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TheoremStatement: Literature-sourcedProof: AI-adaptedSession-authored (Fable 5 assisted)precheck passaudited 2026-08-24
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Lagrange multipliers for a regular vector-valued level-set constraint

Statement

Let URm be open, let f:UR and G:URq be C1, and suppose a is a local maximum or minimum of f subject to G(x)=c. If DG(a) is surjective, then there is a unique λRq such that Df(a)v=λ,DG(a)v(vRm), or equivalently f(a)=DG(a)Tλ. This is a necessary condition, not a sufficient condition for a constrained extremum.

Facts & Assumptions

Given: The maps f,G, the regular constrained point a, and c=G(a).

[L1]

If c is a regular value of a C1 map on an open set, then at every point a of its fibre a vector lies in the tangent space exactly when it is the velocity at zero of a C1 curve through a inside that fibre (Tangent vectors to a regular level set are exactly its curve velocities).

[L4]

For a C1 map the locus where the derivative has rank at least r 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).

[L2]

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).

Proof

technique · direct
1.1

By [L4] the set W of points of U at which DG is surjective is open, and aW; on W every point of every fibre is a submersion point, so c is a regular value of GW and a is a local extremum of f subject to GW=c. Fix vkerDG(a). By [L1] applied to GW, choose a level-set curve γ with γ(0)=a and γ(0)=v inside GW1(c)G1(c). The constrained local extremum condition in [L2] makes fγ locally extremal at 0.

givenL1L2L4choose
2.1

By [L2], Df(a)v=0. Since v was arbitrary, the functional Df(a) vanishes on kerDG(a).

step 1.1L2
3.1

Apply [L3] to the surjection DG(a). It gives a unique λ with Df(a)v=λ,DG(a)v for all v, and the gradient representation turns this equality of functionals into f(a)=DG(a)Tλ.

step 2.1L3
4.1

The argument derives the multiplier equation from a constrained extremum and makes no converse assertion, as claimed.

step 3.1

Depends on

Used by

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Sources