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Related papers: Minimizing the fluctuation of resonance driving te…

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The optimization of the dynamic aperture (DA) of a storage ring is typically a non-convex problem with multiple local optima. Recent studies showed that reducing the variation of resonance driving terms (RDTs) along the longitudinal…

Accelerator Physics · Physics 2026-03-26 Wanbin Li , Zihan Wang , Yuejing Huang , Bingfeng Wei , Zhenghe Bai

Beam lifetime in storage rings and colliders is affected by, among other effects, lattice nonlinearities. Their control are of great benefit to the dynamic aperture of an accelerator, whose enlargement leads in general to more efficient…

Accelerator Physics · Physics 2018-04-18 A. Franchi , L. Farvacque , F. Ewald , G. Le Bec , K. B. Scheidt

A simplified Recycler lattice was created to fine tune injection straight, ring tune, and phase trombone. In this paper, we will present detailed modifications for further optimization of Recycler lattice which requires the investigation of…

Accelerator Physics · Physics 2012-07-25 M. Xiao , L. G. Vorobiev , D. E. Johnson

Off-lattice DLA clusters grown with different levels of noise reduction are found to be consistent with a simple fractal fixed point. Cluster shapes and their ensemble variation exhibit a dominant slowest correction to scaling, and this…

Statistical Mechanics · Physics 2007-05-23 Robin C. Ball , Neill E. Bowler , Leonard M. Sander , Ellak Somfai

We revisit the nonlinear lattice design approach for the National Synchrotron Light Source II (NSLS-II) storage ring. By suppressing chaos, we identify alternative sextupole configurations to the original design, which relied on the…

Accelerator Physics · Physics 2026-03-09 Yongjun Li , Minghao Song , Yoshiteru Hidaka , Victor Smaluk , Timur Shaftan

Data augmentation (DA) is a crucial technique for enhancing the sample efficiency of visual reinforcement learning (RL) algorithms. Notably, employing simple observation transformations alone can yield outstanding performance without extra…

Machine Learning · Computer Science 2023-10-30 Guozheng Ma , Linrui Zhang , Haoyu Wang , Lu Li , Zilin Wang , Zhen Wang , Li Shen , Xueqian Wang , Dacheng Tao

Data augmentation (DA) is commonly used during model training, as it significantly improves test error and model robustness. DA artificially expands the training set by applying random noise, rotations, crops, or even adversarial…

Machine Learning · Computer Science 2019-05-09 Shashank Rajput , Zhili Feng , Zachary Charles , Po-Ling Loh , Dimitris Papailiopoulos

We demonstrate the phenomenon of resonant activation in a non-adiabatically driven dissipative optical lattice with broken time-symmetry. The resonant activation results in a resonance as function of the driving frequency in the current of…

Statistical Mechanics · Physics 2009-11-11 R. Gommers , P. Douglas , S. Bergamini , M. Goonasekera , P. H. Jones , F. Renzoni

For most stochastic dynamical systems, variables which are tightly regulated tend to respond slowly to external changes. This idea is often discussed for applicable systems, within a linear response regime, through the Fluctuation…

General Physics · Physics 2017-11-15 Nash Rochman , Sean X. Sun

The dynamical fluctuations in approaches such as dynamical mean-field theory (DMFT) allow for the self-consistent optimization of a local fragment, hybridized with a true correlated environment. We show that these correlated environmental…

Strongly Correlated Electrons · Physics 2018-12-19 Edoardo Fertitta , George H. Booth

The characterization and monitoring of buildings is an issue that has attracted the interest of many sectors over the last two decades. With the increasing use of permanent, continuous and real-time networks, ambient vibrations can provide…

The fluctuations of the jamming coverage upon Random Sequential Adsorption (RSA) are studied using both analytical and numerical techniques. Our main result shows that these fluctuations (characterized by $\sigma_{\theta_J}$) decay with the…

Statistical Mechanics · Physics 2009-11-10 Ernesto S. Loscar , Rodolfo A. Borzi , Ezequiel V. Albano

We study fluctuating tilt Brownian ratchets based on fractional subdiffusion in sticky viscoelastic media characterized by a power law memory kernel. Unlike the normal diffusion case the rectification effect vanishes in the adiabatically…

Statistical Mechanics · Physics 2012-06-04 Igor Goychuk , Vasyl Kharchenko

Differential Attention (DA) has been proposed as a refinement to standard attention, suppressing redundant or noisy context through a subtractive structure and thereby reducing contextual hallucination. While this design sharpens…

Machine Learning · Computer Science 2026-03-17 Tsubasa Takahashi , Shojiro Yamabe , Futa Waseda , Kento Sasaki

Dynamical mean-field theory (DMFT) provides an optimal local approximation for correlated lattice systems by mapping the lattice onto a self-consistent effective impurity model. To account for the missing long-range correlations, we propose…

Strongly Correlated Electrons · Physics 2026-03-04 S. D. Semenov , A. I. Lichtenstein , A. N. Rubtsov

In scenarios where high penetration of renewable energy sources (RES) is connected to the grid over long distances, the output of RES exhibits significant fluctuations, making it difficult to accurately characterize. The intermittency and…

Optimization and Control · Mathematics 2025-02-27 Yuhong Wang , Xinyao Wang , Chen Shen , Jianquan Liao , Qianni Cao , Yufei Teng , Huabo Shi , Gang Chen

The upgrade of the Swiss Light Source, called SLS 2.0, is scheduled for 2023-24. The current storage ring will be replaced by one based on multi-bend achromats, allowing for about 30 times higher brightness. Due to the stronger focusing and…

Accelerator Physics · Physics 2020-02-21 M. Kranjcevic , B. Riemann , A. Adelmann , A. Streun

We report the first experimental observation of the resonance-assisted dynamical tunneling (RADT) in the inter-mode interaction in an asymmetric-deformed microcavity. A selection rule for strong inter-mode coupling induced by RADT was…

Mesoscale and Nanoscale Physics · Physics 2015-03-24 Hojeong Kwak , Younghoon Shin , Songky Moon , Kyungwon An

Recently, data augmentation (DA) has emerged as a method for leveraging domain knowledge to inexpensively generate additional data in reinforcement learning (RL) tasks, often yielding substantial improvements in data efficiency. While prior…

Machine Learning · Computer Science 2024-03-19 Nicholas E. Corrado , Josiah P. Hanna

Recent studies have suggested frequency-domain Data augmentation (DA) is effec tive for time series prediction. Existing frequency-domain augmentations disturb the original data with various full-spectrum noises, leading to excess domain…

Machine Learning · Computer Science 2024-05-28 Kai Zhao , Zuojie He , Alex Hung , Dan Zeng
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