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Autoregressive processes (AR) have typical short-range memory. Detrended Fluctuation Analysis (DFA) was basically designed to reveal long range correlation in non stationary processes. However DFA can also be regarded as a suitable method…

Biological Physics · Physics 2007-07-11 V. V. Morariu , L. Buimaga-Iarinca , C. Vamos , S. Soltuz

By combining aspects of the coherent and self intermediate scattering functions, measured by dynamical light scattering on a suspension of hard sphere-like particles, we show that the arrest of particle number density fluctuations spreads…

Soft Condensed Matter · Physics 2015-05-13 W. van Megen , V. A. Martinez , G. Bryant

A general approach for the calculation of the incoherent intensity scattered by a random medium with rough boundaries has been developed using a Green function formalism. The random medium consists of spherical particles whose physical…

Atmospheric and Oceanic Physics · Physics 2007-05-23 A. Soubret , G. Berginc

In classical Drude theory the conductivity is determined by the mass of the propagating particles and the mean free path between two scattering events. For a quantum particle this simple picture of diffusive transport loses relevance if…

Strongly Correlated Electrons · Physics 2015-05-13 A Alvermann , D M Edwards , H Fehske

This work focuses on the training dynamics of one associative memory module storing outer products of token embeddings. We reduce this problem to the study of a system of particles, which interact according to properties of the data…

Machine Learning · Computer Science 2024-03-01 Vivien Cabannes , Berfin Simsek , Alberto Bietti

In this work we compare Monte Carlo (MC) simulations of electron transport properties with reflection electron energy loss measurements in diamond and graphite films. We assess the impact of different approximations of the dielectric…

The inclusive probability to record an electron in elastic electromagnetic scattering of an electron by a spin one-half hadron is obtained, the initial quantum states of the electron and the hadron being described by the density matrices of…

High Energy Physics - Phenomenology · Physics 2023-12-08 P. O. Kazinski , D. I. Rubtsova , A. A. Sokolov

When a nucleus in an atom undergoes a collision, there is a small probability to inelastically excite an electron as a result of the Migdal effect. In this Letter, we present a first complete derivation of the Migdal effect from dark…

High Energy Physics - Phenomenology · Physics 2021-09-07 Simon Knapen , Jonathan Kozaczuk , Tongyan Lin

Since the discovery of electron-wave duality, electron scattering instrumentation has developed into a powerful array of techniques for revealing the atomic structure of matter. Beyond detecting local lattice variations in equilibrium…

Memory is the fundamental form of temporal complexity: when present but uncontrollable, it manifests as non-Markovian noise; conversely, if controllable, memory can be a powerful resource for information processing. Memory effects arise…

Quantum Physics · Physics 2024-05-07 Philip Taranto , Marco Túlio Quintino , Mio Murao , Simon Milz

The diffraction patterns of crystalline materials with local order contain sharp Bragg reflections as well as highly structured diffuse scattering. The instrumental requirements, experimental parameters and data processing techniques for…

Materials Science · Physics 2023-11-29 Romy Poppe , Joke Hadermann

We present a general model study of surface-enhanced resonant Raman scattering and fluorescence focusing on the interplay between electromagnetic effects and the molecular dynamics. Our model molecule is placed close to two Ag…

Other Condensed Matter · Physics 2007-05-23 Hongxing Xu , Xue-Hua Wang , Martin P. Persson , H. Q. Xu , Mikael Kall , Peter Johansson

Moments (Variance ($\sigma^2$), Skewness($S$), Kurtosis($\kappa$)) of multiplicity distributions of conserved quantities, such as net-baryon,net-charge and net-strangeness, are predicted to be sensitive to the correlation length of the…

Nuclear Experiment · Physics 2013-09-06 Xiaofeng Luo , Ji Xu , Bedangadas Mohanty , Nu Xu

Fluctuations of conserved quantities are predicted to be sensitive to the correlation length and connected to the thermodynamic susceptibility. Thus, moments of net-baryon, net-charge and net-strangeness have been extensively studied…

Data Analysis, Statistics and Probability · Physics 2016-11-03 Xiaofeng Luo

The theoretical description of observables at collider experiments relies on factorization theorems separating perturbative dynamics from universal non-perturbative matrix elements. Despite significant recent progress in extending these…

High Energy Physics - Phenomenology · Physics 2023-08-04 Kyle Lee , Ian Moult

With the growth of computational resources, the scope of electronic structure simulations has increased greatly. Artificial intelligence and robust data analysis hold the promise to accelerate large-scale simulations and their analysis to…

Materials Science · Physics 2023-07-27 Lenz Fiedler , Karan Shah , Michael Bussmann , Attila Cangi

Stochastic and mixed stochastic-deterministic density functional theory (DFT) are promising new approaches for the calculation of the equation-of-state and transport properties in materials under extreme conditions. In the intermediate warm…

Computational Physics · Physics 2023-09-27 Vidushi Sharma , Lee A. Collins , Alexander J. White

Spontaneous fluctuations and stimulus response are essential features of neural functioning but how they are connected is poorly understood. I derive fluctuation-dissipation relations (FDR) between the spontaneous spike and voltage…

Neurons and Cognition · Quantitative Biology 2022-11-09 Benjamin Lindner

Momentum diffusion is a possible mechanism for driving macroscopic quantum systems towards classical behaviour. Experimental tests of this hypothesis rely on a precise estimation of the strength of this diffusion. We show that…

Quantum Physics · Physics 2020-11-22 Dominic Branford , Christos N. Gagatsos , Jai Grover , Alexander J. Hickey , Animesh Datta

The Dense Associative Memory generalizes the Hopfield network by allowing for sharper interaction functions. This increases the capacity of the network as an autoassociative memory as nearby learned attractors will not interfere with one…

Neural and Evolutionary Computing · Computer Science 2024-09-24 Hayden McAlister , Anthony Robins , Lech Szymanski
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