| Paper | Title | Page |
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| TUPOST001 | Parasitic Optimization of the Transfer Beamline Efficiency at ELSA | 835 |
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| The 3.2 GeV electron accelerator ELSA in Bonn consists of three acceleration stages each interconnected by tunable transfer beamlines. The steering of the electron beam through the transfer line from linear accelerator to the Booster Synchrotron is currently adjusted by hand, which limits a systematic improvement of the transfer efficiency. An automated optimization using the ‘‘simulated annealing’’ technique has been developed and integrated into the control system to improve the situation. It allows for a continuous optimization without interfering with usual beamtime for experiments by utilizing the 6s off-time in between injections into the stretcher ring. In a simulation using the actual accelerator’s settings as starting parameters, transmission rates have been increased significantly. The methods and results with the accelerator hardware are presented. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST001 | |
| About • | Received ※ 06 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 16 June 2022 | |
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| TUPOST002 | Upgrade of the 25 MW RF Station for the Linear Accelerator LINAC2 at ELSA | 838 |
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| At the Electron Stretcher Facility ELSA in Bonn the first acceleration stage consists of a 3 GHz traveling wave linear accelerator. It was powered by a 25 MW pulsed high power klystron amplifier, which had been in use for the last thirty years. After a major failure and due to the lack of spare part availability the RF station was rebuilt. In addition to a new klystron including its high voltage tank, the new setup also consists of major upgrades of the infrastructure, the pulse forming network and the safety interlocks to satisfy the contemporary requirements. A new monitoring system consisting of multi-channel sampling ADCs allows for automatic pulse-by-pulse analysis of the klystron parameters and simultaneous evaluation of RF performance and stability. In this contribution we will present the new RF station setup, which has successfully been operating since the beginning of 2021 as well as the new monitoring capabilities. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST002 | |
| About • | Received ※ 04 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 03 July 2022 | |
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| TUPOST005 | RF Voltage Calibration Using Phase Space Tomography in the CERN SPS | 841 |
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| Voltage calibration using longitudinal phase-space tomography is a purely beam-based technique to determine the effective RF voltage experienced by a bunch. It was applied in the SPS, separately to each of its six accelerating travelling wave structures. A low spread in voltage errors was obtained by carefully optimizing the number of acquired bunch profiles. The technique moreover provided the relative phases of the cavities, which allowed their alignment to be checked. Pairs of cavities were measured as well to validate the consistency of the single-cavity voltages. The beam measurements were repeated after several months to confirm the reproducibility of the results. Longitudinal beam dynamics simulations, including the full SPS impedance model, were performed as a benchmark. The aim was to verify that the effect of the cable transfer-function on the bunch profiles can be neglected, as well as collective effects and small errors in the accelerator parameters. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST005 | |
| About • | Received ※ 30 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 25 June 2022 | |
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| TUPOST006 | Frequency-Dependent RF Voltage Calibration Using Longitudinal Tomography in the CERN PSB | 845 |
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| Longitudinal phase-space tomography reconstructs the phase-space distribution from a set of bunch profiles and the accelerator parameters, which includes the RF voltage. The quality of the reconstruction depends on the accuracy to which these parameters are known. Therefore, it can be used for beam-based RF voltage calibration by analysing oscillations of a mismatched bunch. The actual RF voltage may be different from the programmed one due to uncertainties of the electrical gap voltage measurements and intensity effects. Tomography-based RF voltage calibration was systematically performed with low-intensity bunches in all four rings of the PS Booster (PSB) at injection and extraction energy. For each of the three RF cavities present in a given ring, the calibration was performed separately to extract the voltage errors while avoiding any influence of phase misalignments. The number of synchrotron oscillation periods available for the voltage calibration was constrained by the short duration of the PSB flat-bottom and top. Longitudinal beam dynamics simulations using the full PSB impedance model were performed to benchmark the results provided by the calibrations. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST006 | |
| About • | Received ※ 30 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 14 June 2022 | |
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| TUPOST007 | New Generation of Very Low Noise Beam Position Measurement System for the LHC Transverse Feedback | 849 |
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| Recent studies showed that the transverse feedback system noise floor in the Large Hadron Collider (LHC) must be reduced by at least factor of two in order to operate the machine with large beam-beam tune shift as foreseen in the High Luminosity (HL) LHC. Also, the future feedback system foreseen to suppress the LHC Crab Cavity noise relies on improved noise performance of the beam position measurement system. An upgrade program was launched to lower the LHC transverse feedback system noise floor during the LHC Long Shutdown II. A new generation, very low noise beam position measurement module was developed and tested with beam. Innovative methods in the RF receiver, digital signal processing, thorough optimization of every element in the signal chain from pickup to the kickers allowed to achieve a significant reduction of the system noise floor. This unprecedented noise performance opens also new possibilities for auxiliary instruments, using the position data from the transverse feedback. The paper presents the new system, notable implementation details and measured performance. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST007 | |
| About • | Received ※ 18 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 30 June 2022 | |
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| TUPOST008 | Digital Low-Level RF System for the CERN Linac3 Accelerator | 853 |
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| A major consolidation of the aging RF system of the CERN Linac3, the ion source for the whole CERN accelerator chain, started during the Long Shutdown II. The main changes were an upgrade of the analogue Low-Level RF system (LLRF) and replacement of the 350 kW tube amplifiers by a solid-state equivalent. The state-of-the-art digital LLRF system enabled new sophisticated features in field manipulations, significantly increased the operational flexibility and improved operational reliability and availability. The paper presents the new architecture, a low noise master clock generator, digital signal processing with direct sampling of the RF signals, pulse parameter measurement or cavity resonance control. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST008 | |
