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Mixed Partials, Taylor Formulae, and Extrema

1 · Prerequisites

2 · Summary

For scalar fields on Euclidean open sets, total derivatives provide gradients and the one-variable Taylor theorems provide the analytic input along a line segment. Finite multinomial identities organize repeated directional differentiation, and Euclidean compactness supplies the uniform quadratic estimates used in the Hessian test.

The development introduces multi-index and Hessian notation, separates Peano's and Young's hypotheses for equality of mixed partials, and derives Taylor expansions with Lagrange and Peano remainders. It then treats necessary conditions for extrema, the definite-Hessian test with its semidefinite limitation, and the multiplier equation for explicitly parametrized graph constraints.

3 · Logical flowchart

4 · Definitions, theorems and proofs

DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-02Open item page →

Ck maps and multi-index derivative notation in Euclidean space

Definition

Let m≥1, let U⊆Rm be open, and let f:U→R. A multi-index is α=(α0,…,αm−1)∈Nm. Put

∣α∣:=∑i<mαi,α!:=∏i<mαi!,hα:=∏i<mhiαi(h∈Rm).

Here ∣α∣ and α! use the natural-number sum and product of Finite sums and finite products of natural numbers, ∑k<nak and ∏k<nak in N, and n! is the factorial of The factorial n! and the falling factorial nk‾, defined by recursion in N. By contrast, hα is the finite product in R of Finite sums and finite products, by recursion, with the natural exponents interpreted by Integer powers am. For the zero multi-index 0, set D0f:=f. For nonzero α, write

Dαf:=∂0α0⋯∂m−1αm−1f

for this displayed, canonical order whenever it exists. Coordinate partial derivatives have the meaning fixed in Directional derivatives and partial derivatives of a map U⊆Rm→Rn.

For k∈N, f is of class Ck on U when, for every word (i1,…,ir) of coordinate indices with 0≤r≤k, the iterated derivative ∂ir⋯∂i1f exists and is continuous on U; the word of length 0 denotes f. Thus this definition does not presuppose that differently ordered derivatives are equal. Equality of their values is a later theorem under these regularity hypotheses.

DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-02Open item page →

The Hessian matrix and critical points of a scalar field

Definition

Let U⊆Rm be open and let f:U→R have second partial derivatives. Its Hessian at a∈U is the matrix Hf(a)=(∂i∂jf(a))i,j<m in the matrix space of The vector space Mm×n(F):=F m×n of m by n matrices over a field, with entrywise operations, using the multi-index notation of Ck maps and multi-index derivative notation in Euclidean space. A point a is critical when its gradient ∇f(a) is zero, with the gradient convention of The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

A rectangular second difference equals a mixed partial times the side lengths

Statement

Let R be a closed axis-parallel rectangle and suppose that fx and fxy exist on an open neighbourhood of R. If (x0,y0),(x1,y1) are opposite corners of a nondegenerate subrectangle of R, then some ξ strictly between x0,x1 and some η strictly between y0,y1 satisfy

f(x1,y1)−f(x1,y0)−f(x0,y1)+f(x0,y0)=(x1−x0)(y1−y0)fxy(ξ,η).

Facts & Assumptions

Given: The stated open-neighbourhood hypotheses and a nondegenerate subrectangle of R.

[L1]

After ordering its two endpoints, the one-variable mean-value theorem gives g(v)−g(u)=(v−u)g′(c) for a function continuous on the closed interval and differentiable on its interior, with c strictly between the endpoints (The mean value theorem, as the case g(x)=x of Cauchy's: for f continuous on [a,b] with a<b and differentiable on (a,b) there is c∈(a,b) with f(b)−f(a)=f′(c)(b−a)).

Proof

technique · direct
1.1

Apply [L1] in the x variable to x↦f(x,y1)−f(x,y0). The stated existence of fx on an open neighbourhood gives the required one-variable regularity, and the rectangle difference is (x1−x0)(fx(ξ,y1)−fx(ξ,y0)).

