Related papers: Diagnostics for Linac Optimization With Machine Le…
Multi-instance multi-label (MIML) learning is a challenging problem in many aspects. Such learning approaches might be useful for many medical diagnosis applications including breast cancer detection and classification. In this study subset…
The possibility of using electron beam phase space manipulations to support a free-electron laser accelerator design optimization has motivated our research. An on-going program demonstrating the exchange of transverse horizontal and…
In this paper, we propose BeamLLM, a vision-aided millimeter-wave (mmWave) beam prediction framework leveraging large language models (LLMs) to address the challenges of high training overhead and latency in mmWave communication systems. By…
Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was…
Multi-label classification (MLC) is an ML task of predictive modeling in which a data instance can simultaneously belong to multiple classes. MLC is increasingly gaining interest in different application domains such as text mining,…
Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is…
The Fermilab Proton Improvement Plan (PIP) was formed in late 2011 to address important and necessary upgrades to the Proton Source machines (Injector line, Linac and Booster). The goal is to increase the proton flux by doubling the Booster…
Multimodal large language models (MLLMs) have made significant strides, yet they face challenges in the medical domain due to limited specialized knowledge. While recent medical MLLMs demonstrate strong performance in lab settings, they…
In order to dissipate long-lived radioactive waste, not only high ux proton accelerator but also electron linac have been proposed. A proton accelerator directly induces nuclear fission and mutation. On the other hand, electron beam has two…
The creation of intense radioactive beams requires intense and energetic primary beams. A task force analysis of this subject recommended an acceleration system capable of 400 MeV/u uranium at 1 particle uA as an appropriate driver for such…
The increasing capabilities of Machine Learning (ML) models go hand in hand with an immense amount of data and computational power required for training. Therefore, training is usually outsourced into HPC facilities, where we have started…
Quite good agreement has been achieved between computer modeling and actual performance of the Brookhaven 200 MeV Linac. We will present comparisons between calculated and measured performance for the beam transport through the RFQ, the 6…
The Proton Improvement Plan - II (PIP-II) is a new linear accelerator (LINAC) complex being built at Fermilab. It is based on superconducting radiofrequency cavities and will accelerate H- ions to 800 MeV kinetic energy before injection…
To fully exploit the physics potential of current and future high energy particle colliders, machine learning (ML) can be implemented in detector electronics for intelligent data processing and acquisition. The implementation of ML in…
Ion Beam Analysis (IBA) is an established tool for material characterization, providing precise information on elemental composition, depth profiles, and structural information in the region near the surface of materials. However,…
A new experimental area designed to develop, test and verify muon ionization cooling apparatus using the 400-MeV Fermilab Linac proton beam has been fully installed and is presently being commissioned. Initially, this area was used for…
The photon flux resulting from high-energy electron beam interactions with high field systems, such as in the upcoming FACET-II experiments at SLAC National Accelerator Laboratory, may give deep insight into the electron beam's underlying…
A CW-compatible, pulsed H- superconducting linac "PIP-II" is being planned to upgrade Fermilab's injection complex. To validate the front-end concept, a test accelerator (The PIP-II Injector Test, formerly known as "PXIE") is under…
Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLABC (Reinforcement Learning for Accelerator Beamline Control), an open-source Python…
In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with machine learning (ML) and data mining techniques. While conventional ML methods, including artificial neural network (ANN), principal…