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At least 505 records · Page 28

Continual Learning for Particle Accelerators

Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts

Rajput, Kishansingh [Thomas Jefferson National Acc↗

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗

Particle motion in the tail current sheet

Theory of particle motion in current sheets is reviewed. For small, approximately constant normal magnetic field, Bz, particles oscillate about the current sheet and 'live' within the sheet for one-half gyroperiod based on Bz. This lifetime replaces the mean collision time in the Lorentzian conductivity and thus gives rise to the concept of an inertial (or gyro-) conductivity. A substorm model by Coroniti utilizes this conductivity to allow reconnection to proceed without anomalous processes, due to wave-particle interactions. Chaotic particle orbits may at times be important to the dynamics, depending on parameters such as particle energy, current sheet thickness, and field line curvature. A current sheet model with neutral line predicts a ridge structure and asymmetries in the distribution function. Ion distributions near the plasma sheet boundary layer, during the CDAW 6 interval, are consistent with the model predictions. In recent studies by Mitchell et al. and Williams et al., the major current carriers during the growth phase of a substorm were found to be adiabatic electrons not more than 1 keV, but just before a current disruption event, the tail current was mainly carried by energetic ions undergoing current sheet oscillation.

Speiser, T. W.↗

Classical confined particles

An alternative picture of classical many body mechanics is proposed. In this picture particles possess individual kinematics but are deprived from individual dynamics. Dynamics exists only for the many particle system as a whole. The theory is complete and allows to determine the trajectories of each particle. It is proposed to use our picture as a classical prototype for a realistic theory of confined particles.

Horzela, Andrzej↗

Semi-Classical Models for Virtual Antiparticle Pairs

Virtual particle-antiparticle pairs of massive elementary particle& are predicted in Quantum Field Theory (QFT) to appear from the vacuum and annihilate each other again within their Heisenberg lifetimes h/4mc(exp 2). In this work, semiclassical models of this process - for the cases of massive leptons, quarks, and the massive weak bosons W and Z - are constructed. It is shown that the dynamical lifetime of the particle- antiparticle system in each case equals the Heisenberg lifetime to good approximation, and obeys appropriate quantization conditions on the field fluctuation action. In other words, the dynamical lifetime of the semiclassical model agrees with QED and QCD to good approximation. But the formula for the dynamical lifetime in each model includes the force strength coupling constant (e in the lepton case, alpha(sup s) (q(exp 2)) in the quark cases), while the Heisenberg lifetime formula does not. Observing the agreement of the Heisenberg and dynamical lifetimes, we may derive the QED and QCD coupling constants in terms of h, c, and numerical factors only.

Batchelor, David↗

Study of Static Microchannel Plate Saturation Effects for the Fast Plasma Investigation Dual Electron Spectrometers on NASA's Magnetospheric MultiScale Mission

Imaging detecting systems based on microchannel plates (MCPs) are the most common for low energy plasma measurements for both space borne and ground applications. One of the key parameters of these detection systems is the dynamic range of the MCP's response to the input fluxes of charged particles. For most applications the dynamic range of the linear response should be as wide as possible. This is especially true for the Dual Electron Spectrometers (DESs) of the Fast Plasma Investigation (FPI) on NASA's Magnetospheric MultiScale (MMS) mission because a wide range of input fluxes are expected. To make use of the full available dynamic range, it is important to understand the MCP response behavior beyond the linear regime where the MCPs start to saturate. We have performed extensive studies of this during the characterization and calibration of the DES instruments and have identified several saturation effects of the detection system. The MCP itself exhibits saturation when the channels lack the ability to replenish charge sufficiently rapidly. It is found and will be shown that the ground system can significantly impact the correct measurement of this effect. As the MCP starts to saturate, the resulting pulse height distribution (PHD) changes shape and location (with less pulse height values), which leads to truncation of the PHD by the threshold set on the detection system discriminator. Finally, the detection system pulse amplifier exhibits saturation as the input flux drives pulse rates greater than its linear response speed. All of these effects effectively change the dead time of the overall detection system and as a result can affect the quality and interpretation of the flight data. We present results of detection system saturation effects and their interaction with special emphasis on the MCP related effects.

