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SunRISE: Sun Radio Interferometer Space Experiment: Revealing How Energetic Particles Are Accelerated and Released Into Interplanetary Space
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The 18–19 March 2022 Series of 3He-Rich Events Observed By Solar Orbiter at 0.36 Au Compared With EUV, X-Ray, and Radio Observations
Context. During the first close perihelion pass of Solar Orbiter, a series of impulsive 3He-rich solar particle events was observed on 18–19 March 2022 from a distance of 0.36 au. In addition to the energetic particle, radio, and X-ray data from Solar Orbiter, the events were observed in radio and/or extreme ultraviolet by STEREO-A, SDO, Wind, and Parker Solar Probe. Aims. Observations of the event series along with remote sensing of flaring and radio emission with only small timing delays due to the close distance allow the association with energetic particles to be determined with much higher accuracy than previously possible from 1 au. Methods. By comparing the onsets of type-III bursts with the arrival of electrons of tens of keV at Solar Orbiter only a few minutes later, it can be seen that, overall, each of the more intense type-III bursts was associated with an electron and ion injection. Extreme ultraviolet data show that the times of the type-III bursts coincide with emission from a small (approximately Earth-sized) loop to the west of a nearby active region. Results. The energetic particle spectra and abundances show typical properties of impulsive 3He-rich flares and, when combined with the remote sensing observations, establish that the particle-accelerating mechanism in this series of events operates near the solar surface in association with magnetic loops, and in the absence of other phenomena such as jets and small coronal mass ejections.
Rapid Variability of Mrk 421 During Extreme Flaring as Seen Through the Eyes of XMM-Newton
By studying the variability of blazars across the electromagnetic spectrum, it is possible to resolve the underlying processes responsible for rapid flux increases, so-called flares. We report on an extremely bright X-ray flare in the high-peaked BL Lacertae object Markarian 421 (Mrk 421) that occurred simultaneously with enhanced γ-ray activity detected at very high energies by First G-APD Cherenkov Telescope on 2019 June 9. We triggered an observation with XMM–Newton, which observed the source quasi-continuously for 25 h. We find that the source was in the brightest state ever observed using XMM–Newton, reaching a flux of 2.8 × 10 −9 erg cm -2 s -1 over an energy range of 0.3–10 keV. We perform a spectral and timing analysis to reveal the mechanisms of particle acceleration and to search for the shortest source-intrinsic time-scales. Mrk 421 exhibits the typical harder-when-brighter behaviour throughout the observation and shows a clock-wise hysteresis pattern, which indicates that the cooling dominates over the acceleration process. While the X-ray emission in different sub-bands is highly correlated, we can exclude large time lags as the computed z-transformed discrete correlation functions are consistent with a zero lag. We find rapid variability on time-scales of 1 ks for the 0.3–10 keV band and down to 300 s in the hard X-ray band (4–10 keV). Taking these time-scales into account, we discuss different models to explain the observed X-ray flare, and find that a plasmoid-dominated magnetic reconnection process is able to describe our observation best.
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs
We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. The two complementary FPGA designs are based on OpenCL, a framework for writing programs that execute across heterogeneous platforms, and hls4ml, a high-level-synthesis-based compiler for neural network to firmware conversion. We evaluate and compare the resource usage, latency, and tracking performance of our implementations based on a benchmark dataset. We find a considerable speedup over CPU-based execution is possible, potentially enabling such algorithms to be used effectively in future computing workflows and the FPGA-based Level-1 trigger at the CERN Large Hadron Collider.
Inter-Agency Consultative Group for Space Science (IACG): Handbook of Missions and Payloads
The ACE spacecraft design is based on the Charge Composition Explorer (CCE) built by Johns Hopkins University (JHU) and the Applied Physics Lab (APL) for the AMPTE program. ACE is designed as a spinning spacecraft with its spin axis aligned to the Earth-Sun axis. The ACE launch weight will be approx. 633 kg, including 105 kg of scientific instruments and 184 kg of propellant. Using a Delta-class expendable launch vehicle, ACE will be launched into an L1 libration point (240 R(sub e)) orbit. Telemetry will be 6.7 kbps average, using tape recorder storage with daily readout to DSN. The experiment power requirement is approximately 76 W nominal and 96 W peak. The prime objective of the ACE mission is: (1) to determine accurate elemental and isotropic abundances including solar matter, local interstellar matter and local galactic matter; (2) to study the origin of elements and evolutionary processing in galactic nucleosynthesis, galactic evolution, origin and evolution of the solar system; (3) to study coronal formation and solar-wind acceleration processes; and (4) to study particle acceleration and transport, including coronal shock acceleration, stochastic flare acceleration, interplanetary shock acceleration, and interstellar acceleration and propagation. To accomplish this objective, ACE will perform comprehensive and coordinated determinations of the elemental and isotopic composition of energetic nuclei accelerated on the Sun, in interplanetary space, and from galactic sources. These observations will span five decades in energy, from solar wind to galactic cosmic ray energies, and will cover the element range from H-1 to Zr-40. Comparison of these samples of matter will be used to study the origin and subsequent evolution of both solar system and galactic material by isolating the effects of fundamental processes that include nucleosynthesis, charged and neutral particle separation, bulk plasma acceleration, and the acceleration of suprathermal and high-energy particles.
