Post-compression of multiterawatt long-wave infrared pulses
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The CMS detector at the CERN LHC features a silicon pixel detector as its innermost subdetector. The original CMS pixel detector has been replaced with an upgraded pixel system (CMS Phase-1 pixel detector) in the extended year-end technical stop of the LHC in 2016/2017. The upgraded CMS pixel detector is designed to cope with the higher instantaneous luminosities that have been achieved by the LHC after the upgrades to the accelerator during the first long shutdown in 2013–2014. Compared to the original pixel detector, the upgraded detector has a better tracking performance and lower mass with four barrel layers and three endcap disks on each side to provide hit coverage up to an absolute value of pseudorapidity of 2.5. This paper describes the design and construction of the CMS Phase-1 pixel detector as well as its performance from commissioning to early operation in collision data-taking.
The generation of high-power coherent soft x-ray pulses of sub-100 as duration and 10 nm wavelength using beams from a GeV energy plasma wakefield accelerator has been recently investigated in Emma []. As a future upgrade to this concept, this contribution investigates scaling to shorter x-ray wavelengths by cascading undulators tuned to higher harmonics of the fundamental. We present two simulation studies for plasma-driven attosecond harmonic generation schemes with final photon wavelengths of 2 and 0.40 nm. We demonstrate in these schemes that using undulators with retuned fundamental frequencies can produce GW-scale pulses of sub-nm radiation with tens of attosecond-scale pulse lengths, an order of magnitude shorter than current state-of-the-art attosecond x-ray free electron lasers (XFELs). This multipulse multicolor operation will be broadly applicable to attosecond pump-probe experiments. Published by the American Physical Society 2024
A Beam Position Monitor (BPM) is potentially useful to measure the position and phase of the beam in air in a non-destructive way. An air-gap BPM in experiments, such as beam-induced radioactive waste management and dynamic radiography applications, where a so-called air gap is needed, can be utilized to measure the beam position and phase. In this study, a stripline BPM was used in the air-gap of an 800 MeV proton beam transport line. The downstream end of the primary beamline exit window was made of a thin aluminum plate and allowed the beam to travel 1.2 m in ambient air before re-entering into a vacuum drift section. Such a configuration was arranged to examine the BPM effectiveness in atmospheric temperature and pressure where ionization of air occurs. In this study, a high energy (800 MeV), high current (0.6 A beam peak current/pulse) proton beam of 5 mm radius was transported in the air. The beam position relative to the axis was measured by detecting the signature of the beam in a nanosecond scale. This nanosecond scale detection ability was useful to identify other signals such as plasma effects. The BPM signals were processed at a frequency of 201 MHz; thus, one gets a stronger response in a stripline pattern as it was used in this study instead of a dot-type BPM. Experimental data show that the BPM works well in air, but ionization of air or plasma formation could not be measured over the BPM signal. The design, construction, and performance of a BPM in air environment are presented.
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A machine learning model was created to predict the electron spectrum generated by a GeV-class laser wakefield accelerator. The model was constructed from variational convolutional neural networks, which mapped the results of secondary laser and plasma diagnostics to the generated electron spectrum. An ensemble of trained networks was used to predict the electron spectrum and to provide an estimation of the uncertainty of that prediction. It is anticipated that this approach will be useful for inferring the electron spectrum prior to undergoing any process that can alter or destroy the beam. In addition, the model provides insight into the scaling of electron beam properties due to stochastic fluctuations in the laser energy and plasma electron density.
Fully relativistic particle-in-cell (PIC) simulations are crucial for advancing our knowledge of plasma physics. Modern supercomputers based on graphics processing units (GPUs) offer the potential to perform PIC simulations of unprecedented scale, but require robust and feature-rich codes that can fully leverage their computational resources. In this work, this demand is addressed by adding GPU acceleration to the PIC code Osiris. An overview of the algorithm, which features a CUDA extension to the underlying Fortran architecture, is given. Detailed performance benchmarks for thermal plasmas are presented, which demonstrate excellent weak scaling on NERSC's Perlmutter supercomputer and high levels of absolute performance. The robustness of the code to model a variety of physical systems is demonstrated via simulations of Weibel filamentation and laser-wakefield acceleration run with dynamic load balancing. Finally, measurements and analysis of energy consumption are provided that indicate that the GPU algorithm is up to ~14 times faster and ~7 times more energy efficient than the optimized CPU algorithm on a node-to-node basis. The described development addresses the PIC simulation community's computational demands both by contributing a robust and performant GPU-accelerated PIC code and by providing insight into efficient use of GPU hardware.
Spin polarized photocathodes are key to the future operation of electron accelerators such as the ones at Thomas Jefferson National Accelerator Facility and Brookhaven National Laboratory. Currently, these photocathodes come in short supply due to limited production by molecular beam epitaxy. By developing a process to implement similar structures using metal organic chemical vapor deposition, the availability of these devices can be increased. Here, in this paper, we detail the implementation of recent photocathode advancements via metal organic chemical vapor deposition process and show an improvement in both polarization and quantum efficiency of our devices compared to those fabricated via molecular beam epitaxy, with devices reaching 82% polarization and 2.9% quantum efficiency.
