Graduate What are the equality conditions for proving strict convexity?

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SUMMARY

This discussion focuses on the equality conditions necessary to prove the strict convexity of functions, particularly in the context of Lp norms. It establishes that L1 and L∞ norms are not strictly convex, while L2 is strictly convex. The conversation highlights three essential properties of Lp norms: symmetry, homogeneity with respect to positive scaling, and the triangle inequality. The discussion suggests using counterexamples for L1 and L∞ norms and re-evaluating the equality conditions of the Cauchy-Schwarz inequality as a method to demonstrate strict convexity.

PREREQUISITES
  • Understanding of Lp norms, specifically L1, L2, and L∞ norms
  • Familiarity with the concepts of symmetry and homogeneity in mathematical functions
  • Knowledge of the triangle inequality and its implications for convexity
  • Basic understanding of the Cauchy-Schwarz inequality and its applications
NEXT STEPS
  • Research the properties of Lp norms in-depth, focusing on their geometric interpretations
  • Study the proof of the Cauchy-Schwarz inequality and its relevance to convexity
  • Explore counterexamples that illustrate the lack of strict convexity in L1 and L∞ norms
  • Learn about alternative proofs for strict convexity beyond Hölder's inequality
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Mathematicians, students studying functional analysis, and anyone interested in the properties of convex functions and norms.

member 428835
Hi PF!

Do you know what a strictly convex function is? I understand this notion in the concept of norms, where in the plane I've sketched the ##L_1,L_2,L_\infty## norms, where clearly ##L_1,L_\infty## are not strictly convex and ##L_2## is. Intuitively it would make sense that any ##L_1,L_\infty## function is not strictly convex (similar to it's norm) and ##L_2## functions are, but how would you even show this?
 
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Lp norms have 3 things
(1.) symmetry
(2.) homogeneity with respect to scaling by positive numbers -- consider in particular ## p \in (0,1)##
(3.) triangle inequality (or sub additivity)

if you carefully apply (2.) and (3.) you recover a definition of convexity. As far as strictness of the convexity, what do you know about the proof behind (3.), and in particular the equality conditions underlying it? The typical way is via Hoelder, but there are clever other ways. A more pedestrian approach for this particular problem is to come up with counterexamples on strictness for ##L_1## and ##L_\infty## and re-examine the equality conditions of Cauchy-Schwarz.
 
As shown by this animation, the fibers of the Hopf fibration of the 3-sphere are circles (click on a point on the sphere to visualize the associated fiber). As far as I understand, they never intersect and their union is the 3-sphere itself. I'd be sure whether the circles in the animation are given by stereographic projection of the 3-sphere from a point, say the "equivalent" of the ##S^2## north-pole. Assuming the viewpoint of 3-sphere defined by its embedding in ##\mathbb C^2## as...

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