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Irreversible aggregation is revisited in view of recent work on renormalization of complex networks. Its scaling laws and phase transitions are related to percolation transitions seen in the latter. We illustrate our points by giving the…

Data Analysis, Statistics and Probability · Physics 2011-08-26 Seung-Woo Son , Golnoosh Bizhani , Claire Christensen , Peter Grassberger , Maya Paczuski

A new method (NM) for filtering three-dimensional reconstructed densities is proposed. The algorithm is tested with simulated spectra and employed to study the electronic structure of the rare-earth compound LaB6. For this system, momentum…

Materials Science · Physics 2007-05-23 G. Kontrym-Sznajd , M. Samsel-Czekala , M. Biasini , Y. Kubo

The problem of continuum percolation in dispersions of rods is reformulated in terms of weighted random geometric graphs. Nodes (or sites or vertices) in the graph represent spatial locations occupied by the centers of the rods. The…

Statistical Mechanics · Physics 2015-09-30 Avik P. Chatterjee , Claudio Grimaldi

With the discovery of gravitational waves and fast radio bursts, wave optics has become increasingly relevant in astrophysics. This paper studies the behaviour of random gravitational and plasma lenses, presenting the refractive and…

Cosmology and Nongalactic Astrophysics · Physics 2026-02-26 Job Feldbrugge , Samuel Crew , Ue-Li Pen

Truncated Fourier, Gauss, Kummer and exponential sums can be used to factorize numbers: for a factor these sums equal unity in absolute value, whereas they nearly vanish for any other number. We show how this factorization algorithm can…

Quantum Physics · Physics 2011-02-21 A. A. Rangelov

Recursive partitioning is the core of several statistical methods including CART, random forest, and boosted trees. Despite the popularity of tree based methods, to date, there did not exist methods for combining multiple trees into a…

Data Structures and Algorithms · Computer Science 2016-03-18 Sean Skwerer , Heping Zhang

Paraxial diffraction of monochromatic Gaussian beams by arbitrarily shaped polygonal apertures is analytically explored within the boundary diffraction wave theory framework. Exact closed-form expressions of the diffracted wavefield are…

Optics · Physics 2019-09-04 Riccardo Borghi

We introduce a variational quantum computing approach for quantum state reconstruction within a discretized logical framework, using experimental measurement data as input. By mapping the reconstruction cost function onto an Ising model,…

Quantum Physics · Physics 2026-04-03 Mwezi Koni , Shawal Kassim , Paola C. Obando , Neelan Gounden , Isaac Nape

We introduce a new product representation for general random binary fractal apertures defined by removing voids from Euclidean space, and use it to derive a simple closed-form expression for ensemble-averaged correlations. Power-law scaling…

Optics · Physics 2017-06-21 Jonathan F. Schonfeld

The Particle Number Projected Generator Coordinate Method is formulated for the pairing Hamiltonian in a detailed way in the projection after variation and the variation after projection methods. The dependence of the wave functions on the…

Superconductivity · Physics 2009-11-11 M. A. Fernandez , J. L. Egido

In this paper, we extend the paraxial conical refraction model to the case of the partially coherent light using the unified optical coherence theory. We demonstrate the decomposition of conical refraction correlation functions into…

Optics · Physics 2022-05-12 V. Yu. Mylnikov , V. V. Dudelev , E. U. Rafailov , G. S. Sokolovskii

We present a detailed theoretical treatment of four-wave mixing (FWM) in a quantized paraxial framework, capturing the multi-spatial-mode nature of the biphoton state generated in the process. By analyzing the biphoton state both in…

Quantum Physics · Physics 2025-12-12 Mateus R. L. da Motta , Sandra S. Vianna

In this work, we consider the inverse problem of reconstructing the internal structure of an object from limited x-ray projections. We use a Gaussian process prior to model the target function and estimate its (hyper)parameters from…

Computer Vision and Pattern Recognition · Computer Science 2019-07-04 Zenith Purisha , Carl Jidling , Niklas Wahlström , Simo Särkkä , Thomas B. Schön

Spontaneous parametric down-conversion is a vital method for generating correlated photon pairs in the visible and near-infrared spectral regions; however, its extension to X-ray frequencies has faced substantial barriers. Here, we present…

Probabilistic graphical models are a key tool in machine learning applications. Computing the partition function, i.e., normalizing constant, is a fundamental task of statistical inference but it is generally computationally intractable,…

Machine Learning · Statistics 2020-01-29 Sungsoo Ahn , Michael Chertkov , Adrian Weller , Jinwoo Shin

We show that the time frequency analysis of the autocorrelation function is, in many ways, a more appropriate tool to resolve fractional revivals of a wave packet than the usual time domain analysis. This advantage is crucial in…

Quantum Physics · Physics 2009-04-03 Suranjana Ghosh , J. Banerji

Fractional revival occurs between two vertices in a graph if a continuous-time quantum walk unitarily maps the characteristic vector of one vertex to a superposition of the characteristic vectors of the two vertices. This phenomenon is…

Combinatorics · Mathematics 2019-07-11 Ada Chan , Gabriel Coutinho , Christino Tamon , Luc Vinet , Hanmeng Zhan

X-ray observations of bright AGNs in or behind galaxy clusters offer unique capabilities to constrain axion-like particles (ALPs). Existing analysis technique rely on measurements of the global goodness-of-fit. We develop a new analysis…

Cosmology and Nongalactic Astrophysics · Physics 2019-01-30 Joseph P. Conlon , Markus Rummel

We study the spatial correlations of quantum fluctuations that can be observed in multi-mode spontaneous parametric down-conversion in the regime of high gain. A stochastic model has been solved numerically to obtain quantitative results…

Quantum Physics · Physics 2009-11-10 E. Brambilla , A. Gatti , M. Bache , L. A. Lugiato

We develop a method to infer log-normal random fields from measurement data affected by Gaussian noise. The log-normal model is well suited to describe strictly positive signals with fluctuations whose amplitude varies over several orders…

Instrumentation and Methods for Astrophysics · Physics 2013-03-19 Niels Oppermann , Marco Selig , Michael R. Bell , Torsten A. Enßlin