Convolution Inequality: Conditions for Equality

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    Convolution Inequality
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SUMMARY

The discussion centers on the Convolution Inequality for functions f and g in L^1(R), specifically the condition for equality in the inequality ||f * g||_1 ≤ ||f||_1 ||g||_1. It is established that equality holds if there exists a real function φ(x) such that e^{i φ(x+y)} f(x) g(y) ≥ 0 almost everywhere. Additionally, when f is real and g is non-negative, equality is achieved if the supports of f^+ * g and f^- * g do not intersect. The discussion highlights the challenge of translating these conditions into more general cases, particularly when f and g are not both almost everywhere non-zero.

PREREQUISITES
  • Understanding of L^1 spaces and properties of integrable functions.
  • Familiarity with convolution operations and their properties.
  • Knowledge of support of functions and measures in real analysis.
  • Basic concepts of phase functions and their implications in inequalities.
NEXT STEPS
  • Research the properties of L^1 convolution and its implications on function spaces.
  • Study the conditions for equality in the Minkowski inequality.
  • Explore the role of phase functions in harmonic analysis.
  • Investigate the implications of support intersections in the context of convolutions.
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Mathematicians, analysts, and students studying functional analysis, particularly those focusing on convolution inequalities and their applications in real analysis.

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Given f,g in L^1(R), I'm given the inequality:

[tex]||f * g||_1 \leq ||f||_1 ||g||_1[/tex]

And now I'm supposed to derive the conditions for equality to hold. I keep going around in circles. So far, I can show equality holds iff there is some real function [itex]\phi(x)[/itex] such that [itex]e^{i \phi(x+y)} f(x) g(y) \geq 0[/itex] holds almost everywhere, but I can't easily translate this into conditions on f and g. If f and g were both almost everywhere non-zero, this would just say they need to have linear phases with the same slope, but this doesn't help when they are zero on sets of positive measure.

For the case when f is real and g is non-negative, equality holds iff the support of [itex]f^+*g[/itex] and [itex]f^-*g[/itex] don't intersect, where [itex]f^\pm[/itex] are the positive and negative parts of f (I use the fact that convolutions of L^1 functions are continuous). The best I can do with this is say it is equivalent to there being some x such that the support of g(y) intersects both the support of [itex]f^+(x-y)[/itex] and that of [itex]f^-(x-y)[/itex] in sets of positive measure. Is this the best I can do? And how would I extend it to the general case? Like I said, I'm not getting anywhere.
 
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I'm doing other problems now and I keep coming back to this same related question: when does |f*g(x)|=|f|*|g|(x) hold almost everywhere. This is all I need to know, but I can't figure it out. It seems like I'm overlooking something really simple. Can anyone help me out?
 
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