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Beamline Steering Using Deep Learning Models 利用深度学习模型进行光束线引导
Pub Date : 2024-08-24 DOI: arxiv-2408.13657
Dexter Allen, Isaac Kante, Dorian Bohler
Beam steering involves the calibration of the angle and position at which aparticle accelerator's electron beam is incident upon the x-ray target withrespect to the rotation axis of the collimator. Beam Steering is an essentialtask for light sources. The Linac To Undulator is very difficult to steer andaim due to the changes of each use of the accelerator there must bere-calibration of magnets. However with each use of the Beamline its currentmethod of steering runs into issues when faced with calibrating angles andpositions. Human operators spend a substantial amount of time and resources onthe task. We developed multiple different feed-forward-neural networks withvarying hyper-parameters, inputs, and outputs, seeking to compare theirperformance. Specifically, our smaller models with 33 inputs and 13 outputsoutperformed the larger models with 73 inputs and 50 outputs. We propose thefollowing explanations for this lack of performance in larger models. First, alack of training time and computational power limited the ability of our modelsto mature. Given more time, our models would outperform SVD. Second, when theinput size of the model increases the noise increases as well. In this casemore inputs corresponded to a greater length upon the LINAC accelerator. Lessspecific and larger models that seek to make more predictions will inherentlyperform worse than SVD.
光束转向包括校准粒子加速器的电子束入射到 X 射线靶上时相对于准直器旋转轴的角度和位置。光束转向是光源的一项基本任务。由于每次使用加速器都会发生变化,因此必须对磁铁进行校准。然而,每次使用光束线时,其现有的转向方法都会在校准角度和位置时遇到问题。人类操作员需要花费大量的时间和资源来完成这项任务。我们开发了多种超参数、输入和输出各不相同的前馈神经网络,以比较它们的性能。具体来说,我们采用 33 个输入和 13 个输出的较小模型优于采用 73 个输入和 50 个输出的较大模型。我们对大型模型缺乏性能提出了以下解释。首先,缺乏训练时间和计算能力限制了我们模型的成熟。如果有更多的时间,我们的模型将优于 SVD。其次,当模型的输入大小增加时,噪声也会增加。在这种情况下,更多的输入对应于更长的 LINAC 加速器。如果模型的特异性较低,且规模较大,那么在进行更多预测时,其表现必然会比 SVD 差。
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引用次数: 0
Final Cooling With Thick Wedges for a Muon Collider 用厚楔为缪子对撞机进行最终冷却
Pub Date : 2024-08-22 DOI: arxiv-2408.12696
D. FuUniversity of Chicago, A. Badea. K. Folan Di PetrilloUniversity of Chicago, D. NeufferFermilab, D. StratakisFermilab
In the final cooling stages for a muon collider, the transverse emittancesare reduced while the longitudinal emittance is allowed to increase. Inprevious studies, Final cooling used absorbers within very high field solenoidsto cool low-momentum muons. Simulations of the systems did not reach thedesired cooling design goals. In this study, we develop and optimize adifferent conceptual design for the final 4D cooling channel, which is based onusing dense wedge absorbers. We used G4Beamline to simulate the channel andPython to generate and analyze particle distributions. We optimized the designparameters of the cooling channel and produced conceptual designs(corresponding to possible starting points for the input beam) which achievetransverse cooling in both x and y by a factor of $approx$ 3.5. These channelsachieve a lower transverse and longitudinal emittance than the best previouslypublished design.
