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Supernova remnants (SNRs) are believed to accelerate particles up to high energies through the mechanism of diffusive shock acceleration (DSA). Except for direct plasma simulations, all modeling efforts must rely on a given form of the…

High Energy Astrophysical Phenomena · Physics 2015-06-22 Gilles Ferrand , Rebecca J. Danos , Andreas Shalchi , Samar Safi-Harb , Paul Edmon , Peter Mendygral

In this paper we show the extension of the Nonlinear-Diffusion Acceleration (NDA) to geometries containing small voids using a weighted least-squares (WLS) high order equation. Even though the WLS equation is well defined in voids, the…

Computational Physics · Physics 2019-02-26 Hans Hammer , Jim Morel , Yaqi Wang

Aerial object detection is a challenging task, in which one major obstacle lies in the limitations of large-scale data collection and the long-tail distribution of certain classes. Synthetic data offers a promising solution, especially with…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Yanan Jian , Fuxun Yu , Simranjit Singh , Dimitrios Stamoulis

Shared autonomy is an enabling technology that provides users with control authority over robots that would otherwise be difficult if not impossible to directly control. Yet, standard methods make assumptions that limit their adoption in…

Robotics · Computer Science 2025-05-28 Luzhe Sun , Jingtian Ji , Xiangshan Tan , Matthew R. Walter

The Catani--Seymour dipole subtraction is a general and powerful procedure to calculate the QCD next-to-leading order corrections for collider observables. We clearly define a practical algorithm to use the dipole subtraction. The algorithm…

High Energy Physics - Phenomenology · Physics 2015-11-30 K. Hasegawa

The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system. The effects…

Neurons and Cognition · Quantitative Biology 2012-05-29 Patricio Orio , Daniel Soudry

A collision-based hybrid method for the discrete ordinates approximation of the multigroup neutron transport equation is developed for two-dimensional time-dependent problems. At each time step, this algorithm splits the neutron transport…

Computational Physics · Physics 2025-02-17 Ben Whewell , Ryan G. McClarren

Exploiting sparsity in deep neural networks (DNNs) has been a promising area for meeting the growing computation requirements. To minimize the overhead of sparse acceleration, hardware designers have proposed structured sparsity support,…

Machine Learning · Computer Science 2025-05-27 Geonhwa Jeong , Po-An Tsai , Abhimanyu R. Bambhaniya , Stephen W. Keckler , Tushar Krishna

Diffusion Transformers are fundamental for video and image generation, but their efficiency is bottlenecked by the quadratic complexity of attention. While block sparse attention accelerates computation by attending only critical key-value…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Haopeng Li , Shitong Shao , Wenliang Zhong , Zikai Zhou , Lichen Bai , Hui Xiong , Zeke Xie

In this paper, we propose a novel Dual Inexact Splitting Algorithm (DISA) for distributed convex composite optimization problems, where the local loss function consists of a smooth term and a possibly nonsmooth term composed with a linear…

Optimization and Control · Mathematics 2023-04-25 Luyao Guo , Xinli Shi , Shaofu Yang , Jinde Cao

In the hardware design space exploration process, it is critical to optimize both hardware parameters and algorithm-to-hardware mappings. Previous work has largely approached this simultaneous optimization problem by separately exploring…

Hardware Architecture · Computer Science 2025-09-16 Charles Hong , Qijing Huang , Grace Dinh , Mahesh Subedar , Yakun Sophia Shao

In this paper, we propose Dynamic Self-Attention (DSA), a new self-attention mechanism for sentence embedding. We design DSA by modifying dynamic routing in capsule network (Sabouretal.,2017) for natural language processing. DSA attends to…

Machine Learning · Computer Science 2018-08-23 Deunsol Yoon , Dongbok Lee , SangKeun Lee

Physics-based models often involve large systems of parametrized partial differential equations, where design parameters control various properties. However, high-fidelity simulations of such systems on large domains or with high grid…

Computational Physics · Physics 2025-05-15 Diba Behnoudfar

In this paper the simplified double-spherical harmonics SDPN, approximation of the neutron transport equation is proposed. The SDPN equations are derived from the multi-group DPN equations for N=1,2,3 (comparable to the SP3, SP5, and SP7…

Computational Physics · Physics 2023-10-31 M. Nazari , A. Zolfaghari , M. Abbasi

The neutrino mechanism of core-collapse supernova is investigated via non-relativistic, two-dimensional (2D), neutrino radiation-hydrodynamic simulations. For the transport of electron flavor neutrinos, we use the interaction rates defined…

High Energy Astrophysical Phenomena · Physics 2016-01-27 Kuo-Chuan Pan , Matthias Liebendörfer , Matthias Hempel , Friedrich-Karl Thielemann

The discrete-dipole approximation (DDA) is a flexible technique for computing scattering and absorption by targets of arbitrary geometry. In this paper we perform systematic study of various non-stationary iterative (conjugate gradient)…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Piotr J. Flatau

Computed Tomography (CT) is a widely used imaging modality in medical and industrial applications. To limit radiation exposure and measurement time, there is a growing interest in sparse-view CT, where the number of projection views is…

Image and Video Processing · Electrical Eng. & Systems 2026-05-04 Luis Barba , Johannes Kirschner , Benjamin Bejar

Solving the radiative transfer equation with the discrete ordinates (S$_N$) method leads to a non-physical imprint of the chosen quadrature set on the solution. To mitigate these so-called ray effects, we propose a modification of the S$_N$…

Numerical Analysis · Mathematics 2019-11-22 Martin Frank , Jonas Kusch , Thomas Camminady , Cory D. Hauck

Diffusion Transformers have become a dominant paradigm in visual generation, yet their low inference efficiency remains a key bottleneck hindering further advancement. Among common training-free techniques, caching offers high acceleration…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Tong Shao , Yusen Fu , Guoying Sun , Jingde Kong , Zhuotao Tian , Jingyong Su

We study a discrete denoising diffusion framework that integrates a sample-efficient estimator of single-site conditionals with round-robin noising and denoising dynamics for generative modeling over discrete state spaces. Rather than…

Machine Learning · Computer Science 2026-03-02 Karthik Elamvazhuthi , Abhijith Jayakumar , Andrey Y. Lokhov