One-dimensional Sobolev embedding gives a continuous representative for each , with zero endpoint values, so the pointwise obstacle condition is meaningful. The positive part is Lipschitz and vanishes near both endpoints because . It therefore belongs to and satisfies , proving that is nonempty.
If and , then , so is a convex set. If in , the estimate gives uniform convergence. Passing to the limit in shows . Thus the admissible set is nonempty, closed and convex.
For any , the segment stays in for . Since is a minimizer, the right derivative of its energy at is nonnegative. The first variation therefore gives the variational inequalityThe factor two comes from the quadratic gradient term. Only a one-sided inequality follows because a variation pointing below the obstacle need not be admissible.
The noncontact set is open. For , the positive gap above the obstacle has a positive minimum on the support of . Thus both and are admissible for sufficiently small . Applying the variational inequality to both signs yieldsHence the Euler-Lagrange equation on the noncontact set isIt holds classically under the assumed smoothness. On the contact set the obstacle prevents the negative variations used to obtain this equality, so a variational inequality remains the appropriate global description.
Let both solve the variational inequality. Test the inequality for with and the one for with , then add. Writing givessince cosine is Lipschitz with constant one. Since , the fundamental theorem of calculus and Cauchy-Schwarz inequality give ; integrating gives . ThereforeFor , the coefficient is positive, so and the zero boundary value gives . This proves uniqueness with an explicit sufficient smallness condition. More generally any Poincaré inequality constant gives the condition ; optimizing that constant is unnecessary for the requested conclusion. The underlying principle is uniqueness for a strongly monotone variational inequality.
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