在μ介子对撞机的最后冷却阶段,横向幅射会减小,而纵向幅射会增大。在以前的研究中,最终冷却使用了极高磁场螺线管内的吸收器来冷却低动量μ介子。对系统的模拟没有达到预期的冷却设计目标。在这项研究中,我们开发并优化了基于密集楔形吸收器的最终 4D 冷却通道的不同概念设计。我们使用 G4Beamline 对通道进行模拟,并使用 Python 生成和分析粒子分布。我们优化了冷却通道的设计参数,并产生了概念设计(对应于输入光束的可能起始点),这些设计在 x 和 y 方向上都实现了 3.5 倍的横向冷却。这些通道的横向和纵向幅射均低于以前公布的最佳设计。
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引用次数: 0
Beam-based Identification of Magnetic Field Errors in a Synchrotron using Deep Lie Map Networks 利用深度谎言图网络,基于光束识别同步加速器中的磁场误差
Pub Date : 2024-08-21 DOI: arxiv-2408.11677
Conrad Caliari, Adrian Oeftiger, Oliver Boine-Frankenheim
We present the first experimental validation of the Deep Lie Map Network(DLMN) approach for recovering both linear and non-linear optics in asynchrotron. The DLMN facilitates the construction of a detailed acceleratormodel by integrating charged particle dynamics with machine learningmethodology in a data-driven framework. The primary observable is the centroidmotion over a limited number of turns, captured by beam position monitors. TheDLMN produces an updated description of the accelerator in terms of magneticmultipole components, which can be directly utilized in established acceleratorphysics tools and tracking codes for further analysis. In this study, we applythe DLMN to the SIS18 hadron synchrotron at GSI for the first time. We discuss the validity of the recovered linear and non-linear optics,including quadrupole and sextupole errors, and compare our results withalternative methods, such as the LOCO fit of a measured orbit response matrixand the evaluation of resonance driving terms. The small number of requiredtrajectory measurements, one for linear and three for non-linear opticsreconstruction, demonstrates the method's time efficiency. Our findingsindicate that the DLMN is well-suited for identifying linear optics, and therecovery of non-linear optics is achievable within the capabilities of thecurrent beam position monitor system. We demonstrate the application of DLMNresults through simulated resonance diagrams in tune space and their comparisonwith measurements. The DLMN provides a novel tool for analyzing the causalorigins of resonances and exploring potential compensation schemes.
我们首次对深度谎言图网络(DLMN)方法进行了实验验证,以恢复同步加速器中的线性和非线性光学特性。通过在数据驱动框架中整合带电粒子动力学和机器学习方法,DLMN有助于构建详细的加速度模型。主要观测指标是由光束位置监测器捕捉到的有限圈数的中心点运动。DLMN 根据磁多极分量生成对加速器的最新描述,可直接用于已有的加速器物理工具和跟踪代码,以进行进一步分析。在本研究中,我们首次将 DLMN 应用于 GSI 的 SIS18 强子同步加速器。我们讨论了恢复的线性和非线性光学的有效性,包括四极子和六极子误差,并将我们的结果与其他方法进行了比较,如对测量轨道响应矩阵的 LOCO 拟合和共振驱动项的评估。所需的轨迹测量次数很少,线性光学重建一次,非线性光学重建三次,这证明了该方法的时间效率。我们的研究结果表明,DLMN 非常适合识别线性光学器件,而非线性光学器件的识别在当前光束位置监测系统的能力范围内是可以实现的。我们通过模拟调谐空间共振图及其与测量结果的比较,展示了 DLMN 结果的应用。DLMN 为分析共振的因果关系和探索潜在的补偿方案提供了一种新工具。
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引用次数: 0
PIP-II Linac Cryogenic Distribution System Design Challenges PIP-II 直列加速器低温配送系统设计挑战
Pub Date : 2024-08-20 DOI: arxiv-2408.11018
T. BanaszkiewiczWroclaw University of Science and Technology, Wroclaw, Poland, M. ChorowskiWroclaw University of Science and Technology, Wroclaw, Poland, P. DudaWroclaw University of Science and Technology, Wroclaw, Poland, M. StanclikWroclaw University of Science and Technology, Wroclaw, Poland, R. DhuleyFermi National Accelerator Laboratory, Batavia, USA, A. MartinezFermi National Accelerator Laboratory, Batavia, USA, W. SoyarsFermi National Accelerator Laboratory, Batavia, USA
The PIP-II linac Cryogenic Distribution System (CDS) is characterized byextremely small heat inflows and robust mechanical design. It consists of aDistribution Valve Box (DVB), Intermediate Transfer Line, Tunnel Transfer Line,comprising 25 Bayonet Cans, and ends with a Turnaround Can. Multiple heliumstreams, each characterized by distinct helium parameters, flow through each ofthese elements. The CDS geometry allows maintaining an acceptable pressure dropfor each helium stream, considering the planned flows and helium parameters indifferent operation modes. This is particularly crucial for the return line ofhelium vapors, which return from cryomodules to the cold compressors and thushave very restrictive pressure drop requirements. On both sides of the DVBthere are fixed supports for process pipes. One of the DVB design challengeswas to route the process pipes in such a way that their shape providedsufficient compensation for thermal shrinkage. This ensures th at the forcesresulting from thermal shrinkage acting on the cryogenic valves remain at alevel acceptable to the manufacturer. The required thermal budget of the CDSwas achieved by thermo-mechanical optimization of its components, like processpipes fixed supports in Bayonet Cans.
