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Thurman-Keup, Randy

Publications and source records attributed to Thurman-Keup, Randy.

14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Near-infrared noise in intense electron beams

Requirements for the noise in electron beams (NEB) have recently approached the Shot-noise level in some new applications. The density fluctuations of intense beams in the near-infrared (NIR) region are being measured at the Fermilab Accelerator Science and Technology (FAST) facility. The main goal of the experiment is to accurately compare the Shot-noise model with the observations of optical transition radiation (OTR) generated by the gamma=63 electron beam transiting an Al metal surface. In addition, evidence for longitudinal-space-charge-induced microbunching for the chicane-compressed beam was obtained with coherent enhancements up to 100 in the various bandwidth-filtered NIR OTR photodiode signals. With micropulse charges up to 1 nC, the beam parameters are close to those proposed for a stage in an Electron-Ion Collider (EIC) with coherent electron cooling (CEC). In this paper we present the current progress of the NEB project and compare the low electron energy measurements with ImpactX simulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Disentangling Beam Losses in The Fermilab Main Injector Enclosure Using Real-Time Edge AI

The Fermilab Main Injector enclosure houses two accelerators, the Main Injector and Recycler Ring. During normal operation, high intensity proton beams exist simultaneously in both. The two accelerators share the same beam loss monitors (BLM) and monitoring system. Deciphering the origin of any of the 260 BLM readings is often difficult. The (Accelerator) Real-time Edge AI for Distributed Systems project, or READS, has developed an AI/ML model, and implemented it on fast FPGA hardware, that disentangles mixed beam losses and attributes probabilities to each BLM as to which machine(s) the loss originated from in real-time. The model inferences are then streamed to the Fermilab accelerator controls network (ACNET) where they are available for operators and experts alike to aid in tuning the machines.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Progress on an Electron Beam Profile Monitor at the Fermilab Main Injector

The current program at Fermilab involves the construction of a new superconducting linear accelerator (LINAC) to replace the existing warm version. The new LINAC, together with other planned improvements, is in support of proton beam intensities in the Main Injector (MI) that will exceed 2 MW. Measuring the transverse profiles of these high intensity beams in a ring requires non-invasive techniques. The MI uses ionization profile monitors as its only profile system. An alternative technique involves measuring the deflection of a probe beam of electrons with a trajectory perpendicular to the proton beam. This type of device was installed in MI and initial studies of it have been previously presented. This paper will present the status and recent studies of the device utilizing different techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Semantic Regression for Disentangling Beam Losses in the Fermilab Main Injector and Recycler

Fermilab’s Main Injector enclosure houses two accelerators: the Main Injector (MI) and the Recycler (RR). In periods of joint operation, when both machines contain high intensity beam, radiative beam losses from MI and RR overlap on the enclosure’s beam loss monitoring (BLM) system, making it difficult to attribute those losses to a single machine. Incorrect diagnoses result in unnecessary downtime that incurs both financial and experimental cost. In this work, we introduce a novel neural approach for automatically disentangling each machine’s contributions to those measured losses. Using a continuous adaptation of the popular UNet architecture in conjunction with a novel data augmentation scheme, our model accurately infers the machine of origin on a per-BLM basis in periods of joint and independent operation. Crucially, by extracting beam loss information at varying receptive fields, the method is capable of learning both local and global machine signatures and producing high quality inferences using only raw BLM loss measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Beam Profile Measurements Utilizing an Amplitude Modulated Pulsed Fiber Laser at PIP2IT

Fermilab is undertaking the development of a new 800 MeV superconducting RF linac to replace its present normal conducting 400 MeV linac. The PIP-II linac consists of a warm front-end generating 2 mA of 2.1 MeV H⁻ followed immediately by a series of superconducting RF cryomodules to 800 MeV. To limit the potential damage to the superconducting RF cavities, PIP-II will utilize laser-based monitors to obtain beam profiles via photoionization. This paper will present the results of transverse and longitudinal beam profile measurements using a prototype profile monitor that was tested with 2.1 MeV H⁻ beam at the PIP-II Injector Test (PIP2IT) accelerator. This prototype profile monitor utilizes a high repetition rate fiber laser and fiber optic transport into the PIP2IT enclosure. In addition, results will be shown of narrow-band electron detection from amplitude modulated laser pulses.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Bunch Extinction Measurements at PIP-II Injector Test Facility

The PIP2 particle accelerator is a new upgrade to the Fermilab accelerator complex, featuring an 800-MeV H-superconducting linear accelerator that will inject the beam into the present Fermilab Booster. A test accelerator known as PIP-II Injector Test (PIP2IT) has been built to validate the concept of the front-end of such a machine. One of the paramount challenges of PIP2IT was to validate the bunch by bunch chopping system in the Medium Energy Beam Transport (MEBT). This paper aims to present the direct extinction measurements at PIP2IT and their analysis. These measurements have been taken by two Resistive Wall Current Monitors (RWCM) and recorded by a high bandwidth oscilloscope.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Real-Time Edge AI for Distributed Systems (READS): Progress on Beam Loss De-Blending for the Fermilab Main Injector and Recycler

