depend only on the rank coordinates, A differentiable map on a connected open Euclidean set has zero derivative exactly when it is constant).
Finite sums, differences, componentwise maps, and composites of Euclidean maps are ( Euclidean maps are closed under componentwise algebra and composition).
Proof
Translate the source and target distinguished points to and apply [L1], obtaining on a product neighbourhood.
Define the target shear . It is a diffeomorphism with explicit inverse by [L2].
The composite satisfies . When , [L1] makes locally constant before the target translation; when or , the empty blocks make the same displayed formula literal.
Taking to be the translated source coordinate map gives the asserted local normal form.
A Euclidean submersion is locally a coordinate projection
Statement
Let and let be . Near a submersion point there are coordinates in which the map is . If , it is a local diffeomorphism.
Facts & Assumptions
Given: A submersion point of .
At a submersion point is surjective and has rank (Submersions and immersions between Euclidean open sets); the rank-at-least- locus is open (Differential rank is lower semicontinuous).
A constant-rank- map has local normal form with the target zero block in (The Euclidean constant-rank normal form).
Proof
By [L1], has rank at least on a neighbourhood of ; it cannot have larger rank, so its rank is constantly there.
Apply [L2]. Because , its normal form is exactly the projection .
If , the block is also empty, so the normal form is the identity and is a local diffeomorphism.
A Euclidean immersion is locally the canonical inclusion and is locally an embedding
Statement
Let and let be . Near an immersion point there are coordinates in which the map is the canonical inclusion . After restricting its domain, is an embedding onto its local image. If , it is a local diffeomorphism.
Facts & Assumptions
Given: An immersion point of .
At an immersion point is injective and has rank , and the rank-at-least- locus is open (Submersions and immersions between Euclidean open sets, Differential rank is lower semicontinuous).
An embedding is an injective map whose corestriction is a homeomorphism onto its image (Homeomorphism, open map, closed map, embedding, and what it means for a property to be topological); the constant-rank normal form at rank is (The Euclidean constant-rank normal form).
Proof
By [L1], the derivative has constant rank near .
By [L2], coordinate diffeomorphisms turn the restriction of into . This map is injective and its inverse on is the continuous projection onto the first coordinates.
Conjugating by the coordinate diffeomorphisms shows that the restricted is an embedding. If , the zero block is empty and the normal form is a local diffeomorphism.
Euclidean submersions are open maps
Statement
Every Euclidean submersion is an open map: if is a submersion and is open, then is open in .
Facts & Assumptions
Given: A Euclidean submersion and an open subset of its domain.
Near every point of a submersion there are coordinate diffeomorphisms in which the map is a coordinate projection (A Euclidean submersion is locally a coordinate projection).
Homeomorphisms and coordinate projections are open maps (Homeomorphism, open map, closed map, embedding, and what it means for a property to be topological, A map into a product is continuous iff each of its components is; the projections are continuous and open; and each projection is surjective when every factor is nonempty, which for an infinite index set uses the Axiom of Choice).
Proof
If , its image is open. Otherwise fix and choose with .
Shrink the local source neighbourhood from [L1] so that it lies in . In the local coordinates, [L2] shows that its image contains an open neighbourhood of lying in .
Every point of is therefore interior, so is open.
A constant-rank level set is locally a coordinate slice
Statement
Let be , , and have constant rank near . Put . In the source coordinates of the constant-rank theorem, there is a neighbourhood of such that Thus a nonempty constant-rank level set is locally a coordinate slice of dimension . If a level set is empty, the pointwise assertion has no instance.
Facts & Assumptions
Given: The map , point , value , and constant rank near .
The level set over is (Regular and critical points, regular and critical values, and level sets).
Local coordinates may be chosen so that and become and the map becomes (The Euclidean constant-rank normal form).
Proof
Apply [L2] and restrict to its source coordinate neighbourhood .
By [L1], a point in represents a point of exactly when , which is exactly the condition ; the coordinates are free.
Pulling this slice back by gives the stated local description. The formula also covers and through the empty-block convention.
A regular level set is locally a graph of dimension
Statement
Let be , , and let be a regular value. Near each point, a regular level set is a graph over of dimension .
More precisely, for put and , so . There are neighbourhoods of and of and a map with and such that, near , The empty fibre satisfies the regular-value convention vacuously, and when the local graph has zero-dimensional domain and is the isolated point .
Facts & Assumptions
Given: The stated map, regular value , and a point .
Surjectivity of persists nearby, and a constant-rank level is locally a coordinate slice (Regular and critical points, regular and critical values, and level sets, Differential rank is lower semicontinuous, A constant-rank level set is locally a coordinate slice).
If is a subspace of the finite-dimensional Euclidean inner-product space , then ; rank-nullity gives , and the inverse function theorem turns an invertible derivative into a local diffeomorphism whose inverse is when the original map is (For a subspace of a finite-dimensional inner product space, , Rank-nullity: , The Euclidean inverse function theorem, A local inverse of a regular map is ).
Proof
By [L1], has constant rank near , and its fibre is a coordinate slice. By [L2], put , so and .
The projection of that slice to along has derivative equal to the identity at : its tangent there is , because differentiating the normal-form slice and undoing the source coordinates gives . By [L2], this projection is a local diffeomorphism.
Inverting the projection writes the slice uniquely as . Its derivative at takes values both in and in the tangent , so ; the zero-dimensional case is the same statement with .
This gives the asserted graph and dimension at every point of a nonempty regular fibre, while the empty-fibre case is vacuous.
Tangent vectors to a regular level set are exactly its curve velocities
Statement
Let be , , let be a regular value, and let . A vector lies in if and only if it is the velocity at zero of a curve with .
