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Diffusion models have been recently studied as powerful generative inverse problem solvers, owing to their high quality reconstructions and the ease of combining existing iterative solvers. However, most works focus on solving simple linear…

Machine Learning · Statistics 2025-10-06 Hyungjin Chung , Jeongsol Kim , Michael T. Mccann , Marc L. Klasky , Jong Chul Ye

The problem of diffusion in a porous medium with a spatially varying porosity is considered. The particular microstructure analyzed comprises a collection of impenetrable spheres, though the methods developed are general. Two different…

Fluid Dynamics · Physics 2017-10-12 Maria Bruna , S. Jonathan Chapman

Context. Radar scattering from meteor trails depends on several poorly constrained quantities, such as electron line density, q, initial trail radius, r0, and ambipolar diffusion coefficient, D. Aims. The goal is to apply a numerical model…

Earth and Planetary Astrophysics · Physics 2021-10-20 G. Stober , P. Brown , M. Campbell-Brown , R. J. Weryk

Future high-resolution imaging X-ray observatories may require detectors with both fine spatial resolution and high quantum efficiency at relatively high X-ray energies (>5keV). A silicon imaging detector meeting these requirements will…

The charging of insulating samples degrades the quality and complicates the interpretation of images in scanning electron microscopy and is important in other applications, such as particle detectors. In this paper we analyze this…

Classical Physics · Physics 2020-06-19 Behrouz Raftari , Neil Budko , Kees Vuik

Models of diffusion in white dwarfs universally rely on the coefficients calculated by Paquette et al. (1986). We present new calculations of diffusion coefficients based on an advanced microscopic theory of dense plasmas and a numerical…

Solar and Stellar Astrophysics · Physics 2014-10-29 D. Saumon , C. E. Starrett , J. Daligault

A general theory of efficient estimation for ergodic diffusion processes sampled at high frequency with an infinite time horizon is presented. High frequency sampling is common in many applications, with finance as a prominent example. The…

Statistics Theory · Mathematics 2024-01-10 Michael Sørensen

We consider the inverse problem of determining different type of information about a diffusion process, described by ordinary or fractional diffusion equations stated on a bounded domain, like the density of the medium or the velocity field…

Analysis of PDEs · Mathematics 2019-07-05 Yavar Kian , Zhiyuan Li , Yikan Liu , Masahiro Yamamoto

Diffusion models have gained traction as powerful algorithms for synthesizing high-quality images. Central to these algorithms is the diffusion process, a set of equations which maps data to noise in a way that can significantly affect…

Machine Learning · Computer Science 2024-11-12 Subham Sekhar Sahoo , Aaron Gokaslan , Chris De Sa , Volodymyr Kuleshov

Bulk matter produced in heavy ion collisions has multiple conserved quantum numbers like baryon number, strangeness and electric charge. The diffusion process of these charges can be described by a diffusion matrix describing the…

Nuclear Theory · Physics 2022-08-31 Arpan Das , Hiranmaya Mishra , Ranjita K. Mohapatra

We present a measurement of phonon propagation in a silicon wafer utilizing an array of frequency-multiplexed superconducting resonators coupled to a single transmission line. The electronic readout permits fully synchronous array sampling…

Instrumentation and Detectors · Physics 2015-05-18 L. J. Swenson , A. Cruciani , A. Benoit , M. Roesch , C. S. Yung , A. Bideaud , A. Monfardini

We prove diffusion for a quantum particle coupled to a field of bosons (phonons or photons). The importance of this result lies in the fact that our model is fully Hamiltonian and randomness enters only via the initial (thermal) state of…

Mathematical Physics · Physics 2013-04-23 W. De Roeck , A. Kupiainen

Score-based diffusion models learn to reverse a stochastic differential equation that maps data to noise. However, for complex tasks, numerical error can compound and result in highly unnatural samples. Previous work mitigates this drift…

Machine Learning · Statistics 2023-06-12 Aaron Lou , Stefano Ermon

We present theoretical and numerical results pointing towards a strong connection between the estimates for the diffusion rate along simple resonances in multidimensional nonlinear Hamiltonian systems that can be obtained using the…

2D and 4D transverse phase-space of a low-energy ion-beam is measured with two of the most common emittance scanners. The article covers the description of the installation, the setup, the settings, the experiment and the benchmark of the…

Accelerator Physics · Physics 2023-01-25 F Osswald , T Durand , M Heine , J Michaud , F Poirier , J C Thomas , E Traykov

A novel method to image charge is used to measure the diffusion coefficient of electrons in films of CdSe nanocrystals at room temperature. This method makes possible the study of charge transport in films exhibiting high resistances or…

Mesoscale and Nanoscale Physics · Physics 2009-11-10 M. Drndic , R. Markov , M. V. Jarosz , M. G. Bawendi , M. A. Kastner , N. Markovic , M. Tinkham

Synchrotron emissivities, absorptivities, and Faraday rotation and conversion coefficients are needed in modeling a variety of astrophysical sources, including Event Horizon Telescope (EHT) sources. We develop a method for estimating…

High Energy Astrophysical Phenomena · Physics 2024-05-24 Monika Moscibrodzka , Charles F. Gammie

The role of 3He-3He collisions in our diffusion experiment is addressed and shown to not be relevant to the measurement of 3He diffusion against phonons in superfluid helium.

Materials Science · Physics 2009-11-13 S. K. Lamoreaux , R. Golub

The diffusion model is used to calculate the time-averaged flow of particles in stochastic media and the propagation of waves averaged over ensembles of disordered static configurations. For classical waves exciting static disordered…

Disordered Systems and Neural Networks · Physics 2024-01-11 Azriel Z. Genack , Yiming Huang , Asher Maor , Zhou Shi

Diffusion Models are probabilistic models that create realistic samples by simulating the diffusion process, gradually adding and removing noise from data. These models have gained popularity in domains such as image processing, speech…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Md Manjurul Ahsan , Shivakumar Raman , Yingtao Liu , Zahed Siddique