L1givenchoose
2.1

Apply [L1] in the y variable to y↦fx(ξ,y). Since fxy exists on an open neighbourhood, this one-variable map is continuous on the closed interval and differentiable on its interior. This yields (y1−y0)fxy(ξ,η) and proves the formula.

step 1.1L1givenchoose∎
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Peano's mixed-partial theorem from continuity of one mixed partial

Statement

Let f have fxy in a neighbourhood of (a,b), with fxy continuous at (a,b), and let fyx(a,b) exist. Then fxy(a,b)=fyx(a,b).

Facts & Assumptions

Given: The hypotheses in the statement.

[L1]

When fx and fxy exist on a neighbourhood of a rectangle, its rectangular second difference is the product of the side lengths and a value of fxy (A rectangular second difference equals a mixed partial times the side lengths).

Proof

technique · direct
1.1

For sufficiently small nonzero h,k, apply [L1] to the rectangle with corners (a,b) and (a+h,b+k). After division by hk, continuity of fxy at (a,b) makes the limit, as h,k→0, equal to fxy(a,b).

L1givenalgebra
2.1

For fixed nonzero h, first let k→0 in the same rectangle quotient; it becomes (fy(a+h,b)−fy(a,b))/h. Letting h→0 gives the defining quotient for fyx(a,b).

step 1.1givenalgebra
3.1

The two limits are equal, proving fxy(a,b)=fyx(a,b).

step 1.1step 2.1∎
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Young's theorem: total differentiability of the first partials forces equality of mixed partials

Statement

Let f be defined on a disk U about (a,b), with fx and fy existing on U. If fx and fy are totally differentiable at (a,b), then both mixed partials exist there and fxy(a,b)=fyx(a,b).

Facts & Assumptions

Given: The hypotheses of the statement.

[L1]

Total differentiability supplies a linear approximation with an error that is little-oh of the Euclidean increment (The total (Fréchet) derivative Df(a) as the linear first-order approximation with o(∥h∥2) remainder).

[L2]

A total derivative is linear. Restricting its defining expansion to a coordinate axis shows directly that its corresponding coordinate coefficient is the partial derivative in that coordinate (The total (Fréchet) derivative Df(a) as the linear first-order approximation with o(∥h∥2) remainder).

Proof

technique · direct
1.1

By [L1] and [L2], write Dfx(a,b)(s,t)=As+Bt and Dfy(a,b)(s,t)=Cs+Dt.

L1L2givenalgebra

fx(a+s,b+t)=fx(a,b)+As+Bt+o ⁣(s2+t2)

and analogously fy(a+s,b+t)=fy(a,b)+Cs+Dt+o ⁣(s2+t2). Restricting the first expansion to s=0 and the second to t=0 shows that B=fxy(a,b) and C=fyx(a,b); in particular both mixed partials exist.

2.1

By [L3], for small nonzero h, define the following rectangular difference.

step 1.1L3algebrachoose

Δh:=f(a+h,b+h)−f(a+h,b)−f(a,b+h)+f(a,b).

Apply the mean-value theorem to x↦f(x,b+h)−f(x,b) on the interval with endpoints a,a+h. For some θh between 0 and 1,

Δh=h(fx(a+θhh,b+h)−fx(a+θhh,b))=Bh2+o(h2),

where the last equality is the first expansion of step 1.1 at (θhh,h) and (θhh,0).

2.2

Apply [L3] instead to y↦f(a+h,y)−f(a,y) on the interval with endpoints b,b+h.

step 1.1L3algebrachoose

For some ηh between 0 and 1,

Δh=h(fy(a+h,b+ηhh)−fy(a,b+ηhh))=Ch2+o(h2),

by the second expansion of step 1.1 at (h,ηhh) and (0,ηhh).