ML-based Real-Time Control at the Edge: An Approach Using hls4ml
This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviating from the accelerated proton beam into a cascade of secondary particles. Accelerators employ a large number of sensors to monitor beam loss. The data from these sensors is monitored by human operators who predict the relative contribution of different sub-systems to the beam loss. Using this information, they engage control interventions. In this paper, we present a controller to track this phenomenon in real-time using edge-Machine Learning (ML) and support control with low latency and high accuracy. We implemented this system on an Intel Arria 10 SoC. Optimizations at the algorithm, high-level synthesis, and interface levels to improve latency and resource usage are presented. Our design implements a neural network, which can predict the main source of beam loss (between two possible causes) at speeds up to 575 frames per second (fps) (average latency of 1.74 ms). The practical deployed system is required to operate at 320 fps, with a 3ms latency requirement, which has been met by our design successfully.
Multiphysics modeling of accelerators through code integration
This work aims to improve the ability of particle accelerator researchers to develop high-performance accelerator cavity designs by creating an overall multiphysics framework that integrates and couples existing application codes. This framework will allow accelerator researchers to build multiphysics models that will optimize cavity design, improve understanding of whole-device performance, and reduce the development and fabrication costs of accelerator research. We utilize the open-source VizSchema data standard as an intermediate data structure interface layer to standardize interfaces between individual application codes. VizScema is extensively documented online, and plugins for VizSchema are available for popular visualization packages, including VisIt and ParaView. Currently, the work focuses on coupling the EM field solver COMSOL and the electron gun code MICHELLE to allow COMSOL field-solve results to be seamlessly used by MICHELLE for particle-solve. Later work will extend this integration to include other fields, particles, and thermodynamics simulation codes.
Q-factor optimization for high-beta 650 MHz cavities for PIP-II
High Q-factors are of utmost importance to minimize losses of superconducting radio-frequency cavities deployed in continuous wave particle accelerators. This study elucidates the surface treatment that can maximize the Q-factors in high-beta 650 MHz elliptical niobium cavities. State-of-the-art surface treatments are applied in many single-cell cavities, and surface resistance studies are performed to understand the microwave dissipation at this unexplored frequency. The nitrogen doping treatment is confirmed to be necessary to maximize the Q-factors at medium RF fields. We applied this treatment in five-cell high-beta 650 MHz cavities and demonstrated that extremely high Q-factors were obtained at medium RF fields with this treatment. We also demonstrated that adding a cold electropolishing step after N-doping is crucial to push the quench field of multicell cavities to higher gradients.
Final Technical Report: Enabling High-Gradient Efficient Wakefield Accelerators with High-Quality Shaped Electron Bunches
This final technical report summarizes the development of structure wakefield accelerator (SWFA) technology to enable high-gradient, efficient particle acceleration.
MLOps for Beam Controls
Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.
MLOps for Beam Controls
Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.
MLOps for Beam Controls
Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.
The energy spectra of solar flare electrons
A survey of 50 electron energy spectra from .1 to 100 MeV originating from solar flares was made by the combination of data from two spectrometers onboard the International Sun Earth Explorer-3 spacecraft. The observed spectral shapes of flare events can be divided into two classes through the criteria of fit to an acceleration model. This standard two step acceleration model, which fits the spectral shape of the first class of flares, involves an impulsive step that accelerates particles up to 100 keV and a second step that further accelerates these particles up to 100 MeV by a single shock. This fit fails for the second class of flares that can be characterized as having excessively hard spectra above 1 MeV relative to the predictions of the model. Correlations with soft X-ray and meter radio observations imply that the acceleration of the high energy particles in the second class of flares is dominated by the impulsive phase of the flares.
Positron acceleration in plasma wakefields
Plasma acceleration has emerged as a promising technology for future particle accelerators, particularly linear colliders. Significant progress has been made in recent decades toward high-efficiency and high-quality acceleration of electrons in plasmas. However, this progress does not generalize to the acceleration of positrons, as plasmas are inherently charge asymmetric. Here, we present a comprehensive review of historical and current efforts to accelerate positrons using plasma wakefields. Proposed schemes that aim to increase energy efficiency and beam quality are summarized and quantitatively compared. A dimensionless metric that scales with the luminosity-per-beam power is introduced, indicating that positron-acceleration schemes are currently below the ultimate requirement for colliders. The primary issue is electron motion; the high mobility of plasma electrons compared to plasma ions, which leads to nonuniform accelerating and focusing fields that degrade the beam quality of the positron bunch, particularly for high efficiency acceleration. Finally, we discuss possible mitigation strategies and directions for future research.
Accelerator Neutrinos
Neutrino beams generated by particle accelerators are essential for probing fundamental physics. This presentation will examine the creation of high-intensity, well-collimated neutrino beams, crucial for long-baseline experiments like DUNE and NOvA. These experiments are pushing proton beam power to multi-MW levels and utilizing large-scale detectors to overcome the challenge of limited event statistics. At LBNF, the DUNE experiment will rigorously test the three-neutrino flavor model and explore CP violation by analyzing oscillation signatures in high-intensity νμ(νμˉ)νμ(νμˉ) to νe(νeˉ)νe(νeˉ) beams. We'll explore the technical complexities of beamline components, the drive towards higher beam powers, and the strategies for measuring and managing neutrino flux. The presentation will also cover advancements in neutrino beam instrumentation and efforts to enhance beam precision, which are key to achieving the next generation of multi-megawatt accelerator facilities. By reviewing past achievements and future prospects, this talk aims to provide a clear overview of the current state and future potential of neutrino beam technology.