Tootfinder

Quantum Transport Protected by Acceleration From Nonadiabaticity and Dissipation
Arnab Chakrabarti, Biswarup Ash, Igor Mazets, Xi Chen, Gershon Kurizki
https://arxiv.org/abs/2506.21462

Quantum Transport Protected by Acceleration From Nonadiabaticity and Dissipation
We put forth a hitherto unexplored control strategy that enables high-fidelity fast transport of an unstable quantum wavepacket even in the presence of bath-induced dissipation. The wavepacket, which is confined within any shallow (anharmonic) potential trap is steered in acceleration, so as to maximize the transfer fidelity. This strategy can generally optimize any non-Markovian bath-dressed continuous-variable system dynamics. It can simultaneously cope with wavepacket leakage via non-adiabat…

Excitation of Giant Surface Waves During Laser Wake Field Acceleration
Travis Garrett, Christopher Pieronek, E. Rockafellow, Oliver Sale, Sahir Virani, J. E. Shrock, B. Miao, A. Sloss, Jennifer Elle, H. M. Milchberg
https://arxiv.org/abs/2506.21503

Excitation of Giant Surface Waves During Laser Wake Field Acceleration
We have detected the presence of very high intensity surface waves that are excited during plasma waveguided laser wakefield acceleration. Wakefield acceleration can be enchanced by the introduction of an ``all optical" plasma waveguide that confines and guides a laser pulse at the optimal intensity over long distances, producing quasimonoenergetic multi-GeV electron bunches. However strong pulses of radio frequency radiation (RF) are also produced, and particle in cell simulations show why: a …

Static Communication Analysis for Hardware Design
Mads Rosendahl (Roskilde University), Maja H. Kirkeby (Roskilde University)
https://arxiv.org/abs/2505.20849

Static Communication Analysis for Hardware Design
Hardware acceleration of algorithms is an effective method for improving performance in high-demand computational tasks. However, developing hardware designs for such acceleration fundamentally differs from software development, as it requires a deep understanding of the highly parallel nature of the hardware architecture. In this paper, we present a framework for the static analysis of communication within datapath architectures designed for field-programmable gate arrays (FPGAs). Our framewor…

from my link log —
HAFLANG: hardware acceleration of functional languages.
https://haflang.github.io/
saved 2025-03-22 https://dotat.at…

Global properties and stability of transonic plasma acceleration in the magnetic nozzle
N. Sheth, A. Smolyakov, J. Deguire, S. Pande, P. N. Yushmanov
https://arxiv.org/abs/2506.20880

Global properties and stability of transonic plasma acceleration in the magnetic nozzle
It is shown that transonic plasma acceleration in the converging-diverging magnetic field (magnetic nozzle) follows the unique global solution which is fully defined by the magnetic field. Such solution, which was analytically obtained earlier in the paraxial approximation, is compared here with results of the axisymmetric two-dimensional (rz) magnetohydrodynamics(MHD) simulations. It is shown that analytical solution describes well the region near the axis but also can be applied to arbitrary …

Evidence of Time-Dependent Diffusive Shock Acceleration in the 2022 September 5 Solar Energetic Particle Event
Xiaohang Chen, Lulu Zhao, Joe Giacalone, Nishtha Sachdeva, Igor Sokolov, Gabor Toth, Christina Cohen, David Lario, Fan Guo, Athanasios Kouloumvakos, Tamas Gombosi, Zhenguang Huang, Ward Manchester, Bart van der Holst, Weihao Liu, David McComas, Matthew Hill, George Ho

Evidence of Time-Dependent Diffusive Shock Acceleration in the 2022 September 5 Solar Energetic Particle Event
On 2022 September 5, a large solar energetic particle (SEP) event was detected by Parker Solar Probe (PSP) and Solar Orbiter (SolO), at heliocentric distances of 0.07 and 0.71 au, respectively. PSP observed an unusual velocity-dispersion signature: particles below $\sim$1 MeV exhibited a normal velocity dispersion, while higher-energy particles displayed an inverse velocity arrival feature, with the most energetic particles arriving later than those at lower energies. The maximum energy increas…

Speeding up Local Optimization in Vehicle Routing with Tensor-based GPU Acceleration
Zhenyu Lei, Jin-Kao Hao, Qinghua Wu
https://arxiv.org/abs/2506.17357 h…

Speeding up Local Optimization in Vehicle Routing with Tensor-based GPU Acceleration
Local search plays a central role in many effective heuristic algorithms for the vehicle routing problem (VRP) and its variants. However, neighborhood exploration is known to be computationally expensive and time consuming, especially for large instances or problems with complex constraints. In this study, we explore a promising direction to address this challenge by introducing an original tensor-based GPU acceleration method designed to speed up the commonly used local search operators in veh…

An Accretion Flare Interpretation for the UHE Neutrino Event KM3-230213A
Chengchao Yuan, Leonard Pfeiffer, Walter Winter, Sara Buson, Federico Testagrossa, Jose Maria Sanchez Zaballa, Alessandra Azzollini
https://arxiv.org/abs/2506.21111

An Accretion Flare Interpretation for the UHE Neutrino Event KM3-230213A
We study the origin of the ultra-high-energy (UHE) astrophysical neutrino event KM3-230213A detected by KM3NeT, focusing on MRC 0614-083 which has been pinpointed as the closest blazar to the neutrino localization. A joint interpretation of the optical, infrared, and X-ray light curves suggests that MRC 0614-083 has undergone a super-Eddington accretion flare accompanied by efficient proton acceleration. That flare has initiated a delayed infrared echo within the surrounding dust torus, which s…

Learning Accurate Whole-body Throwing with High-frequency Residual Policy and Pullback Tube Acceleration
Yuntao Ma, Yang Liu, Kaixian Qu, Marco Hutter
https://arxiv.org/abs/2506.16986

Learning Accurate Whole-body Throwing with High-frequency Residual Policy and Pullback Tube Acceleration
Throwing is a fundamental skill that enables robots to manipulate objects in ways that extend beyond the reach of their arms. We present a control framework that combines learning and model-based control for prehensile whole-body throwing with legged mobile manipulators. Our framework consists of three components: a nominal tracking policy for the end-effector, a high-frequency residual policy to enhance tracking accuracy, and an optimization-based module to improve end-effector acceleration co…

Enhanced quantum sensing of gravitational acceleration constant
Giorgio Stucchi, Matteo G. A. Paris
https://arxiv.org/abs/2506.20352 https://

Enhanced quantum sensing of gravitational acceleration constant
We investigate the use of quantum probes to accurately determine the strength of the local gravitational field on Earth. Our findings show that delocalized probes generally outperform localized ones, with the precision enhancement scaling quadratically with the separation between the two wavefunction components. This advantage persists under realistic position measurements, which can achieve precision not too far from the ultimate bound. We also discuss the influence of Earth's surface, demonst…

Physics Of Eclipsing Binaries. IX. Spectroscopic module
Miroslav Bro\v{z}, Andrej Pr\v{s}a, Kyle E. Conroy, Michael Abdul-Masih
https://arxiv.org/abs/2506.20868

Physics Of Eclipsing Binaries. IX. Spectroscopic module
Spectroscopic observations constrain the fundamental properties of stellar atmospheres, in particular, the effective temperature, the gravitational acceleration, or the metallicity. In this work, we describe the spectroscopic module for Phoebe, which allows for modelling of spectra, either normalized, or in absolute units (${\rm W}\,{\rm m}^{-2}\,{\rm m}^{-1}$). The module is based on extensive grids of synthetic spectra, taken from literature, which are interpolated and integrated over the sur…

Scattering and Chirping at Accelerated Interfaces
Klaas De Kinder, Amir Bahrami, Christophe Caloz
https://arxiv.org/abs/2506.19575 https://

Scattering and Chirping at Accelerated Interfaces
Space-time varying media with moving interfaces unlock new ways to manipulate electromagnetic waves. Yet, analytical solutions have been mostly limited to interfaces moving at constant velocity or constant proper acceleration. Here, we present exact scattering solutions for an arbitrarily accelerating interface, derived directly in the laboratory frame through a suitable change of variables. We show that acceleration introduces rich effects that do not occur with uniform motion, including trans…