The Fermilab Main Injector enclosure houses two accelerators, the Main Injector and Recycler. During normal operation, high intensity proton beams exist simultaneously in both. The two accelerators share the same beam loss monitors (BLM) and monitoring system. Beam losses in the Main Injector enclosure are monitored for tuning the accelerators and machine protection. Losses are currently attributed to a specific machine based on timing. However, this method alone is insufficient and often inaccurate, resulting in more difficult machine tuning and unnecessary machine downtime. Machine experts can often distinguish the correct source of beam loss. This suggests a machine learning (ML) model may be producible to help de-blend losses between machines. Work is underway as part of the Fermilab Real-time Edge AI for Distributed Systems Project (READS) to develop a ML empowered system that collects streamed BLM data and additional machine readings to infer in real-time, which machine generated beam loss.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Machine Learning Training for HOM reduction and Emittance Preservation in a TESLA-type Cryomodule at FAST

Low emittance electron beams are of high importance at facilities like the LCLS-II at SLAC. Emittance dilution effects due to off-axis beam transport for a TESLA-type cryomodule (CM) have been shown at the Fermilab Accelerator Science and Technology facility. The results showed the correlation between the electron beam-induced cavity high-order modes (HOMs) and submacropulse centroid slewing and oscillation downstream of the CM. Mitigation of emittance dilution can be achieved by reducing the HOM signals and the variances in the submacropulse beam positions downstream of the CM. Here we present a Machine Learning based optimization and model construction for HOM signal level reduction using Neural Networks and Gaussian Processes. To gather training data we performed experiments using single bunch and 50 bunch electron beams with charges up to 125 pC/b. We measured HOM signals of all cavities and beam position with a set of BPMs downstream of the CM. The beam trajectory was changed using V/H125 corrector set located upstream of the CM. The results presented here will inform the LCLS-II injector commissioning and will serve as a prototype for HOM reduction and emittance preservation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Commissioning of the LCLS-II Prototype HOM Detectors with Tesla-Type Cavities at Fast

Experiments at the Fermilab Accelerator Science and Technology* (FAST) facility detected electron beam-induced high order mode (HOM) signals from Tesla superconducting cavities. This paper describes some of the signal detection hardware used in this experiment, as well as measurements of the HOM signal magnitude versus beam trajectory. These measurements were made both with a single bunch and with a train of 50 bunches at bunch charges from 400 pC/b down to 10 pC/b. The detection hardware is designed for use with the Tesla superconducting cavities of LCLS-II at SLAC** and is based on a prototype already in use at Fermilab. The HOM signal passes through a bandpass filter that is centered on several cavity dipole modes and a zero bias Schottky diode detects its magnitude. Direct comparisons were made between the FNAL chassis and the SLAC prototype for identical beam steering conditions. To support measurements with bunch charges as low as 10 pC, the SLAC detector has RF amplification between the bandpass filter and the diode detector. With this hardware, usable HOM signal measurements are obtained with a single bunch of 10 pC in cryomodule cavities as will be needed for LCLS-II.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Optimizing Mu2e Spill Regulation System Algorithms

A slow extraction system is being developed for the Fermilab’s Delivery Ring to deliver protons to the Mu2e experiment. During the extraction, the beam on target experiences small intensity variations owing to many factors. Various adaptive learning algorithms will be employed for beam regulation to achieve the required spill quality. We discuss here preliminary results of the slow and fast regulation algorithms validation through the computer simulations before their implementation in the FPGA. Particle tracking with sextupole resonance was used to determine the fine shape of the spill profile. Fast semi-analytical simulation schemes and Machine Learning models were used to optimize the fast regulation loop.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Observations On Submicropulse Electron-beam Effects From Short-range Wakefields In Tesla-type Superconducting RF Cavities

aExperiments were performed at The Fermilab Accelerator Science and Technology (FAST) facility to elucidate the effects of short-range wakefields (SRWs) in TESLA-type rf cavities. FAST has a unique configuration of a photocathode rf gun beam injecting two TESLA-type single cavities (CC1 and CC2) in series prior to the cryomodule. To investigate short-range wakefield effects, we have steered the beam to minimize the signals in the higher-order mode (HOM) detectors of CC1 and CC2 for a baseline, and then selected a vertical corrector to steer the beam off axis at an angle into CC1 or CC2. A Hamamatsu synchro-scan streak camera viewing a downstream OTR screen provided an image of y-t effects within the micropulses with ~10-micron spatial resolution and 2-ps temporal resolution. At 500 pC/b, 50 b, and 2 mrad off-axis steering into CC2, we observed an ~ 100-micron head-tail centroid shift in the streak camera image y(t)-profiles. This centroid shift value is consistent wit h a calculated short-range wakefield effect using ASTRA simulations.

43 PARTICLE ACCELERATORS↗