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The Direct Method and Euler--Lagrange Equations — Examples
1 · Prerequisites
- Absolute and Conditional Convergence; Rearrangement; Products
- Absolute Continuity and the Sharp Fundamental Theorem of Calculus
- Approximation and Compactness in C(K)
- Arc Length and Rectifiable Curves
- Areas of Elementary Plane Figures
- Banach Alaoglu Goldstine and Krein Milman
- Banach Valued Integration and the Radon Nikodym Property
- Banach-Space Differential Calculus and Banach Manifolds
- Binary Operations, Monoids, Groups and Subgroups
- Bounded Linear Operators and Quotient Spaces
- Bounded Variation and the Riemann–Stieltjes Integral
- Compact Operators and Riesz Schauder Theory
- Compactness
- Compactness in Metric Spaces
- Complete Metrizability, Čech-Completeness, and Baire Category
- Completeness, Completion, and Uniform Continuity
- Complex Lp Spaces and Test-Function Conventions
- 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
- Convergence: Nets and Filters
- Convex and Semicontinuous Functions on Rⁿ
- Convexity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Countability Axioms and Cardinal Functions
- Density Separability and Convolution in Lᵖ
- Determinants of Matrices over a Commutative Ring
- Differentiation of Monotone Functions and the Vitali Covering Theorem
- Distributions Test Functions and Differentiation
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Dual Spaces Adjoint Operators and Annihilators
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Euclidean Surface Measure, Divergence, and Green Identities
- Filters and Ultrafilters
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Fourier Transform Convolution and Approximate Identities
- Fubini and Change of Variables
- Gaussian Elimination, Elementary Matrices and Reduced Row Echelon Form
- Geometric Hahn Banach and Convex Separation
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Harmonic Functions and Mean Values in Rn
- Hausdorff via the Diagonal
- Hilbert Space Geometry and Riesz Representation
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Lax--Milgram and Weak Elliptic Solutions
- Lebesgue Measure on Euclidean Space
- 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
- Measurable Functions and Simple Approximation
- Measures and Their Basic Properties
- Metric Spaces
- Mixed Partials, Taylor Formulae, and Extrema
- Modes of Convergence Egorov and Lusin
- Monadicity and Beck's Theorem
- Monotone Functions, Discontinuities, and Continuity Sets
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Normed and Banach Spaces
- Norming and Separation under Hahn–Banach
- Order, Zorn's Lemma, and the Axiom of Choice
- Orthonormal Bases, Parseval and Fourier Series
- Outer Measure and the Caratheodory Extension Theorem
- Polynomial Rings, the Division Algorithm and Roots
- Power Series and Real-Analytic Functions
- Product Measures and the Fubini Tonelli Theorems
- Properties of the Integral and the Working FTC
- Radon Measures and the Riesz Markov Kakutani Theorem
- Reflexivity and Eberlein Smulian
- Regular Surfaces and Surface Integrals
- Relations, Functions, and Quotients
- Rellich Kondrachov and Sobolev Compactness
- Rings, Subrings, Integral Domains and Fields
- Rⁿ as a Normed Space; Vector-Valued Functions
- Roots, Rational Powers, and Classical Inequalities
- Schwartz Space and the Plancherel Theorem
- Separation Axioms: the Hierarchy
- Sequences and Limits
- Sequences and Series of Functions; Uniform Convergence
- Series: Convergence and the Nonnegative Tests
- Sigma Algebras and Borel Sets
- Signed and Complex Measures Hahn and Jordan
- Simple Field Extensions and the Construction of the Complex Numbers
- Smooth Approximation and Sobolev Extension
- Smooth Partitions of Unity and Exhaustions
- Sobolev Poincare and Morrey Inequalities
- Sobolev Traces and Zero Boundary Values
- Subspaces, Products, and Quotients
- Suprema and Infima
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Analytic Hahn Banach Theorem
- The Baire Principles of Functional Analysis
- The Cantor Set, Baire Category, and Measure Zero in ℝ
- The Complex Exponential and Euler's Formula
- The Derivative and the Mean Value Theorems
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Direct Method and Euler--Lagrange Equations
- The Divergence Theorem and Classical Stokes
- The Duality of Lᵖ and L^q
- The Exponential Function
- The Fundamental Theorems of Calculus
- The Inverse and Implicit Function Theorems
- The Inverse Function Theorem Completed
- The Lebesgue and Riemann Integrals Compared
- The Lebesgue Integral and the Convergence Theorems
- The Logarithm and General Powers
- The Lᵖ Spaces Holder Minkowski and Riesz Fischer
- The Maximal Function and Lebesgue Differentiation
