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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 Lp\mathcal{L}^p spaces for 1<p<1< p<\infty. Our main tool is the Clarkson inequalities. We also derive a nonlinear uncertainty principle for weak parallelogram spaces and Type-p Banach spaces.

Keywords

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

R2 v1 2026-06-28T14:47:32.164Z