| About • | Received ※ 27 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 15 June 2022 | |
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| TUPOST009 | Online Correction of Laser Focal Position Using FPGA-Based ML Models | 857 |
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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 Numbers DE-SC 00259037 and DE-AC02-05CH11231. High repetition-rate, ultrafast laser systems play a critical role in a host of modern scientific and industrial applications. We present a prototype diagnostic and correction scheme for controlling and determining laser focal position at 10 s of Hz rate by utilizing fast wavefront sensor measurements from multiple positions to train a focal position predictor. This predictor is used to determine corrections for actuators along the beamline to provide the desired correction to the focal position on millisecond timescales. Our initial proof-of-principle demonstrations leverage pre-compiled data and pre-trained networks operating ex-situ from the laser system. We then discuss the application of a high-level synthesis framework for generating a low-level hardware description of ML-based correction algorithms on FPGA hardware coupled directly to the beamline. Lastly, we consider the use of remote computing resources, such as the Sirepo scientific framework* , to actively update these correction schemes and deploy models to a production environment. * M.S. Rakitin et al., "Sirepo: an open-source cloud-based software interface for X-ray source and optics simulations", Journal of Synchrotron Radiation 25, 1877-1892 (Nov 2018). |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST009 | |
| About • | Received ※ 20 May 2022 — Revised ※ 14 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 23 June 2022 | |
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| TUPOST011 | Simulation Studies of Intra-Train, Bunch-by-Bunch Feedback Systems at the International Linear Collider | 861 |
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| The International Linear Collider (ILC) is a proposed electron-positron collider targeting collision energies from 250 GeV to 1 TeV. With design luminosities of order 1034 cm2s-1, a beam-based, intra-train feedback system would be required near the Interaction Point (IP) to provide nanometre-level stabilisation of the beam overlap in the collisions. Here we present results from beam-tracking simulations of the 500 GeV ILC, including the impact of beam-trajectory imperfections on the luminosity, and the capability of the IP feedback system to compensate for them. Effects investigated include the position jitter introduced by the damping ring extraction kicker, short-range and long-range wakefields, and ground motion. The feedback system was shown to be able to correct for beam-beam offsets of up to 200 nm and stabilise the collision overlap to the nanometre level, within a few bunch crossings. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST011 | |
| About • | Received ※ 03 June 2022 — Revised ※ 11 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 22 June 2022 | |
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| TUPOST012 | Sirius Storage Ring RF Plant Identification | 865 |
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| The design configuration of the Sirius Light Source RF System is based on two superconducting RF cavities and eight 65 kW solid-state amplifiers operating at 500 MHz. The current configuration, based on a 7-cell normal conducting PETRA cavity, was initially planned for commissioning and initial tests of the beamlines. A digital low-level RF (DLLRF) system based on ALBA topology has been operating since 2019. Sirius is currently operating in decay mode for beamline tests with 100 mA stored current. During the commissioning, several studies were carried out to increase the stored current with stable beam. This paper presents a study using parametric data-driven models to identify the Storage Ring RF plant, aiming to optimize the DLLRF PI control parameters. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST012 | |
| About • | Received ※ 08 June 2022 — Accepted ※ 23 June 2022 — Issue date ※ 01 July 2022 | |
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| TUPOST013 | Concept and Development of 65 kW Solid-State RF Amplifiers for Sirius | 868 |
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| Sirius is a 4th generation synchrotron light source currently operating with 100 mA stored beam and one room temperature RF cavity driven by two 65 kW solid-state amplifiers (SSAs). After installation of the cryogenic plant, two superconducting (SC) RF cavities are planned to replace the room temperature cavity. Each SC cavity is going to be driven by a 250 kW RF signal at 500 MHz, resulting from the combination of four 65 kW RF SSAs. Due to the recent development of 900 W solid-state power amplifier modules, a new topology is proposed for the four amplifiers that still need to be constructed. For the amplifier’s combining stage, a cavity combiner with 80 input ports was simulated. For the dividing stage, 8-way and 10-way power splitters were designed. The general scheme of the amplifier is presented, as well as simulation and measurement results. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST013 | |
| About • | Received ※ 08 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 12 June 2022 — Issue date ※ 03 July 2022 | |
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| TUPOST014 | Sirius Storage Ring RF System Status Update | 872 |
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| Sirius’s nominal operation phase consists of two 500 MHz CESR-B type superconducting cavities, each being driven by four 65 kW solid-state amplifiers, and a passive superconducting third harmonic cavity. Currently a normal conducting 7-cell PETRA cavity is being used along with two 65 kW RF amplifiers and was recently able to achieve 100 mA stored current. The performance of the storage ring RF system and the updated installation plans update are presented and discussed. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST014 | |
| About • | Received ※ 08 June 2022 — Revised ※ 10 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 23 June 2022 | |
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| TUPOST015 | Commissioning and First Results of an X-Band LLRF System for TEX Test Facility at LNF-INFN | 876 |