PIP-II 直列加速器低温分配系统(CDS)的特点是热流入量极小,机械设计坚固耐用。它由一个分配阀箱 (DVB)、中间传输线、隧道传输线(包括 25 个卡口罐)和一个周转罐组成。多股氦气流流经上述每个元件,每股氦气流都具有不同的氦气参数。考虑到不同运行模式下的计划流量和氦气参数,CDS 的几何形状允许每股氦气流保持可接受的压降。这一点对于氦蒸汽的回流管线尤为重要,因为氦蒸汽会从低温模块返回到冷压缩机,因此对压降的要求非常严格。在 DVB 的两侧有用于工艺管道的固定支架。DVB 的设计难点之一是如何使工艺管道的形状为热收缩提供足够的补偿。这样可以确保热收缩作用在低温阀门上的力保持在制造商可以接受的水平。CDS 所需的热预算是通过对其组件(如卡口罐中的工艺管固定支架)进行热机械优化来实现的。
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引用次数: 0
Results of High Order Modes Spectra Measurements in 1.3 GHz Cavities for LCLS-II 用于 LCLS-II 的 1.3 GHz 腔内高阶模频谱测量结果
Pub Date : 2024-08-20 DOI: arxiv-2408.10991
A. LuninFermilab, Batavia, USA, T. KhabiboullineFermilab, Batavia, USA, A. SukhanovFermilab, Batavia, USA, V. YakovlevFermilab, Batavia, USA
Fermilab recently completed production and testing of 1.3 GHz cryomodules forthe LCLS-II project. Each cryomodule consists of eight TESLA-shapedsuperconducting elliptical cavities equipped with two High Order Mode (HOM)coupler ports. Measurement of the HOM spectrum is part of the incoming qualitycontrol of cavities at room temperature and the final qualification cold testof cryomodules at the Cryomodule Test Facility (CMTF). In this paper wedescribe the procedure for measuring the HOM spectrum along with further dataprocessing. Finally, we present accumulated statistics of individual HOMfrequencies and quality factors related to various cavity vendors and discussthe possible contribution of HOMs to heat loads and beam dynamics.
费米实验室最近完成了用于 LCLS-II 项目的 1.3 GHz 低温模块的生产和测试。每个低温模块由八个 TESLA 形超导椭圆腔组成,配备两个高阶模式(HOM)耦合器端口。对高阶模频谱的测量是室温下空腔进场质量控制和低温模组测试设施(CMTF)低温模组最终鉴定的一部分。在本文中,我们介绍了测量 HOM 光谱的程序以及进一步的数据处理。最后,我们介绍了与各种腔体供应商相关的单个 HOM 频率和质量因子的累积统计数据,并讨论了 HOM 对热负荷和光束动力学可能造成的影响。
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引用次数: 0
Conceptual Design of A 20 T Dipole Based on Hybrid REBCO/Nb3Sn Cos-theta Coil* 基于 REBCO/Nb3Sn 混合型 Cos-theta 线圈的 20 T 偶极子概念设计*
Pub Date : 2024-08-20 DOI: arxiv-2408.11023
A. V. ZlobinFermilab, Batavia, IL, USA
This paper presents a design concept of an HTS/LTS hybrid dipole with 50 mmaperture and 20 T nominal field based on a cos-theta coil and a cold iron yoke.The HTS part of magnet coil uses REBCO Twisted Stacked Tape cable. The LTS partis graded and made of two Nb3Sn Rutherford cables. Due to high sensitivity ofHTS/LTS coils to large stresses and strains at high fields, a Stress Management(SM) concept combined with the cos-theta coil geometry is used. The results ofmagnet magnetic analysis are presented and discussed.