- The Radon Nikodym Theorem and Lebesgue Decomposition
- The Riemann Integral in Rᵐ and Jordan Content
- 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
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
- Weak and Weak Star Topologies
- Weak Derivatives and Sobolev Spaces
2 · Summary
These companions compute the direct method and the Euler--Lagrange equation on explicit energies and delimit each hypothesis by a witness. On the one hand two worked computations: an affine function on a bounded domain is the unique minimiser of the Dirichlet energy among all functions with the same boundary trace, and on a compact interval the energy with fixed endpoint values has its local minimisers satisfying , while free endpoints add the natural conditions at each free endpoint. The fixed-trace and free-trace versions of the -forced Dirichlet energy are then contrasted: the same energy yields the Dirichlet problem in the first case and the Neumann condition in the second. Constant shifts obey , so the free energy is invariant under constants exactly when , and is never coercive on the whole space. Under the stated connected extension-domain hypotheses, compatible zero-mean forcing gives a unique mean-zero weak Neumann solution. Nonzero mean forbids a free local minimiser and cannot be repaired by normalising the solution; on disconnected domains compatibility and normalisation are required on each component.
On the other hand the hypotheses are shown to be load-bearing: coercivity alone does not attain its infimum when weak lower semicontinuity fails at the only candidate ( with , otherwise); a minimising sequence for a weakly lower semicontinuous convex functional need not converge strongly to the minimiser (the standard basis of in the unit ball); a norm-closed set that is not convex need not be weakly closed (the unit sphere of an infinite-dimensional Hilbert space is weakly dense in the unit ball); strict convexity is genuinely needed for uniqueness of a minimiser ( on minimises along a line); a nonconvex gradient integrand can lose weak lower semicontinuity altogether (the sawtooth sequence makes vanish on the sequence but equal at the weak limit ); and stationarity in the Euler--Lagrange equation does not imply a minimum, since has as its only stationary point on yet is unbounded below.
The conventions are those of the main page: bounded domains in Euclidean space, , weak limits taken sequentially, and the Euler--Lagrange equation written . The Dirichlet and free-trace comparison and the nonconvex-gradient counterexample declare the choice principles used by their suppliers. The Hilbert-space counterexamples assume AC for the counting-measure reflexivity and duality interfaces; the unit-sphere example also invokes the HB-dependent weak-closure theorem. The weighted-energy example checks its explicit weak limit directly, without a subsequence extraction. The scalar convexity witness uses no choice principle, while the one-dimensional variation examples explicitly assume Countable Choice for their measure and fundamental-lemma interfaces.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
Non-strict convexity allows many minimisers
Statement refuted
Counterexample. On the real Banach space consider . Then is convex (Convex and strictly convex functionals on a convex subset of a real vector space) and an affine line of minimisers: and for every , while for , . The functional is not strictly convex, so the strictness hypothesis in Strict convexity gives uniqueness of a minimiser is genuinely needed: convexity alone does not force uniqueness of a minimiser.
Facts & Assumptions
Given: The functional , , on the real Banach space .
A function on a convex set is convex when for all and , and strictly convex when the inequality is strict for and with finite values (Convex and strictly convex functionals on a convex subset of a real vector space).
A proper, strictly convex functional has at most one minimiser on a convex set; in particular at most one finite minimiser (Strict convexity gives uniqueness of a minimiser).
Counterexample
is convex. For , and one computes and , whose difference is ; hence is convex by [F1].
The minimisers. Since for every , and exactly when , the infimum of on is and the set of minimisers is exactly the affine line .
is not strictly convex. Take the distinct points and , which satisfy , and . Then , so the strict inequality required by [F1] fails; hence is not strictly convex.
Uniqueness genuinely needs strictness. The line consists of pairwise distinct minimisers of the convex functional by step 1.2, so convexity alone does not force uniqueness; by [F2] the uniqueness conclusion requires the strict convexity hypothesis, which fails for this functional by step 1.3. This is exactly the sharpness recorded in the statement refuted.