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Funding: Latino is a project co-funded by Regione Lazio within POR-FESR 2014-2020 program In the framework of LATINO project (Laboratory in Advanced Technologies for INnOvation) funded by Lazio regional government, the commissioning of the TEst stand for X-band (TEX) facility has started in 2021 at Frascati National Laboratories of INFN. Born as a collaboration with CERN to test high gradient accelerating structures, during 2022 TEX aims at feeding the first EuPRAXIA@SPARC_LAB X-band structure prototype. During 2021 the commissioning has been successfully carried out up to 48 MW. The power unit is driven by an X-band low level RF system, that employs a commercial S-band (2.856 GHz) Libera digital LLRF (manufactured by Instrumentation Technologies), with an up/down conversion stage and a reference generation and distribution system able to produce coherent frequencies for the American S-band and European X-band (11.994 GHz), both designed and realized at LNF. The performance of the system, with a particular focus on amplitude and phase resolution, together with klystron and driver amplifier jitter measurements, will be reviewed in this paper. Moreover, considerations on its suitability and main limitations in view of EuPRAXIA@SPARC_LAB project will be discussed. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST015 | |
| About • | Received ※ 20 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 28 June 2022 | |
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| TUPOST016 | Status of LLRF and Resonance Control Dedicated Algorithms Extension for PolFEL | 880 |
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| PolFEL (POLish Free Electron Laser) is the new super-conducting based facility, which is under construction in Poland. It will provide a continuous electron beam with energy up to 160 MeV, which will be converted to light pulses with wavelengths as short as 150 nm. CW (Continuous Wave) operation of the superconducting linear accelerator with narrow bandwidth and high electromagnetic field gradient (presumably above 30 MV/m for single structure) creates new challenges while dealing with RF field stability, the influence of mechanical de-tuning of resonating structures and must take into account all limits induced by power amplifiers and cryo-system. The real-time control algorithm responsible for RF field, motor tuners, and piezo control must strictly interact with each other to provide the satisfactory performance of the whole facility. In addition, constant monitoring of such parameters as detuning, bandwidth, power margins of the amplifier, state of cavities must be done. The paper presents the current status of implementation of PolFEL’s LLRF Controller (extending GDR to other modes of operation as SEL, PLL) and Piezo Controller (both hardware and firmware layers). | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST016 | |
| About • | Received ※ 08 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 03 July 2022 | |
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| TUPOST017 | PEG Contribution to the LLRF System for Superconducting Elliptical Cavities of ESS Accelerator Linac | 884 |
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| The LLRF (Low-Level Radio Frequency) system optimizes energy transfer from the superconducting resonator to the accelerating beam. At ESS, one LLRF system regulates a single cavity. This digital system’s HW platform is the MTCA.4 standard. The system has been co-designed by ESS, Lund University, and the PEG (Polish Electronic Group) consortium. The PEG is also responsible for the system components design, evaluation, and production (like Local Oscillator Rear transition module, piezo tuner driver RTM, RTM carrier board, and others). The PEG delivers a HW/SW cavity simulator, an LLRF system test-stand, and provides necessary integration and installation services required for complete system preparation for the linac commissioning and operation phase. The paper summarizes the PEG work on the development and preparation of the LLRF systems for the ESS elliptical structures. The efforts concerning hardware and software components prototyping and evaluation are discussed. Moreover, we present the current status of the project, including components mass production, integration, and installation work. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST017 | |
| About • | Received ※ 08 June 2022 — Revised ※ 16 June 2022 — Accepted ※ 19 June 2022 — Issue date ※ 20 June 2022 | |
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| TUPOST018 | Long Pulse Operation of the E-XFEL Cryomodule | 888 |
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| The CW operation becomes more attractive mode of beam and RF operation, even for infrastructures initially developed as pulsed experiments. Compared to the short (single ms) pulse the CW or long pulse (LP) operation allows for a more relaxed bunch scheme and enables higher bunch quantities during the experiment run. The Long Pulse operation scenario is one of the possible EXFEL modes of work in the future. LLRF systems that work in CW (and LP) are in operation worldwide. Most of them are dedicated to single cavity control. The XFEL dedicated system is capable of multicavity cryomodules vector-sum operation. In such a configuration switching from short-pulse operation into long-pulse with the existing limitations from the allowed cryo heat load level, average input power per coupler (and others) can be extremely challenging. For this setup the support from the dynamic resonance control system is essential. This paper summarizes efforts towards the successful vector-sum operation of the X-FEL type cryomodule in the LP operation mode. Modifications to the original LLRF setup together with challenges of narrow bandwidth operation in moderate and high gradients are discussed. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST018 | |
| About • | Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 21 June 2022 — Issue date ※ 23 June 2022 | |
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| TUPOST019 | Evaluation of PIP-II Master Oscillator Components | 892 |
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Funding: The paper was prepared by WUT and PIP-II, using the resources of Fermilab, a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is acting under Contract No. DE-AC02-07CH11359. The Proton Improvement Plan-II (PIP-II) is a planned proton facility at Fermilab. The short- and long-term beam energy stabilization requirements necessitate using a high-quality Master Oscillator (MO). The consecutive sections of the Linac will operate at 162.5, 325, and 650 MHz. The phase relations between reference signals of harmonic frequencies should be kept constant, and the phase noise should be correlated in a wide bandwidth. The possibility of simultaneously meeting both requirements using popular frequency synthesis schemes is discussed. The ultra-low noise floor of the fundamental source is challenging for other devices in the phase reference distribution system. Therefore, the sensitivity to operating conditions, including impedance matching, input power level, and power supply voltage, must be considered. This paper presents a preliminary performance test of critical components selected for the PIP-II Master Oscillator system performed using a state-of-the-art phase noise analyzer. The paper was prepared by WUT and PIP-II, using the resources of Fermilab, a U.S. Department of Energy, Office of Science, HEP User Facility. Fermilab is acting under Contract No. DE-AC02-07CH11359. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST019 | |
| About • | Received ※ 08 June 2022 — Revised ※ 16 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 23 June 2022 | |
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| TUPOST021 | The CERN SPS Low Level RF: The Beam-Control | 895 |
