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Reluctance actuators are preferred for high-precision applications. Due to resistive losses in the coils, the accuracy of this type of actuator will reduce in quasi-static operation mode within a vacuum environment. By using soft permanent…

Systems and Control · Electrical Eng. & Systems 2022-12-05 W. B. Hoekwater , J. D. Wiersema1 , S. H. HosseinNia

In an open-loop experiment, an input sequence is applied to an unknown linear time-invariant system (in continuous or discrete time) affected also by an unknown-but-bounded disturbance sequence (with an energy or instantaneous bound); the…

Systems and Control · Electrical Eng. & Systems 2022-10-19 Andrea Bisoffi , Claudio De Persis , Pietro Tesi

Understanding the thermal behaviour of superconducting accelerator magnets is essential to ensure their stable and reliable operation. This work presents an extension of the Finite Element Quench Simulator (FiQuS) Multipole module to…

Superconducting REBCO ($RE$Ba$_2$Cu$_3$O$_{7-x}$, where $RE$ is a rare earth, typically Y, Gd or Eu) electromagnets are useful for many applications like medical magnetic resonace imaging (MRI), nuclear magnetic resonance (NMR)…

Applied Physics · Physics 2026-02-16 Enric Pardo , Anang Dadhich , Nikola Jerance , Philippe Fazilleau

As the potential for neural networks to augment our daily lives grows, ensuring their quality through effective testing, debugging, and maintenance is essential. This is especially the case as we acknowledge the prospects of negative…

Software Engineering · Computer Science 2025-07-08 Fatema Tuz Zohra , Brittany Johnson

Energy-Based Models (EBMs) present a flexible and appealing way to represent uncertainty. Despite recent advances, training EBMs on high-dimensional data remains a challenging problem as the state-of-the-art approaches are costly, unstable,…

Machine Learning · Computer Science 2021-06-08 Will Grathwohl , Jacob Kelly , Milad Hashemi , Mohammad Norouzi , Kevin Swersky , David Duvenaud

The demagnetizing factor N is of both conceptual interest and practical importance. Considering localized magnetic moments on a lattice, we show that for non-ellipsoidal samples, N depends on the spin dimensionality (Ising, XY, or…

A major problem of state-of-the-art Nb$_3$Sn accelerator magnets is their long training due to thermo-mechanical perturbations. Increasing the specific heat, $C_p$, of the Rutherford cable would reduce and/or eliminate training by limiting…

Applied Physics · Physics 2022-05-04 E. Barzi , I. Novitsky , D. Turrioni , A. V. Zlobin , X. Peng , M. Tomsic

The Large Hadron Collider (LHC) at CERN in Geneva (Switzerland) will go in operation in the coming months and will soon enable us to analyze the highest energy collisions ever produced at an accelerator. Beyond Standard Model searches at…

High Energy Physics - Experiment · Physics 2009-09-29 S. Beauceron

Recent progress in hardware and methodology for training neural networks has ushered in a new generation of large networks trained on abundant data. These models have obtained notable gains in accuracy across many NLP tasks. However, these…

Computation and Language · Computer Science 2019-06-07 Emma Strubell , Ananya Ganesh , Andrew McCallum

Under the U.S. High Luminosity LHC Accelerator Upgrade Project (HL-LHC AUP), the 150 mm bore, high-field Nb3Sn low-\b{eta} MQXFA quadrupole magnets are being fabricated, assembled and tested, in the context of the CERN Hi-Luminosity LHC…

Much of the current work on reinforcement learning studies episodic settings, where the agent is reset between trials to an initial state distribution, often with well-shaped reward functions. Non-episodic settings, where the agent must…

Machine Learning · Computer Science 2020-06-23 John D. Co-Reyes , Suvansh Sanjeev , Glen Berseth , Abhishek Gupta , Sergey Levine

Recent research has shown that generative models with highly disentangled representations fail to generalise to unseen combination of generative factor values. These findings contradict earlier research which showed improved performance in…

Machine Learning · Computer Science 2024-06-17 Milton L. Montero , Jeffrey S. Bowers , Rui Ponte Costa , Casimir J. H. Ludwig , Gaurav Malhotra

The dynamics of molecular motors which occasionally detach from a heterogeneous track like DNA or RNA is considered. Motivated by recent single molecule experiments, we study a simple model for a motor moving along a disordered track using…

Statistical Mechanics · Physics 2009-11-10 Yariv Kafri , David K. Lubensky , David R. Nelson

We present the results of simulations of forced turbulence in a slab where the mean kinetic helicity has a maximum near the mid-plane, generating gradients of magnetic helicity of both large and small-scale fields. We also study systems…

Solar and Stellar Astrophysics · Physics 2010-11-30 A. Hubbard , A. Brandenburg

High energy resolution spectroscopic studies of quantum magnets have proven to be extremely valuable in directly accessing magnetodynamics quantities, such as energy barriers, magnetic interactions, lifetime of excited states and…

Mesoscale and Nanoscale Physics · Physics 2022-02-17 Sascha Brinker , Felix Küster , Stuart S. P. Parkin , Paolo Sessi , Samir Lounis

Recently, Sironi (PRL, 128, 145102; S22) reported the correlation between particles accelerated into high energy and their crossings of regions with electric field larger than magnetic field (E>B regions) in kinetic simulations of…

High Energy Astrophysical Phenomena · Physics 2023-05-17 Fan Guo , Xiaocan Li , Omar French , William Daughton , William Matthaeus , Qile Zhang , Yi-Hsin Liu , Patrick Kilian , Grant Johnson , Hui Li

One of the most intensely studied scenarios of high-temperature superconductivity (HTS) postulates pairing by exchange of magnetic excitations [1]. Indeed, such excitations have been observed up to around optimal doping in the cuprates…

From magnetic deflection experiments on isolated Co doped Nb clusters we made the interesting observation of some clusters being magnetic, while others appear to be non-magnetic. There are in principle two explanations for this behavior.…

Strongly Correlated Electrons · Physics 2018-05-02 A. Diaz-Bachs , L. Peters , R. Logemann , V. Chernyy , J. M. Bakker , M. I. Katsnelson , A. Kirilyuk

Active learning agents typically employ a query selection algorithm which solely considers the agent's learning objectives. However, this may be insufficient in more realistic human domains. This work uses imitation learning to enable an…

Machine Learning · Computer Science 2019-07-02 Kalesha Bullard , Yannick Schroecker , Sonia Chernova