A coercive functional need not attain without weak lower semicontinuity
Statement refuted
Counterexample. Assume the Axiom of Choice (The Axiom of Choice). Let (Square-summable families on an arbitrary index set and the space ), let be the family that is at and elsewhere, and define by Then is proper and coercive (Proper, coercive and weakly lower semicontinuous extended-real functionals) and , but no point of minimises : the value is not attained, because only gives and . The functional is not weakly sequentially lower semicontinuous at : for , while . Hence the weak lower semicontinuity hypothesis in The direct method in a reflexive Banach space cannot be replaced by coercivity alone, even in a reflexive space.
Facts & Assumptions
Given: The Axiom of Choice; the real Hilbert space (Square-summable families on an arbitrary index set and the space ), its coordinate vectors , namely the family that is at and elsewhere, and the functional with and for . The counting-measure dictionary is the space of counting measure identifies with real , which is reflexive (and thus Banach) by Reflexivity of Lp for one less p less infinity under Countable Choice, supplied here by AC; the series pairing is its inner product.
Proper, coercive and weakly sequentially lower semicontinuous functionals are defined as in Proper, coercive and weakly lower semicontinuous extended-real functionals; a functional is proper when its effective domain is nonempty, equivalently when its infimum is less than (it may be ).
In the direct method, weak sequential lower semicontinuity is a hypothesis alongside coercivity; The direct method in a reflexive Banach space states all of its hypotheses explicitly, so a coercive proper functional on a reflexive space need not attain when that hypothesis fails.
Each coordinate vector satisfies and , and : by the duality of and every bounded linear functional on is for a unique (Counting measure specializes the representation theorem to and ), so , and because a square-summable family has small tails, that is, for every there is a finite with (Square-summable families on an arbitrary index set and the space ), whence for every beyond all elements of ; weak convergence means convergence against every bounded linear functional (Weak convergence of nets and sequences).
Counterexample
is proper. The effective domain of is all of , which is nonempty, and with as , so ; by [F1] the functional is proper.
is coercive. For one has (and the value does not affect large norms). Given , put ; then implies , so every sublevel set is bounded and is coercive by [F1].
None of the values is attained. If then and , hence , a contradiction; and . Since , the infimum is not attained.
Failure of weak lower semicontinuity at . Let for . Then by [F3], and for every bounded linear functional on one has by [F3]; hence . On the other hand gives . Hence , and is not weakly sequentially lower semicontinuous at .
Conclusion. The functional is proper and coercive on the reflexive space , yet attains no minimum and fails weak lower semicontinuity; hence the weak lower semicontinuity hypothesis of [F2] cannot be dropped, and coercivity alone does not give attainment even in a reflexive space.
A minimising sequence need not converge strongly
Statement refuted
Counterexample. Assume the Axiom of Choice (The Axiom of Choice). Let , let be its closed unit ball and let Then is nonnegative, convex and continuous, , and is a minimising sequence for with ; moreover and is the unique minimiser of on , but for every , so no subsequence of the minimising sequence converges strongly to the minimiser. The compactness recovered in the direct method is therefore genuinely weak compactness (The direct method in a reflexive Banach space).
Facts & Assumptions
Given: The Axiom of Choice; the real Hilbert space (Square-summable families on an arbitrary index set and the space ), its coordinate vectors , namely the family that is at and elsewhere, its closed unit ball , and the functional . The counting-measure dictionary is the space of counting measure identifies with real , which is reflexive (and thus Banach) by Reflexivity of Lp for one less p less infinity under Countable Choice, supplied here by AC; the series pairing is its inner product.
The series defining converges absolutely for every because and ; moreover , so is continuous, and is convex and nonnegative (Square-summable families on an arbitrary index set and the space ).
Each coordinate vector satisfies , and : by the duality of and every bounded linear functional on is for a unique (Counting measure specializes the representation theorem to and ), so , and because a square-summable family has small tails, that is, for every there is a finite with (Square-summable families on an arbitrary index set and the space ), whence for every beyond all elements of ; weak convergence means convergence against every bounded linear functional (Weak convergence of nets and sequences).
In the direct method the compactness recovered is weak sequential compactness: a norm-bounded sequence in a reflexive Banach space has a weakly convergent subsequence (A bounded sequence in a reflexive Banach space has a weakly convergent subsequence), and the limit need not be a strong limit (The direct method in a reflexive Banach space, Proper, coercive and weakly lower semicontinuous extended-real functionals).