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| The Super Proton Synchrotron (SPS) Low Level RF (LLRF) has been completely upgraded during the CERN long shutdown (LS2, 2019-2020). The old NIM and VME based, mainly analog system has been replaced with modern digital electronics implemented on a MicroTCA platform. The architecture has also been reviewed, with synchronization between RF stations now resting on the White Rabbit (WR) deterministic link. This paper is the first of a series of three on the SPS LLRF upgrade. It covers the Beam-Control part, that is responsible for the generation of the RF reference frequency from a measurement of the magnetic field, and beam phase and radial position. It broadcasts this frequency word to the RF stations, via a White Rabbit network. The paper presents the architecture, gives details on the signal processing, firmware, hardware and software. Finally, results from the first year of beam commissioning are presented (2021). | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST021 | |
| About • | Received ※ 07 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 05 July 2022 | |
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| TUPOST022 | The CERN SPS Low Level RF: Lead Ions Acceleration | 899 |
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| This paper is the third of a series of three on the Super Proton Synchrotron (SPS) Low Level RF (LLRF). Its focus is the upgrade concerned with the acceleration of Lead ions for injection into the LHC. Lead ions are far from relativistic at injection into the SPS. Therefore, the classic acceleration scheme at constant harmonic number (h=4620) does not work as the RF frequency swing does not fit within the cavity bandwidth. Fixed Frequency Acceleration (FFA) is therefore used. The upgraded LLRF uses a completely new implementation of the FFA, based on a Numerically Controlled Oscillator (NCO) implemented as an FPGA IP in the Controller of each cavity. In addition, the 2022 scheme for LHC ions filling calls for slip stacking of two families of bunches, 100 ns spacing, to generate a 50 ns spacing after interleaving. The paper presents the key components for FFA and ions slip stacking as implemented in the new system, together with successful first tests performed in Autumn 2021. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST022 | |
| About • | Received ※ 08 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 24 June 2022 | |
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| TUPOST023 | The CERN SPS Low level RF: The Cavity-Controller | 903 |
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| This paper is the second of a series of three on the Super Proton Synchrotron (SPS) Low Level RF (LLRF) upgrade. It covers the 200MHz Cavity-Controller part, that is responsible for the regulation of the accelerating field in a single SPS cavity. When the SPS is used as Large Hadron Collider (LHC) proton injector, the issue is the high beam loading that must be compensated to guarantee longitudinal stability and constant parameters over the bunch train. That calls for strong One-Turn Delay Feedback (OTFB) and Feed-Forward (FFWD). The SPS is also accelerating Lead ions (Pb). There the issue is Frequency-Modulation (FM) and Amplitude-Modulation (AM) over the turn (so called Fixed Frequency Acceleration - FFA) plus RF gymnastics for the new ions slip-stacking. The paper reviews the functional requirements, presents the block diagram, then gives details on the signal processing, firmware and hardware. Finally results from the first year of beam commissioning are presented (2021). | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST023 | |
| About • | Received ※ 07 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 19 June 2022 | |
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| TUPOST024 | A New Beam Loading Compensation and Blowup Control System Using Multi-Harmonic Digital Feedback Loops in the CERN Proton Synchrotron Booster | 907 |
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| As part of the LHC Injectors Upgrade, the CERN Proton Synchrotron Booster (PSB) has been upgraded with new wide-band Finemet cavities and a renovated Low-Level Radio Frequency system with digital cavity controllers implemented in FPGAs. Each controller synchronously receives the computed revolution frequency, used to generate 16 harmonic references. These are then used to IQ demodulate the voltage gap and modulate the 16 RF drive signals each controlled through a Cartesian feedback loop (with individual voltage and phase control). The sum of these digital drive signals is then sent to the cavities. In addition, a configurable blow-up system providing a sinusoidal or custom noise pattern can be used to excite the beam. An embedded network analyzer allows studying the stability of the feedback loops of the individual harmonics. The 16 harmonic feedback loops have been successfully operated during 2021, allowing to reduce the beam induced voltage and control the longitudinal emittance of the beam. In this paper we present the system architecture as well as the performance of the complete cavity controller during operation in the PSB. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST024 | |
| About • | Received ※ 23 May 2022 — Revised ※ 14 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 28 June 2022 | |
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| TUPOST025 | Beam Commissioning of the New Digital Low-Level RF System for CERN’s AD | 911 |
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| CERN’s Antiproton Decelerator (AD) has been re-furbished to provide reliable operation for the Extra Low ENergy Antiproton ring (ELENA). In particular, AD was equipped with a new digital Low-Level RF (LLRF) system that was successfully commissioned during the summer 2021. The new AD LLRF system has routinely captured and decelerated more than 3·107 antiprotons from 3.5 GeV/c to 100 MeV/c in successive steps, referred to as RF segments, interleaved by cooling periods. The LLRF system implements the frequency program from Btrain data received over optical fiber. Beam phase/radial and cavity amplitude/phase feedback loops are operated during each RF segment. An extraction synchronization loop is triggered on the extraction RF segment to transfer a single bunch of antiprotons to ELENA. Extensive diagnostics features are available and operational modes such as bunched beam cooling and bunch rotation have been successfully deployed. The LLRF parameters can be different for each RF segment and are controlled by a dedicated application. This paper gives an overview of the AD LLRF beam commissioning results obtained and challenges overcome. Hints on future steps are also provided. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST025 | |
| About • | Received ※ 25 May 2022 — Accepted ※ 15 June 2022 — Issue date ※ 17 June 2022 | |
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| TUPOST027 | Machine Learning-Based Tuning of Control Parameters for LLRF System of Superconducting Cavities | 915 |
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| The multiple systems involved in the operation of particle accelerators use diverse control systems to reach the desired operating point for the machine. Each system needs to tune several control parameters to achieve the required performance. Traditional Low-Level RF (LLRF) systems are implemented as proportional-integral feedback loops, whose gains need to be optimized. In this paper, we explore Machine Learning (ML) as a tool to improve a traditional LLRF controller by tuning its gains using a Neural Network (NN). We present the data production scheme and a control parameter optimization using a NN. The NN training is performed using the THETA supercomputer. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST027 | |