Particle Injection Problem in Magnetic Reconnection and Turbulence
Fan Guo, Omar French, Qile Zhang, Xiaocan Li, Jeongbhin Seo
https://arxiv.org/abs/2506.19938

Particle Injection Problem in Magnetic Reconnection and Turbulence
Magnetic reconnection and turbulence in magnetically-dominated environments have been proposed as important nonthermal particle acceleration mechanisms that generate high energy particles and associated emissions. While the acceleration to high energy that produces the power-law energy distribution has drawn strong interest, recent studies actively discuss pre-acceleration, or injection, to a sufficient energy for a sustained and prolonged Fermi-like acceleration. The injection process is impor…

Laser Wakefield Acceleration Driven by a Discrete Flying Focus
Jacob R. Pierce, Kyle G. Miller, Fei Li, John P. Palastro, Warren B. Mori
https://arxiv.org/abs/2506.19824

Laser Wakefield Acceleration Driven by a Discrete Flying Focus
Laser wakefield acceleration (LWFA) may enable the next generation of TeV-scale lepton colliders. Reaching such energies will likely require multiple LWFA stages to overcome limitations on the energy gain achievable in a single stage. The use of stages, however, introduces challenges such as alignment, adiabatic matching between stages, and a lower average accelerating gradient. Here, we propose a discrete flying focus that can deliver higher energy gain in a single stage, thereby reducing the …

Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
Chao Li, Jiawei Fan, Anbang Yao
https://arxiv.org/abs/2506.18251 https://

Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
In this paper, we present Morse, a simple dual-sampling framework for accelerating diffusion models losslessly. The key insight of Morse is to reformulate the iterative generation (from noise to data) process via taking advantage of fast jump sampling and adaptive residual feedback strategies. Specifically, Morse involves two models called Dash and Dot that interact with each other. The Dash model is just the pre-trained diffusion model of any type, but operates in a jump sampling regime, creat…

On the local thermodynamic relations in relativistic spin hydrodynamics
Francesco Becattini, Rajeev Singh
https://arxiv.org/abs/2506.20681 https://

On the local thermodynamic relations in relativistic spin hydrodynamics
We demonstrate, by providing two specific examples, that the local differential thermodynamic relations used as educated guesses in relativistic hydrodynamics with spin, do not hold even at global thermodynamic equilibrium, where the expression of the entropy current is totally unambiguous. We show, by using a rigorous quantum statistical method, that for massless free fermions and massive free fermions with rotation and acceleration at global thermodynamic equilibrium, the derivative of the pr…

Electromagnetic and Centrifugal Effects on Plasma Acceleration in the Magnetic Nozzle
A. I. Smolyakov, A. Sabo, S. I. Krasheninnikov, P. N. Yushmanov
https://arxiv.org/abs/2506.19647

Electromagnetic and Centrifugal Effects on Plasma Acceleration in the Magnetic Nozzle
Plasma flow and acceleration in the converging-diverging magnetic field configuration, such as magnetic nozzle in electric propulsion and open magnetic mirrors for fusion applications are considered. This work analyses plasma acceleration in the magnetic nozzle with an emphasis on the electromagnetic effects and centrifugal forces due to plasma rotation. Intrinsic coupling of the azimuthal rotation and azimuthal magnetic field is analyzed, and additional plasma acceleration due to the conversio…

Adaptive Acceleration Without Strong Convexity Priors Or Restarts
Joao V. Cavalcanti, Laurent Lessard, Ashia C. Wilson
https://arxiv.org/abs/2506.13033 htt…

Adaptive Acceleration Without Strong Convexity Priors Or Restarts
Accelerated optimization methods are typically parametrized by the Lipschitz smoothness and strong convexity parameters of a given problem, which are rarely known in practice. While the Lipschitz smoothness parameter L can be easily estimated by backtracking, directly estimating (i.e., without restarts) the strong convexity parameter m remains an open problem. This paper addresses this challenge by proposing NAG-free, an optimization method that achieves acceleration while estimating m online w…

Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference
Muhammad Ihsan Al Hafiz, Naresh Ravichandran, Anders Lansner, Pawel Herman, Artur Podobas
https://arxiv.org/abs/2506.18530

Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference
Edge AI applications increasingly require models that can learn and adapt on-device with minimal energy budget. Traditional deep learning models, while powerful, are often overparameterized, energy-hungry, and dependent on cloud connectivity. Brain-Like Neural Networks (BLNNs), such as the Bayesian Confidence Propagation Neural Network (BCPNN), propose a neuromorphic alternative by mimicking cortical architecture and biologically-constrained learning. They offer sparse architectures with local …

Acceleration of Lagrangian Particles in Shell Models of Turbulence
Lorenzo Piro, Massimo Cencini, Roberto Benzi
https://arxiv.org/abs/2506.09633 https://…

Acceleration of Lagrangian Particles in Shell Models of Turbulence
Lagrangian acceleration has been investigated both experimentally and numerically in the past, and it has been shown to exhibit extreme fluctuations, which have been rationalized as events in which tracer particles get trapped into vortical structures such as vortex tubes or filaments. Here, we consider the statistics of acceleration within the multifractal framework, as in Biferale et al. Phys. Rev. Lett. 93 064502 (2004), and investigate the statistics of Lagrangian acceleration using shell m…

Heise Online reports about a Chinese maglev train prototype (or laboratory experiment) that accelerates from zero to 650 km/h in seven seconds. Yay. Except that this is completely useless performance for passenger transport. That means almost 3g acceleration.

Electron Acceleration via Trapping inside Ion Mirror-mode Structures within A Large-scale Magnetic Flux Rope
Z. H. Zhong, H. Zhang, M. Zhou, D. B. Graham, R. X. Tang, X. H. Deng, Yu. V. Khotyaintsev
https://arxiv.org/abs/2506.09754

Electron Acceleration via Trapping inside Ion Mirror-mode Structures within A Large-scale Magnetic Flux Rope
Fermi acceleration is believed as a crucial process for the acceleration of energetic electrons within flux ropes (FRs) during magnetic reconnection. However, in finite-length FRs with a large core field, the finite contracting and the escaping of electrons along the axis can significantly limit the efficiency of Fermi acceleration. Using observations from the Magnetospheric Multiscale mission in the magnetotail, we demonstrate that magnetic mirror structures inside the FR can effectively preve…

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
Junli Shao, Jing Dong, Dingzhou Wang, Kowei Shih, Dannier Li, Chengrui Zhou
https://arxiv.org/abs/2506.11421

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems
With the rapid growth of Internet services, recommendation systems play a central role in delivering personalized content. Faced with massive user requests and complex model architectures, the key challenge for real-time recommendation systems is how to reduce inference latency and increase system throughput without sacrificing recommendation quality. This paper addresses the high computational cost and resource bottlenecks of deep learning models in real-time settings by proposing a combined s…

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
Chao Li, Jiawei Fan, Anbang Yao

Starting to think about GPU acceleration of protocol decodes (rather than just basic math blocks) in ngscopeclient.
Here's the filter graph I'm thinking of using as a benchmark: dual lane QSGMII, 20M points per channel.
The filter graph takes 944 ms end to end to run on my box (2x Xeon 6144 2080 Ti).
Major time consumers:
* Eye pattern (~345 ms)
* QSGMII (~337 ms)
* CDR PLL (~310 ms)
* 8B10B (~160 ms)
* SGMII (~120 ms)
Note that the …

The Hyperbolic Tangent as an Educational Tool for Teaching Variable Acceleration
Scott C. Scharlach
https://arxiv.org/abs/2505.11658 https://

The Hyperbolic Tangent as an Educational Tool for Teaching Variable Acceleration
This paper presents an approximate analytical solution to the Falling Astronaut Problem by means of the hyperbolic tangent, and it explores the educational opportunities presented by this technique. The author's previous paper presented a function for time in terms of position t(x) that modeled the motion of an astronaut as she falls from an arbitrary height to the surface of a spherical planet with no air resistance, but an exact analytical function for position in terms of time x(t) was not f…

