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Related papers: Ordered level spacing probability densities

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In this communication with computer simulation we evaluate simple cubic random-site percolation thresholds for neighbourhoods including the nearest neighbours (NN), the next-nearest neighbours (2NN) and the next-next-nearest neighbours…

Mathematical Physics · Physics 2012-11-30 Lukasz Kurzawski , Krzysztof Malarz

We construct a hybrid quantum-classical approach for the $K$-Nearest Neighbour algorithm, where the information is embedded in a phase-distributed multimode coherent state with the assistance of a single photon. The task of finding the…

Quantum Physics · Physics 2024-04-19 Vivek Mehta , Francesco Petruccione , Utpal Roy

The $K$-nearest neighbors is a basic problem in machine learning with numerous applications. In this problem, given a (training) set of $n$ data points with labels and a query point $p$, we want to assign a label to $p$ based on the labels…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-25 Reza Fathi , Anisur Rahaman Molla , Gopal Pandurangan

The finest state space resolution that can be achieved in a physical dynamical system is limited by the presence of noise. In the weak-noise approximation the neighborhoods of deterministic periodic orbits can be computed as distributions…

Chaotic Dynamics · Physics 2015-12-31 Jeffrey M. Heninger , Domenico Lippolis , Predrag Cvitanovic

Three different levels of noisy quantum schemes modeling are considered: vectors, density matrices and Choi-Jamiolkowski related states. The implementations for personal computers and supercomputers are described, and the corresponding…

Suppose $V$ is an $n$-element set where for each $x \in V$, the elements of $V \setminus \{x\}$ are ranked by their similarity to $x$. The $K$-nearest neighbor graph is a directed graph including an arc from each $x$ to the $K$ points of $V…

Combinatorics · Mathematics 2020-12-29 Jacob D. Baron , R. W. R. Darling

We derive a formula for the level spacing probability distribution in quantum graphs. We apply it to simple examples and we discuss its relation with previous work and its possible application in more general cases. Moreover, we derive an…

Quantum Physics · Physics 2015-06-26 F. Barra , P. Gaspard

The statistical properties of level spacings provide valuable insights into the dynamical properties of a many-body quantum systems. We investigate the level statistics of the Fermi-Hubbard model with dimerized hopping amplitude and find…

Quantum Gases · Physics 2023-09-14 Karin Haderlein , David J. Luitz , Corinna Kollath , Ameneh Sheikhan

The distribution of higher order level spacings, i.e. the distribution of $\{s_{i}^{(n)}=E_{i+n}-E_{i}\}$ with $n\geq 1$ is derived analytically using a Wigner-like surmise for Gaussian ensembles of random matrix as well as Poisson…

Disordered Systems and Neural Networks · Physics 2020-08-05 Wen-Jia Rao

In order to study the resonance spectra of chaotic cavities subject to some damping (which can be due to absorption or partial reflection at the boundaries), we use a model of damped quantum maps. In the high-frequency limit, the…

Chaotic Dynamics · Physics 2009-04-23 Stéphane Nonnenmacher , Emmanuel Schenck

We analyze the nearest neighbor spacing distributions of low-lying 2+ levels of even-even nuclei. We grouped the nuclei into classes defined by the quadrupole deformation parameter (Beta2). We calculate the nearest neighbor spacing…

Nuclear Theory · Physics 2011-02-14 A. Al-Sayed

The energy level statistics of uniform random graphs are studied, by treating the graphs as random tight-binding lattices. The inherent random geometry of the graphs and their dynamical spatial dimensionality, leads to various quantum…

Disordered Systems and Neural Networks · Physics 2024-12-20 Ioannis Kleftogiannis , Ilias Amanatidis

The Nearest Neighbour Spacing (NNS) distribution can be computed for generalized symmetric 2x2 matrices having different variances in the diagonal and in the off-diagonal elements. Tuning the relative value of the variances we show that the…

Chaotic Dynamics · Physics 2022-01-12 Adway Kumar Das , Anandamohan Ghosh

We study the statistics of level spacing of geometric resonances in the disordered binary networks. For a definite concentration $p$ within the interval $[0.2,0.7]$, numerical calculations indicate that the unfolded level spacing…

Soft Condensed Matter · Physics 2007-05-23 Y. Gu , K. W. Yu , Z. R. Yang

Let $P$ be a set of $n$ colored points. We develop efficient data structures that store $P$ and can answer chromatic $k$-nearest neighbor ($k$-NN) queries. Such a query consists of a query point $q$ and a number $k$, and asks for the color…

Computational Geometry · Computer Science 2022-05-03 Thijs van der Horst , Maarten Löffler , Frank Staals

Order statistics of periodic, Gaussian noise with 1/f^{\alpha} power spectrum is investigated. Using simulations and phenomenological arguments, we find three scaling regimes for the average gap d_k=<x_k-x_{k+1}> between the k-th and…

Statistical Mechanics · Physics 2013-05-29 N. R. Moloney , K. Ozogany , Z. Racz

We give a general unified method that can be used for $L_1$ {\em closeness testing} of a wide range of univariate structured distribution families. More specifically, we design a sample optimal and computationally efficient algorithm for…

Data Structures and Algorithms · Computer Science 2015-08-25 Ilias Diakonikolas , Daniel M. Kane , Vladimir Nikishkin

Quantum statistical models (i.e., families of normalized density matrices) and quantum measurements (i.e., positive operator-valued measures) can be regarded as linear maps: the former, mapping the space of effects to the space of…

Quantum Physics · Physics 2025-02-06 Michele Dall'Arno , Francesco Buscemi

A numerical study is made of the spectra of a tight-binding hamiltonian on square approximants of the quasiperiodic octagonal tiling. Tilings may be pure or random, with different degrees of phason disorder considered. The level statistics…

Condensed Matter · Physics 2009-10-22 Frederic Piechon , Anuradha Jagannathan

Motivated by the mode estimation problem of an unknown multivariate probability density function, we study the problem of identifying the point with the minimum k-th nearest neighbor distance for a given dataset of n points. We study the…

Machine Learning · Statistics 2020-10-27 Anirudh Singhal , Subham Pirojiwala , Nikhil Karamchandani