| About • | Received ※ 14 June 2022 — Revised ※ 15 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 20 June 2022 | |
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| TUPOST029 | Small Talk on AT | 918 |
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| Tracy 3 ’ was implemented by the 3rd author by pursuing a first principles approach, aka Hamiltonian dynamics for an on-line modeel to guide the ALS and LBL comissioning in the early 1990s. with its origin as a Hamiltonian based pascal online model used 90 ’ is the core of today’s accelerator tool box. These Hamiltonians have not been changed. Soft- ware design has evolved since then: C++ and in particular its standardisation C++11 and C++2xa. In this paper we out- line our strategy of modernisation of tracy: reorganisation of the beam dynamics library in cleanly designed modules, using well proven open-source libraries (GSL, armadillo) and so on. Furthermore, Python and Matlab Interfaces based on modern tools are being pursued. We report on the in- terface design, the status of modernisation. This project has been renamed to thor-scsi-lib and is available at Github. Collaboration’s welcome. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST029 | |
| About • | Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 28 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST031 | Online Optimization of the Transfer Line from UNILAC towards SIS18 at GSI Using a Genetic Autotune Algorithm | 922 |
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| Due to the complexity of GSI’s accelerator facilities and it’s upcoming expansion FAIR, various methods for optimizing accelerator settings are currently being studied to increase efficiency and to minimize the need for manual intervention. Besides a necessary improvement of the accelerator models, a better reproducibility of settings and the development of feedback systems, also heuristic methods are in the focus of the investigation. This work presents the results, recently achieved in optimizing the transfer line from UNILAC to SIS18 using the Autotune algorithm. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST031 | |
| About • | Received ※ 18 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 14 June 2022 — Issue date ※ 17 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST032 | SLS 2.0, the Upgrade of the Swiss Light Source | 925 |
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The Swiss Light Source (SLS) will be upgraded by replacing the storage ring in the existing hall in 2023–24. The SLS lattice build from 12~triple-bend arcs operating at 2.4 GeV is replaced by a 12x7-BA lattice operating at 2.7 GeV to increase hard X-ray brightness by a factor 60. The layout is constrained by the existing tunnel to 288 m circumference, nevertheless a low emittance of 158 pm is realized using longitudinal gradient and reverse bends. Dynamic aperture is sufficient to start with classical injection based on a 4-kicker bump. An upgrade path for on-axis injection with fast kickers has been implemented. Small beam pipes of 18 mm inner diameter and corresponding reduction of magnet bores, and the use of permanent magnets for all bending magnets enables a densely packed lattice and contributes most to a reduction of total power consumption of the facility by 30%.
On behalf of the SLS 2.0 Team. Technical Design Report: https://www.dora.lib4ri.ch/psi/islandora/object/psi%3A39635 |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST032 | |
| About • | Received ※ 16 May 2022 — Accepted ※ 16 June 2022 — Issue date ※ 29 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST033 | A Python Framework for High-level Applications in Accelerator Operations | 929 |
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| A Python graphical framework providing reusable components to facilitate the development of accelerator applications, that meet the basic requirements of experts and operators alike, is presented. Such a collective approach serves to bridge the gap between the expert developer and the operational team, resulting in applications that are inherently cohesive, durable and easily navigable. The operational advantages and underlying principles are exemplified in a reference application that provides executable examples of customary practices, and further highlights several composite and control system-enabled widgets. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST033 | |
| About • | Received ※ 16 May 2022 — Revised ※ 19 May 2022 — Accepted ※ 16 June 2022 — Issue date ※ 28 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST035 | BOLINA, a Suite for High Level Beam Optimization: First Experimental Results on the Adige Injection Beamline of SPES | 933 |
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| A high-level software BOLINA (Beam Orbit for LINear Accelerators) has been designed to fully characterise and automatically correct the ion beams trajectory, to help operators during the beam transport with an easily scalable suite for LINACs. Currently, the high-level software, interfaced with an EPICS control system, automatically manages accelerator devices to preserve the beam quality, including beam-based alignment and, if needed, dispersion-free steering software. The suite has been developed to satisfy and commutate the software easily on different machine, using interceptive /not interceptive diagnostics. The software was designed for ELI-np and now is under test at Legnaro National Laboratories of INFN using the installed accelerators complex. In particular, BOLINA has been successfully tested on the Adige Injector 1+ beamline of the SPES Project where the system response matrix is measured on interceptive beam diagnostic by varying both electrostatic and magnetic steerers. This paper describes results and strategies to reduce trajectory residuals close to the diagnostic resolutions and their effectiveness to prepare the commissioning of LINACs. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST035 | |
| About • | Received ※ 12 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 13 June 2022 — Issue date ※ 16 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST037 | Reconstruction of Transverse Phase Space From Transverse Feedback Data for Real Time Extraction of Vital LHC Machine Parameters | 937 |
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| The LHC transverse feedback system (ADT) provides bunch by bunch, turn by turn, normalized and digitized beam position signals from four pick-ups per plane and for each beam. Together with already existing powerful computer-based observation systems, this data can be used to reconstruct in real-time the transverse phase space coordinates of the centre-of-charges, for each individual bunch. Such information is extremely valuable for machine operation, or transverse instability diagnostics. This paper aims on discussing and evaluating methods of combining four position signals for such analysis in the presence of noise and with active transverse feedback. Comparisons are made based on the extraction of vital parameters like the fractional tune or transverse activity. Analytical and numerical results are further benchmarked against real beam data. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST037 | |