RETENTION: Resource-Efficient Tree-Based Ensemble Model Acceleration with Content-Addressable Memory
Yi-Chun Liao, Chieh-Lin Tsai, Yuan-Hao Chang, Cam\'elia Slimani, Jalil Boukhobza, Tei-Wei Kuo
https://arxiv.org/abs/2506.05994

RETENTION: Resource-Efficient Tree-Based Ensemble Model Acceleration with Content-Addressable Memory
Although deep learning has demonstrated remarkable capabilities in learning from unstructured data, modern tree-based ensemble models remain superior in extracting relevant information and learning from structured datasets. While several efforts have been made to accelerate tree-based models, the inherent characteristics of the models pose significant challenges for conventional accelerators. Recent research leveraging content-addressable memory (CAM) offers a promising solution for acceleratin…

This https://arxiv.org/abs/2506.05096 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Astraea: A GPU-Oriented Token-wise Acceleration Framework for Video Diffusion Transformers
Video diffusion transformers (vDiTs) have made impressive progress in text-to-video generation, but their high computational demands present major challenges for practical deployment. While existing acceleration methods reduce workload at various granularities, they often rely on heuristics, limiting their applicability. We introduce ASTRAEA, an automatic framework that searches for near-optimal configurations for vDiT-based video generation. At its core, ASTRAEA proposes a lightweight token …

From NLVO to NAO: Reactive Robot Navigation using Velocity and Acceleration Obstacles
Asher Stern, Zvi Shiller
https://arxiv.org/abs/2506.06255 https://

From NLVO to NAO: Reactive Robot Navigation using Velocity and Acceleration Obstacles
This paper introduces a novel approach for robot navigation in challenging dynamic environments. The proposed method builds upon the concept of Velocity Obstacles (VO) that was later extended to Nonlinear Velocity Obstacles (NLVO) to account for obstacles moving along nonlinear trajectories. The NLVO is extended in this paper to Acceleration Obstacles (AO) and Nonlinear Acceleration Obstacles (NAO) that account for velocity and acceleration constraints. Multi-robot navigation is achieved by usi…

GPU Acceleration of SQL Analytics on Compressed Data
Zezhou Huang, Krystian Sakowski, Hans Lehnert, Wei Cui, Carlo Curino, Matteo Interlandi, Marius Dumitru, Rathijit Sen
https://arxiv.org/abs/2506.10092

GPU Acceleration of SQL Analytics on Compressed Data
GPUs are uniquely suited to accelerate (SQL) analytics workloads thanks to their massive compute parallelism and High Bandwidth Memory (HBM) -- when datasets fit in the GPU HBM, performance is unparalleled. Unfortunately, GPU HBMs remain typically small when compared with lower-bandwidth CPU main memory. Besides brute-force scaling across many GPUs, current solutions to accelerate queries on large datasets include leveraging data partitioning and loading smaller data batches in GPU HBM, and hyb…

Replaced article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- Assessing Tenstorrent's RISC-V MatMul Acceleration Capabilities
Hiari Pizzini Cavagna, Daniele Cesarini, Andrea Bartolini

Acceleration via silver step-size on Riemannian manifolds with applications to Wasserstein space
Jiyoung Park, Abhishek Roy, Jonathan W. Siegel, Anirban Bhattacharya
https://arxiv.org/abs/2506.06160

Acceleration via silver step-size on Riemannian manifolds with applications to Wasserstein space
There is extensive literature on accelerating first-order optimization methods in a Euclidean setting. Under which conditions such acceleration is feasible in Riemannian optimization problems is an active area of research. Motivated by the recent success of varying step-size methods in the Euclidean setting, we undertake a study of such algorithms in the Riemannian setting. We show that varying step-size acceleration can be achieved in non-negatively curved Riemannian manifolds under geodesic s…

Particle-in-cell simulations of plasma wakefield formation in microwave waveguides
Jes\'us E. L\'opez, Eduardo A. Orozco
https://arxiv.org/abs/2506.17752

Particle-in-cell simulations of plasma wakefield formation in microwave waveguides
The acceleration of charged particles is fundamental not only for experimental studies in particle physics but also for applications in fields such as semiconductor manufacturing and medical therapies. However, conventional accelerators face limitations due to their large size, driven by low acceleration gradients. Plasma-based accelerators have emerged as a promising alternative, offering ultrahigh acceleration gradients, though their implementation is often limited by the need for high-intens…

Studying mirror acceleration via kinetic simulations of relativistic plasma turbulence
Saikat Das, Siyao Xu, Joonas N\"attil\"a
https://arxiv.org/abs/2506.04212

Studying mirror acceleration via kinetic simulations of relativistic plasma turbulence
Efficient turbulent acceleration of particles is indicated by recent astrophysical observations, but its mechanism is not well understood. Mirror acceleration has recently been proposed as an efficient mechanism for particle energization in turbulence-compressed magnetic fields. We employ a 3D particle-in-cell (PIC) simulation of pair plasma in magnetized and relativistic turbulence to study this new mechanism and its acceleration efficiency. By tracking individual particles, we see that revers…

Numerical investigations of heavy ion driven plasma wakefield acceleration
Jiangdong Li, Jiancheng Yang, Guoxing Xia, Jie Liu, Wenlong Zhan, Ruihu Zhu
https://arxiv.org/abs/2506.14132

Numerical investigations of heavy ion driven plasma wakefield acceleration
Plasma-Based Acceleration (PBA) has emerged as a promising approach to achieve ultra-high gradient particle acceleration. While extensive PBA studies have been conducted using laser, electron, and proton drivers, significant challenges remain in achieving high efficiency, stable acceleration, and scalable energy gain. Meanwhile, due to their higher beam charge density, heavier particle mass and higher kinetic energy, heavy-ion beam drivers represent an interesting direction in PBA research. In …

This https://arxiv.org/abs/2410.23818 has been replaced.
initial toot: https://mastoxiv.page/@…

Acceleration-induced transport of quantum vortices in joined atomtronic circuits
Persistent currents--inviscid quantized flow around an atomic circuit--are a crucial building block of atomtronic devices. We investigate how acceleration influences the transfer of persistent currents between two density-connected, ring-shaped atomic Bose-Einstein condensates, joined by a tunable weak link that controls system topology. We find that the acceleration of this system modifies both the density and phase dynamics between the rings, leading to a bias in the periodic vortex oscillati…

Extended datasamples under the lens of Brane World Theory
Kyra Jacobo, Dorian Araya
https://arxiv.org/abs/2506.15002 https://arxiv.or…

Extended datasamples under the lens of Brane World Theory
This work revises the Brane World Theory known as Randall-Sundrum with the modification of an exponential, redshift-dependent brane tension. This model is studied in a scenario assuming no dark energy, with the aim of determining whether it can reproduce the universe's acceleration on its own, without the addition of a dark energy fluid. Bayesian statistical analysis is performed in order to constrain the free parameters of each scenario using SLS, SNIa, OHD, and BAO data samples, the last two …

250 Magnetic Tunnel Junctions-Based Probabilistic Ising Machine
Shuhan Yang, Andrea Grimaldi, Youwei Bao, Eleonora Raimondo, Jia Si, Giovanni Finocchio, Hyunsoo Yang
https://arxiv.org/abs/2506.14590

250 Magnetic Tunnel Junctions-Based Probabilistic Ising Machine
In combinatorial optimization, probabilistic Ising machines (PIMs) have gained significant attention for their acceleration of Monte Carlo sampling with the potential to reduce time-to-solution in finding approximate ground states. However, to be viable in real applications, further improvements in scalability and energy efficiency are necessary. One of the promising paths toward achieving this objective is the development of a co-design approach combining different technology layers including …

Replaced article(s) found for math.NA. https://arxiv.org/list/math.NA/new
[1/1]:
Generalized Gearhart-Koshy acceleration is a Krylov subspace method

From Explicit Diffeomorphism Breaking to Spontaneous Unimodularization
Yuri Bonder, Johas D. Morales
https://arxiv.org/abs/2506.12499 https://