Facts & Assumptions
Given: The map, regular value, point, and vector .
The tangent space is (The tangent space to a regular level set), and the chain rule gives (The chain rule for total derivatives: , The derivative and the Riemann integral of a vector-valued function: an intrinsic derivative and a componentwise integral).
Locally the fibre is over , with and (A regular level set is locally a graph of dimension ).
Proof
For the forward direction, suppose lies in the fibre and . Then is constant, so [L1] gives and hence .
For the reverse direction, suppose . Using [L2], define for sufficiently small . This curve lies in the fibre, satisfies , and has .
The two implications are independent and exhaustive. In particular is realized by the same construction, or by the constant curve.
A linear functional annihilating the kernel of a surjection is a unique transpose multiple
Statement
Let be a surjective linear map, with , and let be linear. If vanishes on , then there is a unique such that Equivalently, the row vector of is .
Facts & Assumptions
Given: The surjective linear map and the linear functional vanishing on .
Surjectivity provides a preimage of each standard basis vector, and the standard basis gives the coordinate expansion of every vector in (Injection, surjection, bijection, The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension ).
Kernels are the vectors mapped to zero, and linear maps preserve finite linear combinations (Kernel and image of a linear map, Linear map between vector spaces over the same field, The kernel and image are linear subspaces, and a linear map is injective if and only if its kernel is trivial); the Euclidean inner product is the coordinate dot product (The Euclidean inner product on ).
Proof
For each standard basis vector , choose with , and define . These are finitely many choices.
For , put . Then by [L1] and linearity, so and .
If both and work, surjectivity gives with ; then , so . This proves existence and uniqueness.
Lagrange multipliers for a regular vector-valued level-set constraint
Statement
Let be open, let and be , and suppose is a local maximum or minimum of subject to . If is surjective, then there is a unique such that or equivalently This is a necessary condition, not a sufficient condition for a constrained extremum.
Facts & Assumptions
Given: The maps , the regular constrained point , and .
If is a regular value of a map on an open set, then at every point of its fibre a vector lies in the tangent space exactly when it is the velocity at zero of a curve through inside that fibre (Tangent vectors to a regular level set are exactly its curve velocities).
For a map the locus where the derivative has rank at least is open, so the submersion locus is open (Differential rank is lower semicontinuous); a value is regular when every point of its fibre is a submersion point (Regular and critical points, regular and critical values, and level sets).
A local extremum is defined by the objective inequality on a neighbourhood, and if a differentiable function restricted to a differentiable curve has a local extremum, then its derivative along the curve is zero (Local and strict local extrema for scalar fields on Euclidean open sets, A constrained local extremum annihilates every velocity of a differentiable parametrization).
A linear functional vanishing on the kernel of a surjection is a unique transpose multiple; (A linear functional annihilating the kernel of a surjection is a unique transpose multiple, For a differentiable scalar field, and the unit direction of steepest ascent is the normalized gradient, The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case).
Proof
By [L4] the set of points of at which is surjective is open, and ; on every point of every fibre is a submersion point, so is a regular value of and is a local extremum of subject to . Fix . By [L1] applied to , choose a level-set curve with and inside . The constrained local extremum condition in [L2] makes locally extremal at .
By [L2], . Since was arbitrary, the functional vanishes on .
Apply [L3] to the surjection . It gives a unique with for all , and the gradient representation turns this equality of functionals into .
The argument derives the multiplier equation from a constrained extremum and makes no converse assertion, as claimed.
For one regular constraint, the objective gradient is a scalar multiple of the constraint gradient
Statement
Let be , and suppose is a local maximum or minimum of subject to . If , then there is a unique scalar such that
Facts & Assumptions
Given: The functions, constrained local extremum, and nonzero constraint gradient.
For a scalar function, the Jacobian is the row (The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case), so is surjective exactly when .
At a constrained local extremum with surjective, there is a unique such that (Lagrange multipliers for a regular vector-valued level-set constraint).
Proof
By [L1], the nonzero-gradient hypothesis makes surjective.
Apply [L2]. Since the transpose of the one-row matrix sends to , its conclusion is the displayed equation.
Uniqueness is part of [L2] and also follows directly from .
5 · Examples, counterexamples and false statements
None yet.
Sources
- J. M. Lee, Introduction to Smooth Manifolds, Theorems 7.13 and 8.8-8.12
- L. W. Tu, An Introduction to Manifolds, Sections 11.1-11.2
- J. M. Lee, Introduction to Smooth Manifolds, Theorem 7.13
- L. W. Tu, An Introduction to Manifolds, Section 11.1
- J. M. Lee, Introduction to Smooth Manifolds, rank theorem discussion
- J. M. Lee, Introduction to Smooth Manifolds, Theorems 8.8-8.11
- J. M. Lee, Introduction to Smooth Manifolds, Section 8
- L. W. Tu, An Introduction to Manifolds, Section 11.2
- J. M. Lee, Introduction to Smooth Manifolds, Theorem 8.8
- J. M. Lee, Introduction to Smooth Manifolds, proof of Theorem 7.13
- L. W. Tu, An Introduction to Manifolds, proof of Theorem 11.1
- L. W. Tu, An Introduction to Manifolds, Theorem 11.1
- J. M. Lee, Introduction to Smooth Manifolds, Submersion Theorem
- J. M. Lee, Introduction to Smooth Manifolds, Immersion Theorem
- J. M. Lee, Introduction to Smooth Manifolds, Regular Level Set Theorem
- J. M. Lee, Introduction to Smooth Manifolds, tangent-space discussion after Theorem 8.8
- J. M. Lee, Introduction to Smooth Manifolds, Lagrange multipliers discussion
- University of Toronto MAT237 notes, Section 2.8