Paper | Title | Page |
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MOPAB212 | 3-D Quantum Lifetime | 700 |
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Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. The quantum lifetime of electron beam in storage rings is defined by the particle loss that caused by the aperture limitation. Based on the equilibrium beam distribution produced by radiation damping and quantum excitation, the 1-d quantum lifetime has been well studied by A. Piwinski. In this paper, we give the derivation of the 3-d quantum lifetime, which can be applied to the machines with elliptical aperture and momentum acceptance. |
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DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB212 | |
About • | paper received ※ 04 June 2021 paper accepted ※ 21 June 2021 issue date ※ 16 August 2021 | |
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TUPAB181 | Demonstration of Electron Cooling using a Pulsed Beam from an Electrostatic Electron Cooler | 1827 |
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Funding: This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under contract DE-AC05-06OR23177. Electron cooling continues to be an invaluable technique to reduce and maintain the emittance in hadron storage rings in cases where stochastic cooling is inefficient and radiative cooling is negligible. Extending the energy range of electron coolers beyond what is feasible with the conventional, electrostatic approach necessitates the use of RF fields for acceleration and, thus, a bunched electron beam. To experimentally investigate how the relative time structure of the two beams affects the cooling properties, we have set up a pulsed-beam cooling device by adding a synchronized pulsing circuit to the conventional electron source of the CSRm cooler at Institute of Modern Physics *. We show the effect of the electron bunch length and longitudinal ion focusing strength on the temporal evolution of the longitudinal and transverse ion beam profile and demonstrate the detrimental effect of timing jitter as predicted by theory and simulations. Compared to actual RF-based coolers, the simplicity and flexibility of our setup will facilitate further investigations of specific aspects of bunched cooling such as synchro-betatron coupling and phase dithering. * M. W. Bruker et al., Phys. Rev. Accel. Beams 24, 012801 (2021) |
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Poster TUPAB181 [3.699 MB] | ||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-TUPAB181 | |
About • | paper received ※ 19 May 2021 paper accepted ※ 15 June 2021 issue date ※ 21 August 2021 | |
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WEXA02 | Operational Electron Cooling in the Relativistic Heavy Ion Collider | 2516 |
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Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. Since the invention of the electron cooling technique its application to cool hadron beams in colliders was considered for numerous accelerator physics projects worldwide. However, achieving the required high-brightness electron beams of required quality and cooling of ion beams in collisions was deemed to be challenging. An electron cooling of ion beams employing a high-energy approach with RF-accelerated electron bunches was recently successfully implemented at BNL. It was used to cool ion beams in both collider rings with ion beams in collision. Electron cooling in RHIC became fully operational during the 2020 physics run and led to substantial improvements in luminosity. This presentation will discuss implementation, optimization and challenges of electron cooling for colliding ion beams in RHIC. |
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DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEXA02 | |
About • | paper received ※ 18 May 2021 paper accepted ※ 15 June 2021 issue date ※ 31 August 2021 | |
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WEPAB306 | Applying Machine Learning to Optimization of Cooling Rate at Low Energy RHIC Electron Cooler | 3391 |
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Funding: Work supported by Brookhaven Science Associates, LLC under Contract No. DE-SC0012704 with the U.S. Department of Energy. The Low Energy RHIC electron Cooler (LEReC) is a novel, state-of-the-art, electron accelerator for cooling RHIC ion beams, which was recently built and commissioned. Optimization of cooling with LEReC requires fine-tuning of numerous LEReC parameters. In this work, initial optimization results of using Machine Learning (ML) methods - Bayesian Optimization (BO) and Q-learning are presented. Specially, we focus on exploring the influence of the electron trajectory on the cooling rate. In the first part, simulations are conducted by utilizing a LEReC simulator. The results show that both methods have the capability of deriving electron positions that can optimize the cooling rate. Moreover, BO takes fewer samples to converge than the Q-learning method. In the second part, Bayesian optimization is further trained on the historical cooling data. In the new samples generated by the BO, the percentage of larger cooling rates data is greatly enhanced compared with the original historical data. |
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Poster WEPAB306 [1.083 MB] | ||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-WEPAB306 | |
About • | paper received ※ 12 May 2021 paper accepted ※ 01 July 2021 issue date ※ 24 August 2021 | |
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