| About • | Received ※ 20 May 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 04 July 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST040 | Automated Intensity Optimisation Using Reinforcement Learning at LEIR | 941 |
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| High intensities in the CERN Low Energy Ion Ring (LEIR) are achieved by stacking up to seven consecutive multi-turn injections from Linac3. Two inclined septa combined with a collapsing horizontal orbit bump allow a 6-D phase space painting via a linearly ramped mean momentum along the Linac3 pulse and injection at high dispersion. The beam is cooled and dragged longitudinally via electron cooling (e-cooling) into a stacking momentum. For optimal accumulation, the electron energy and trajectory need to match the ion energy and orbit at the e-cooler section. In this paper, a reinforcement learning (RL) agent is trained to adjust various e-cooler and Linac3 parameters to maximise the intensity at the end of the injection plateau. Variational Auto-Encoders (VAE) are used to compress longitudinal Schottky spectra into a compact representation as input for the RL agent. The RL agent is pre-trained on a surrogate model of the LEIR e-cooling dynamics, which in turn is learned from the data collected for the training of the VAE. The performance of the VAE, the surrogate model, and the RL agent is investigated in this paper. An overview of planned tests in the upcoming LEIR runs is given. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST040 | |
| About • | Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 10 July 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST041 | Experience with Computer-Aided Optimizations in LINAC4 and PSB at CERN | 945 |
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| Accelerator optimization is routinely performed with the help of computer algorithms that fully automate these tasks. However, their efficiency, speed, and time to implement varies greatly depending on the algorithms used. In LINAC4 some of the automatic optimization routines were programmed using different algorithms to find the most suitable. We present the problems for which the computer algorithms were used and the results of our comparative study. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST041 | |
| About • | Received ※ 09 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 22 June 2022 — Issue date ※ 08 July 2022 | |
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| TUPOST042 | Towards the Automatic Setup of Longitudinal Emittance Blow-Up in the CERN SPS | 949 |
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| Controlled longitudinal emittance blow-up in the CERN SPS is necessary to stabilize high-intensity beams for the High-Luminosity LHC (HL-LHC) by increasing the synchrotron frequency spread. The process consists of injecting bandwidth-limited noise into the main RF phase loop to diffuse particles in the core of the bunch. The setting up of the noise parameters, such as frequency band and amplitude, is a non-trivial and time-consuming procedure that has been performed manually so far. In this preliminary study, several optimization methods are investigated to set up the noise parameters automatically. We apply the CERN Common Optimization Interfaces as a generic framework for the optimization algorithm. Single-bunch profiles generated with the BLonD simulation code have been used to investigate the optimization algorithms offline. Furthermore, analysis has been carried out on measured bunch profiles in the SPS to define the problem constraints and properly formulate the objective function. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST042 | |
| About • | Received ※ 31 May 2022 — Revised ※ 10 June 2022 — Accepted ※ 13 June 2022 — Issue date ※ 17 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST043 | A Novel Method for Detecting Unidentified Falling Object Loss Patterns in the LHC | 953 |
| SUSPMF100 | use link to see paper's listing under its alternate paper code | |
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| Understanding and mitigating particle losses in the Large Hadron Collider (LHC) is essential for both machine safety and efficient operation. Abnormal loss distributions are telltale signs of abnormal beam behaviour or incorrect machine configuration. By leveraging the advancements made in the field of Machine Learning, a novel data-driven method of detecting anomalous loss distributions during machine operation has been developed. A neural network anomaly detection model was trained to detect Unidentified Falling Object events using stable beam, Beam Loss Monitor (BLM) data acquired during the operation of the LHC. Data-driven models, such as the one presented, could lead to significant improvements in the autonomous labelling of abnormal loss distributions, ultimately bolstering the ever ongoing effort toward improving the understanding and mitigation of these events. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST043 | |
| About • | Received ※ 19 May 2022 — Revised ※ 15 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 21 June 2022 | |
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| TUPOST044 | Fortune Telling or Physics Prediction? Deep Learning for On-Line Kicker Temperature Forecasting | 957 |
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| The injection kicker system MKP of the Super Proton Synchrotron SPS at CERN is composed of 4 kicker tanks. The MKP-L tank provides additional kick needed to inject 26 GeV Large Hadron Collider LHC 25 ns type beams. This device has been a limiting factor for operation with high intensity, due to the magnet’s broadband beam coupling impedance and consequent beam induced heating. To optimise the usage of the SPS and avoid idle (kicker cooling) time, studies were conducted to develop a recurrent deep learning model that could predict the measured temperature evolution of the MKP-L, using the beam conditions and temperature history as input. In a second stage, the ferrite temperature is also estimated putting together the external temperature predictions from accurate thermo-mechanical simulations of the kicker magnet. In this paper, the methodology is described and details of the neural network architecture used, together with the implementation of an ad-hoc loss function, are given. The results applied to the SPS 2021 operational data are presented. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST044 | |
| About • | Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 18 June 2022 | |
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| TUPOST045 | Overview of the Machine Learning and Numerical Optimiser Applications on Beam Transfer Systems for LHC and Its Injectors | 961 |
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| Machine learning and numerical optimisation algorithms are getting more and more popular in the accelerator physics community and, thanks to the computing power available, their application in daily operation more likely. In the CERN accelerator complex, and specifically on the beam transfer systems, many promising exploitation of these numerical tools have been put in place in the last years. Some of the state-of-the-art machine learning models have been explored and used to solve problems that were never fully addressed in the past. In this paper, the most recent results of application of machine learning and numerical optimisation for injection, extraction and transfer of beam from machine and to experimental areas are presented. An overview of the possible next steps and shortcomings is finally discussed. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST045 | |