3.1

Steps 2.1 and 2.2 give (B−C)h2=o(h2). Divide by h2 and let h→0 to obtain B=C, hence fxy(a,b)=fyx(a,b).

step 1.1step 2.1step 2.2algebra∎
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Clairaut--Schwarz theorem for continuous second partial derivatives

Statement

If f is C2 on an open subset of Rm, then ∂i∂jf=∂j∂if for every pair of coordinate indices.

Facts & Assumptions

Given: A C2 scalar field and coordinate indices i,j<m.

[L1]

If fxy exists on a neighbourhood of a point and is continuous at that point, while fyx exists there, then the two values are equal (Peano's mixed-partial theorem from continuity of one mixed partial).

[L2]

The C2 condition supplies every ordered partial derivative of length at most two, continuously on the open set (Ck maps and multi-index derivative notation in Euclidean space).

Proof

technique · direct
1.1

At an arbitrary point, [L2] supplies ∂i∂jf on a neighbourhood and continuously there, as well as the reversed partial ∂j∂if at the point.

L2given
2.1

Apply [L1] at an arbitrary point to obtain ∂i∂jf=∂j∂if.

step 1.1L1∎
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

The Hessian of a C2 scalar field is symmetric

Statement

For a C2 scalar field f, Hf(a)T=Hf(a) at every point a.

Facts & Assumptions

Given: A C2 scalar field f and a point a.

[L1]

The (i,j) entry of the Hessian is ∂i∂jf(a) (The Hessian matrix and critical points of a scalar field).

[L2]

Continuous second partial derivatives commute (Clairaut--Schwarz theorem for continuous second partial derivatives).

Proof

technique · direct
1.1

For every i,j, [L1] and [L2] give (Hf(a))ij=∂j∂if(a)=(Hf(a))ji.

L1L2
2.1

Entrywise equality with the transpose proves symmetry.

step 1.1algebra∎
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Continuous mixed partials of order k are invariant under permutations

Statement

Let k≥2. If f∈Ck(U) for an open U⊆Rm, then every iterated derivative of f of order k is unchanged by any permutation of its coordinate differentiations.

Facts & Assumptions

Given: A Ck scalar field on U and a word of k coordinate indices.

[L1]

Adjacent second coordinate derivatives commute under the C2 hypotheses (Clairaut--Schwarz theorem for continuous second partial derivatives).

[L2]

A Ck field has every ordered iterated partial derivative through length k, continuously on U (Ck maps and multi-index derivative notation in Euclidean space).

Proof

technique · induction
1.1

Label the k differentiation positions and count inversions of a permutation of these labels. A permutation with zero inversions is the identity, so it leaves the derivative unchanged.

basealgebra
1.2

Assume every reordering with at most n inversions leaves the derivative unchanged.

ih
2.1

A reordering with n+1 inversions has an adjacent inverted pair; exchanging that pair reduces its inversion count by one. If that pair occupies positions r,r+1 in the sequence of differentiation operations, first apply only the operations in positions 1,…,r−1 and call the resulting field g. Every ordered partial of g through order two is an ordered partial of f of length at most k, hence is continuous by [L2]; thus g∈C2(U) and [L1] swaps precisely the operations in positions r,r+1. Apply the remaining outer operations in positions r+2,…,k to this equality; their existence is again supplied by [L2].

step 1.2L1L2algebra
3.1

The induction hypothesis applies after the swap in step 2.1, so the original reordering leaves the derivative unchanged. Induction on inversion number proves the claim for every finite permutation.

step 1.1step 1.2step 2.1discharge-induction∎
LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Repeated derivatives along a line expand by the multinomial formula

Statement

Let k∈N, let U⊆Rm be open, f∈Ck(U), and let I⊆R be an open interval such that a+th∈U for every t∈I. Write ι:N→R for the canonical-natural map of The canonical natural ι(n)=n⋅1F of a field. For g(t)=f(a+th) and every 0≤r≤k,

g(r)(t)=∑∣α∣=rι(r!)ι(α!)Dαf(a+th)hα(t∈I).

Facts & Assumptions

Given: The stated open-domain, open-interval, Ck, and direction hypotheses.

