Related papers: Intra-bunch feedback system developments at DAFNE
Deep neural network (DNN) inference relies increasingly on specialized hardware for high computational efficiency. This work introduces a field-programmable gate array (FPGA)-based dynamically configurable accelerator featuring systolic…
The Large Particle Physics Laboratory Directors Group (LDG) established the Working Group (WG) on the Sustainability Assessment of Future Accelerators in 2024 with the mandate to develop guidelines and a list of key parameters for the…
Two injector accelerator options for HE-LHC of p+ - p+ collisions at 33 TeV cms energy are briefly outlined. One option is based on the Super-SPS (S-SPS) [1] accelerator in the SPS tunnel, and the other one is based on the LER…
The diverse community of scientists involved in Deep Inelastic Scattering includes about 2000 experimental and theoretical physicists worldwide and envisages projects such as the EIC, LHeC, FCC-eh and VHEeP as future lepton-hadron…
A 52MHz Radio Frequency Quadrupole (RFQ) linear accelerator (linac) is designed to serve as an initial structure for the SSC-linac system (injector into Separated Sector Cyclotron). The designed injection and output energy are 3.5 keV/u and…
The Gamma Factory (GF) proposal \cite{Krasny:2015ffb} is motivated by the recognition of a largely untapped potential of the CERN accelerator complex to enable a new research programme at the intersection of particle, nuclear, atomic,…
Reinforcement learning (RL) and brain-computer interfaces (BCI) have experienced significant growth over the past decade. With rising interest in human-in-the-loop (HITL), incorporating human input with RL algorithms has given rise to the…
Machine learning is used extensively in recommender systems deployed in products. The decisions made by these systems can influence user beliefs and preferences which in turn affect the feedback the learning system receives - thus creating…
The maximum magnetic field available to guide and focus the proton beams will be the most important factor driving the design of the High Energy LHC. The US LHC Accelerator Research Program (LARP) is a collaboration of US National…
Accelerator technology has advanced tremendously since the introduction of accelerators in the 1930s, and particle accelerators have become indispensable instruments in high energy physics (HEP) research to probe Nature at smaller and…
We develop a physics-informed neural networks (PINNs) framework for the inverse scattering problem in nuclear physics and apply it to the $P_{3/2}$ partial wave of neutron-alpha elastic scattering. The radial potential is represented by a…
Complex dynamics of silicon microring resonators loaded by delayed feedback elements enable high-speed photonic reservoir computing. Implementing feedback is especially challenging when the required delay should match the time scales of…
Electron injection in an evolving ellipsoid bubble for laser wakefield acceleration is investigated by 2.5D PIC (Particle-In-Cell) simulation. Generally speaking, the self-injection electrons come from the position near the transverse…
The stabilization of unstable nonlinear systems and tracking control are challenging engineering problems due to the encompassed nonlinearities in dynamic systems and their scale. In the past decades, numerous observer-based control designs…
Linear transformations are cornerstone operations utilized in modern computing, but are computationally expensive on current electronic platforms. Optical computing has been positioned as a new computing solution, promising high speed and…
The ATLAS experiment will undergo around the year 2025 a replacement of the tracker system in view of the high luminosity phase of the LHC (HL-LHC) with a new 5-layer pixel system. Thin planar pixel sensors are promising candidates to…
Laser has unique advantages such as abundant spectrum resources and low propagation divergence in wireless charging and wireless communications, compared with radio frequency. Resonant beams, as a kind of intra-cavity laser beams, have been…
In many electron spin qubit systems coherent control is impaired by the fluctuating nuclear spin bath of the host material. Previous experiments have shown dynamic nuclear polarization with feedback to significantly prolong the…
In-memory computing technology is used extensively in artificial intelligence devices due to lower power consumption and fast calculation of matrix-based functions. The development of such a device and its integration in a system takes a…
The dissipativity framework is widely used to analyze stability and performance of nonlinear systems. By embedding nonlinear systems in an LPV representation, the convex tools of the LPV framework can be applied to nonlinear systems for…