Counterexample
is nonnegative, convex and continuous. Nonnegativity and convexity are immediate from the formula. For continuity, expanding the squares gives , and by Cauchy-Schwarz, while ; hence as .
The minimising sequence. The point has , and , so . By [F2] the vectors lie in and satisfy , so is a minimising sequence for .
The unique minimiser. If has , then for every , hence for every and . So is the unique minimiser of on .
No strong convergence of the minimising sequence. By [F2] one has with for every , so does not tend to ; a fortiori no subsequence of converges in norm to , the unique minimiser of step 2.1.
Conclusion. The bounded minimising sequence converges weakly to by [F2], but no subsequence converges in norm to the unique minimiser by step 3.1. Thus the weak subsequence conclusion described in [F3], under that theorem's stated principles, cannot be upgraded to strong convergence of minimising sequences. No additional extraction is needed for this explicit witness.
A norm-closed nonconvex set need not be weakly closed
Statement refuted
Counterexample. Assume the Axiom of Choice (The Axiom of Choice). Let (Hilbert space, Square-summable families on an arbitrary index set and the space ) and let be its unit sphere. Then is norm closed and norm bounded, but it is not weakly sequentially closed: the coordinate vectors , the families that are at and elsewhere, lie in and satisfy . Indeed the weak closure of is the closed unit ball (Weak closure of the unit sphere is the closed unit ball). So the convexity hypothesis in A norm-closed convex set is weakly sequentially closed cannot be dropped, and a norm-closed admissible set need not be weakly closed for The direct method in a reflexive Banach space.
Facts & Assumptions
Given: The Axiom of Choice; the real Hilbert space (Hilbert space, Square-summable families on an arbitrary index set and the space ), its coordinate vectors , the families that are at and elsewhere, and its unit sphere . The counting-measure dictionary is the space of counting measure identifies with real , which is reflexive (and thus Banach) by Reflexivity of Lp for one less p less infinity under Countable Choice, supplied here by AC; the series pairing is its inner product.
The unit sphere of an infinite-dimensional Hilbert space is norm closed and norm bounded; its weak closure is the closed unit ball (Weak closure of the unit sphere is the closed unit ball).
Each coordinate vector satisfies , and : by the duality of and every bounded linear functional on is for a unique (Counting measure specializes the representation theorem to and ), so , and because a square-summable family has small tails, that is, for every there is a finite with (Square-summable families on an arbitrary index set and the space ), whence for every beyond all elements of ; weak convergence means convergence against every bounded linear functional (Weak convergence of nets and sequences). Hence the sequence lies in and converges weakly to the origin, which is not in .
A norm-closed convex set is weakly closed under the Axiom of Choice (A norm-closed convex set is weakly sequentially closed); the direct method's admissibility requirement is weak sequential closedness (The direct method in a reflexive Banach space).
Counterexample
is norm closed and norm bounded. The map is continuous for the norm topology and is closed in , so , its preimage, is norm closed; and for , so is norm bounded.
is not weakly sequentially closed. By [F2] the orthonormal sequence lies in , satisfies , and ; hence a sequence in converges weakly to a point outside , so is not weakly sequentially closed.
The failure is not an artefact of the sequence. By [F1] the full weak closure of is the closed unit ball, which strictly contains ; so is not weakly closed. This is a property of the set, independent of which witness sequence is used.
Conclusion. The set is norm closed (even bounded) but not weakly sequentially closed, so the convexity hypothesis in [F3] cannot be dropped; consequently a norm-closed nonconvex admissible set need not qualify for the direct method on the strength of norm closedness alone.
Stationarity of the Euler-Lagrange equation does not imply a minimum
Statement refuted
Counterexample. Assume the Axiom of Choice (The Axiom of Choice). Let be a bounded domain and let Then is the only stationary point: its weak Euler-Lagrange (stationarity) equation reads for every , which forces and then almost everywhere by the Poincare inequality (The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction). But is not bounded below: for any fixed nonzero one has as . So the Euler-Lagrange equation is a necessary condition only; the functional is concave, not convex, and Stationarity is sufficient for a global minimum of a convex differentiable functional does not apply.
Facts & Assumptions
Given: The Axiom of Choice; a bounded domain , the functional on , and the Lagrangian .
