On jet-convex functions and their tensor products
Vladimir Shikhman and Oliver Stein
Abstract. In this paper we introduce necessary and sufficient conditions for the tensor product of two convex  functions 
to be convex. For our analysis we introduce the notions of true convexity, jet-convexity, true  jet-convexity 
as well as true log-convexity. The links between jet-convex and log-convex functions are elaborated. 
As an algebraic tool we introduce the jet product of two symmetric matrices and study some of its  properties. 
We illustrate our results by an application from global optimization, where a convex underestimator  for the 
tensor product of two functions is constructed as the tensor product of convex underestimators of  the single 
functions.
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