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We study long-range power-law correlated disorder on square and cubic lattices. In particular, we present high-precision results for the percolation thresholds and the fractal dimension of the largest clusters as function of the correlation…

Statistical Mechanics · Physics 2018-01-03 Johannes Zierenberg , Niklas Fricke , Martin Marenz , F. P. Spitzner , Viktoria Blavatska , Wolfhard Janke

The parallel computational complexity of the quadratic map is studied. A parallel algorithm is described that generates typical pseudotrajectories of length t in a time that scales as log t and increases slowly in the accuracy demanded of…

Chaotic Dynamics · Physics 2015-06-26 J. Machta

Quantum networks are essential to quantum information distributed applications, and communicating over them is a key challenge. Complex networks have rich and intriguing properties, which are as yet unexplored in the quantum setting. Here,…

Quantum Physics · Physics 2009-12-15 M. Cuquet , J. Calsamiglia

We investigate the effect of structural distortion on bond percolation in simple cubic and body-centered cubic lattices using extensive Monte Carlo simulations. Distortion is introduced through controlled random displacements of lattice…

Statistical Mechanics · Physics 2026-02-18 Bishnu Bhowmik , Sayantan Mitra , Robert M. Ziff , Ankur Sensharma

Accurately measuring the translations of objects between images is essential in many fields, including biology, medicine, chemistry, and physics. One important application is tracking one or more particles by measuring their apparent…

Usage of multiprocessor and multicore computers implies parallel programming. Tools for preparing parallel programs include parallel languages and libraries as well as parallelizing compilers and convertors that can perform automatic…

Mathematical Software · Computer Science 2022-12-12 Pavel Telegin , Anton Baranov , Boris Shabanov , Artem Tikhomirov

Global physical properties of random media change qualitatively at a percolation threshold, where isolated clusters merge to form one infinite connected component. The precise knowledge of percolation thresholds is thus of paramount…

Statistical Mechanics · Physics 2008-01-13 Richard A. Neher , Klaus Mecke , Herbert Wagner

We propose an approach to calculate the critical percolation threshold for finite-sized Erdos-Renyi digraphs using minimal Hamiltonian cycles. We obtain an analytically exact result, valid non-asymptotically for all graph sizes, which…

Statistical Mechanics · Physics 2014-05-12 Michelle Rudolph-Lilith , Lyle E. Muller

We present here two promising techniques for the application of the complex network approach to continuous spatio-temporal systems that have been developed in the last decade and show large potential for future application and development…

Data Analysis, Statistics and Probability · Physics 2015-07-19 Norbert Marwan , Jürgen Kurths

Site percolation in a distorted simple cubic lattice is characterized numerically employing the Newman-Ziff algorithm. Distortion is administered in the lattice by systematically and randomly dislocating its sites from their regular…

Statistical Mechanics · Physics 2022-09-12 Sayantan Mitra , Dipa Saha , Ankur Sensharma

Considering an example of the long-range Kitaev model, we are looking for a correlation length in a model with long range interactions whose correlation functions away from a critical point have power-law tails instead of the usual…

Strongly Correlated Electrons · Physics 2021-07-07 Debasis Sadhukhan , Jacek Dziarmaga

Percolation theory concerns the emergence of connected clusters that percolate through a networked system. Previous studies ignored the effect that a node outside the percolating cluster may actively induce its inside neighbours to exit the…

Statistical Mechanics · Physics 2013-09-12 Jin-Hua Zhao , Hai-Jun Zhou , Yang-Yu Liu

Fractal dimension is widely adopted in spatial databases and data mining, among others as a measure of dataset skewness. State-of-the-art algorithms for estimating the fractal dimension exhibit linear runtime complexity whether based on…

Databases · Computer Science 2009-05-27 Christos Attikos , Michael Doumpos

Many realistic systems such as infrastructures are characterized by spatial structure and anisotropic alignment. Here we propose and study a model for dealing with such characteristics by introducing a parameter that controls the strength…

Physics and Society · Physics 2022-06-08 Ouriel Gotesdyner , Bnaya Gross , Dana Vaknin Ben Porath , Shlomo Havlin

Recently increasing attention has been addressed to the fluctuations observed in percolation defined in single and multiplex networks. These fluctuations are extremely important to characterize the robustness of real finite networks but…

Disordered Systems and Neural Networks · Physics 2019-08-21 Ginestra Bianconi

We propose a powerful method based on the Hoshen-Kopelman algorithm for simulating percolation asynchronously on distributed machines. Our method demands very little of hardware and yet we are able to make high precision measurements on…

Statistical Mechanics · Physics 2009-11-07 Nicholas R. Moloney , Gunnar Pruessner

The two-point correlation function is computed for galaxies and groups of galaxies selected using 3-dimensional information from the Updated Zwicky Galaxy Catalog - (UZC). The redshift space distortion of the correlation function…

Several real-world systems can be represented as multi-layer complex networks, i.e. in terms of a superposition of various graphs, each related to a different mode of connection between nodes. Hence, the definition of proper mathematical…

Physics and Society · Physics 2016-10-31 Valerio Gemmetto , Diego Garlaschelli

The correlation functions related to topological phase transitions in inversion-symmetric lattice models described by $2\times 2$ Dirac Hamiltonians are discussed. In one dimension, the correlation function measures the charge-polarization…

Mesoscale and Nanoscale Physics · Physics 2017-02-08 Wei Chen , Markus Legner , Andreas Rüegg , Manfred Sigrist

Spatial relations between objects in an image have proved useful for structural object recognition. Structural constraints can act as regularization in neural network training, improving generalization capability with small datasets.…

Computer Vision and Pattern Recognition · Computer Science 2021-02-23 Mateus Riva , Pietro Gori , Florian Yger , Roberto Cesar , Isabelle Bloch
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