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In this work, we present a theoretical and experimental study about the spatial correlations of paired photons generated by type-II spontaneous parametric down-conversion. In particular, we show how these correlations can be positive or…

Modulated symmetries are internal symmetries that act in a non-uniform, spatially modulated way and are generalizations of, for example, dipole symmetries. In this paper, we systematically study the gauging of finite Abelian modulated…

Strongly Correlated Electrons · Physics 2025-01-20 Salvatore D. Pace , Guilherme Delfino , Ho Tat Lam , Ömer M. Aksoy

Doubts regarding the completeness of quantum mechanics as raised by Einstein, Podolsky and Rosen(EPR) have predominantly been resolved by resorting to a measurement of correlations between entangled photons which clearly demonstrate…

Quantum Physics · Physics 2017-05-03 Keerthan Subramanian , Nirmal K. Viswanathan

We show that linearly repetitive weighted Delone sets in groups of polynomial growth have a uniquely ergodic hull. This result applies in particular to the linearly repetitive weighted Delone sets in homogeneous Lie groups constructed in…

Dynamical Systems · Mathematics 2025-06-11 Siegfried Beckus , Tobias Hartnick , Felix Pogorzelski

The parametric variation of the eigenfrequencies of a chaotic plate is measured and compared to random matrix theory using recently calculated universal correlation functions. The sensitivity of the flexural modes of the plate to pressure…

Condensed Matter · Physics 2009-10-31 K. Schaadt , A. Kudrolli

Comparing spatial data sets is a ubiquitous task in data analysis, however the presence of spatial autocorrelation means that standard estimates of variance will be wrong and tend to over-estimate the statistical significance of…

Applications · Statistics 2024-01-12 Rudy Arthur

The increasing application of deep-learning is accompanied by a shift towards highly non-linear statistical models. In terms of their geometry it is natural to identify these models with Riemannian manifolds. The further analysis of the…

Statistics Theory · Mathematics 2020-06-23 Patrick Michl

It is known that discrete scale invariance leads to log-periodic corrections to scaling. We investigate the correlations of a system with discrete scale symmetry, discuss in detail possible extension of this symmetry such as translation and…

Condensed Matter · Physics 2009-11-07 N. Abed-Pour , A. Aghamohammadi , M. Khorrami , M. Reza Rahimi Tabar

The explicit calculation of the scaling form of the two-time autocorrelation function in phase-ordering kinetics and in those cases of non-equilibrium critical dynamics where the dynamical exponent z=2 through the extension of dynamical…

Statistical Mechanics · Physics 2011-02-16 Malte Henkel , Florian Baumann

Two-photon states generated through degenerate spontaneous parametric down-conversion (SPDC) can exhibit sharp correlations in the transverse spatial coordinates. This property leads to unique free-space propagation features. Here, we show…

Quantum Physics · Physics 2025-05-20 Nazanin Dehghan , Alessio D'Errico , Yingwen Zhang , Benjamin Sussman , Ebrahim Karimi

Motivated by the simultaneous association analysis with the presence of latent confounders, this paper studies the large-scale hypothesis testing problem for the high-dimensional confounded linear models with both non-asymptotic and…

Methodology · Statistics 2023-08-24 Yinrui Sun , Li Ma , Yin Xia

We quantize the electromagnetic field in the presence of a nonmoving dielectric sphere in vacuum. The sphere is assumed to be lossless, dispersionless, isotropic, and homogeneous. The quantization is performed using normalized eigenmodes as…

Quantum Physics · Physics 2023-11-15 Patrick Maurer , Carlos Gonzalez-Ballestero , Oriol Romero-Isart

Several classes of tempered measures are characterised that are eigenmeasures of the Fourier transform, the latter viewed as a linear operator on (generally unbounded) Radon measures on $\RR^d$. In particular, we classify all periodic…

Spectral Theory · Mathematics 2024-04-22 Michael Baake , Timo Spindeler , Nicolae Strungaru

Testing the independence between random vectors is a fundamental problem in statistics. Distance correlation, a recently popular dependence measure, is universally consistent for testing independence against all distributions with finite…

Methodology · Statistics 2024-08-22 Yuwei Ke , Hok Kan Ling , Yanglei Song

Tilings based on the cut and project method are key model systems for the description of aperiodic solids. Typically, quantities of interest in crystallography involve averaging over large patches, and are well defined only in the…

Disordered Systems and Neural Networks · Physics 2020-09-04 Michael Baake , Uwe Grimm

The relevance of parity and time reversal (PT)-symmetric structures in optical systems is known for sometime with the correspondence existing between the Schrodinger equation and the paraxial equation of diffraction where the time parameter…

Quantum Physics · Physics 2014-01-21 Bijan Bagchi , Subhrajit Modak , Prasanta K. Panigrahi

We study the isoperimetric problem for the radially symmetric measures. Applying the spherical symmetrization procedure and variational arguments we reduce this problem to a one-dimensional ODE of the second order. Solving numerically this…

Probability · Mathematics 2015-03-13 Alexander V. Kolesnikov , Roman I. Zhdanov

It is shown that the partial amplitudes of the pure point part of the diffraction spectrum of an aperiodic Delone point pattern of finite local complexity are linked by a set of linear constraints. These relations can be explicitly derived…

Mathematical Physics · Physics 2022-02-09 Pavel Kalugin , André Katz

A class of two-species ({\it three-states}) bimolecular diffusion-limited models of classical particles with hard-core reacting and diffusing in a hypercubic lattice of arbitrary dimension is investigated. The manifolds on which the…

Statistical Mechanics · Physics 2009-10-31 Mauro Mobilia , Pierre-Antoine Bares

Hyperbolic deep learning leverages the metric properties of hyperbolic spaces to develop efficient and informative embeddings of hierarchical data. Here, we focus on the solvable group structure of hyperbolic spaces, which follows naturally…

Machine Learning · Computer Science 2025-06-02 Federico Milanesio , Matteo Santoro , Pietro G. Fré , Guido Sanguinetti
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