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The general concept of radiation therapy used in conventional cancer treatment is to increase the therapeutic index by creating a physical dose differential between tumors and normal tissues through precision dose targeting, image guidance, and radiation beams that deliver a radiation dose with high conformality, e.g., protons and ions. However, the treatment and cure are still limited by normal tissue radiation toxicity, with the corresponding side effects. A fundamentally different paradigm for increasing the therapeutic index of radiation therapy has emerged recently, supported by preclinical research, and based on the FLASH radiation effect. FLASH radiation therapy (FLASH-RT) is an ultra-high-dose-rate delivery of a therapeutic radiation dose within a fraction of a second. Experimental studies have shown that normal tissues seem to be universally spared at these high dose rates, whereas tumors are not. While dose delivery conditions to achieve a FLASH effect are not yet fully characterized, it is currently estimated that doses delivered in less than 200 ms produce normal-tissue-sparing effects, yet effectively kill tumor cells. Despite a great opportunity, there are many technical challenges for the accelerator community to create the required dose rates with novel compact accelerators to ensure the safe delivery of FLASH radiation beams.
A technique for more accurately modeling and improving the spatial resolution of heavy ion beam probe measurements is described. We use a set of particle trajectories to numerically determine the focusing properties of a complicated three-dimensional magnetic field and characterize those properties with a transfer matrix. We then modify the transfer matrix approach of traditional ion optics to include a parameter that describes the ionization location of the detected ions. The ion optics model calculated using this technique enables a more accurate description of the particle trajectories than previously feasible. The model also allows one to easily determine an initial beam focus that could be used during experimental operation to optimize the spatial resolution of measurements. The technique has been applied to the design of a heavy ion beam probe diagnostic for the Wendelstein 7-X stellarator and improvements in the modeled spatial resolution by a factor of about 2 over previous estimates are possible. As a result, the improved spatial resolution will enable measurements of plasma fluctuations with smaller wavelengths than would otherwise be possible.
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Professional Development in Accelerator Safety / Operations
The production of high-intensity muon beams is crucial for advancing particle and accelerator physics, both now and in the future. Achieving these high-intensity goals requires overcoming significant challenges in high-power targetry. Here, we will outline the key challenges and explore the selection of target materials, focusing on muon production and susceptibility to radiation damage -- key factors for optimal target designs.
The dataset was created to train machine learning models for the task of identifying the (1) cavity and (2) fault type from C100-type cryomodules at the Thomas Jefferson National Accelerator Facility (Jefferson Lab), thereby replacing the time-consuming efforts of a subject matter expert. Superconducting radio-frequency (SRF) cavity trips represent a significant source of accelerator downtime. Real-time – rather than post-mortem – identification of the offending cavity and classification of the fault type would give control room operators valuable feedback for corrective action planning. The anticipated benefit is increased beam-on-target time for users and provides performance metrics that can be used to improve future cavity designs. A series of 17 RF signals are recorded for each of the 8 cavities in a C100 cryomodule every time a cavity trips. These time-series signals are written to file using a specially designed data acquisition system. The dataset represents fault events recorded during Continuous Electron Beam Accelerator Facility (CEBAF) beam operations between January 18, 2019 and March 9, 2020. The following filtering steps were applied to collected data; (1) only 4 of the 17 signals per cavity are retained (GMES, GASK, CRFP, DETA2) (2) only events with data from each of the eight cavities in the cryomodule are kept, (3) only events that were sampled at 5 kHz were kept, (4) events from cryomodule 0L04 were neglected, (5) events occurring between February 4, 3PM and February 5, 12PM were neglected. As a result of preprocessing, the dataset is comprised of 2,375 unique events. The full dataset is comprised of three files: features.csv, cavity_labels.csv, fault_labels.csv. Each instance in faults.csv includes a timestamp (“date_time”), a label for the cryomodule which experienced the trip (“zone_label”), and 192 features (“feature_1”, “feature_2”... “feature_192”). The features correspond to 6 autoregressive features for each of 4 signals per cavity for each of the 8 cavities (6 × 4 signals/cavity × 8 cavities/cryomodule = 192). To deal with the large variation of signal amplitudes, time-series standardization via the z-score (standard score) function was applied prior to computing the features. For each instance, there is an associated label for the (1) cavity which faulted first (cavity_labels.csv) and (2) the type of fault that caused the trip (fault_labels.csv). The cavity identification can take values of [0, 1, 2, 3, 4, 5, 6, 7, 8] and the fault type can take values of [‘Microphonics’, ‘Quench_100ms’, ‘Controls_Fault’, ‘E_Quench’, ‘Quench_3ms’, ‘Single_Cav_Turn_Off’ , ‘Heat_Riser_Choke’, ‘Multi_Cav_Turn_Off’].