detecting system↗

Thermodynamic and Dynamic Aspects of Ice Nucleation

It is known that ice nucleating particles (INP) immersed within supercooled droplets promote the formation of ice. Common theoretical models used to represent this process assume that the immersed particle lowers the work of ice nucleation without significantly affecting the dynamics of water in the vicinity of the particle. This is contrary to evidence showing that immersed surfaces significantly affect the viscosity and diffusivity of vicinal water. To study how this may affect ice formation this work introduces a model linking the ice nucleation rate to the modification of the dynamics and thermodynamics of vicinal water by immersed particles. It is shown that INP that significantly reduce the work of ice nucleation also pose strong limitations to the growth of the nascent ice germs. This leads to the onset of a new ice nucleation regime, called spinodal ice nucleation, where the dynamics of ice germ growth instead of the ice germ size determines the nucleation rate. Nucleation in this regime is characterized by an enhanced sensitivity to particle area and cooling rate. Comparison of the predicted ice nucleation rate against experimental measurements for a diverse set of species relevant to cloud formation suggests that spinodal ice nucleation may be common in nature.

Barahona, Donifan↗

A review of low-rank methods for time-dependent kinetic simulations

Time-dependent kinetic models are ubiquitous in computational science and engineering. The underlying integro-differential equations in these models are high-dimensional, comprised of a six–dimensional phase space, making simulations of such phenomena extremely expensive. In this article we demonstrate that in many situations, the solution to kinetics problems lives on a low dimensional manifold that can be described by a low-rank matrix or tensor approximation. We then review the recent development of so-called low-rank methods that evolve the solution on this manifold. The two classes of methods we review are the dynamical low-rank (DLR) method, which derives differential equations for the low-rank factors, and a Step-and-Truncate (SAT) approach, which projects the solution onto the low-rank representation after each time step. Thorough discussions of time integrators, tensor decompositions, and method properties such as structure preservation and computational efficiency are included. We further show examples of low-rank methods as applied to particle transport and plasma dynamics.

97 MATHEMATICS AND COMPUTING↗

High-accuracy method for modeling nucleation and growth of particles

State-of-the-art numerical models describing the kinetics of aerosol particle nucleation and growth from a cooling vapor primarily use a nodal method, in which particles that are smaller than the critical size are omitted from consideration because they are thermodynamically unfavorable. This omission is based on the assumption that most newly formed particles are above the critical size, so that subcritical-size particles are not important to take into account. Due to the nature of the nodal method, it suffers from numerical diffusion, which can cause an artificial broadening of the cluster size distribution leading to a significant overestimation of the number of large-size particles. To address these issues, we propose a more accurate numerical method that explicitly models particles of all sizes, and uses a special numerical scheme that substantially reduces the numerical diffusion and provides high solution accuracy and numerical stability. We extensively compare this novel method to the commonly used nodal solver of the general dynamic equation (GDE) for particle growth and demonstrate that it offers GDE solutions with higher accuracy with low numerical diffusion. Incorporating small subcritical clusters into the solution is crucial for: 1) more precise determination of the entire particle size distribution function and 2) wider applicability of the model to experimental studies with non-monotonic temperature variations leading to particle evaporation. The computational code implementing this numerical method in Python is available upon request.

42 ENGINEERING↗

Interactive Terascale Particle Visualization

This paper describes the methods used to produce an interactive visualization of a 2 TB computational fluid dynamics (CFD) data set using particle tracing (streaklines). We use the method introduced by Bruckschen et al. [2001] that pre-computes a large number of particles, stores them on disk using a space-filling curve ordering that minimizes seeks, and then retrieves and displays the particles according to the user's command. We describe how the particle computation can be performed using a PC cluster, how the algorithm can be adapted to work with a multi-block curvilinear mesh, and how the out-of-core visualization can be scaled to 296 billion particles while still achieving interactive performance on PG hardware. Compared to the earlier work, our data set size and total number of particles are an order of magnitude larger. We also describe a new compression technique that allows the lossless compression of the particles by 41% and speeds the particle retrieval by about 30%.

