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We study the properties of the level statistics of 1D disordered systems with long-range spatial correlations. We find a threshold value in the degree of correlations below which in the limit of large system size the level statistics…

Disordered Systems and Neural Networks · Physics 2009-11-10 Pedro Carpena , Pedro Bernaola-Galvan , Plamen Ch. Ivanov

A unified treatment is developed for the XXX-Heisenberg model and a long-ranged interaction model (the $H_2$ in Haldane-Shastry model) from the point of view of shift operators (or raising and lowering operators), based on which the energy…

Quantum Physics · Physics 2007-05-23 Jing-Ling Chen , Mo-Lin Ge , Kang Xue , Xian-Geng Zhao

The bivariate distribution of degrees of adjacent vertices (degree-degree distribution) is an important network characteristic defining the statistical dependencies between degrees of adjacent vertices. We show the asymptotic degree-degree…

Probability · Mathematics 2017-01-05 Mindaugas Bloznelis

Using a formalism based on the spectral decomposition of the replicated transfer matrix for disordered Ising models, we obtain several results that apply both to isolated one-dimensional systems and to locally tree-like graph and factor…

Disordered Systems and Neural Networks · Physics 2014-08-04 Carlo Lucibello , Flaviano Morone , Tommaso Rizzo

We evaluate the scattering functions of a gas of spin-polarized, non-interacting fermions confined in a quasi-onedimensional harmonic trap at zero temperature. The main focus is on the inelastic scattering spectrum and on the angular…

Statistical Mechanics · Physics 2009-11-07 Patrizia Vignolo , Anna Minguzzi , M. P. Tosi

Level curvature is a measure of sensitivity of energy levels of a disordered/chaotic system to perturbations. In the bulk of the spectrum Random Matrix Theory predicts the probability distributions of level curvatures to be given by…

Mathematical Physics · Physics 2012-02-23 Yan V Fyodorov

Hierarchical tree structures are common in many real-world systems, from tree roots and branches to neuronal dendrites and biologically inspired artificial neural networks, as well as in technological networks for organizing and searching…

Statistical Mechanics · Physics 2025-02-04 Davide Cipollini , Lambert Schomaker

We consider the statistical properties of the gravitational field F in an infinite one-dimensional homogeneous Poisson distribution of particles, using an exponential cut-off of the pair interaction to control and study the divergences…

Statistical Mechanics · Physics 2015-05-14 Andrea Gabrielli , Michael Joyce

The spin polarization (P) of high-density InSb two-dimensional electron systems (2DESs) has been measured using both parallel and tilted magnetic fields. P is found to exhibit a superlinear increase with the total field B. This P-B…

Strongly Correlated Electrons · Physics 2011-08-18 K. F. Yang , H. W. Liu , T. D. Mishima , M. B. Santos , K. Nagase , Y. Hirayama

An appropriate model for the random energy landscape in organic glasses is a spatially correlated Gaussian field. We calculated the distribution of the average value of a Gaussian random field in a finite domain. The results of the…

Disordered Systems and Neural Networks · Physics 2013-03-21 S. V. Novikov

The dynamics of individual colloidal particles in random potential energy landscapes were investigated experimentally and by Monte Carlo simulations. The value of the potential at each point in the two-dimensional energy landscape follows a…

We show that numerical linked cluster expansions (NLCEs) based on sufficiently large building blocks allow one to obtain accurate low-temperature results for the thermodynamic properties of spin lattice models with continuous disorder…

Statistical Mechanics · Physics 2024-06-04 Mahmoud Abdelshafy , Marcos Rigol

Quasi-one-dimensional spin-Peierls and spin-ladder systems are characterized by a gap in the spin-excitation spectrum, which can be modeled at low energies by that of Dirac fermions with a mass. In the presence of disorder these systems can…

Disordered Systems and Neural Networks · Physics 2009-10-30 M. Steiner , M. Fabrizio , Alexander O. Gogolin

We present Direct Numerical Simulation (DNS) of heavy inertial particles (dust) immersed in two-dimensional turbulent flow (gas). The dust are modeled as mono-dispersed heavy particles capable of modifying the flow through two-way coupling.…

Fluid Dynamics · Physics 2019-07-31 Vikash Pandey , Dhrubaditya Mitra , Prasad Perlekar

A new integrable spin chain of the Haldane-Shastry type is introduced. It is interpreted as the inverse-square interacting spin chain with a {\it reflecting end}. The lattice points of this model consist of the square roots of the zeros of…

Condensed Matter · Physics 2009-10-28 Takashi Yamamoto , Osamu Tsuchiya

We find that the spin susceptibility of a two-dimensional electron system with valley degeneracy does not grow critically at low densities, at variance with experimental results [A. Shashkin et al., Phys. Rev. Lett. 96, 036403 (2006)]. We…

Strongly Correlated Electrons · Physics 2009-07-09 M. Marchi , S. De Palo , S. Moroni , Gaetano Senatore

Using arguments built on ergodicity, we derive an analytical expression for the Renyi entanglement entropies corresponding to the finite-energy density eigenstates of chaotic many-body Hamiltonians. The expression is a universal function of…

Statistical Mechanics · Physics 2019-03-12 Tsung-Cheng Lu , Tarun Grover

A relation between O$(n)$ models and Ising models has been recently conjectured [L. Casetti, C. Nardini, and R. Nerattini, Phys. Rev. Lett. 106, 057208 (2011)]. Such a relation, inspired by an energy landscape analysis, implies that the…

Statistical Mechanics · Physics 2015-07-29 Rachele Nerattini , Andrea Trombettoni , Lapo Casetti

We investigate the N-leg spin-S Heisenberg Ladders by using the density matrix renormalization group method. We present estimates of the spin gap $\Delta_{s}$ and of the ground state energy per site $e_{\infty}^{N}$ in the thermodynamic…

Strongly Correlated Electrons · Physics 2014-04-10 F. B. Ramos , J. C. Xavier

Granular gas mixtures modeled as systems of inelastic and rough particles, either hard disks on a plane or hard spheres, are considered. Both classes of systems are embedded in a three-dimensional space ($d=3$) but, while in the hard-sphere…

Soft Condensed Matter · Physics 2019-08-14 Alberto Megías , Andrés Santos