[L1]

A function with continuous first partial derivatives near a point is totally differentiable there, and the total chain rule then applies to the affine line map t↦a+th (If all partial derivatives exist on a neighbourhood and are continuous at a point, then the map is totally differentiable there with Jacobian derivative, The chain rule for total derivatives: D(g∘f)(a)=Dg(f(a))∘Df(a)).

[L2]

Ordered mixed derivatives through order k commute under permutation (Continuous mixed partials of order k are invariant under permutations).

[L3]

The multi-index conventions ∣α∣, α!, hα, and the canonical derivative Dαf are those of Ck maps and multi-index derivative notation in Euclidean space.

[L4]

The canonical-natural map carries finite natural sums and products to the corresponding real sums and products (The canonical natural ι(n)=n⋅1F of a field, Laws of finite sums and products in N, and ι(∑k<nak)=∑k<nι(ak)).

Proof

technique · induction
1.1

For r=0 the displayed sum consists of the zero multi-index and equals f(a+th)=g(t).

baseL3
1.2

Fix r<k and assume the formula at order r.

ih
1.3

Each Dαf with ∣α∣=r has continuous first partials, so [L1] differentiates its composition with the affine line. By [L3], we use the canonical multi-index notation for the resulting derivatives. When r=0 the resulting first derivatives are already canonical; when r≥1, [L2] permits the resulting derivatives to be written as Dα+eif. By [L4], collecting the coefficient of a fixed β with ∣β∣=r+1 gives

∑i: βi>0ι(r!)ι((β−ei)!)=ι(r!)ι(β!)∑i<mι(βi)=ι((r+1)!)ι(β!).

Thus the formula at order r+1 follows. [step 1.2, L1, L2, L3, L4, algebra]

2.1

Steps 1.1--2.1 prove the formula successively for every r≤k.

step 1.1step 1.2step 1.3discharge-induction∎
DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-02Open item page →

The multivariable Taylor polynomial in multi-index notation

Definition

For a natural k, a map f:U⊆Rm→R with the derivatives Dαf(a) for ∣α∣≤k, and with ι:N→R the canonical embedding of The canonical natural ι(n)=n⋅1F of a field, the Taylor polynomial of degree at most k at a is

Tkf(a;h):=∑∣α∣≤kDαf(a)ι(α!)hα.

The multi-index conventions are those of Ck maps and multi-index derivative notation in Euclidean space, and the displayed sum is the real finite sum of Finite sums and finite products, by recursion. When m=1, this agrees with the polynomial of Taylor polynomials and their remainders.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Multivariable Taylor formula with a Lagrange remainder along a line segment

Statement

Let k∈N, let U⊆Rm be open and convex, a,a+h∈U, and f∈Ck+1(U). Write ι:N→R for the canonical-natural map of The multivariable Taylor polynomial in multi-index notation. Then some θ∈(0,1) satisfies

f(a+h)=Tkf(a;h)+∑∣α∣=k+1Dαf(a+θh)ι(α!)hα.

Facts & Assumptions

Given: The hypotheses of the statement.

[L1]

Convexity keeps the segment a+th in U for 0≤t≤1 (A convex subset of Rm contains every line segment between two of its points).

[L2]

On an open interval containing [0,1], the derivatives of t↦f(a+th) have the multi-index expansion through order k+1 (Repeated derivatives along a line expand by the multinomial formula).

[L3]

By The Lagrange and Cauchy forms of Taylor's remainder, if a one-variable function has derivatives through order k+1 on [0,1] with the required endpoint continuity, then some θ∈(0,1) satisfies

g(1)=∑j=0kg(j)(0)ι(j!)+g(k+1)(θ)ι((k+1)!)

by the Lagrange remainder formula.

Proof

technique · direct
1.1

Put I:={t∈R:a+th∈U} and g(t):=f(a+th). The set I is open, contains [0,1] by [L1], and is an interval because U is convex. Hence [L2] shows that g has the derivatives through order k+1 required by [L3].