Ellsworth, David↗

Active experiments in the distant magnetosphere - The AMPTE program

The Active Magnetospheric Particle Tracer Explorers (AMPTE) program consists of three spacecraft that will be launched to inject tracer ions (lithium and barium) inside and outside the earth's magnetosphere and to detect and monitor these ions as they convect and diffuse through the inner magnetosphere. The principal objectives of the program are: (1) to investigate the transfer of mass from the solar wind to the magnetosphere and its further transport and energization within the magnetosphere; (2) to study the interaction between artificially injected and cosmical plasmas; (3) to establish the elemental and charge composition and dynamics of the charged particle population in the magnetosphere over a broad energy range; and (4) to explore further the structure and dynamics of ambient plasmas in the magnetosphere. The implementation of the above objectives is discussed, with emphasis placed on the tracer aspect of the program.

Krimigis, S. M.↗

Chain Dynamics in Magnetorheological Suspensions

Magnetorheological (MR) suspensions are composed of colloidal particles which acquire dipole moments when subjected to an external magnetic field. At sufficient field strengths and concentrations, the dipolar particles rapidly aggregate to form long chains. Subsequent lateral cross-linking of the dipolar chains is responsible for a rapid liquid-to-solid-like rheological transition. The unique, magnetically-activated rheological properties of MR suspensions make them ideal for interfacing mechanical systems to electronic controls. Additionally, the ability to experimentally probe colloidal suspensions interacting through tunable anisotropic potentials is of fundamental interest. Our current experimental work has focused on understanding the fluctuations of dipolar chains. It has been proposed by Halsey and Toor (HT) that the strong Landau-Peierls thermal fluctuations of dipolar chains could be responsible for long-range attractions between chains. Such interactions will govern the long-time relaxation of MR suspensions. We have synthesized monodisperse neutrally buoyant MR suspensions by density matching stabilized ferrofluid emulsion droplets with D2O. This allows us to probe the dynamics of the dipolar chains using light scattering without gravitational, interfacial, and polydispersity effects to resolve the short-wavelength dynamics of the dipolar chains. We used diffusing wave spectroscopy to measure these dynamics. The particle displacements at short times that show an independence to the field strength, but at long times exhibit a constrained, sub-diffusive motion that slows as the dipole strength is increased. The experiments are in good qualitative agreement with Brownian dynamics simulations of dipolar chains. Although there have been several important and detailed studies of the structure and interactions in MR suspensions, there has not been conclusive evidence that supports or contradicts the HT model prediction that long-range interactions exist between fluctuating chains of dipolar particles. Resolving this issue would contribute greatly to the understanding of these interesting and important materials. We have begun to test the predictions of the HT model by both examining the dynamics of individual chains and by measuring the forces between dipolar chains directly to accurately and quantitatively assess the interactions that they experience. To do so, we employ optical trapping techniques and video-microscopy to manipulate and observe our samples on the microscopic level. With these techniques, it is possible to observe chains that are fluctuating freely in three-dimensions, independent of interfacial effects. More importantly, we are able to controllably observe the interactions of two chains at various separations to measure the force-distance profile. The techniques also allow us to study the mechanical properties of individual chains and chain clusters. Our work to this point has focused on reversibly-formed dipolar chains due to field induced dipoles where the combination of this chaining, the dipolar forces, and the hydrodynamic interactions that dictate the rheology of the suspensions. One can envision, however, many situations where optical, electronic, or rheological behavior may be optimized with magneto-responsive anisotropic particles. Chains of polarizable particles may have the best properties as they can coil and flex in the absence of a field and stiffen and orient when a field is applied. We have recently demonstrated a synthesis of stable, permanent paramagnetic chains by both covalently and physically linking paramagnetic colloidal particles. The method employed allows us to create monodisperse chains of controlled length. We observed the stability, field-alignment, and rigidity of this new class of materials. The chains may exhibit unique rheological properties in an applied magnetic field over isotropic suspensions of paramagnetic particles. They are also useful rheological models as bead-spring systems. These chains form the basis for our current experiments with optical traps.