A stationary point of is a point whose first variation vanishes in every direction . The quadratic expansion below computes this variation directly for every . For , its vanishing is also the fixed-zero-trace weak Euler-Lagrange formula of The weak Euler-Lagrange equation for integral functionals with fixed trace, since , and the differentiation growth bounds hold.
On the full linear space , at a local minimiser the first variation vanishes (The first variation vanishes at an interior minimiser); the converse requires convexity and stationarity in the sense for all competitors, by Stationarity is sufficient for a global minimum of a convex differentiable functional.
Poincare's inequality controls the norm by the Dirichlet energy on (The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction); in particular forces almost everywhere.
The Lagrangian is concave, not convex, in (Convex and strictly convex functionals on a convex subset of a real vector space).
Counterexample
The stationary equation. For one has and , so the exact expansion gives the bounded first variation by Holder (Holder's inequality for integrals, including the endpoint cases). Thus a point satisfies the weak Euler-Lagrange equation of [F1] exactly when for every .
is not a minimiser, not even locally. Fix any nonzero , which exists: choose a ball and a nonzero smooth bump supported inside it (Compactly supported scaled Euclidean bumps). Poincare [F3] gives , and consider . As this tends to , so is not bounded below on ; and for every one has , and as , so is not a local minimiser either.
The only stationary point. If is stationary, step 1.1 applies with the admissible test function , giving ; by [F3] this forces and hence almost everywhere. Conversely satisfies the equation because . So is the only stationary point of .
Conclusion. The only stationary point of fails to be a minimiser by step 1.2, so the Euler-Lagrange equation is a necessary condition only; the failure is consistent with [F2], since is concave in the gradient by [F4] and the convex stationarity-sufficiency theorem therefore does not apply.
The one-dimensional Euler-Lagrange equation for an energy with a potential
Example
Example. Assume Countable Choice (The Axiom of Countable Choice ()). Let , let be real numbers and let On the admissible class with fixed endpoint values , , a local minimiser in the norm satisfies the boundary value problem the classical Euler-Lagrange equation of the Lagrangian (The classical Euler-Lagrange equation under regularity). In the special case this is the one-dimensional Laplace equation with the affine solution ; for it is the equation of an inverted harmonic oscillator .
Facts & Assumptions
Given: Countable Choice; a function , a compact interval with , the functional on the admissible class of with fixed endpoint values , , and the Lagrangian .
The conclusion has the shape of the classical Euler-Lagrange equation of The classical Euler-Lagrange equation under regularity for the Lagrangian , whose partials are and . That corollary also assumes and the growth hypotheses of the weak Euler-Lagrange theorem (The weak Euler-Lagrange equation for integral functionals with fixed trace), which need not hold for a general ; the verification below therefore computes the equation directly from the minimality of .
One-variable mean value theorem and Fermat's interior-extremum theorem: a differentiable function on an interval with an interior local extremum has vanishing derivative there, and the mean value theorem identifies with for some (The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with , Fermat's interior extremum theorem: if has a local extremum at a point interior to its domain and is differentiable at , then ).
Integration by parts on a compactly supported test function: for and . This is Integration by parts for continuous factors with Riemann-integrable extensions of their interior derivatives with and ; its continuous integrands have equal Riemann and Lebesgue integrals by A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral.
Fundamental lemma: a continuous function on an open set orthogonal to every compactly supported smooth test function vanishes identically (The fundamental lemma of the calculus of variations).
A function on with on is affine, since has vanishing derivative and is therefore constant (The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with ).
Verification
The first variation. Let . Since vanishes near the endpoints, belongs to the admissible class for every , and for small it is close to in , so has a local minimum at . Computing the difference quotient, , and by the mean value theorem [F2] the last term equals with ; as this converges to uniformly on , because is uniformly continuous by Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous on a compact interval containing the values and . Hence is differentiable at with . This is the direct computation announced in [F1].
Fermat's theorem. The point is an interior local minimum of the differentiable function , so [F2] gives , that is for every .
The differential equation. For integration by parts [F3] gives , so the identity of step 2.1 reads for every such . The function is continuous on , being a sum of continuous functions, so the fundamental lemma [F4] gives on , that is .
Endpoint conditions and the two instances. The admissible class fixes and , so solves the boundary value problem of the statement. For the equation is , and [F5] makes affine, with values determined by the endpoints: . For one has , so the equation reads , the equation of an inverted harmonic oscillator.