| About • | Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 10 July 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST046 | Machine Learning Applied for the Calibration of the Hard X-Ray Single-Shot Spectrometer at the European XFEL | 965 |
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| Single-crystal monochromators are used in free electron lasers for hard x-ray self-seeding, selecting a very narrow spectral range of the original SASE signal for further amplification. When rotating the crystal around the roll and pitch axes, one can exploit several symmetric and asymmetric reflections as established by Bragg’s law. This work describes the implementation of a machine learning classifier to identify the crystal indices corresponding to a given reflection, and eventually calculate the difference between the photon energy as measured by a single-shot spectrometer and the actual one. The image processing techniques to extract the properties of the crystal reflection are described, as well as how this information is used to calibrate two spectrometer parameters. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST046 | |
| About • | Received ※ 07 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 24 June 2022 — Issue date ※ 09 July 2022 | |
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| TUPOST048 | Development of a Virtual Diagnostic for Estimating Key Beam Descriptors | 969 |
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Funding: Science and Technology Facilities Council (STFC), U.K. Research and Innovation (UKRI) Real-time beam descriptive data such as emittance, envelope and loss, are central to accelerator operations, including online diagnostics, maintenance and beam quality control. However, these cannot always be obtained without disrupting user runs. Physics-based simulations, such as particle tracking codes, can be leveraged to provide estimates of these beam descriptors. However, such simulation-based methods are computationally intensive requiring access to high performance computing facilities, and hence, they are often non-realistic for real-time purposes. The proposed work explores the feasibility of using machine learning to replace these simulations with fast-executing inference models based on surrogate modelling. The approach is intended to provide the operators with estimates of key beam properties in real time. Bayesian optimisation is used to generate a synthetic dataset to ensure the input space is efficiently sampled and representative of operating conditions. This is used to train a surrogate model to predict beam envelope, emittance and loss. The methodology is applied to the ISIS MEBT as a case study to evaluate the performance of the surrogate model. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST048 | |
| About • | Received ※ 01 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 27 June 2022 — Issue date ※ 02 July 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST049 | Simulation Study for an Inverse Designed Narrowband THz Radiator for Ultrarelativistic Electrons | 973 |
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| THz radiation has many applications, including medical physics, pump-probe experiments, communications, and security systems. Dielectric grating structures can be used to generate cost-effective and beam synchronous THz radiation based on the Smith Purcell effect. We present a 3-D finite difference time domain (FDTD) simulation study for the THz radiation emitted from an inverse designed grating structure after a 3 GeV electron bunch traverses through it. Our farfield simulation results show a narrowband emission spectrum centred around 881 um, close to the designed value of 900 um. The grating structure was experimentally tested at the SwissFEL facility, and our simulated spectrum shows good agreement with the observed one. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST049 | |
| About • | Received ※ 08 June 2022 — Revised ※ 10 June 2022 — Accepted ※ 11 June 2022 — Issue date ※ 12 June 2022 | |
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| TUPOST050 | Liverpool Centre for Doctoral Training for Innovation in Data Intensive Science | 976 |
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Funding: This new Center for Doctoral Training has received funding from the UK’s Science and Technology Facilities Council. The Liverpool center for doctoral training for innovation in data intensive science (LIV. INNO) is an inclusive hub for training three cohorts of students in data intensive science. Starting in October 2022, each year will train about 12 PhD students in applying data skills to address cutting edge research challenges across astrophysics, nuclear, theoretical and particle physics, as well as accelerator science. This framework is expected to provide an ideal basis for driving science and innovation, as well as boosting the employability of the LIV. INNO PhD students. This contribution gives examples of the accelerator science R&D projects in the center. It includes details about research into the optimization of 3D imaging techniques and the characterization of photocathodes for accelerator applications. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST050 | |
| About • | Received ※ 05 June 2022 — Revised ※ 09 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 06 July 2022 | |
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| TUPOST051 | Using Data Intensive Science for Accelerator Optimization | 980 |
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Funding: This work was supported by STFC under grant agreement ST/P006752/1. Particle accelerators and light sources are some of the largest, most data intensive, and most complex scientific systems. The connections and relations between machine subsystems are complicated and often nonlinear with system dynamics involving large parameter spaces that evolve over multiple relevant time scales and accelerator systems. In 2017, the Liverpool Centre for Doctoral Training in Data Intensive Science (LIV. DAT) was established. With almost 40 PhD students, the centre is now established as an international hub for training PhD students in data intensive science. This contribution presents results from studies carried out in LIV. DAT into novel high gradient accelerators with a focus on the data science techniques that were used. This includes studies into inverse-designed narrowband THz radiators for ultra-relativistic electrons, simulation of the transverse asymmetry and inhomogeneity on seeded self-modulation of beams in plasma, as well as studies into the physical aspects of collinear laser injection in Trojan Horse laser plasma experiments. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST051 | |
| About • | Received ※ 08 June 2022 — Revised ※ 09 June 2022 — Accepted ※ 17 June 2022 — Issue date ※ 05 July 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST053 | Beam Tuning at the FRIB Front End Using Machine Learning | 983 |