From Explicit Diffeomorphism Breaking to Spontaneous Unimodularization
This contribution investigates modifications of General Relativity that allow or mimic energy nonconservation. We focus on Unimodular Gravity (UG), a theory that explicitly breaks diffeomorphism invariance, and show that it can lead to particle acceleration, opening the door to experimental constraints. We also argue that UG admits a well-posed initial value formulation, despite the presence of nondynamical structures. Finally, we introduce a simple model that spontaneously mimics UG, but in wh…

Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
Filippo Marostica, Alessio Carpegna, Alessandro Savino, Stefano Di Carlo
https://arxiv.org/abs/2506.13268

Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
This paper presents a comprehensive evaluation of Spiking Neural Network (SNN) neuron models for hardware acceleration by comparing event driven and clock-driven implementations. We begin our investigation in software, rapidly prototyping and testing various SNN models based on different variants of the Leaky Integrate and Fire (LIF) neuron across multiple datasets. This phase enables controlled performance assessment and informs design refinement. Our subsequent hardware phase, implemented on …

Multi-GPU Acceleration of PALABOS Fluid Solver using C Standard Parallelism
Jonas Latt, Christophe Coreixas
https://arxiv.org/abs/2506.09242 https://

Multi-GPU Acceleration of PALABOS Fluid Solver using C++ Standard Parallelism
This article presents the principles, software architecture, and performance analysis of the GPU port of the lattice Boltzmann software library Palabos (J. Latt et al., "Palabos: Parallel lattice Boltzmann solver", Comput. Math. Appl. 81, 334-350, (2021)). A hybrid CPU-GPU execution model is adopted, in which numerical components are selectively assigned to either the CPU or the GPU, depending on considerations of performance or convenience. This design enables a progressive porting strategy, a…

In the end, the Iranian Military's statement sounds at least to me like this is a one-and-done retaliation on USA assets. Nothing further unless there is “repetition”?
"Any repetition of U.S. aggression will lead to the acceleration of the collapse of the U.S. military pillars in the region, their ignominious escape from West Asia, and the realization of the common aspiration of the Islamic Ummah and the freedom-loving nations of the world in eradicating the cancerous tumor of Zion.’”
#Iran #USA #Israel #IsraelIranWar #MiddleEast

Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model
Anirud Aggarwal, Abhinav Shrivastava, Matthew Gwilliam
https://arxiv.org/abs/2506.15682

Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model
Diffusion-based image generation models excel at producing high-quality synthetic content, but suffer from slow and computationally expensive inference. Prior work has attempted to mitigate this by caching and reusing features within diffusion transformers across inference steps. These methods, however, often rely on rigid heuristics that result in limited acceleration or poor generalization across architectures. We propose Evolutionary Caching to Accelerate Diffusion models (ECAD), a genetic a…

Late-Time Cosmic Acceleration from QCD Confinement Dynamics
Jonathan Rinc\'on, Humberto Mart\'inez-Huerta, Adolfo Huet, Alberto Hern\'andez-Almada, Miguel A. Garc\'ia-Aspeitia
https://arxiv.org/abs/2506.13812

Late-Time Cosmic Acceleration from QCD Confinement Dynamics
We explore a phenomenological extension of the Polyakov-Nambu-Jona-Lasinio (PNJL) model by introducing a coupling between the Polyakov loop potential and the Hubble parameter $H(t)$, inspired by the hypothesis that the QCD vacuum, particularly in the confined phase, may be sensitive to the large-scale dynamics of the universe. The coupling term, proportional to $(H(t)/H_0)^d f(Φ)$, vanishes in the deconfined regime and acts as a dynamical dark energy contribution at late times, without invokin…

MARS: Processing-In-Memory Acceleration of Raw Signal Genome Analysis Inside the Storage Subsystem
Melina Soysal, Konstantina Koliogeorgi, Can Firtina, Nika Mansouri Ghiasi, Rakesh Nadig, Haiyu Mayo, Geraldo F. Oliveira, Yu Liang, Klea Zambaku, Mohammad Sadrosadati, Onur Mutlu
https://arxiv.org/abs/2506.10931

MARS: Processing-In-Memory Acceleration of Raw Signal Genome Analysis Inside the Storage Subsystem
Raw signal genome analysis (RSGA) has emerged as a promising approach to enable real-time genome analysis by directly analyzing raw electrical signals. However, rapid advancements in sequencing technologies make it increasingly difficult for software-based RSGA to match the throughput of raw signal generation. This paper demonstrates that while hardware acceleration techniques can significantly accelerate RSGA, the high volume of genomic data shifts the performance and energy bottleneck from co…

Replaced article(s) found for cs.ET. https://arxiv.org/list/cs.ET/new
[1/1]:
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning

Speed-dependent Threshold for Electron Injection into Diffusive Shock Acceleration
Siddhartha Gupta, Damiano Caprioli, Anatoly Spitkovsky
https://arxiv.org/abs/2506.09134

Speed-dependent Threshold for Electron Injection into Diffusive Shock Acceleration
Finding the injection threshold for diffusive shock acceleration (DSA) of electrons in collisionless shocks has been a longstanding unsolved problem. Using first-principles kinetic simulations, we identify the conditions for electron injection into DSA and quantify the evolution of the nonthermal tail in self-generated electromagnetic turbulence. By analyzing electron trajectories and their momentum gain during shock-recrossing cycles, we demonstrate that electrons start participating in DSA wh…

Observation of laser plasma accelerated electrons with transverse momentum spread below the thermal level
T. L. Steyn, A. Panchal, O. Vasilovici, S. Sch\"obel, P. Ufer, F. M. Herrmann, Y. -Y. Chang, I. Moulanier, M. Masckala, O. Khomyshyn, C. Ballage, M. LaBerge, F. Massimo, S. Dobosz Dufr\'enoy, U. Schramm, A. Irman, B. Cros
https://…

Observation of laser plasma accelerated electrons with transverse momentum spread below the thermal level
Achieving high-quality electron beams from laser-plasma accelerators critically relies on density tailoring to control electron dynamics during injection, acceleration, and extraction. We report on the experimental observation of electron beam acceleration and 3D shaping, in transverse momentum and longitudinal phase space, controlled by plasma density tailoring in a gas cell. It leads to relativistic electron beams with a transverse momentum spread of 0.2 mec, below the thermal level imprinted…

The SPARTA project: toward a demonstrator facility for multistage plasma acceleration
C. A. Lindstr{\o}m, E. Adli, H. B. Anderson, P. Drobniak, D. Kalvik, F. Pe\~na, K. N. Sjobak
https://arxiv.org/abs/2505.14493

The SPARTA project: toward a demonstrator facility for multistage plasma acceleration
Plasma accelerators promise greatly reduced size and cost for future particle-accelerator facilities. However, several challenges remain to be solved; in particular that of coupling beams between plasma stages (i.e., staging) without beam-quality degradation, and that of ensuring a stable acceleration process. In order to mature the technology, it is also key to identify an application that requires staging and high stability but is not overly challenging in other parameters such as energy effi…

Implicit Neural Representation-Based MRI Reconstruction Method with Sensitivity Map Constraints
Lixuan Rao, Xinlin Zhang, Yiman Huang, Tao Tan, Tong Tong
https://arxiv.org/abs/2506.06043

Implicit Neural Representation-Based MRI Reconstruction Method with Sensitivity Map Constraints
Magnetic Resonance Imaging (MRI) is a widely utilized diagnostic tool in clinical settings, but its application is limited by the relatively long acquisition time. As a result, fast MRI reconstruction has become a significant area of research. In recent years, Implicit Neural Representation (INR), as a scan-specific method, has demonstrated outstanding performance in fast MRI reconstruction without fully-sampled images for training. High acceleration reconstruction poses a challenging problem, …

Torsion Balance Experiments Enable Direct Detection of Sub-eV Dark Matter
Shigeki Matsumoto, Jie Sheng, Chuan-Yang Xing, Lin Zhu
https://arxiv.org/abs/2506.07763

Torsion Balance Experiments Enable Direct Detection of Sub-eV Dark Matter
Light dark matter with sub-eV masses has a high number density in our galaxy, and its scattering cross section with macroscopic objects can be significantly enhanced by coherence effects. Repeated scattering with a target object can induce a measurable acceleration. Torsion balance experiments with geometric asymmetry are, in principle, capable of detecting such signals. Our analysis shows that existing torsion balances designed to test the Equivalence Principle already place the most stringent…