本文介绍了一种 HTS/LTS 混合偶极子的设计理念,该偶极子具有 50 mm 的孔径和 20 T 的额定磁场,基于一个 cos-theta 线圈和一个冷铁轭。LTS 部分是分级的,由两根 Nb3Sn 卢瑟福电缆组成。由于 HTS/LTS 线圈在高磁场下对大应力和应变非常敏感,因此采用了应力管理(SM)概念与 cos-theta 线圈几何形状相结合。本文介绍并讨论了磁体磁性分析的结果。
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引用次数: 0
Preliminary Results of the 2023 International Fermilab Booster Studies 2023 年费米实验室国际助推器研究的初步结果
Pub Date : 2024-08-16 DOI: arxiv-2408.08987
Jeffrey Eldred, Michael Balcewicz, Frank Schmidt, Benjamin Simons
An overview is given of the methods and preliminary results from dedicatedbeam studies on three topics conducted over five days in July 2023. In thefirst study, the Fermilab Booster magnets were held constant at magnetic fieldscorresponding to the injection energy. The beam loss and emittance growth wereobserved under varying intensity, tunes, and sextupole resonances. Thecorresponding beam conditions were also simulated with the MADX-SCcode~cite{Schmidt:2644660}. In the second study, measurements of the verticalhalf-integer resonance and correction methods are conducted for high-intensitybeams ramping in the Booster. Finally, syncho-betatron instabilities areobserved during transition-crossing in the Booster under strong space-chargeconditions.
本文概述了 2023 年 7 月用五天时间对三个主题进行的专用光束研究的方法和初步结果。在第一项研究中,费米实验室助推器磁铁在与注入能量相对应的磁场中保持恒定。在不同的强度、调谐和六极共振条件下观察了光束损耗和幅射增长。相应的光束条件也用 MADX-SCcode~cite{Schmidt:2644660} 进行了模拟。在第二项研究中,针对助推器中的高强度光束斜坡,进行了垂直半整数共振的测量和修正方法。最后,在强空间电荷条件下,观测到了助推器中过渡交叉时的同步加速器不稳定性。
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引用次数: 0
Beam dynamics performance of the proposed PETRA IV storage ring 拟议 PETRA IV 储存环的光束动力学性能
Pub Date : 2024-08-15 DOI: arxiv-2408.07995
I. Agapov, S. Antipov, R. Bartolini, R. Brinkmann, Y-C. Chae, E. C. Cortes-Garcia, D. Einfeld, T. Hellert, M. Huening, M. A. Jebramcik, J. Keil, C. Li, L. Malina, R. Wanzenberg
The PETRA IV project for upgrading the 2.3 km 6 GeV PETRA III storage ring toa diffraction-limited synchrotron radiation source is nearing the end of itsdetailed technical design phase. We present the ring lattice based on thehybrid six-bend achromat (H6BA) cell and a detailed evaluation of its beamdynamics performance. Design challenges as well as unique opportunitiesassociated with a low emittance ring of a large size are discussed.
