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In high-energy heavy-ion collisions, propagation of the energy deposited into the medium by energetic partons that traverse the quark-gluon plasma (QGP) leads to Mach-cone-like jet-induced medium response. Full simulations of such…

Nuclear Theory · Physics 2026-05-19 Kai-Yi Wu , Zhong Yang , Long-Gang Pang , Xin-Nian Wang

The ductile-to-brittle transition (DBT) in body-centred cubic systems is a central design constraint for cryogenic structures. Performing parametric studies to enhance the understanding on DBT using fully coupled thermomechanical continuum…

Materials Science · Physics 2026-03-20 P G Kubendran Amos

The Bhatnagar-Gross-Krook (BGK) model of the Boltzmann equation allows for efficient flow simulations, especially in the transition regime between continuum and high rarefaction. However, ensuring efficient performances for multiscale…

Fluid Dynamics · Physics 2025-05-09 Félix Garmirian , Marcel Pfeiffer

The simulation of granular media is usually done either with event-driven codes that treat collisions as instantaneous but have difficulty with very dense packings, or with molecular dynamics methods that approximate rigid grains using a…

Materials Science · Physics 2015-05-27 Nicholas Guttenberg

Skeleton-based gait emotion recognition has received significant attention due to its wide-ranging applications. However, existing methods primarily focus on extracting spatial and local temporal motion information, failing to capture…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Junjie Zhou , Haijun Xiong , Junhao Lu , Ziyu Lin , Bin Feng

Two-fluid Braginskii codes have simulated open-field line turbulence for over a decade, and only recently has it become possible to study these systems with continuum gyrokinetic codes. This work presents a first-of-its-kind comparison…

We develop a new Gibbs sampler for a linear mixed model with a Dirichlet process random effect term, which is easily extended to a generalized linear mixed model with a probit link function. Our Gibbs sampler exploits the properties of the…

Statistics Theory · Mathematics 2010-02-26 Minjung Kyung , Jeff Gill , George Casella

Linear gyrokinetic simulations covering the collisional -- collisionless transitional regime of the tearing instability are performed. It is shown that the growth rate scaling with collisionality agrees well with that predicted by a…

Plasma Physics · Physics 2015-05-30 R. Numata , W. Dorland , G. G. Howes , N. F. Loureiro , B. N. Rogers , T. Tatsuno

This paper introduces a new simulation-based inference procedure to model and sample from multi-dimensional probability distributions given access to i.i.d.\ samples, circumventing the usual approaches of explicitly modeling the density…

Methodology · Statistics 2024-04-09 YoonHaeng Hur , Wenxuan Guo , Tengyuan Liang

Moment-based estimation is a theoretically attractive approach to parametric inference, especially when likelihood-based estimation is unavailable, misspecified, or computationally inconvenient. However, the moment equations involve sample…

Statistics Theory · Mathematics 2026-05-28 Liu Zhang , Amit Singer

We review the main results on the generalization of the DGLAP evolution equations within the cut Mellin moments (CMM) approach, which allows one to overcome the problem of kinematic constraints in Bjorken $x$. CMM obtained by multiple…

High Energy Physics - Phenomenology · Physics 2017-08-15 D. Kotlorz , S. V. Mikhailov , O. V. Teryaev , A. Kotlorz

A variant of consensus based distributed gradient descent (\textbf{DGD}) is studied for finite sums of smooth but possibly non-convex functions. In particular, the local gradient term in the fixed step-size iteration of each agent is…

Optimization and Control · Mathematics 2026-05-27 Lei Qin , Michael Cantoni , Ye Pu

Ion temperature gradient(ITG) and trapped electron modes(TEM) driven turbulent transport in an ITER-like plasma is investigated by means of multi-species gyrokinetic Vlasov simulations with D, T, He, and real-mass kinetic electrons…

Plasma Physics · Physics 2026-02-27 Motoki Nakata , Mitsuru Honda

Wave--current interaction (WCI) dynamics energizes and mixes the ocean thermocline by producing a combination of Langmuir circulation, internal waves and turbulent shear flows, which interact over a wide range of time scales. Two…

Fluid Dynamics · Physics 2019-09-04 Darryl D. Holm

Many commodity sensors that measure the robot and dynamic obstacle's state have non-Gaussian noise characteristics. Yet, many current approaches treat the underlying-uncertainty in motion and perception as Gaussian, primarily to ensure…

Robotics · Computer Science 2022-09-23 Anish Gupta , Arun Kumar Singh , K. Madhava Krishna

In this paper, we theoretically and numerically verify that the discontinuous Galerkin (DG) methods with central fluxes for linear hyperbolic equations on non-uniform meshes have sub-optimal convergence properties when measured in the…

Numerical Analysis · Mathematics 2020-03-03 Yong Liu , Chi-Wang Shu , Mengping Zhang

Geometric median (\textsc{Gm}) is a classical method in statistics for achieving a robust estimation of the uncorrupted data; under gross corruption, it achieves the optimal breakdown point of 0.5. However, its computational complexity…

Machine Learning · Computer Science 2021-06-17 Anish Acharya , Abolfazl Hashemi , Prateek Jain , Sujay Sanghavi , Inderjit S. Dhillon , Ufuk Topcu

We apply the collision-based hybrid introduced in \cite{hauck} to the Boltzmann equation with the BGK operator and a hyperbolic scaling. An implicit treatment of the source term is used to handle stiffness associated with the BGK operator.…

Numerical Analysis · Mathematics 2023-06-21 Minwoo Shin , Cory D. Hauck , Ryan G. McClarren

Simulating inhomogeneous flows with different characteristic scales in different coordinate directions using the collide-and-stream based lattice Boltzmann methods (LBM) can be accomplished efficiently using rectangular lattice grids. We…

Fluid Dynamics · Physics 2021-06-02 Eman Yahia , Kannan Premnath

In this study, we introduce a novel method for generating new synthetic samples that are independent and identically distributed (i.i.d.) from high-dimensional real-valued probability distributions, as defined implicitly by a set of Ground…

Machine Learning · Statistics 2024-07-09 Hamidreza Behjoo , Michael Chertkov
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