Towards Employing FPGA and ASIP Acceleration to Enable Onboard AI/ML in Space Applications
Vasileios Leon, George Lentaris, Dimitrios Soudris, Simon Vellas, Mathieu Bernou
https://arxiv.org/abs/2506.12970

Towards Employing FPGA and ASIP Acceleration to Enable Onboard AI/ML in Space Applications
The success of AI/ML in terrestrial applications and the commercialization of space are now paving the way for the advent of AI/ML in satellites. However, the limited processing power of classical onboard processors drives the community towards extending the use of FPGAs in space with both rad-hard and Commercial-Off-The-Shelf devices. The increased performance of FPGAs can be complemented with VPU or TPU ASIP co-processors to further facilitate high-level AI development and in-flight reconfigu…

Electric field measurements made in space
Forrest Mozer, Oleksiy Agapitov
https://arxiv.org/abs/2505.14979 https://arxiv.org/pdf/2505…

Electric field measurements made in space
The operating principles of a DC and low frequency electric field detector are developed, after which, examples of earlier important electric field measurements are presented, including, the first observation of parallel electric fields in the auroral acceleration region, the first observation of time domain structures in space, the first experimental verification of symmetric magnetic field reconnection, the first observations of triggered ion acoustic waves, and oblique whistlers that directl…

Reuse or Generate? Accelerating Code Editing via Edit-Oriented Speculative Decoding
Peiding Wang, Li Zhang, Fang Liu, Yinghao Zhu, Wang Xu, Lin Shi, Xiaoli Lian, Minxiao Li, Bo Shen, An Fu
https://arxiv.org/abs/2506.02780

Reuse or Generate? Accelerating Code Editing via Edit-Oriented Speculative Decoding
Large Language Models (LLMs) have demonstrated remarkable capabilities in code editing, substantially enhancing software development productivity. However, the inherent complexity of code editing tasks forces existing approaches to rely on LLMs' autoregressive end-to-end generation, where decoding speed plays a critical role in efficiency. While inference acceleration techniques like speculative decoding are applied to improve the decoding efficiency, these methods fail to account for the uniqu…

Risks of AI-driven product development and strategies for their mitigation
Jan G\"opfert, Jann M. Weinand, Patrick Kuckertz, Noah Pflugradt, Jochen Lin{\ss}en
https://arxiv.org/abs/2506.00047

Risks of AI-driven product development and strategies for their mitigation
Humanity is progressing towards automated product development, a trend that promises faster creation of better products and thus the acceleration of technological progress. However, increasing reliance on non-human agents for this process introduces many risks. This perspective aims to initiate a discussion on these risks and appropriate mitigation strategies. To this end, we outline a set of principles for safer AI-driven product development which emphasize human oversight, accountability, and…

Multi-cloud crushing -- the collective survival of cold clouds in galactic outflows
Benedikt S. Seidl, Max Gronke, Ryan Jeffrey Farber, Klaus Dolag
https://arxiv.org/abs/2506.05448

Multi-cloud crushing -- the collective survival of cold clouds in galactic outflows
The ram-pressure acceleration of cold gas by hot outflows plays a crucial role in the dynamics of multiphase galactic winds. Recent numerical studies incorporating radiative cooling have identified a size threshold for idealized cold clouds to survive within high-velocity outflows. This study extends the investigation to a more complex morphology of cold gas as observed in the interstellar medium. We conduct three-dimensional hydrodynamic simulations of ensembles of individual spherical clouds …

An atom in front of Lorentz violating Kalb-Ramond black hole background
Anisur Rahaman
https://arxiv.org/abs/2506.01006 https://arxiv…

An atom in front of Lorentz violating Kalb-Ramond black hole background
We investigate the role of Lorentz violation in the acceleration radiation produced when an atom falls into a Kalb-Ramond (KR) black hole and observe that the amplitude and an exponential (Planck-like) factor are both shaped by the Lorentz-violating parameter, indicating a breach of the equivalence principle and resembling characteristics observed in bumblebee gravity models. We further investigate how Lorentz violation and conformal symmetry work together to determine the thermodyn…

Machine Learning Acceleration of Neutron Star Pulse Profile Modeling
Preston G. Waldrop, Dimitrios Psaltis, Tong Zhao
https://arxiv.org/abs/2506.11194 http…

Machine Learning Acceleration of Neutron Star Pulse Profile Modeling
Ray tracing algorithms that compute pulse profiles from rotating neutron stars are essential tools for constraining neutron-star properties with data from missions such as NICER. However, the high computational cost of these simulations presents a significant bottleneck for inference algorithms that require millions of evaluations, such as Markov Chain Monte Carlo methods. In this work, we develop a residual neural network model that accelerates this calculation by predicting the observed flux …

Simple quintessence models in light of DESI-BAO observations
James M. Cline, Varun Muralidharan
https://arxiv.org/abs/2506.13047 https://

Simple quintessence models in light of DESI-BAO observations
Recent analyses from the DESI collaboration suggest that the dark energy density of the Universe may be decreasing with time, slowing the acceleration of the scale factor $a$. Typically these studies are performed assuming an ansatz for the equation of state $w(a)$. In this work, we instead consider simple models of a scalar quintessence potential with linear and quadratic behavior, which could be more representative of real models than particular parametrizations of $w(a)$. We observe a signif…

Replaced article(s) found for math.NA. https://arxiv.org/list/math.NA/new
[1/1]:
Rejuvenating AMLI-Cycle: From Chebyshev Polynomials to Momentum Acceleration

Energy budget in the 2017-09-07 "cold" solar flare
Gregory D. Fleishman, Galina G. Motorina, Sijie Yu, Gelu M. Nita
https://arxiv.org/abs/2506.15501

Energy budget in the 2017-09-07 "cold" solar flare
A subclass of early impulsive solar flares, cold flares, was proposed to represent a clean case, where the release of the free magnetic energy (almost) entirely goes to acceleration of the nonthermal electrons, while the observed thermal response is entirely driven by the nonthermal energy deposition to the ambient plasma. This paper studies one more example of a cold flare, which was observed by a unique combination of instruments. In particular, this is the first cold flare observed with the …

Phase space and Data analyses of a non-minimally coupled scalar field system with decaying dark energy model
Yerlan Myrzakulov, Saddam Hussain, M. Shahalam
https://arxiv.org/abs/2506.11755

Phase space and Data analyses of a non-minimally coupled scalar field system with decaying dark energy model
We investigate a class of scalar field dark energy models non-minimally coupled to gravity, characterized by a double exponential potential and parameterized coupling ξ. First, we study the cosmological dynamics for a recently proposed Q-SC-CDM model. Initially, we choose two distinct values of ξ: 0.1 and 0.5. In case of ξ=0.1, the evolution of the universe is split up into three different phases: deceleration, acceleration and slow-contraction, and provide Big Crunch Singularity at distant …

This https://arxiv.org/abs/2505.21036 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

RainFusion: Adaptive Video Generation Acceleration via Multi-Dimensional Visual Redundancy
Video generation using diffusion models is highly computationally intensive, with 3D attention in Diffusion Transformer (DiT) models accounting for over 80\% of the total computational resources. In this work, we introduce {\bf RainFusion}, a novel training-free sparse attention method that exploits inherent sparsity nature in visual data to accelerate attention computation while preserving video quality. Specifically, we identify three unique sparse patterns in video generation attention calcu…

An analytical optimization of plasma density profiles for downramp injection in laser wake-field acceleration
Gaetano Fiore, Paolo Tomassini
https://arxiv.org/abs/2506.06814

An analytical optimization of plasma density profiles for downramp injection in laser wake-field acceleration
We propose and detail a multi-step analytical procedure, based on an improved fully relativistic plane model for Laser Wake Field Acceleration, to tailor the initial density of a cold diluted plasma to the laser pulse profile, so as to control and optimize the partial wave-breaking of the plasma wave and maximize the acceleration of small bunches of electrons self-injected by the first wave-breaking at the density down-ramp, at least in the first stages of their acceleration phase. We find an e…