L1L2
2.1

Apply [L3] to g between 0 and 1.

step 1.1L3choose
3.1

Substitute the formula of [L2] for g(j)(0) and g(k+1)(θ); the degree-k part is the definition of Tkf(a;h).

step 2.1L2algebra∎
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Multivariable Taylor formula with o(∥h∥k) remainder

Statement

Let k∈N with k≥1, let V⊆Rm be open and convex, let a∈V, and let f∈Ck(V). Then, as h→0 with a+h∈V,

f(a+h)=Tkf(a;h)+o(∥h∥k).

Facts & Assumptions

Given: The hypotheses of the statement and small h with a+h∈V.

[L1]

By Multivariable Taylor formula with a Lagrange remainder along a line segment, applying the multivariable Lagrange formula with degree k−1 gives some θh∈(0,1) such that

f(a+h)=Tk−1f(a;h)+∑∣α∣=kDαf(a+θhh)ι(α!)hα

[L2]

For every ∣α∣=k, Dαf is continuous at a (Ck maps and multi-index derivative notation in Euclidean space).

Proof

technique · direct
1.1

Subtract the degree-k Taylor polynomial from the equality of [L1]. The remainder is the following.

L1algebra

∑∣α∣=kDαf(a+θhh)−Dαf(a)ι(α!)hα.

2.1

For h≠0, divide the absolute value in step 1.1 by ∥h∥k. Since ∣hα∣≤∥h∥k, it is bounded by the finite sum of the coefficient differences divided by ι(α!). As h→0, also a+θhh→a, so every term tends to zero by [L2].

step 1.1L2algebra
3.1

This proves that the remainder in step 1.1 is o(∥h∥k), and the subtracted polynomial is Tkf(a;h) by The multivariable Taylor polynomial in multi-index notation.

step 2.1∎
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Second-order Taylor expansion f(a+h)=f(a)+∇f(a)⋅h+12hTHf(a)h+o(∥h∥2)

Statement

For a C2 scalar field near a,

f(a+h)=f(a)+∇f(a)⋅h+12⟨Hf(a)h,h⟩+o(∥h∥2).

Facts & Assumptions

Given: A C2 scalar field near a.

[L1]

The degree-two multi-index Taylor formula has a Peano remainder (Multivariable Taylor formula with o(∥h∥k) remainder).

Proof

technique · direct
1.1

Expand the degree-one and degree-two multi-index sums in [L1].

L1algebra
2.1

The degree-one sum is ∇f(a)⋅h, while symmetry of the repeated second derivatives identifies the degree-two sum with 12⟨Hf(a)h,h⟩.

step 1.1L2algebra∎
DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-02Open item page →

Local and strict local extrema for scalar fields on Euclidean open sets

Definition

Let U⊆Rm be open, a∈U, and f:U→R. The point a is a local minimum when some Euclidean neighbourhood V of a satisfies f(a)≤f(x) for every x∈U∩V; it is a strict local minimum when the inequality is strict for x≠a. Local and strict local maxima reverse these inequalities. Euclidean neighbourhoods use 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. A critical point is as in The Hessian matrix and critical points of a scalar field.

TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Fermat's theorem: an interior differentiable local extremum has zero gradient

Statement

If f:U⊆Rm→R is differentiable at an interior local maximum or minimum a, then ∇f(a)=0.

Facts & Assumptions

Given: A differentiable scalar field with a local extremum at a.

[L1]

The one-variable Fermat theorem gives derivative zero at an interior differentiable local extremum (Fermat's interior extremum theorem: if f has a local extremum at a point c interior to its domain and is differentiable at c, then f′(c)=0).

[L2]

The gradient consists of the coordinate partial derivatives (The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case).

Proof

technique · direct
1.1

Restrict f to each coordinate line through a. The restriction has a local extremum at 0, so [L1] makes its derivative zero.