A nonconvex gradient energy can lose weak lower semicontinuity
Statement refuted
Counterexample. Assume the Axiom of Choice, the ultrafilter lemma, DC and HB (The Axiom of Choice, The ultrafilter extension principle (UL/BPI), The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain, The real dominated-extension principle as an additional hypothesis over ZF). On let be the -periodic function with on and on , and put for integers . Then uniformly, almost everywhere, and in . For the nonnegative integrand , which is not convex since , The integral is interpreted in on ; it need not be finite for every function. satisfies for every , while . Hence and is not weakly sequentially lower semicontinuous. Also is not convex: , so A convex norm-lower-semicontinuous functional is weakly lower semicontinuous does not apply. Nevertheless attains its minimum at every . This example does not refute the existence conclusion of The direct method for convex integral functionals with convexity removed: it also lies outside that theorem's and upper-growth hypotheses.
Facts & Assumptions
Given: The Axiom of Choice (for ACL), the ultrafilter lemma, DC and HB; the interval ; the -periodic continuous function with on and on ; the functions ; and the integrand with . The weak compactness step uses the ultrafilter lemma, DC and HB (The ultrafilter extension principle (UL/BPI), The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain, The real dominated-extension principle as an additional hypothesis over ZF).
The function is continuous, -periodic, satisfies and , and is piecewise linear with almost everywhere. Hence is absolutely continuous on with a.e. derivative ; by the ACL characterisation with weak derivative (The ACL characterisation of , Integer-order Sobolev spaces and their norms).
For the maps and are bounded linear functionals on with operator norm at most , by Cauchy-Schwarz against the two components of the Sobolev norm (Integer-order Sobolev spaces and their norms).
is a reflexive Banach space, so every norm-bounded sequence in it has a weakly convergent subsequence under the ultrafilter lemma, DC and HB (W^{1,p}(Omega) is reflexive for 1<p<infinity, Reflexivity is equivalent to weak subsequential compactness of bounded sequences).
If has for all real , take to obtain , so as an class. This directly identifies the subsequential Sobolev limit; uniqueness of weak probability-measure limits is not used.
The weak lower semicontinuity lemma assumes convexity of the functional (A convex norm-lower-semicontinuous functional is weakly lower semicontinuous). The convex integral existence theorem also assumes and a -growth upper bound (The direct method for convex integral functionals); the present interval and quartic integrand fail these hypotheses for . Nonconvexity is checked by the midpoint inequality (Convex and strictly convex functionals on a convex subset of a real vector space), and existence here is decided by the explicit values of .
Counterexample
The sequence and its bounds. By [F1] the functions lie in with and almost everywhere; hence and for every , so converges to in and is norm bounded in .
The values of . Since almost everywhere, for every ; and . Hence .
in . Suppose not; then there are a bounded linear functional on and with for infinitely many . Along that subsequence, which stays norm bounded, [F3] provides a further subsequence with for some . For every the bounded functional of [F2] gives , while because in by step 1.1; passing to the limit, for all , so by taking in [F4]. But then , contradicting . Hence in .
Conclusion and scope. Steps 1.2 and 2.1 give along a sequence converging weakly to , so is not weakly sequentially lower semicontinuous. Since but , is not convex. Yet and , so its minimum is attained. Thus the example shows loss of weak lower semicontinuity for a nonconvex gradient energy, without asserting necessity of convexity for existence; the cited convex integral theorem also has dimensional and growth hypotheses absent here.
The natural Neumann condition from a free endpoint in one dimension
Example
Example. Assume Countable Choice (The Axiom of Countable Choice ()) and let . On consider with , no boundary conditions, and let be a free-endpoint local minimiser in the norm. Retaining the boundary term produced by integration by parts gives, in addition to the Euler-Lagrange equation (The classical Euler-Lagrange equation under regularity), the two natural boundary conditions which are precisely the one-dimensional case of The natural boundary condition for free boundary variations. For they read on with .
Facts & Assumptions
Given: Countable Choice and ; a function , the functional on with no boundary conditions, and a free-endpoint local minimiser : for all with small.
The endpoint conditions are the one-dimensional analogue of The natural boundary condition for free boundary variations, whose stated domain and Sobolev hypotheses do not cover this example. They will be proved directly below; the outward signs are at and at .