Towards Zero-Stall Matrix Multiplication on Energy-Efficient RISC-V Clusters for Machine Learning Acceleration
Luca Colagrande, Lorenzo Leone, Maximilian Coco, Andrei Deaconeasa, Luca Benini
https://arxiv.org/abs/2506.10921

Towards Zero-Stall Matrix Multiplication on Energy-Efficient RISC-V Clusters for Machine Learning Acceleration
The growing computational demands of machine learning (ML) workloads have driven the design of ML accelerators aiming at an optimal tradeoff between efficiency and flexibility. A widely explored architecture for flexible ML accelerators is based on clusters of lightweight instruction processors sharing multi-banked L1 memory, augmented with specialized instruction extensions for key ML-related computations, such as matrix multiplication (matmul). However, instruction extensions should be couple…

Relativistic quantum mechanics of charged vortex particles accelerated in a uniform electric field
Qi Meng, Ziqiang Huang, Xuan Liu, Wei Ma, Zhen Yang, Liang Lu, Alexander J. Silenko, Pengming Zhang, Liping Zou
https://arxiv.org/abs/2506.18492

Relativistic quantum mechanics of charged vortex particles accelerated in a uniform electric field
The relativistic quantum-mechanical description of a charged Laguerre-Gauss beam accelerated in a uniform electric field has been fulfilled. Stationary wave eigenfunctions are rigorously derived. The evolution of the beam parameters during acceleration is considered in detail. The practically important effect of extraordinary suppression of transverse spreading of the beam is discovered, carefully analyzed, and properly explained. Our results provide direct evidence that vortex particle beams c…

Spatiotemporal evolution of UV pulsations and their connection to 3D magnetic reconnection and particle acceleration
Stefan Purkhart, Hannah Collier, Laura A. Hayes, Astrid M. Veronig, Miho Janvier, S\"am Krucker
https://arxiv.org/abs/2506.03825

Spatiotemporal evolution of UV pulsations and their connection to 3D magnetic reconnection and particle acceleration
Quasi-periodic pulsations (QPPs) are a common feature of impulsive solar flare emissions, yet their driving mechanism(s) remain unresolved. We study long-period (3.4 min) QPPs in the M3.7 flare on Feb 24, 2023, using SDO/AIA and Solar Orbiter/STIX to pinpoint their source and driver. We analyzed UV and HXR emissions from four subregions covering the flare ribbons and footpoints of the erupting filament. We find the QPP characteristics varied significantly across these regions. The strongest UV …

On the prospects of thermalization of axion-SU(2) inflation
Sukannya Bhattacharya, Matteo Fasiello, Alexandros Papageorgiou, Ema Dimastrogiovanni
https://arxiv.org/abs/2506.11853 …

On the prospects of thermalization of axion-SU(2) inflation
Axion inflation models coupled to a gauge sector via a Chern-Simons term exhibit an array of interesting phenomenology including a chiral gravitational wave spectrum and primordial black hole production. They may also provide a useful mechanism for generating lepton asymmetry. The possibility to embed this class of models in UV-finite theories and their intriguing, testable, signatures make for a compelling candidate for early acceleration. Due to the Chern-Simons coupling, gauge modes may unde…

FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency
Yifei Su, Ning Liu, Dong Chen, Zhen Zhao, Kun Wu, Meng Li, Zhiyuan Xu, Zhengping Che, Jian Tang
https://arxiv.org/abs/2506.08822

FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency
Generative modeling-based visuomotor policies have been widely adopted in robotic manipulation attributed to their ability to model multimodal action distributions. However, the high inference cost of multi-step sampling limits their applicability in real-time robotic systems. To address this issue, existing approaches accelerate the sampling process in generative modeling-based visuomotor policies by adapting acceleration techniques originally developed for image generation. Despite this progr…

Plasma refilling of the lunar wake: plasma-vacuum interactions, electrostatic shocks, and electromagnetic instabilities
Xin An, Vassilis Angelopoulos, Terry Z Liu, Anton Artemyev, Andrew R. Poppe, Donglai Ma
https://arxiv.org/abs/2505.12497

Plasma refilling of the lunar wake: plasma-vacuum interactions, electrostatic shocks, and electromagnetic instabilities
A plasma void forms downstream of the Moon when the solar wind impacts the lunar surface. This void gradually refills as the solar wind passes by, forming the lunar wake. We investigate this refilling process using a fully kinetic particle-in-cell (PIC) simulation. The early stage of refilling follows plasma-vacuum interaction theory, characterized by exponential decay of plasma density into the wake, along with ion acceleration and cooling in the expansion direction. Our PIC simulation confirm…

Spatiotemporal coupled Airy-Airy wavepacket and its propagation dynamics
Zhaofeng Huang, Xiaolin Su, Qian Cao, Andy Chong, Qiwen Zhan
https://arxiv.org/abs/2506.05805

Spatiotemporal coupled Airy-Airy wavepacket and its propagation dynamics
Airy beams, celebrated for their self-acceleration, diffraction-free propagation, and self-healing properties, have garnered significant interest in optics and photonics, with applications spanning ultrafast optics, laser processing, nonlinear optics, and optical communications. Recent research primarily aims at independent control of Airy beams in both spatial and spatiotemporal domains. In a pioneering approach, we have successfully generated and controlled a spatiotemporal coupled (STc) Airy…

HBAR entropy of Infalling Atoms into a GUP-corrected Schwarzschild Black Hole and equivalence principle
Ali \"Ovg\"un, Reggie C. Pantig
https://arxiv.org/abs/2506.10621 …

HBAR entropy of Infalling Atoms into a GUP-corrected Schwarzschild Black Hole and equivalence principle
In this work, we have investigated the phenomenon of acceleration radiation exhibited by a two-level atom freely falling into a Generalized Uncertainty Principle (GUP)-corrected Schwarzschild black hole. We derive analytic expressions for the atom's excitation probability with simultaneous emission of a scalar quantum and observe that it satisfies the Einstein equivalence principle when compared to the excitation probability induced by a uniformly accelerating mirror, motivated by studies [10.1…

SLED: A Speculative LLM Decoding Framework for Efficient Edge Serving
Xiangchen Li, Dimitrios Spatharakis, Saeid Ghafouri, Jiakun Fan, Dimitrios Nikolopoulos
https://arxiv.org/abs/2506.09397

SLED: A Speculative LLM Decoding Framework for Efficient Edge Serving
Regardless the advancements in device capabilities, efficient inferencing advanced large language models (LLMs) at the edge remains challenging due to limited device memory and power constraints. Existing strategies, such as aggressive quantization, pruning, or remote inference, trade accuracy for efficiency or lead to substantial cost burdens. This position paper introduces a new approach that leverages speculative decoding, previously viewed primarily as a decoding acceleration technique for …

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration
Mukul Lokhande, Santosh Kumar Vishvakarma
https://arxiv.org/abs/2506.08785

POLARON: Precision-aware On-device Learning and Adaptive Runtime-cONfigurable AI acceleration
The increasing complexity of AI models requires flexible hardware capable of supporting diverse precision formats, particularly for energy-constrained edge platforms. This work presents PARV-CE, a SIMD-enabled, multi-precision MAC engine that performs efficient multiply-accumulate operations using a unified data-path for 4/8/16-bit fixed-point, floating point, and posit formats. The architecture incorporates a layer adaptive precision strategy to align computational accuracy with workload sensi…

A semi-Lagrangian scheme for First-Order Mean Field Games based on monotone operators
Elisabetta Carlini, Valentina Coscetti
https://arxiv.org/abs/2506.10509

A semi-Lagrangian scheme for First-Order Mean Field Games based on monotone operators
We construct a semi-Lagrangian scheme for first-order, time-dependent, and non-local Mean Field Games. The convergence of the scheme to a weak solution of the system is analyzed by exploiting a key monotonicity property. To solve the resulting discrete problem, we implement a Learning Value Algorithm, prove its convergence, and propose an acceleration strategy based on a Policy iteration method. Finally, we present numerical experiments that validate the effectiveness of the proposed schemes an…

