Related papers: Diagnostics for Linac Optimization With Machine Le…
Advanced detector R&D for both new and ongoing experiments in HEP requires performing computationally intensive and detailed simulations as part of the detector-design optimisation process. We propose a versatile approach to this task that…
This study proposes a framework for the automated hyperparameter optimization of a bearing fault detection pipeline for permanent magnet synchronous motors (PMSMs) without the need of external sensors. A automated machine learning (AutoML)…
Machine learning (ML) provides access to fast and accurate quantum chemistry (QC) calculations for various properties of interest such as excitation energies. It is often the case that high accuracy in prediction using an ML model, demands…
Configuring clinical linear accelerators (linacs) for ultra-high dose rate (UHDR) electron experiments typically requires invasive hardware manipulation and/or irreversible manufacturer modifications, limiting broader implementation. We…
Solving the optimal symbol detection problem in multiple-input multiple-output (MIMO) systems is known to be NP-hard. Hence, the objective of any detector of practical relevance is to get reasonably close to the optimal solution while…
The problem of Raman amplifier optimization is studied. A differentiable interpolation function is obtained for the Raman gain coefficient using machine learning (ML), which allows for the gradient descent optimization of…
In the automotive industry, the full cycle of managing in-use vehicle quality issues can take weeks to investigate. The process involves isolating root causes, defining and implementing appropriate treatments, and refining treatments if…
The high thermal efficiency and reliability of the compression-ignition engine makes it the first choice for many applications. For this to continue, a reduction of the pollutant emissions is needed. One solution is the use of machine…
This work investigates robust monotonic convergent iterative learning control (ILC) for uncertain linear systems in both time and frequency domains, and the ILC algorithm optimizing the convergence speed in terms of $l_{2}$ norm of error…
Microbunching instability usually exists in the linear accelerator (linac) of a free electron laser (FEL) facility. If it is not controlled effectively, the beam quality will be damaged seriously and the machine will not operate properly.…
The paradigm of Multimodal Large Language Models (MLLMs) offers a promising blueprint for advancing the electromagnetic (EM) domain. However, prevailing approaches often deviate from the native MLLM paradigm, instead using task-specific or…
Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks. The MAML algorithm performs well on few-shot learning…
We investigate a bias-corrected machine learning (ML) strategy for estimating traces of the inverse Dirac operator, $\text{Tr}\, M^{-n}$ ($n=1,2,3,4$), motivated by the need for higher-order cumulants of the chiral condensate near the…
We summarize the current state of a concept for muon acceleration aimed at a future Neutrino Factory. The main thrust of these studies was to reduce the overall cost while maintaining performance by exploring the interplay between the…
The main `bottleneck' limiting the beam power in circular machines is caused by space charge effects that produce beam instabilities. To increase maximally the beam power of a `proton driver', it is proposed to build a facility consisting…
The construction of the initial part of a normally conducting linac for hydrogen ion beams with a pulsed current of ~20 mA up to an energy of ~70 MeV is considered. The RFQ at a frequency of ~160 MHz accelerates ions to an energy of ~4 MeV.…
Fermilab is developing a Proton Improvement Plan (PIP) to increase throughput of its proton source. The plan addresses hardware modifications to increase repetition rate and improve beam loss while ensuring viable operation of the proton…
The proposed Next Linear Collider contains a large number of linac RF systems with new requirements for wideband klystron modulation and accurate RF vector detection. The system will be capable of automatically phasing each klystron and…
The S-DALINAC is a 130 MeV superconducting recirculating electron accelerator serving several nuclear and radiation physics experiments as well as driving an infrared free-electron laser. A system of normal conducting rf resonators for…
A well-known approach to describe the dynamics of an open quantum system is to compute the master equation evolving the reduced density matrix of the system. This approach plays an important role in describing excitation transfer through…