Author: Diaz Cruz, J.A.
Paper Title Page
MOPAB232 Observation of Polarization-Dependent Changes in Higher-Order Mode Responses as a Function of Transverse Beam Position in Tesla-Type Cavities at FAST 756
 
  • R.M. Thurman-Keup, D.R. Edstrom, A.H. Lumpkin, P.S. Prieto, J. Ruan
    Fermilab, Batavia, Illinois, USA
  • J.A. Diaz Cruz
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz, B.T. Jacobson, J.P. Sikora, F. Zhou
    SLAC, Menlo Park, California, USA
 
  Funding: FNAL supported by U.S. Department of Energy, Office of Science, under contract DE-AC02-07CH11359. SLAC supported by U.S. Department of Energy, Office of Science, under contract DE-AC02-76SF00515.
Higher-order modes (HOMs) in superconducting rf cavities present problems for an electron bunch traversing the cavity in the form of long-range wakefields from previous bunches. These may dilute the emittance of the macropulse average, especially with low emittance beams at facilities such as the European X-ray Free-electron Laser (XFEL) and the upgraded Linac Coherent Light Source (LCLS-II). Here we present observations of HOMs driven by the beam at the Fermilab Accelerator Science and Technology (FAST) facility. The FAST facility features two independent TESLA-type cavities (CC1 and CC2) after a photocathode rf gun followed by an 8-cavity cryomodule. The HOM signals were acquired from cavities using bandpass filters of 1.75 ± 0.15 GHz, 2.5 ± 0.2 GHz, and 3.25 ± 0.2 GHz and recorded using an 8-GHz, 20 GSa/s oscilloscope. The frequency resolution obtained is sufficient to separate polarization components of many of the HOMs. These HOM signals were captured from CC1 and cavities 1 and 8 of the cryomodule for various initial trajectories through the cavities, and we observe correlations between trajectory, HOM signals, and which polarization component of a mode is affected.
 
poster icon Poster MOPAB232 [2.144 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB232  
About • paper received ※ 20 May 2021       paper accepted ※ 25 May 2021       issue date ※ 10 August 2021  
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MOPAB289 Machine Learning Training for HOM reduction and Emittance Preservation in a TESLA-type Cryomodule at FAST 916
 
  • J.A. Diaz Cruz
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz, A.L. Edelen, B.T. Jacobson, J.P. Sikora
    SLAC, Menlo Park, California, USA
  • D.R. Edstrom, A.H. Lumpkin, R.M. Thurman-Keup
    Fermilab, Batavia, Illinois, USA
 
  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.  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB289  
About • paper received ※ 19 May 2021       paper accepted ※ 09 June 2021       issue date ※ 14 August 2021  
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MOPAB290 Machine Learning-Based LLRF and Resonance Control of Superconducting Cavities 920
 
  • J.A. Diaz Cruz, S. Biedron, M. Martínez-Ramón
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz
    SLAC, Menlo Park, California, USA
  • R. Pirayesh
    UNM-ME, Albuquerque, New Mexico, USA
  • S. Sosa
    ODU, Norfolk, Virginia, USA
 
  Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of High Energy Physics, under award number DE-SC0019468.
Superconducting radio frequency (SRF) cavities with high loaded quality factors that operate in continuous wave (CW) and low beam loading are sensitive to microphonics-induced detuning. Cavity detuning can result in an increase of operational power and/or in a cavity quench. Such SRF cavities have bandwidths on the order of 10 Hz and detuning requirements can be as tight as 10 Hz. Passive methods to mitigate vibration sources and their impact in the cryomodule/cavity environment are widely used. Active resonance control techniques that use stepper motors and piezoelectric actuators to tune the cavity resonance frequency by compensating for microphonics detuning have been investigated. These control techniques could be further improved by applying Machine Learning (ML), which has shown promising results in other particle accelerator control systems. In this paper, we describe a Low-level RF (LLRF) and resonance control system based on ML methods that optimally and adaptively tunes the control parameters. We present simulations and test results obtained using a low power test bench with a cavity emulator.
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB290  
About • paper received ※ 03 June 2021       paper accepted ※ 11 June 2021       issue date ※ 29 August 2021  
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MOPAB323 Commissioning of the LCLS-II Prototype HOM Detectors with Tesla-Type Cavities at Fast 996
 