Self-seeded photon acceleration by electron beam-driven transition radiation
Chaolu Ding, Xuesong Geng, Liangliang Ji
https://arxiv.org/abs/2506.06531 http…

Self-seeded photon acceleration by electron beam-driven transition radiation
Photon acceleration (PA) driven by ultra-relativistic electron beams offers a promising approach to generating high-power, high-frequency coherent radiation sources. While current methods typically rely on external optical laser pulses injected into beam-driven plasma wakefields, they face significant challenges in synchronization and alignment between electron accelerators and laser systems. We propose utilizing transition radiation (TR) generated by the drive electron bunch transversing the v…

FastFLUX: Pruning FLUX with Block-wise Replacement and Sandwich Training
Fuhan Cai, Yong Guo, Jie Li, Wenbo Li, Xiangzhong Fang, Jian Chen
https://arxiv.org/abs/2506.10035

FastFLUX: Pruning FLUX with Block-wise Replacement and Sandwich Training
Recent advancements in text-to-image (T2I) generation have led to the emergence of highly expressive models such as diffusion transformers (DiTs), exemplified by FLUX. However, their massive parameter sizes lead to slow inference, high memory usage, and poor deployability. Existing acceleration methods (e.g., single-step distillation and attention pruning) often suffer from significant performance degradation and incur substantial training costs. To address these limitations, we propose FastFLU…

Energy Consumption Optimization for Autonomous Vehicles via Positive Control Input Minimization
Andreas Hadjigeorgiou, Stelios Timotheou
https://arxiv.org/abs/2506.04685

Energy Consumption Optimization for Autonomous Vehicles via Positive Control Input Minimization
Autonomous vehicles (AVs) present a unique opportunity to improve the sustainability of transportation systems by adopting eco-driving strategies that reduce energy consumption and emissions. This paper introduces a novel surrogate model for energy and fuel consumption that minimizes Positive Control Input (PCI). Unlike conventional objectives such as squared acceleration, which often misrepresent actual energy usage, PCI provides a more accurate and optimization-friendly alternative. Building …

This https://arxiv.org/abs/2501.12613 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Study of the IC 443 region with the HAWC observatory
Supernova remnants are one potential source class considered a PeVatron (i.e. capable of accelerating cosmic rays above PeV energies). The shock fronts produced after the explosion of the supernova are ideal regions for particle acceleration. IC 443 is a supernova remnant that has been studied extensively at different wavelengths. Using 2966 days of gamma-ray data from the HAWC observatory, we study the emission of IC 443 with the objective of finding signatures of cosmic-ray acceleration at th…

A Visibility-based 21 cm Bispectrum Estimator for Radio-interferometric Data
Sukhdeep Singh Gill, Somnath Bharadwaj
https://arxiv.org/abs/2506.10526 https:…

A Visibility-based 21 cm Bispectrum Estimator for Radio-interferometric Data
We present a fast and scalable estimator for the binned multi-frequency angular bispectrum (MABS) and the 3D bispectrum (BS) of the redshifted 21 cm signal from radio interferometric observations. The estimator operates on gridded visibilities and leverages the FFT-based acceleration to efficiently compute the MABS and the 3D BS covering all possible triangle configurations. We present the formalism and validate the estimator using simulated visibility data for a known input model BS, consideri…

This https://arxiv.org/abs/2405.05047 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

An adaptive finite element multigrid solver using GPU acceleration
Adaptive finite elements combined with geometric multigrid solvers are one of the most efficient numerical methods for problems such as the instationary Navier-Stokes equations. Yet despite their efficiency, computations remain expensive and the simulation of, for example, complex flow problems can take many hours or days. GPUs provide an interesting avenue to speed up the calculations due to their very large theoretical performance. However, the large degree of parallelism and non-standard API…

A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problems
Jonathan Fried, Santiago Paternain
https://arxiv.org/abs/2506.03982 https://

A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problems
In this work, we present a method for minimizing the time required for a redundant dual-arm robot to follow a desired relative Cartesian path at constant path speed by optimizing its joint trajectories, subject to position, velocity, and acceleration limits. The problem is reformulated as a bi-level optimization whose lower level is a convex, closed-form subproblem that maximizes path speed for a fixed trajectory, while the upper level updates the trajectory using a single-chain kinematic formu…

High-charge relativistic electrons by vacuum laser acceleration from plasma mirrors using flying focus pulses
Jiaxin Liu, Zeyue Pang, Hehanlin Wang, Zi-Yu Chen
https://arxiv.org/abs/2505.24614

High-charge relativistic electrons by vacuum laser acceleration from plasma mirrors using flying focus pulses
Relativistic electron beams produced by intense lasers over short distances have important applications in high energy density physics and medical technologies. Vacuum laser acceleration with plasma mirrors injectors has garnered substantial research interest recently. However, a persistent challenge remains unresolved that electrons inevitably detach from the laser acceleration phase due to velocity mismatch. Here, we employ flying focus lasers to address this limitation. Through three-dimensi…

Hybrid SLC-MLC RRAM Mixed-Signal Processing-in-Memory Architecture for Transformer Acceleration via Gradient Redistribution
Chang Eun Song, Priyansh Bhatnagar, Zihan Xia, Nam Sung Kim, Tajana Rosing, Mingu Kang
https://arxiv.org/abs/2506.00020

Hybrid SLC-MLC RRAM Mixed-Signal Processing-in-Memory Architecture for Transformer Acceleration via Gradient Redistribution
Transformers, while revolutionary, face challenges due to their demanding computational cost and large data movement. To address this, we propose HyFlexPIM, a novel mixed-signal processing-in-memory (PIM) accelerator for inference that flexibly utilizes both single-level cell (SLC) and multi-level cell (MLC) RRAM technologies to trade-off accuracy and efficiency. HyFlexPIM achieves efficient dual-mode operation by utilizing digital PIM for high-precision and write-intensive operations while ana…

Total Power and Low-energy Cut-off Time Evolution of Solar Flare Accelerated Electrons Using X-Ray Observations and Warm-Target Model
Debesh Bhattacharjee (School of Physics & Astronomy, University of Glasgow, Glasgow, UK), Eduard P. Kontar (School of Physics & Astronomy, University of Glasgow, Glasgow, UK), Yingjie Luo (School of Physics & Astronomy, University of Glasgow, Glasgow, UK)

Total Power and Low-energy Cut-off Time Evolution of Solar Flare Accelerated Electrons Using X-Ray Observations and Warm-Target Model
A primary characteristic of solar flares is the efficient acceleration of electrons to nonthermal deka-keV energies. While hard X-Ray (HXR) observation of bremsstrahlung emission serves as the key diagnostic of these electrons. In this study, we investigate the time evolution of flare-accelerated electrons using the warm-target model. This model, unlike the commonly used cold-target model, can determine the low-energy cut-off in the nonthermal electron distribution, so that the energetics of no…

Laser-plasma acceleration in a conical plasma channel with longitudinally inhomogeneous plasma profile
D. S. Bondar, W. Leemans, V. I. Maslov, I. N. Onishchenko
https://arxiv.org/abs/2506.04021

Laser-plasma acceleration in a conical plasma channel with longitudinally inhomogeneous plasma profile
Laser-plasma acceleration is considered as a modern method of accelerating bunches using a wakefield excited by a laser pulse. This paper demonstrates the use of a longitudinally inhomogeneous increasing plasma density gradient in a conical channel to increase of the energy of a self-injected bunch. Comparison of a conical channels with homogeneous and inhomogeneous plasma and also conical and cylindrical homogeneous channels, shows a clear advantage of an inhomogeneous conical channel. The lon…

VUSA: Virtually Upscaled Systolic Array Architecture to Exploit Unstructured Sparsity in AI Acceleration
Shereef Helal, Alberto Garcia-Ortiz, Lennart Bamberg
https://arxiv.org/abs/2506.01166

VUSA: Virtually Upscaled Systolic Array Architecture to Exploit Unstructured Sparsity in AI Acceleration
Leveraging high degrees of unstructured sparsity is a promising approach to enhance the efficiency of deep neural network DNN accelerators - particularly important for emerging Edge-AI applications. We introduce VUSA, a systolic-array architecture that virtually grows based on the present sparsity to perform larger matrix multiplications with the same number of physical multiply-accumulate MAC units. The proposed architecture achieves saving by 37% and 68% in area and power efficiency, respecti…