Gast, A. P.↗

Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) Science Plan

Coastal cities provide the opportunity to characterize marine clouds and the substantial effects of manmade particles on cloud properties and processes. La Jolla lies to the north of San Diego, California, but it is often about a day directly downwind of the major pollution sources located in the ports of Los Angeles and Long Beach. The large dynamic range of aerosol particle concentrations combined with the multi-hour to multi-day persistence of stratocumulus cloud layers makes the site ideal for investigating the seasonal changes in cloud and aerosol properties as well as the quantitative relationships between cloud and aerosol properties. The focus of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) is to characterize the extent, radiative properties, aerosol interactions, and precipitation characteristics of stratocumulus clouds in the Eastern Pacific across all four seasons at a coastal location, the Scripps Pier and the Scripps Mt. Soledad sites in La Jolla. An important enhancement to this study will be the collection of simultaneous in-cloud aerosol and droplet measurements to investigate the differences in these cloud properties during regional polluted and clean marine conditions. The combined observations will provide an unprecedented set of constraints for the following questions: 1. Cloud and Aerosol Climatology: What are the seasonal and diurnal cycles of marine stratocumulus cloud and aerosol properties on the northeastern Pacific coast? 2. Cloud Radiative Fluxes: How do cloud properties, including the ratio of direct-to-diffuse radiation, change as coastal clouds are advected inland? 3. Aerosol-Cloud Interactions: Will retrieved cloud properties reflect the regional signatures of aerosol?

Eastern Pacific Cloud Aerosol Precipitation Experi↗

Measurements and Analyses to Enable Science for the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE)

Coastal cities provide the opportunity to characterize the substantial effects of manmade particles on marine cloud properties and processes. La Jolla lies to the north of San Diego, California, but it is often about a day directly downwind of the major pollution sources located in the ports of Los Angeles and Long Beach. The large dynamic range of aerosol particle concentrations combined with the multi-hour to multi-day persistence of stratocumulus cloud layers makes the site ideal for investigating the seasonal changes in cloud and aerosol properties as well as the quantitative relationships between cloud and aerosol properties. The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized the extent, radiative properties, aerosol interactions, and precipitation characteristics of stratocumulus clouds in the Eastern Pacific across all four seasons at two coastal sites in La Jolla. This project was designed to enhance and expand the scientific uses of the ARM AMF1 measurements from EPCAPE. The goal was to ensure meaningful observations were collected that would enable science. The project included the following objectives: (1) Reviewing the ARM AMF1 measurements [ARM, 2021a; b] and circulating a summary of the measurements each week, (2) Comparing AMF1 measurements to those provided by collaborators (including filter measurements at the pier), (3) Collecting and analyzing filter samples from Scripps Pier by Fourier Transform Infrared spectroscopy (FTIR) and X-ray Fluorescence (XRF), (4) Assisting in operations of instruments provided by Guest PIs when possible, and (5) Providing an initial compilation of EPCAPE aerosol and cloud seasonal differences. The expected outcomes of these objectives were enhanced proposals and publications using EPCAPE measurements by helping to identify instrument issues, expanded data access and awareness by distributing weekly plots and related summaries, improved source-related attribution of aerosols with elemental tracers, additional observations provided by Guest PIs, and accelerated ACI studies enabled by the compiled seasonal summaries of aerosol and cloud properties. Three examples of the science enabled by this project are findings that (i) aerosol and cloud aqueous production contributes more than half of sulfate particle mass concentration, (ii) upwind sources make chemical composition very similar at nearby sites despite local differences in meteorology, and (iii) most of the large mass concentration of semi-volatile organic components is co-emitted and co-evaporated with nitrate. Together these findings illustrate how ARM extended field campaigns in coastal regions can be used to constrain ACI processes with direct observations. By using the unique ARM suite of cloud radiative products in addition to the measured aerosol properties at a coastal location, we were able to address the more specific question of which aerosol particles cause how much of the effects on clouds. Identifying this signature in coastal areas provides an opportunity to test the representation of aerosol sources by global models in a range of clean and urban-influenced conditions.

