
Let \(K\) be a Chebyshev subset of a smooth Banach space \(B\). An old open question in Banach space geometry asks if \(K\) must be convex. The answer is not known even if \(B\) is a Hilbert space. There are many beautiful partial results. For example, compact Chebyshev subsets of a smooth Banach space are convex. Other partial results involve conditions on \(B\), and its dual space, \(B^*\), or geometric or topological properties of \(K\). This paper shows that \(K\) is convex if the distance function, \(d(x)=\min\{\|x-k\|: k \in K\}\), satisfies smoothness conditions such as Gâteaux differentiability or continuity. When stricter smoothness conditions are assumed for \(B\) or \(B^*\), less restrictive conditions are required for \(d\). The paper contains, for example, the following nice statement: Theorem. If the norms on \(B\) and \(B^*\) are Fréchet differentiable, then \(K\) is convex if and only if \(d\) is Fréchet differentiable.
Best approximation, Chebyshev systems, Mathematics(all), Numerical Analysis, Geometry and structure of normed linear spaces, Abstract approximation theory (approximation in normed linear spaces and other abstract spaces), Fréchet derivatives, convex sets, Applied Mathematics, Chebyshev subset, uniformly smooth spaces, Analysis
Best approximation, Chebyshev systems, Mathematics(all), Numerical Analysis, Geometry and structure of normed linear spaces, Abstract approximation theory (approximation in normed linear spaces and other abstract spaces), Fréchet derivatives, convex sets, Applied Mathematics, Chebyshev subset, uniformly smooth spaces, Analysis
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