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The location of the mobility edge is a long standing problem in Anderson localization. In this paper, we show that the effective confining potential introduced in the localization landscape (LL) theory predicts the onset of delocalization…

Disordered Systems and Neural Networks · Physics 2024-05-24 Marcel Filoche , Pierre Pelletier , Dominique Delande , Svitlana Mayboroda

We consider the Hamiltonian $H$ of a particle in one dimension with a position dependent mass for which we apply the recent strategy of the so-called {\em abstract ladder operators}, in the attempt to find its eigenvalues and eigenvectors.…

Mathematical Physics · Physics 2026-05-05 Fabio Bagarello , Emanuele Balistreri , Antonino Faddetta

We study Anderson localisation on high-dimensional graphs with spatial structure induced by long-ranged but distance-dependent hopping. To this end, we introduce a class of models that interpolate between the short-range Anderson model on a…

Disordered Systems and Neural Networks · Physics 2026-04-22 Bibek Saha , Sthitadhi Roy

We study Anderson localization of ultracold atoms in weak, one-dimensional speckle potentials, using perturbation theory beyond Born approximation. We show the existence of a series of sharp crossovers (effective mobility edges) between…

Electrons at the Fermi energy may lose their ability to propagate to long distances in certain random media. We use Green functions and solve parquet equations for the non-local electron-hole vertex in high spatial dimensions to describe…

Disordered Systems and Neural Networks · Physics 2025-05-12 Václav Janiš

Anderson localization is related to exponential localization of a particle in the configuration space in the presence of a disorder potential. Anderson localization can be also observed in the momentum space and corresponds to quantum…

Atomic Physics · Physics 2017-06-07 Krzysztof Giergiel , Krzysztof Sacha

We consider two bidimensional random models characterised by the following features: a) their Hamiltonians are separable in polar coordinates and b) the random part of the potential depends either on the angular coordinate or on the radial…

Disordered Systems and Neural Networks · Physics 2023-02-14 Gabino Corona-Patricio , Ulrich Kuhl , Fabrice Mortessagne , Patrizia Vignolo , Luca Tessieri

We consider the parabolic Anderson problem $\partial_tu=\Delta u+\xi(x)u$ on $\mathbb{R}_+\times\mathbb{Z}^d$ with localized initial condition $u(0,x)=\delta_0(x)$ and random i.i.d. potential $\xi$. Under the assumption that the…

Probability · Mathematics 2009-09-29 Jürgen Gärtner , Wolfgang König , Stanislav Molchanov

Motivated by applications of the discrete random Schr\"odinger operator, mathematical physicists and analysts, began studying more general Anderson-type Hamiltonians; that is, the family of self-adjoint operators $$H_\omega = H + V_\omega$$…

Functional Analysis · Mathematics 2019-09-19 Constanze Liaw

We consider the Anderson model at large disorder on $\mathbb{Z}^2$ where the potential has a symmetric Bernoulli distribution. We prove that Anderson localization happens outside a small neighborhood of finitely many energies. These…

Analysis of PDEs · Mathematics 2022-03-18 Linjun Li

Nonunitary versions of Newtonian gravity leading to wavefunction localization admit natural special-relativistic generalizations. They include the first consistent relativistic localization models. At variance with the unified model of…

High Energy Physics - Theory · Physics 2009-11-10 Sergio De Filippo , Filippo Maimone

The $L^2$ localisation landscape of L. Herviou and J. H. Bardarson is a generalisation of the localisation landscape of M. Filoche and S. Mayboroda. We propose a stochastic method to compute the $L^2$ localisation landscape that enables the…

Disordered Systems and Neural Networks · Physics 2024-04-05 Masataka Kakoi , Keith Slevin

We investigate the top of the spectrum of discrete Anderson Hamiltonians with correlated Gaussian noise in the large volume limit. The class of Gaussian noises under consideration allows for long-range correlations. We show that the largest…

Probability · Mathematics 2025-05-26 Giuseppe Cannizzaro , Cyril Labbé , Willem van Zuijlen

We consider the classical momentum- or velocity-dependent two-dimensional Hamiltonian given by $$\mathcal H_N = p_1^2 + p_2^2 +\sum_{n=1}^N \gamma_n(q_1 p_1 + q_2 p_2)^n ,$$ where $q_i$ and $p_i$ are generic canonical variables, $\gamma_n$…

Mathematical Physics · Physics 2023-01-06 Alfonso Blasco , Ivan Gutierrez-Sagredo , Francisco J. Herranz

This paper addresses the so-called inverse problem which consists in searching for (possibly multiple) parent target Hamiltonian(s), given a single quantum state as input. Starting from $\Psi_0$, an eigenstate of a given local Hamiltonian…

Disordered Systems and Neural Networks · Physics 2019-10-09 Maxime Dupont , Nicolas Macé , Nicolas Laflorencie

The Typical Medium Theory provides conceptually the simplest order parameter description of Anderson localization by self-consistently calculating the geometrically-averaged (typical) local density of states (LDOS). Here we show how spatial…

Disordered Systems and Neural Networks · Physics 2016-08-08 Samiyeh Mahmoudian , Vladimir Dobrosavljević

Anderson localization provides a challenge to numerical approaches due to the inherent randomness, and hence absence of simple symmetries, in its discrete Hamiltonian representation. Numerous algorithmic approaches have been developed or…

Disordered Systems and Neural Networks · Physics 2025-03-04 Rudolf A. Römer

We introduce a conceptual reformulation of the Mott-Berezinski\u{i} (MB) theory of low-frequency AC conductivity in disordered systems based on localization landscape theory. Instead of assuming uniform localization and fixed hopping…

Disordered Systems and Neural Networks · Physics 2025-12-30 Gabriel Hayoun , Ilya A. Gruzberg , Marcel Filoche

We prove localization at the bottom of the spectrum for a random Schr\"odinger operator in the continuum with a single-site potential probability distribution supported by a Cantor set of zero Lebesgue measure. This distribution is too…

Mathematical Physics · Physics 2007-08-20 François Germinet , Abel Klein

By embedding physical intuition, network architectures enforce fundamental properties, such as energy conservation laws, leading to plausible predictions. Yet, scaling these models to intrinsically high-dimensional systems remains a…

Machine Learning · Computer Science 2026-05-14 Katharina Friedl , Noémie Jaquier , Alyx Liao , Danica Kragic