Let
The proximal operator optimality condition says
By subgradient inversion under convex conjugacy, which uses Fenchel–Young inequality and from the Fenchel-Moreau theorem,
Consequently , meaning . Uniqueness of the backward subgradient step identifies the result:
This is the scaled Moreau decomposition. It requires one backward step on , with reciprocal parameter and scaled input , followed by a scalar multiplication and subtraction. No separate proximal computation of the convex conjugate is needed.

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