L1given
2.1

These derivatives are the entries of ∇f(a) by [L2], so every entry vanishes.

step 1.1L2∎
DefinitionDefinition: Literature-sourcedProof: Not applicableaudited 2026-08-02Open item page →

Positive definite, negative definite, semidefinite, and indefinite quadratic forms

Definition

For a real m×m matrix H, write qH(h):=⟨Hh,h⟩ using The Euclidean inner product ⟨x,y⟩=∑k<nxkyk on Rn. It is positive definite when qH(h)>0 for every h≠0, negative definite when qH(h)<0 for every h≠0, positive semidefinite when qH(h)≥0 for every h, negative semidefinite when qH(h)≤0 for every h, and indefinite when it takes both positive and negative values. For a twice differentiable scalar field, its Hessian matrix is the matrix of The Hessian matrix and critical points of a scalar field.

LemmaStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

A definite quadratic form has a uniform signed bound on the Euclidean unit sphere

Statement

Let n≥1 and let q be a positive definite quadratic form on Rn. Then some c>0 satisfies q(u)≥c whenever ∥u∥2=1. For a negative definite q, some c>0 satisfies q(u)≤−c on the same sphere.

Facts & Assumptions

Proof

technique · direct
1.1

The unit sphere is nonempty because it contains e0, closed by [L1], and bounded since it lies in the radius-two ball about zero.

L1givenalgebra
2.1

It is compact by [L2].

step 1.1L2
3.1

The finite coordinate formula for q makes it continuous; [L3] therefore gives a point where q attains its minimum and maximum on the sphere.

step 2.1L3algebra
4.1

In the positive definite case the attained minimum is positive, and in the negative definite case the attained maximum is negative, by the definition of definiteness.

step 3.1given
5.1

Taking c to be the positive minimum or the negative maximum gives the asserted uniform signed bounds.

step 4.1algebra∎
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

The multivariable second-derivative test by definiteness of the Hessian

Statement

Let a be a critical point of a C2 scalar field. A positive definite Hessian gives a strict local minimum, a negative definite Hessian gives a strict local maximum, and an indefinite Hessian gives neither. If the Hessian is semidefinite but not definite, the Hessian test gives no conclusion in general.

Facts & Assumptions

Given: A C2 scalar field and a critical point a.

[L1]

The second-order Taylor expansion has quadratic term 12⟨Hf(a)h,h⟩ and remainder o(∥h∥2) (Second-order Taylor expansion f(a+h)=f(a)+∇f(a)⋅h+12hTHf(a)h+o(∥h∥2)).

[L2]

A definite quadratic form has a uniform signed bound on the unit sphere (A definite quadratic form has a uniform signed bound on the Euclidean unit sphere).

Proof

technique · direct
1.1

At a critical point the linear term in [L1] vanishes.

L1given
2.1

Write h=ru with r=∥h∥2 and ∥u∥2=1 when h≠0. The sign bound in [L2] dominates the o(r2) remainder for sufficiently small r.

step 1.1L2algebra
3.1

This gives the strict minimum and maximum conclusions in the definite cases; two unit directions of opposite quadratic sign give neither extremum in the indefinite case.

step 2.1algebra
4.1

For a semidefinite Hessian which is not definite, its quadratic form has a nonzero null direction, so step 2.1 supplies no signed quadratic bound. No universal conclusion is possible: at 0 the one-variable functions x4, −x4, and x3 all have zero Hessian, but respectively have a strict local minimum, a strict local maximum, and neither.

step 2.1algebra∎
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

The two-variable Hessian determinant test

Statement

Let a be a critical point of a C2 function of two variables, and put A=fxx(a), B=fxy(a), C=fyy(a) and Δ=AC−B2. If Δ>0, then A>0 gives a strict local minimum and A<0 a strict local maximum. If Δ<0, there is neither. If Δ=0, this test gives no conclusion.

Facts & Assumptions

Given: a is a critical point of a C2 scalar field f on an open subset of R2.

