On the spectrum of the hierarchical Schr\"{o}dinger type operators
Alexander Bendikov, Alexander Grigor'yan, Stanislav Molchanov

TL;DR
This paper conducts a spectral analysis of a Schr"{o}dinger type operator on the Dyson hierarchical lattice, revealing the structure of its spectrum, effects of sparse and random potentials, and providing asymptotic and localization results.
Contribution
It introduces a detailed spectral analysis of Schr"{o}dinger operators with hierarchical structure, including sparse and random potentials, and derives new asymptotic and localization results.
Findings
Discrete spectrum can contain negative energies.
Spectral gaps of the base operator can host eigenvalues.
Precise asymptotics for sparse potentials with rapidly increasing distances.
Abstract
The goal of this paper is the spectral analysis of the Schr\"{o}dinger type operator , the perturbation of the Taibleson-Vladimirov multiplier by a potential . Assuming that belongs to a certain class of potentials we show that the discrete part of the spectrum of may contain negative energies, it also appears in the spectral gaps of . We will split the spectrum of in two parts: high energy part containing eigenvalues which correspond to the eigenfunctions located on the support of the potential and low energy part which lies in the spectrum of certain bounded Schr\"{o}dinger-type operator acting on the Dyson hierarchical lattice. We pay special attention to the class of sparse potentials. In this case we obtain precise spectral asymptotics for provided the sequence of distances between locations tends to infinity fast enough.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSpectral Theory in Mathematical Physics · Differential Equations and Boundary Problems · Numerical methods in inverse problems