PETRA IV 项目旨在将 2.3 公里长的 6 GeV PETRA III 储存环升级为衍射极限同步辐射源,其详细技术设计阶段已接近尾声。我们介绍了基于混合六弯消色差(H6BA)单元的环形晶格,以及对其光束动力学性能的详细评估。我们还讨论了与大尺寸低发射率环相关的设计挑战和独特机遇。
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引用次数: 0
Estimate of Multi-Shot Laser-Induced Polarization for High Energy Electrons 高能电子的多束激光诱导极化估计
Pub Date : 2024-08-14 DOI: arxiv-2408.08917
Katherine D. Ranjbar, Emily Snyder, Alice Snyder, Vahid H. Ranjbar
The use of an intense ultrashort laser pulse to induce electron polarizationhas been proposed in existing literature. The Python programming language isused to recreate the local constant crossed-field approximation (LCFA) with theaim of determining values for transverse polarization given a nonzero initialpolarization. It has been shown that over multiple laser shots, lower values ofthe quantum efficiency parameter are associated with higher transversepolarization output, yet require a greater number of shots to attain maximalpolarization. Moreover, the quantum efficiency parameter has been redefined asa function of intensity for a Ti:sapphire laser necessary to inducepolarization in the Electron-Ion Collide
现有文献已经提出了使用强超短激光脉冲诱导电子极化的方法。利用 Python 编程语言重新创建了局部恒定交叉场近似(LCFA),目的是在初始极化不为零的情况下确定横向极化值。研究表明,在多次激光照射中,量子效率参数值越低,横向极化输出越高,但需要更多的照射次数才能达到最大极化。此外,量子效率参数已被重新定义为电子-离子对撞中诱导极化所需的钛:蓝宝石激光强度的函数。
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引用次数: 0
Time-inversion of spatiotemporal beam dynamics using uncertainty-aware latent evolution reversal 利用不确定性感知潜演化反转实现时空光束动力学的时间反转
Pub Date : 2024-08-14 DOI: arxiv-2408.07847
Mahindra Rautela, Alan Williams, Alexander Scheinker
Charged particle dynamics under the influence of electromagnetic fields is achallenging spatiotemporal problem. Many high performance physics-basedsimulators for predicting behavior in a charged particle beam arecomputationally expensive, limiting their utility for solving inverse problemsonline. The problem of estimating upstream six-dimensional phase space givendownstream measurements of charged particles in an accelerator is an inverseproblem of growing importance. This paper introduces a reverse Latent EvolutionModel (rLEM) designed for temporal inversion of forward beam dynamics. In thistwo-step self-supervised deep learning framework, we utilize a ConditionalVariational Autoencoder (CVAE) to project 6D phase space projections of acharged particle beam into a lower-dimensional latent distribution.Subsequently, we autoregressively learn the inverse temporal dynamics in thelatent space using a Long Short-Term Memory (LSTM) network. The coupledCVAE-LSTM framework can predict 6D phase space projections across all upstreamaccelerating sections based on single or multiple downstream phase spacemeasurements as inputs. The proposed model also captures the aleatoricuncertainty of the high-dimensional input data within the latent space. Thisuncertainty, which reflects potential uncertain measurements at a given module,is propagated through the LSTM to estimate uncertainty bounds for all upstreampredictions, demonstrating the robustness of the LSTM against in-distributionvariations in the input data.
电磁场影响下的带电粒子动力学是一个具有挑战性的时空问题。许多用于预测带电粒子束行为的高性能物理模拟器计算成本高昂,限制了它们在线解决逆问题的实用性。根据加速器中带电粒子的下游测量结果估算上游六维相空间是一个日益重要的逆问题。本文介绍了一种反向潜伏进化模型(rLEM),该模型专为前向光束动力学的时间反演而设计。在分两步进行的自我监督深度学习框架中,我们利用条件变异自动编码器(CVAE)将粒子束的 6D 相空间投影投射到低维潜在分布中。耦合 CVAE-LSTM 框架可以根据单个或多个下游相空间测量结果作为输入,预测所有上游加速段的 6D 相空间投影。所提出的模型还能捕捉潜空间内高维输入数据的不确定性。这种不确定性反映了特定模块上潜在的不确定测量值,通过 LSTM 传播来估计所有上游加速预测的不确定性边界,证明了 LSTM 对输入数据分布变化的鲁棒性。
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引用次数: 0
期刊
arXiv - PHYS - Accelerator Physics
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