Brian Chase

Bio: Brian Chase is an academic researcher from Fermilab. The author has contributed to research in topics: Cryomodule & Fermilab. The author has an hindex of 12, co-authored 92 publications receiving 591 citations.

Neural Networks for Modeling and Control of Particle Accelerators

Abstract: Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

ILC Reference Design Report Volume 3 - Accelerator

Abstract: The International Linear Collider (ILC) is a 200-500 GeV center-of-mass high-luminosity linear electron-positron collider, based on 1.3 GHz superconducting radio-frequency (SCRF) accelerating cavities. The ILC has a total footprint of about 31 km and is designed for a peak luminosity of 2x10^34 cm^-2 s^-1. The complex includes a polarized electron source, an undulator-based positron source, two 6.7 km circumference damping rings, two-stage bunch compressors, two 11 km long main linacs and a 4.5 km long beam delivery system. This report is Volume III (Accelerator) of the four volume Reference Design Report, which describes the design and cost of the ILC.

Superconducting cavity driving with FPGA controller

Abstract: A digital control of superconducting cavities for a linear accelerator is presented. FPGA-based controller, supported by Matlab system, was applied. Electrical model of a resonator was used for design of a control system. Calibration of the signal path is considered. Identification of cavity parameters has been carried out for adaptive control algorithm. Feed-forward and feedback modes were applied in operating the cavities. Required performance has been achieved; i.e. driving on resonance during filling and field stabilization during flattop time, while keeping reasonable level of the power consumption. Representative results of the experiments are presented for different levels of the cavity field gradient.

The PIP-II Conceptual Design Report

Abstract: The Proton Improvement Plan-II (PIP-II) encompasses a set of upgrades and improvements to the Fermilab accelerator complex aimed at supporting a world-leading neutrino program over the next several decades. PIP-II is an integral part of the strategic plan for U.S. High Energy Physics as described in the Particle Physics Project Prioritization Panel (P5) report of May 2014 [1] and formalized through the Mission Need Statement approved in November 2015. As an immediate goal, PIP-II is focused on upgrades to the Fermilab accelerator complex capable of providing proton beam power in excess of 1 MW on target at the initiation of the Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE) program [2], currently anticipated for the mid- 2020s. PIP-II is a part of a longer-term goal of establishing a high-intensity proton facility that is unique within the world, ultimately leading to multi-MW capabilities at Fermilab....

A Large Hadron Electron Collider at CERN: Report on the Physics and Design Concepts for Machine and Detector

Abstract: The physics programme and the design are described of a new collider for particle and nuclear physics, the Large Hadron Electron Collider (LHeC), in which a newly built electron beam of 60 GeV, up to possibly 140 GeV, energy collides with the intense hadron beams of the LHC. Compared to HERA, the kinematic range covered is extended by a factor of twenty in the negative four-momentum squared, $Q^2$, and in the inverse Bjorken $x$, while with the design luminosity of $10^{33}$ cm$^{-2}$s$^{-1}$ the LHeC is projected to exceed the integrated HERA luminosity by two orders of magnitude. The physics programme is devoted to an exploration of the energy frontier, complementing the LHC and its discovery potential for physics beyond the Standard Model with high precision deep inelastic scattering measurements. These are designed to investigate a variety of fundamental questions in strong and electroweak interactions. The physics programme also includes electron-deuteron and electron-ion scattering in a $(Q^2, 1/x)$ range extended by four orders of magnitude as compared to previous lepton-nucleus DIS experiments for novel investigations of neutron's and nuclear structure, the initial conditions of Quark-Gluon Plasma formation and further quantum chromodynamic phenomena. The LHeC may be realised either as a ring-ring or as a linac-ring collider. Optics and beam dynamics studies are presented for both versions, along with technical design considerations on the interaction region, magnets and further components, together with a design study for a high acceptance detector. Civil engineering and installation studies are presented for the accelerator and the detector. The LHeC can be built within a decade and thus be operated while the LHC runs in its high-luminosity phase. It thus represents a major opportunity for progress in particle physics exploiting the investment made in the LHC.

Machine learning at the energy and intensity frontiers of particle physics.

Abstract: Our knowledge of the fundamental particles of nature and their interactions is summarized by the standard model of particle physics Advancing our understanding in this field has required experiments that operate at ever higher energies and intensities, which produce extremely large and information-rich data samples The use of machine-learning techniques is revolutionizing how we interpret these data samples, greatly increasing the discovery potential of present and future experiments Here we summarize the challenges and opportunities that come with the use of machine learning at the frontiers of particle physics

The International Linear Collider Technical Design Report - Volume 3.II: Accelerator Baseline Design

Abstract: The International Linear Collider Technical Design Report (TDR) describes in four volumes the physics case and the design of a 500 GeV centre-of-mass energy linear electron-positron collider based on superconducting radio-frequency technology using Niobium cavities as the accelerating structures. The accelerator can be extended to 1 TeV and also run as a Higgs factory at around 250 GeV and on the Z0 pole. A comprehensive value estimate of the accelerator is give, together with associated uncertainties. It is shown that no significant technical issues remain to be solved. Once a site is selected and the necessary site-dependent engineering is carried out, construction can begin immediately. The TDR also gives baseline documentation for two high-performance detectors that can share the ILC luminosity by being moved into and out of the beam line in a "push-pull" configuration. These detectors, ILD and SiD, are described in detail. They form the basis for a world-class experimental programme that promises to increase significantly our understanding of the fundamental processes that govern the evolution of the Universe.

IOTA (Integrable Optics Test Accelerator): Facility and Experimental Beam Physics Program

Abstract: The Integrable Optics Test Accelerator (IOTA) is a storage ring for advanced beam physics research currently being built and commissioned at Fermilab. It will operate with protons and electrons using injectors with momenta of 70 and 150 MeV/c, respectively. The research program includes the study of nonlinear focusing integrable optical beam lattices based on special magnets and electron lenses, beam dynamics of space-charge effects and their compensation, optical stochastic cooling, and several other experiments. In this article, we present the design and main parameters of the facility, outline progress to date and provide the timeline of the construction, commissioning and research. The physical principles, design, and hardware implementation plans for the major IOTA experiments are also discussed.

Machine learning-based longitudinal phase space prediction of particle accelerators

Abstract: We report on the application of machine learning (ML) methods for predicting the longitudinal phase space (LPS) distribution of particle accelerators. Our approach consists of training a ML-based virtual diagnostic to predict the LPS using only nondestructive linac and e-beam measurements as inputs. We validate this approach with a simulation study for the FACET-II linac and with an experimental demonstration conducted at LCLS. At LCLS, the e-beam LPS images are obtained with a transverse deflecting cavity and used as training data for our ML model. In both the FACET-II and LCLS cases we find good agreement between the predicted and simulated/measured LPS profiles, an important step towards showing the feasibility of implementing such a virtual diagnostic on particle accelerators in the future.