[L1]
[L2]

The second-derivative test classifies a critical point from definiteness or indefiniteness of its Hessian (The multivariable second-derivative test by definiteness of the Hessian).

Proof

technique · calculation
1.1

By [L1], the Hessian quadratic form is Q(s,t)=As2+2Bst+Ct2. If A≠0, completing the square gives Q=A(s+(B/A)t)2+(Δ/A)t2.

L1algebra
2.1

If Δ>0, the two coefficients in step 1.1 have the sign of A, so Q is positive definite for A>0 and negative definite for A<0.

step 1.1algebra
2.2

If Δ<0 and A≠0, then Q(1,0)=A while Q(−B/A,1)=Δ/A, which have opposite signs; hence Q is indefinite. If A=0, then −B2=Δ<0, so B≠0, and Q(1,t)=2Bt+Ct2 has both signs for sufficiently small positive and negative t.

step 1.1algebra
3.1

Apply [L2] to steps 2.1 and 2.2. When Δ=0 and A≠0, step 1.1 makes Q=A(s+(B/A)t)2, so it is semidefinite but not definite; when A=0, then B=0 and Q=Ct2, with the same conclusion (including Q=0). Thus this is the inconclusive case of [L2].

L2step 1.1step 2.1step 2.2algebra∎
TheoremStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

A constrained local extremum annihilates every velocity of a differentiable parametrization

Statement

Let f:U→R be differentiable at a∈U⊆RN, and let γ:(−η,η)→U be differentiable at 0 with γ(0)=a. If f∘γ has a local maximum or minimum at 0, then Df(a)γ′(0)=0.

Facts & Assumptions

Given: The hypotheses of the statement.

[L1]

The total-derivative chain rule is D(f∘γ)(0)=Df(γ(0))Dγ(0) (The chain rule for total derivatives: D(g∘f)(a)=Dg(f(a))∘Df(a)).

Proof

technique · direct
1.1

The composite g=f∘γ is differentiable at 0 by [L1], and 0 is an interior local extremum of g by the hypothesis.

givenL1algebra
2.1

Fermat's theorem gives g′(0)=0.

step 1.1L2
3.1

The chain-rule identity in [L1] and γ(0)=a give g′(0)=Df(a)γ′(0). Combining with step 2.1 proves the conclusion.

L1step 2.1algebra∎
CorollaryStatement: Literature-sourcedProof: AI-adaptedprecheck passaudited 2026-08-02Open item page →

Lagrange multipliers for a regular graph constraint y=ψ(x)

Statement

Let V⊆Rm and W⊆Rm+n be open, let x0∈V, let ψ:V→Rn be differentiable at x0, put a=(x0,ψ(x0))∈W, and let f:W→R be differentiable at a. If f∣W∩graph⁡(ψ) has a local extremum at a, then for G:V×Rn→Rn given by G(x,y)=y−ψ(x) there is λ∈Rn such that ∇f(a)=DG(a)Tλ.

Facts & Assumptions

Given: The hypotheses of the statement.

[L1]

A constrained local extremum annihilates every tangent velocity of a differentiable parametrization (A constrained local extremum annihilates every velocity of a differentiable parametrization).

Proof

technique · direct
1.1

Parametrize the graph by Γ(x)=(x,ψ(x)). Since ψ is differentiable at x0, Γ is continuous there; because V and W are open, for every v∈Rm the curve t↦Γ(x0+tv) is defined and lies in W for sufficiently small t. Apply [L1] to get Df(a)(v,Dψ(x0)v)=0.

L1givenalgebra
2.1

In block gradient coordinates, step 1.1 says ∇xf(a)+Dψ(x0)T∇yf(a)=0.

step 1.1L2algebra
3.1

Set λ=∇yf(a). Since DG(a)=(−Dψ(x0),In), step 2.1 yields DG(a)Tλ=(∇xf(a),∇yf(a))=∇f(a).

step 2.1L2algebra∎

5 · Examples, counterexamples and false statements

None yet.

Sources