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| The Facility for Rare Isotope Beams (FRIB) at Michigan State University produced and identified the first rare isotopes demonstrating the key performance parameter and completion of the project. An important next step toward FRIB user operation includes fast tuning of the Front End (FE) decision parameters to maintain optimal beam optics. The FE consists of the ion source, charge selection system, LEBT, RFQ, and MEBT. The strong coupling of many ion source parameters, strong space-charge effects in multi-component ion beams, and a not well-known neutralization factor in the beamline from the ion source to the charge selection system make the FE modeling difficult. In this paper, we present our first effort toward the Machine Learning (ML) application for automatic control of the beam exiting the FE. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST053 | |
| About • | Received ※ 09 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 26 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST054 | Experiment of Bayesian Optimization for Trajectory Alignment at Low Energy RHIC Electron Cooler | 987 |
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Funding: Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy; U.S. National Science Foundation under Award PHY-1549132, the Center for Bright Beams. As the world’s first electron cooler that uses radio frequency (rf) accelerated electron bunches, the low energy RHIC electron cooling (LEReC) system is a nonmagnetized cooler of ion beams in RHIC at Brookhaven National Laboratory. Beam dynamics in LEReC are different from the more conventional electron coolers due to the bunching of the electron beam. To ensure an efficient cooling performance at LEReC, many parameters need to be monitored and fine-tuned. The alignment of the electron and ion trajectories in the LEReC cooling sections is one of the most critical parameters. This work explores using a machine learning (ML) method - Bayesian Optimization (BO) to optimize the trajectories’ alignment. Experimental results demonstrate that ML methods such as BO can perform control tasks efficiently in the RHIC controls system. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST054 | |
| About • | Received ※ 04 June 2022 — Revised ※ 11 June 2022 — Accepted ※ 13 June 2022 — Issue date ※ 27 June 2022 | |
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| TUPOST055 | Toward Machine Learning-Based Adaptive Control and Global Feedback for Compact Accelerators | 991 |
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Funding: This work was supported by the DOE Office of Science Graduate Student Research (SCGSR) program, by the DOE Office of Basic Energy Sciences under Contract No. DE-AC02-05CH11231, … continued The HiRES beamline at Lawrence Berkeley National Laboratory (USA) is a state-of-the-art compact accelerator providing ultrafast relativistic electron pulses at MHz repetition rates, for applications in ultrafast science and for particle accelerator science and technology R&D. Using HiRES as testbed, we seek to apply recent developments in machine learning and computational techniques for machine-learning-based adaptive control, and eventually, a full control system based on global feedback. The ultimate goal is to demonstrate the benefits of such a suite of controls to UED, including increased temporal and spatial resolution. Concrete steps toward these goals are presented, including automatic, model-independent tuning for accelerators, and energy virtual diagnostics with direct application to improving UED temporal resolution. … [continued from below] by the DOE Office of Science, Office of High Energy Physics under contract number 89233218CNA000001 and DE-AC02-05CH11231 and by the NSF under Grant No. PHY-1549132. |
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| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST055 | |
| About • | Received ※ 08 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 20 June 2022 | |
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| TUPOST056 | Multi-Objective Bayesian Optimization at SLAC MeV-UED | 995 |
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| SLAC MeV-UED, part of the LCLS user facility, is a powerful ’electron camera’ for the study of ultrafast molecular structural dynamics and the coupling of electronic and atomic motions in a variety of material and chemical systems. The growing demand of scientific applications calls for rapid switching between different beamline configurations for delivering electron beams meeting specific user run requirements, necessitating fast online tuning strategies to reduce set up time. Here, we utilize multi-objective Bayesian optimization(MOBO) for fast searching the parameter space efficiently in a serialized manner, and mapping out the Pareto Front which gives the trade-offs between key beam parameters, i.e., spot size, q-resolution, pulse length, pulse charge, etc. Algorithm, model deployment and first test results will be presented. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST056 | |
| About • | Received ※ 08 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 16 June 2022 — Issue date ※ 09 July 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST058 | Badger: The Missing Optimizer in ACR | 999 |
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| Badger is an optimizer specifically designed for Accelerator Control Room (ACR). It’s the spiritual successor of Ocelot optimizer. Badger abstracts an optimization run as an optimization algorithm interacts with an environment, by following some pre-defined rules. The environment is controlled by the algorithm and tunes/observes the control system/machine through an interface, while the users control/monitor the optimization flow through a graphical user interface (GUI) or a command line interface (CLI). This paper would introduce the design principles and applications of Badger. | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST058 | |
| About • | Received ※ 08 June 2022 — Revised ※ 10 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 17 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |
| TUPOST059 | PyEmittance: A General Python Package for Particle Beam Emittance Measurements with Adaptive Quadrupole Scans | 1003 |
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| The emittance of a particle beam is a critically important parameter for many particle accelerator applications. Its measurements guide the initial tuning of an accelerator and are typically done using quadrupole or wire scans. Quadrupole scans are time-intensive, and it can be difficult to determine scan values that provide a good emittance measurement. To address this issue, we describe an adaptive quadrupole scan method that automates the determination of the scan range. With a given initial set of scanning values, our method adapts the range to capture the waist of the beam, and returns the Twiss parameters and a measure of the beam matching at the measurement screen. With the added capability to repeat beam size measurements when needed, this method provides a reliable measurement of the emittance even with sub-optimal initial conditions. To efficiently integrate these measurements into Python-based machine learning optimizations, the method was developed into a Python package, PyEmittance, at the SLAC National Accelerator Laboratory. We present the experimental tests of PyEmittance as performed at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Test (FACET-II). | ||
| DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOST059 | |
| About • | Received ※ 08 June 2022 — Revised ※ 13 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 17 June 2022 | |
| Cite • | reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml) | |