  • J.P. Sikora, J.A. Diaz Cruz, B.T. Jacobson
    SLAC, Menlo Park, California, USA
  • J.A. Diaz Cruz
    UNM-ECE, Albuquerque, USA
  • D.R. Edstrom, A.H. Lumpkin, P.S. Prieto, J. Ruan, R.M. Thurman-Keup
    Fermilab, Batavia, Illinois, USA
 
  Funding: *Work supported by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy. **Work supported by the U.S. Department of Energy, contract DE-AC02-76SF00515.
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.
 
poster icon Poster MOPAB323 [2.076 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB323  
About • paper received ※ 17 May 2021       paper accepted ※ 07 June 2021       issue date ※ 14 August 2021  
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TUPAB272 Observation of Long-Range Wakefield Effects Generated in an Off-Resonance Tesla-Type Cavity 2101
 
  • A.H. Lumpkin, D.R. Edstrom, A. Lunin, P.S. Prieto, J. Ruan, R.M. Thurman-Keup
    Fermilab, Batavia, Illinois, USA
  • J.A. Diaz Cruz
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz, B.T. Jacobson, J.P. Sikora
    SLAC, Menlo Park, California, USA
 
  Funding: Work supported by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics
The interest in controlling emittance dilution effects due to off-axis beam transport in accelerator cavities and the resulting dipolar modes is especially important for the facilities with lower emittance beams. The Fermilab Accelerator Science and Technology (FAST) facility has a unique configuration of two single cavities after the photocathode rf gun followed by a cryomodule. The second capture cavity (CC2) was run 15 kHz off resonance and without rf power while a 25-MeV beam was injected into it. The beam centroid effects were tracked by 10 rf button BPMs with bunch-by-bunch position readout capability downstream in a 12-m drift. Possible LRW effects seemed to dominate our previously observed near-resonant HOM effects at mode 14 in this cavity. This mode also shifted in frequency compared to that of the tuned case based on direct measurements. Submacropulse vertical position slewing of 1400 microns at 11 m downstream was observed with a 125 pC/bunch, 50 bunches per macropulse, and 25-MeV beam. The y-position slew amplitudes as a function of z were also measured. Horizontal positions also showed a slew effect. Both are emittance-dilution effects which one wants to mitigate.
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB272  
About • paper received ※ 18 May 2021       paper accepted ※ 09 June 2021       issue date ※ 20 August 2021  
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TUPAB273 Observations on Submicropulse Electron-Beam Effects From Short-Range Wakefields in Tesla-Type Superconducting Rf Cavities 2105
 
  • A.H. Lumpkin, D.R. Edstrom, P.S. Prieto, J. Ruan, R.M. Thurman-Keup
    Fermilab, Batavia, Illinois, USA
  • J.A. Diaz Cruz
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz, A.L. Edelen, B.T. Jacobson, F. Zhou
    SLAC, Menlo Park, California, USA
 
  Funding: Work supported by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.
In previous experiments at the Fermilab Accelerator Science and Technology (FAST) facility, the effects of higher-order modes (HOMs) in TESLA-type cavities on submacropulse centroid motion were elucidated*. We now have extended our investigations to short-range wakefields (SRWs) in these cavities. The latter result in submicropulse effects where the transverse wakefields cause head-tail centroid shifts. We used a Hamamatsu C5680 UV-visible synchroscan streak camera to synchronously sum the OTR from each of the 50 micropulses in the macropulse. We generated the y-t effect in the 41-MeV beam by purposely steering the beam off axis in y at the entrance of the first capture cavity. The head-tail transverse kicks within the 11-ps-long micropulses of 500 pC each were observed at the 100-micron level for steering off-axis in one cavity and several 100 microns for two cavities. These SRW results will be compared to simulations from the ASTRA model of a single micropulse in FAST. Since the SRW kicks go inversely with energy, these emittance-dilution effects are particularly relevant to the LCLS-II injector commissioning plans where <1 MeV beam will be injected into a TESLA-type cryomodule.
* A.H. Lumpkin et al, Phys. Rev. Accel. and Beams 23, 054401 (2020).
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB273  
About • paper received ※ 18 May 2021       paper accepted ※ 09 June 2021       issue date ※ 28 August 2021  
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TUPAB274 Investigations of Long-Range Wakefield Effects in a TESLA-type Cryomodule at FAST 2109
 
