For a proper lower-semicontinuous convex function , its proximal operator is
The squared norm is strongly convex, so the minimizer is unique. The subdifferential sum rule gives the necessary and sufficient condition
More generally,
The subgradient inversion rule for the convex conjugate says exactly when . Hence
which is precisely the proximal optimality condition
Since , this proves the generalized Moreau decomposition

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