Nonlinear Maccone-Pati Uncertainty Principle
Functional Analysis
2024-02-14 v1 Information Theory
Mathematical Physics
math.IT
math.MP
Abstract
We show that one of the two important uncertainty principles derived by Maccone and Pati \textit{[Phys. Rev. Lett., 2014]} can be derived for arbitrary maps defined on subsets of spaces for . Our main tool is the Clarkson inequalities. We also derive a nonlinear uncertainty principle for weak parallelogram spaces and Type-p Banach spaces.
Cite
@article{arxiv.2402.08591,
title = {Nonlinear Maccone-Pati Uncertainty Principle},
author = {K. Mahesh Krishna},
journal= {arXiv preprint arXiv:2402.08591},
year = {2024}
}
Comments
6 pages, 0 figures