  • A.H. Lumpkin, D.R. Edstrom, P.S. Prieto, J. Ruan, R.M. Thurman-Keup
    Fermilab, Batavia, Illinois, USA
  • J.A. Diaz Cruz
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz, B.T. Jacobson, J.P. Sikora, F. Zhou
    SLAC, Menlo Park, California, USA
 
  Funding: *Work supported by Fermi Research Alliance, LLC under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics.
The preservation of low emittance of electron beams during transport in the accelerating structures of large facilities is an ongoing challenge. In the cases of the TESLA-type superconducting rf cavities currently used in the European X-ray Free-electron Laser (XFEL) and the under-construction Linac Coherent Light Source upgrade (LCLS-II), off-axis beam transport may result in emittance dilution due to transverse long-range wakefields (LRWs) and short-range wakefields (SRW)***. To investigate such effects, experiments were performed at the Fermilab Accelerator Science and Technology (FAST) facility with its unique configuration of two TESLA-type cavities after the photocathode rf gun followed by an 8-cavity cryomodule CM). We generated beam trajectory changes with the H/V125 corrector set located 4 m upstream of the cryomodule. At 125 pC/bunch, 50 bunches, 25-MeV input, and 100-MeV exit energy, we observed for the first time submacropulse position slews of up to 500 microns at locations ~3 m after the CM and a centroid oscillation at a difference frequency of 240 kHz further downstream. Both are emittance-dilution effects which we mitigated with selective upstream beam steering.
***W.K.H. Panofsky and M. Bander, Rev. Sci. Instr. 39, 206 (1968).
 
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB274  
About • paper received ※ 18 May 2021       paper accepted ※ 09 June 2021       issue date ※ 31 August 2021  
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THPAB268 Hierarchical Intelligent Real-Time Optimal Control for LLRF Using Time Series Machine Learning Methods and Transfer Learning 4329
 
  • R. Pirayesh, S. Biedron
    UNM-ME, Albuquerque, New Mexico, USA
  • S. Biedron, J.A. Diaz Cruz, M. Martínez-Ramón
    UNM-ECE, Albuquerque, USA
  • J.A. Diaz Cruz
    SLAC, Menlo Park, California, USA
 
  Funding: supported by DOE, Office of Science, Office of High Energy Physics, under award number DE-SC0019468, Contract No. DE-AC02-76SF00515, also supported Office of Basic Energy Sciences. ALCF, Element Aero
Machine learning (ML) has recently been applied to Low-level RF (LLRF) control systems to keep the voltage and phase of Superconducting Radiofrequency (SRF) cavities stable within 0.01 degree in phase and 0.01% amplitude as constraints. Model predictive control (MPC) uses an optimization algorithm offline to minimize a cost function with constraints on the states and control input. The surrogate model optimally controls the cavities online. Time series deep ML structures including recurrent neural network (RNN) and long short-term memory (LSTM) can model the control input of MPC and dynamics of LLRF as a surrogate model. When the predicted states diverge from the measured states more than a threshold at each time step, the states’ measurements from the cavity fine-tune the surrogate model with transfer learning. MPC does the optimization offline again with the updated surrogate model, and, next, transfer learning fine-tunes the surrogate model with the new data from the optimal control inputs. The surrogate model provides us with a computationally faster and accurate modeling of MPC and LLRF, which in turn results in a more stable control system.
Machine learning, Surrogate model, control, LLRF, MPC, Transfer learning
 
poster icon Poster THPAB268 [0.377 MB]  
DOI • reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-THPAB268  
About • paper received ※ 16 May 2021       paper accepted ※ 13 July 2021       issue date ※ 18 August 2021  
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