Alphabeta Math
LemmaStatement: AI-adaptedProof: AI-adaptedSession-authored (Fable 5 assisted)precheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-26
How statement and proof provenance work

The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.

  • Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
  • AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
  • AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.

These labels describe origin, not correctness: citations and verification chips remain separate evidence.

Each coordinate of the oriented area vector is the Jacobian determinant of the matching cyclic projection

Statement

Let OR2 be open and let φ=(φx,φy,φz):OR3 be C1, with parameters named u,v and φu:=uφ, φv:=vφ. Then at every point of O,

(φu×φv)k=detD(πkφ)

for each of the three coordinate directions k{x,y,z}, where πk is the cyclic coordinate projection of Simple solid regions in a coordinate direction and their cyclic coordinate projection.

Facts & Assumptions

Given: The open set OR2 and the C1 map φ:OR3 of the Statement.

[F1]

For u=(ux,uy,uz) and v=(vx,vy,vz) in R3, u×v=(uyvzuzvy,uzvxuxvz,uxvyuyvx) (The cross product in R3).

[F2]

For a C1 map g of an open subset of Rn into Rn, its Jacobian determinant is detDg(x), the determinant of its Jacobian matrix (The Jacobian determinant of a square-dimensional C1 map is the determinant of its Jacobian matrix).

[F3]

If every partial derivative jfi(a) of f exists, the Jacobian matrix is Jf(a)=(jfi(a))i<n,j<m (The Jacobian matrix of partial derivatives and the gradient in the scalar-valued case).

[F4]

For a commutative ring R, n1 and A=(aij)Mn(R), det(A)=σSnsgn(σ)i<naσ(i),i, with columns indexed by i<n and rows by σ(i) (For n1, the determinant over a commutative ring by the Leibniz formula, and detA for a real matrix).

[F5]

An inversion of σSn is a pair (i,j) with i<j<n and σ(i)>σ(j), and sgn(σ)=(1)inv(σ) (Inversions, inversion number, the sign sgn(σ)=(1)inv(σ), and even and odd permutations).

[F6]

The cyclic coordinate projections are πx(p)=(py,pz), πy(p)=(pz,px) and πz(p)=(px,py) (Simple solid regions in a coordinate direction and their cyclic coordinate projection).

[F7]

A map f:URq is of class Ck when each component is of class Ck (Ck Euclidean maps and diffeomorphisms).

Proof

technique · direct
1.1

Each πkφ is a map of the two parameters into R2 whose two components are components of φ, hence C1 by [F7], so by [F2] and [F3] it has a Jacobian matrix (a00a01a10a11) with ai0=u and ai1=v of its ith component. There are exactly two elements of S2: the identity, with no inversion and sign +1, contributing a00a11, and the transposition sending 0 to 1 and 1 to 0, with the single inversion (0,1) and sign 1, contributing a10a01. So [F4] and [F5] give detD(πkφ)=a00a11a10a01.

givenF2F3F4F5F7
1.2

By [F1] with u=φu and v=φv, whose coordinates are the partial derivatives named in [F3], the oriented area vector has coordinates (φu×φv)x=uφyvφzuφzvφy, (φu×φv)y=uφzvφxuφxvφz, (φu×φv)z=uφxvφyuφyvφx.

givenF1F3
2.1

By [F6] the projection πx retains the coordinates y then z, so πxφ=(φy,φz) and step 1.1 gives detD(πxφ)=uφyvφzuφzvφy, which is the first coordinate computed in step 1.2.

step 1.1step 1.2F6
2.2

By [F6] the projection πy retains the coordinates z then x, in that cyclic order, so πyφ=(φz,φx) and step 1.1 gives detD(πyφ)=uφzvφxuφxvφz, the second coordinate computed in step 1.2. Retaining x then z in increasing order instead would exchange the two rows and give the opposite sign, which is why the cyclic order is part of the projection.

step 1.1step 1.2F6
2.3

By [F6] the projection πz retains the coordinates x then y, so πzφ=(φx,φy) and step 1.1 gives detD(πzφ)=uφxvφyuφyvφx, the third coordinate computed in step 1.2.

step 1.1step 1.2F6
3.1

Steps 2.1, 2.2 and 2.3 are the three asserted identities, valid at every point of O; in particular all three determinants vanish exactly where the oriented area vector does.

step 2.1step 2.2step 2.3

Remarks

  • The identity holds where the patch is not regular. Nothing above uses φu×φv0. That matters because the lateral faces of a boundary presentation are exactly the patches whose kth projected Jacobian determinant vanishes, and the identity is what turns that analytic condition into a geometric one.

Depends on

Used by

Dependency tree · two levels

33 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.

Sources