This https://arxiv.org/abs/2311.12098 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Union Through UNITY: Cosmology with 2,000 SNe Using a Unified Bayesian Framework
Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the universe's expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of two in redshift, so compilations of multiple SN datasets are strongly beneficial. We assemble an up-to-date "Union" compilation of 2087 cosmologically useful SNe …

This https://arxiv.org/abs/2503.00339 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Falcon: Fast Visuomotor Policies via Partial Denoising
Diffusion policies are widely adopted in complex visuomotor tasks for their ability to capture multimodal action distributions. However, the multiple sampling steps required for action generation significantly harm real-time inference efficiency, which limits their applicability in real-time decision-making scenarios. Existing acceleration techniques either require retraining or degrade performance under low sampling steps. Here we propose Falcon, which mitigates this speed-performance trade-of…

DPUV4E: High-Throughput DPU Architecture Design for CNN on Versal ACAP
Guoyu Li (AMD), Pengbo Zheng (AMD), Jian Weng (AMD), Enshan Yang (AMD)
https://arxiv.org/abs/2506.11441

DPUV4E: High-Throughput DPU Architecture Design for CNN on Versal ACAP
Convolutional Neural Networks (CNNs) remain prevalent in computer vision applications, and FPGAs, known for their flexibility and energy efficiency, have become essential components in heterogeneous acceleration systems. However, traditional FPGAs face challenges in balancing performance and versatility due to limited on-chip resources. AMD's Versal ACAP architecture, tailored for AI applications, incorporates AI Engines (AIEs) to deliver high computational power. Nevertheless, the platform suf…

FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators
Victor Isachi, Alessandro Nadalini, Riccardo Fiorani Gallotta, Angelo Garofalo, Francesco Conti, Davide Rossi
https://arxiv.org/abs/2506.11668

FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators
The slow-down of technology scaling and the emergence of Artificial Intelligence (AI) workloads have led computer architects to increasingly exploit parallelization coupled with hardware acceleration to keep pushing the performance envelope. However, this solution comes with the challenge of synchronization of processing elements (PEs) in massive heterogeneous many-core platforms. To address this challenge, we propose FractalSync, a hardware accelerated synchronization mechanism for Bulk Synchr…

Helical Electron Beam Micro-Bunching by High-Order Modes in a Micro-Plasma Waveguide
Xinju Guo, Longqing Yi
https://arxiv.org/abs/2506.15094 https://

Helical Electron Beam Micro-Bunching by High-Order Modes in a Micro-Plasma Waveguide
Electron acceleration by a high-power Laguerre-Gaussian pulse in a micro-plasma waveguide is investigated. When the incident laser travels in the waveguide, electrons on the wall are extracted into the vacuum core and accelerated by the longitudinal field of the waveguide mode. Using 3D particle-in-cell simulations, we demonstrate that high energy (~100 MeV) electron beams with extremely high charge (~10 nC), ultrashort duration (~30 fs) and small divergence (~1 deg) can be produced by a 100-TW…

Observational Insights on DBI K-essence Models Using Machine Learning and Bayesian Analysis
Samit Ganguly, Arijit Panda, Eduardo Guendelman, Debashis Gangopadhyay, Abhijit Bhattacharyya, Goutam Manna
https://arxiv.org/abs/2506.05674

Observational Insights on DBI K-essence Models Using Machine Learning and Bayesian Analysis
We present a comparative observational data analysis of two DBI-type k-essence scalar field models for late-time cosmic acceleration: one treats dark energy with standard matter, while the other unifies dark energy and dark matter within a single scalar field, each governed by distinct non-canonical Lagrangians. The background dynamics are formulated via modified Friedmann and scalar field equations, constrained by Pantheon+ SNe Ia, Hubble, and BAO data, using Bayesian inference (NUTS in NumPyr…

Replaced article(s) found for cs.AR. https://arxiv.org/list/cs.AR/new
[1/1]:
Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective

Collimated Hard X-Rays from Hybrid Laser and Plasma Wakefield Accelerators
Hong Zhang, Jianmeng Wei, Mengyuan Chu, Jiale Zheng, Zhiheng Lou, Ruoxuan Ma, Xizhuan Chen, Hao Wang, Jiacheng Zhu, Zongxin Zhang, Yi Xu, Yuxin Leng, Song Li, Ke Feng, Wentao Wang, Ruxin Li
https://arxiv.org/abs/2506.06833…

Collimated Hard X-Rays from Hybrid Laser and Plasma Wakefield Accelerators
We report a synergistic enhancement of betatron radiation based on the hybrid laser and plasma wakefield acceleration scheme. Quasi-phase-stable acceleration in an up-ramp plasma density first generates GeV-energy electron beams that act as a drive beam for PWFA, which then further accelerates the witness beam to GeV energies, enhancing both photon energy and flux. A full width at half maximum divergence $(6.1 \pm 1.9)\times(5.8\pm 1.6) $ mrad$^2$ of betatron radiation, a critical energy of $71…

Laser-driven ion acceleration in long-lived optically shaped gaseous targets enhanced by magnetic vortices
I. Tazes, S. Passalidis, G. Andrianaki, A. Skoulakis, C. Karvounis, D. Mancelli, J. Pasley, E. Kaselouris, I. Fitilis, M. Bakarezos, E. P. Benis, N. A. Papadogiannis, V. Dimitriou, M. Tatarakis
https://arxiv.org/abs/2505.24…

Laser-driven ion acceleration in long-lived optically shaped gaseous targets enhanced by magnetic vortices
This research demonstrates high-repetition-rate laser-accelerated ion beams via dual, intersecting, counterpropagating laser-driven blast waves to precisely shape underdense gas into long-lived near-critical density targets. The collision of the shock fronts compresses the gas and forms steep density gradients with scale lengths of a few tens of microns. The compressed target persists for several nanoseconds, eliminating laser synchronization constraints. Measurements of multi-MeV ion energy sp…

This https://arxiv.org/abs/2404.11135 has been replaced.
initial toot: https://mastoxiv.page/@a…

Ion acceleration from micrometric targets immersed in an intense laser field
We report on an experimental study of proton acceleration by intense laser irradiation of micrometric bar targets, whose dimensions are transversely immersed in the laser focal volume and are longitudinally smaller than half its wavelength. With only 120 mJ of laser energy, we recorded proton energies in excess of 6~MeV, three times higher than those achieved with flat-foil irradiation using similar pulse energies. 3D particle-in-cell simulations revealed that the efficient energy transfer from…

This https://arxiv.org/abs/2504.03116 has been replaced.
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Electron Penetration Acceleration in Turbulent Magnetic Loops
Using particle-in-cell simulations to study fast radio burst (FRB) propagation in a tenuous plasma, we identified a novel mechanism that occurs during the growth of turbulent magnetic loops: electron penetration acceleration. The loops have an electromagnetic left-hand chirality distinct from that of well-known quasistatic magnetic islands. The fast electrons penetrate through the loops and thus are accelerated to unexpected relativistic energies due to the symmetry breaking induced by the coup…

Reaching extreme fields in laser-electron beam collisions with XUV laser light
Brandon K. Russell, Christopher P. Ridgers, Stepan S. Bulanov, Kyle G. Miller, Christopher Arran, Thomas G. Blackburn, Sergei V. Bulanov, Gabriele M. Grittani, John P. Palastro, Qian Qian, Alexander G. R. Thomas
https://arxiv.org/abs/2506.01727…

Reaching extreme fields in laser-electron beam collisions with XUV laser light
Plasma-based particle accelerators promise to extend the revolutionary work performed with conventional particle accelerators to studies with smaller footprints, lower costs, and higher energies. Here, we propose a new approach to access an unexplored regime of strong-field quantum electrodynamics by plasma wakefield acceleration of both charged particles and photons. Instead of using increasingly powerful accelerators and lasers, we show that photon acceleration of optical pulses into the extr…