Russell, Lynn [Univ. of California, San Diego, CA ↗

Design and testing of a unique randomized gravity, continuous flow bioreactor

A rotating, null gravity simulator, or Couette bioreactor was successfully used for the culture of mammalian cells in a simulated microgravity environment. Two limited studies using Lipomyces starkeyi and Streptomyces clavuligerus were also conducted under conditions of simulated weightlessness. Although these studies with microorganisms showed promising preliminary results, oxygen limitations presented significant limitations in studying the biochemical and cultural characteristics of these cell types. Microbial cell systems such as bacteria and yeast promise significant potential as investigative models to study the effects of microgravity on membrane transport, as well as substrate induction of inactive enzyme systems. Additionally, the smaller size of the microorganisms should further reduce the gravity induced oscillatory particle motion and thereby improve the microgravity simulation on earth. Focus is on the unique conceptual design, and subsequent development of a rotating bioreactor that is compatible with the culture and investigation of microgravity effects on microbial systems. The new reactor design will allow testing of highly aerobic cell types under simulated microgravity conditions. The described reactor affords a mechanism for investigating the long term effects of reduced gravity on cellular respiration, membrane transfer, ion exchange, and substrate conversions. It offers the capability of dynamically altering nutrients, oxygenation, pH, carbon dioxide, and substrate concentration without disturbing the microgravity simulation, or Couette flow, of the reactor. All progeny of the original cell inoculum may be acclimated to the simulated microgravity in the absence of a substrate or nutrient. The reactor has the promise of allowing scientists to probe the long term effects of weightlessness on cell interactions in plants, bacteria, yeast, and fungi. The reactor is designed to have a flow field growth chamber with uniform shear stress, yet transfer high concentrations of oxygen into the culture medium. The system described allows for continuous, on line sampling for production of product without disturbing fluid and particle dynamics in the reaction chamber. It provides for the introduction of substrate, or control substances after cell adaptation to simulated microgravity has been accomplished. The reactor system provides for the nondisruptive, continuous flow replacement of nutrient and removal of product. On line monitoring and control of growth conditions such as pH and nutrient status are provided. A rotating distribution valve allows cessation of growth chamber rotation, thereby preserving the simulated microgravity conditions over longer periods of time.

Lassiter, Carroll B.↗

Quantifying structural errors in cloud condensation nuclei activity from reduced representation of aerosol size distributions

Aerosol effects on clouds and radiation are the dominant contribution to uncertainty in radiative forcing relative to the pre-industrial atmosphere. While previous studies have assessed the impact of parametric uncertainty on modeled forcing, structural errors from the numerical representation of particle distributions have not been well quantified. Here we present a framework for quantifying error in aerosol size distributions and cloud condensation nuclei activity, which we apply to the widely used 4-mode version of the Modal Aerosol Module (MAM4). Box model predictions from the MAM4 are evaluated against the Particle Monte Carlo Model for Simulating Aerosol Interactions and Chemistry (PartMC-MOSAIC), a benchmark model that tracks the evolution of individual particles. We show that size distributions simulated by MAM4 diverge from those simulated by PartMC-MOSAIC after only a few hours of aging by condensation and coagulation in polluted conditions, which leads to large errors in modeled cloud condensation nuclei concentrations. We find that differences between MAM4 and PartMC-MOSAIC are largest under polluted conditions, where the size distribution evolves rapidly though aging by condensation of semi-volatile substances and coagulation among particles. These findings suggest that structural error in modeled aerosol properties contributes to the large inter-model variability in aerosol radiative forcing.

Fierce, Laura M.↗