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Accurately analyzing NMR and MRI diffusion experimental data relies on the theoretical expression used for signal attenuation or phase evolution. In a complex system, the encountered magnetic field is often inhomogeneous, which may be…

Chemical Physics · Physics 2025-11-05 Chenghao Xua , Guoxing Lin

We study magnetic fluctuations in a system of interacting spins on a lattice at high temperatures and in the presence of a spatially varying magnetic field. Starting from a microscopic Hamiltonian we derive effective equations of motion for…

Statistical Mechanics · Physics 2013-03-28 Andrew Sykes , Dmitry Solenov , Dmitry Mozyrsky

In a previous paper (gr-qc/0105100) we derived a set of near-optimal signal detection techniques for gravitational wave detectors whose noise probability distributions contain non-Gaussian tails. The methods modify standard methods by…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Bruce Allen , Jolien D. E. Creighton , Eanna E. Flanagan , Joseph D. Romano

Atomic scale qubits, as may be realized in nitrogen vacancy (NV) centers in diamond, offer the opportunity to study magnetic field noise with nanometer scale spatial resolution. Using these spin qubits, one can learn a great deal about the…

Quantum Physics · Physics 2025-06-24 Jonathan B. Curtis , Amir Yacoby , Eugene Demler

Analysis with the characteristic functional of stochastic motion is used for the gradient spin echo measurement of restricted motion to clarify details of the diffraction-like effect in a porous structure. It gives the diffusive diffraction…

Materials Science · Physics 2010-10-07 Janez Stepisnik

Due to the growing number of publications and applications based on the exploitation of Bloch surface waves and the gross errors and approximations that are regularly used to evaluate the properties of this type of wave, we judge seriously…

Optics · Physics 2020-10-02 Fadi Issam Baida , Maria-Pilar Bernal

We study the influence of diffusion on NMR experiments when the molecules undergo random motion under the influence of a force field, and place special emphasis on parabolic (Hookean) potentials. To this end, the problem is studied using…

Medical Physics · Physics 2016-05-11 Cem Yolcu , Muhammet Memiç , Kadir Şimşek , Carl-Fredrik Westin , Evren Özarslan

We introduce a location statistic for distributions on non-linear geometric spaces, the diffusion mean, serving as an extension and an alternative to the Fr\'echet mean. The diffusion mean arises as the generalization of Gaussian maximum…

Statistics Theory · Mathematics 2022-12-06 Benjamin Eltzner , Pernille Hansen , Stephan F. Huckemann , Stefan Sommer

We study the dynamics of a bounded gravitational collapsing configuration emitting gravitational waves, where the exterior spacetime is described by Robinson-Trautman geometries. The full nonlinear regime is examined by using the Galerkin…

General Relativity and Quantum Cosmology · Physics 2009-11-10 H. P. de Oliveira , I. Damião Soares

We consider $N\times N$ self-adjoint Gaussian random matrices defined by an arbitrary deterministic sparsity pattern with $d$ nonzero entries per row. We show that such random matrices exhibit a canonical localization-delocalization…

Probability · Mathematics 2024-01-03 Laura Shou , Ramon van Handel

We propose a regression model for non-central $\chi$ (NC-$\chi$) distributed functional magnetic resonance imaging (fMRI) and diffusion weighted imaging (DWI) data, with the heteroscedastic Rician regression model as a prominent special…

Applications · Statistics 2016-12-22 Bertil Wegmann , Anders Eklund , Mattias Villani

The temperature dependence of magnetization in ferromagnetic nanostructures (e.g., nanoparticles or nanoclusters) is usually analyzed by means of an empirical extension of the Bloch law sufficiently flexible for a good fitting to the…

Mesoscale and Nanoscale Physics · Physics 2014-04-02 S. Cojocaru , A. Naddeo , R. Citro

Denoising diffusion models have recently emerged as the predominant paradigm for generative modelling on image domains. In addition, their extension to Riemannian manifolds has facilitated a range of applications across the natural…

Machine Learning · Computer Science 2023-11-10 Nic Fishman , Leo Klarner , Emile Mathieu , Michael Hutchinson , Valentin de Bortoli

Gravitational wave detectors will need optimal signal-processing algorithms to extract weak signals from the detector noise. Most algorithms designed to date are based on the unrealistic assumption that the detector noise may be modeled as…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Bruce Allen , Jolien D. E. Creighton , Eanna E. Flanagan , Joseph D. Romano

Last year in [Phys. Rev. E 102, 042121 (2020)] the authors studied an overdamped dynamics of nonequilibrium noise driven Brownian particle dwelling in a spatially periodic potential and discovered a novel class of Brownian, yet non-Gaussian…

Statistical Mechanics · Physics 2021-12-22 Karol Białas , Jakub Spiechowicz

Relaxation of linear magnetization dynamics is well described by the viscous Gilbert damping processes. However, for strong excitations, nonlinear damping processes such as the decay via magnon-magnon interactions emerge and trigger…

Mesoscale and Nanoscale Physics · Physics 2021-03-09 M. Mohseni , Q. Wang , B. Heinz , M. Kewenig , M. Schneider , F. Kohl , B. Lägel , C. Dubs , A. V. Chumak , P. Pirro

In the machine learning literature stochastic gradient descent has recently been widely discussed for its purported implicit regularization properties. Much of the theory, that attempts to clarify the role of noise in stochastic gradient…

Machine Learning · Computer Science 2022-10-21 Alberto Lanconelli , Christopher S. A. Lauria

With today's NMR techniques some microscopic geometry of tissue can still not be resolved directly. Often, there is also a specific off resonance field related to this geometry. In this work the impact of these off resonances on the…

Biological Physics · Physics 2013-05-28 Martin Rückl

In this work we establish a link between two different phenomena that were studied in a large and growing number of biological, composite and soft media: the diffusion in compartmentalized environment and the Brownian yet non-Gaussian…

Statistical Mechanics · Physics 2020-08-05 Jakub Ślęzak , Stanislav Burov

Gaussian random fields (GRFs) constitute an important part of spatial modelling, but can be computationally infeasible for general covariance structures. An efficient approach is to specify GRFs via stochastic partial differential equations…

Methodology · Statistics 2016-08-11 Geir-Arne Fuglstad , Finn Lindgren , Daniel Simpson , Håvard Rue