The interior equation has the form in The classical Euler-Lagrange equation under regularity, but is derived directly in step 2.1 because no global Sobolev growth bound is imposed here.
Continuous partials make the integrand totally differentiable (If all partial derivatives exist on a neighbourhood and are continuous at a point, then the map is totally differentiable there with Jacobian derivative), and the chain rule (The chain rule for total derivatives: ) computes its derivative along as . First variation: for every the function has an interior local minimum at and, by the mean value theorem applied to the integrand, (Fermat's interior extremum theorem: if has a local extremum at a point interior to its domain and is differentiable at , then , The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with ).
Integration by parts and the fundamental lemma: for , one has for every by Integration by parts for continuous factors with Riemann-integrable extensions of their interior derivatives; the continuous integrands have equal Riemann and Lebesgue integrals by A bounded Riemann integrable function on a closed bounded interval is Lebesgue measurable and has the same integral. A continuous function orthogonal to all compactly supported test functions vanishes (The fundamental lemma of the calculus of variations).
Composites of Euclidean maps are , so is when and ( Euclidean maps are closed under componentwise algebra and composition, maps and multi-index derivative notation in Euclidean space).
Verification
The first-variation identity. Let . Since no boundary conditions are imposed, lies in the admissible class for every and for small it is close to in the norm, so has an interior local minimum at ; the mean value theorem expresses the integrand difference quotient as for some . Heine--Cantor (Heine-Cantor: a continuous map from a compact metric space to any metric space is uniformly continuous) makes the partials uniformly continuous on a compact set containing these arguments, this quotient therefore converges uniformly to its value at , and its integral is . Fermat's theorem in [F3] then gives .
The interior equation. Taking in step 1.1 and integrating by parts, using that is by [F5] and has derivative , gives for every compactly supported ; the integrand is continuous, so [F4] gives on , the classical Euler-Lagrange equation.
The boundary identity. Let now be arbitrary. Writing and using the interior equation of step 2.1, step 1.1 becomes by [F4], that is for every .
Both natural conditions, and the instance. Choosing in step 3.1 gives , and gives ; these are the one-dimensional natural boundary conditions, the general form of [F1]. For one has and , so the interior equation of step 2.1 reads on and the natural conditions read .
The harmonic affine extension minimises the Dirichlet energy
Example
Example. Assume the Axiom of Choice (The Axiom of Choice). Let , , be a bounded domain and let be affine on , so that and is constant. Then is the unique minimiser of the Dirichlet energy on the affine trace class (The trace operator on a bounded domain): for every , and with equality if and only if almost everywhere, and then almost everywhere by the Poincare inequality on (The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction).
Facts & Assumptions
Given: The Axiom of Choice; a bounded domain , an affine function on (so is a constant field and ), the Dirichlet energy , and the affine trace class .
is nonempty, convex and weakly closed, and for every by the kernel description (The kernel of the trace is the closure of the test functions, The trace operator on a bounded domain).
Poincare's inequality on : if almost everywhere for , then (The Poincare inequality for zero-boundary Sobolev closures on domains bounded in one direction).
Under the Axiom of Choice, the ultrafilter lemma, Dependent Choice and Hahn--Banach, the Dirichlet principle also identifies an affine-class minimiser with the unique weak solution (The Dirichlet principle for the Poisson equation). In the zero-forcing case here, is weakly harmonic with trace , since is constant and for every (The notation and the reserved zero-boundary symbol).
Verification
Orthogonality of the cross term. For one has by [F1], and is a constant field, so : each component of has vanishing integral, because is the -limit of functions in and for those the integral of each partial derivative vanishes by integration by parts against the smooth constant field (Divergence on a bounded C1 Euclidean domain). Passage to the limit is valid since by Holder (Holder's inequality for integrals, including the endpoint cases).
The energy identity. Expanding the square, , and integrating with step 1.1 gives .
Equality case. Equality holds exactly when almost everywhere, which by [F2] forces , that is almost everywhere.
is the minimiser. By steps 2.1 and 3.1 every satisfies with equality only for ; since , it is the unique minimiser of on . This direct completion-of-the-square argument proves the example's claim. Under the additional choice hypotheses stated in [F3], the general Dirichlet principle also identifies this minimiser with the weak solution; the weak harmonicity of was checked in [F3].
Fixed-trace and free-trace variations give different boundary equations
Example
Example. Assume the Axiom of Choice (The Axiom of Choice). Let , , be a bounded domain, let , and put (a) Fixed trace: a local minimiser in the norm on the nonempty affine class , with , solves the weak Dirichlet problem , (The Dirichlet principle for the Poisson equation, The affine Dirichlet trace class is nonempty, convex and weakly closed). (b) Free trace: if is a local minimiser in the norm on , then almost everywhere in and on . Choosing the continuous representative makes the interior equation pointwise. This is the boundary condition suggested by The natural boundary condition for free boundary variations, proved directly here since a general forcing need not give a integrand.
The constant-shift identity is . Thus is invariant under global constants exactly when , and it is never coercive on all of . If , no free local minimiser exists. On a connected domain satisfying the extension-domain hypothesis of Weak Neumann solvability on the mean-zero subspace, zero-mean forcing gives a unique mean-zero weak Neumann solution; nonzero mean cannot be repaired merely by normalising the solution. On a disconnected domain compatibility is required on each component and the additive constants are independent on those components.
Facts & Assumptions
Given: The Axiom of Choice; the real domain and data above; local minimality in on in (a), or in on the whole space in (b).
The fixed-trace class is a translate of ; its admissible directions are exactly that subspace (The affine Dirichlet trace class is nonempty, convex and weakly closed). The weak Euler–Lagrange identity holds for these directions (The weak Euler-Lagrange equation for integral functionals with fixed trace).
The Dirichlet principle identifies its energy minimiser with the unique weak Poisson solution (The Dirichlet principle for the Poisson equation).
First Green identity holds for and smooth tests under Countable Choice, supplied by AC (First Green identity). A locally integrable function pairing to zero with all compactly supported tests is zero almost everywhere (The fundamental lemma of the calculus of variations). A continuous boundary flux pairing to zero with all ambient smooth tests vanishes on the boundary (The boundary fundamental lemma of the calculus of variations).
The Neumann supplier requires a bounded connected extension domain and a bounded forcing functional with ; it gives a unique mean-zero solution and all other solutions differ by constants. It also records the componentwise compatibility needed in the disconnected case (Weak Neumann solvability on the mean-zero subspace).
Holder makes bounded on , and bounds all terms in the quadratic expansion below (Holder's inequality for integrals, including the endpoint cases). Fermat's theorem gives a zero derivative at a two-sided interior local minimum (Fermat's interior extremum theorem: if has a local extremum at a point interior to its domain and is differentiable at , then ).
Verification
Fixed trace. For every , the curve stays in by [F1]. Its energy is exactly . Local minimality and [F5] give , the weak Dirichlet equation. Moreover the same expansion at shows , so this local minimiser is global and [F2] applies.
Free trace. For every , the curve is admissible and close to in the norm as . The same quadratic expansion and [F5] give . For compactly supported tests, Green identity [F3] then yields , so almost everywhere by the fundamental lemma. Returning to arbitrary smooth tests gives by Green identity; the continuous field and the boundary fundamental lemma force .
Constants and compatibility. Direct expansion gives . If , arbitrarily small constant shifts in the appropriate sign lower the energy, and large shifts make it tend to ; if , arbitrarily large shifts leave it fixed. In both cases coercivity on the full space fails. In case (b), testing the first variation with gives . At each boundary point the one-sided graph convention gives a smaller connected subgraph neighbourhood meeting only one component; at interior points use a ball in the component. Thus a component indicator extends locally constantly to and is a admissible direction, giving the componentwise condition. Under the connected extension-domain hypotheses of [F4], the functional is bounded by [F5] and satisfies precisely for zero-mean forcing, so [F4] supplies the normalised weak solution.
Sources
- Gerald Teschl, Partial Differential Equations: From Classical to Modern (2026 author manuscript; complete 392-page archived text)
- Riccardo Cristoferi, Calculus of Variations: Lecture Notes, Carnegie Mellon University 2016 (complete 133-page notes)
- Francesco Paolo Maiale (course by Giovanni Alberti), Lecture Notes Calculus of Variations A, University of Pisa (last update 21 August 2019; complete 149-page notes)
- Viktor Grigoryan, Math 246B Partial Differential Equations, UCSB 2011 (complete 31-page course notes)
- Sung-Jin Oh, Lecture Notes for Math 222A, UC Berkeley, 19 March 2024 (complete 179-page author PDF)