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DOE OSTI2025

Minimizing CGYRO HPC Communication Costs in Ensembles with XGYRO by Sharing the Collisional Constant Tensor Structure

First-principles fusion plasma simulations are both compute and memory intensive, and CGYRO is no exception. The use of many HPC nodes to fit the problem in the available memory thus results in significant communication overhead, which is hard to avoid for any single simulation. That said, most fusion studies are composed of ensembles of simulations, so we developed a new tool, named XGYRO, that executes a whole ensemble of CGYRO simulations as a single HPC job. By treating the ensemble as a unit, XGYRO can alter the global buffer distribution logic and apply optimizations that are not feasible on any single simulation, but only on the ensemble as a whole. The main saving comes from the sharing of the collisional constant tensor structure, since its values are typically identical between parameter-sweep simulations. This data structure dominates the memory consumption of CGYRO simulations, so distributing it among the whole ensemble results in drastic memory savings for each simulation, which in turn results in overall lower communication overhead.

CGYRO↗

DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2017

Advanced Software V&V for Civil Aviation and Autonomy

With the advances in high-computing platform (e.g., advanced graphical processing units or multi-core processors), computationally-intensive software techniques such as the ones used in artificial intelligence or formal methods have provided us with an opportunity to further increase safety in the aviation industry. Some of these techniques have facilitated building safety at design time, like in aircraft engines or software verification and validation, and others can introduce safety benefits during operations as long as we adapt our processes. In this talk, I will present how NASA is taking advantage of these new software techniques to build in safety at design time through advanced software verification and validation, which can be applied earlier and earlier in the design life cycle and thus help also reduce the cost of aviation assurance. I will then show how run-time techniques (such as runtime assurance or data analytics) offer us a chance to catch even more complex problems, even in the face of changing and unpredictable environments. These new techniques will be extremely useful as our aviation systems become more complex and more autonomous.

software assurance↗

DOE OSTI2016

WarpIV: In situ visualization and analysis of ion accelerator simulations

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analytics to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

SU-E-T-278: Realization of Dose Verification Tool for IMRT Plan Based On DPM

Purpose: To build a Monte Carlo dose verification tool for IMRT Plan by implementing a irradiation source model into DPM code. Extend the ability of DPM to calculate any incident angles and irregular-inhomogeneous fields. Methods: With the virtual source and the energy spectrum which unfolded from the accelerator measurement data,combined with optimized intensity maps to calculate the dose distribution of the irradiation irregular-inhomogeneous field. The irradiation source model of accelerator was substituted by a grid-based surface source. The contour and the intensity distribution of the surface source were optimized by ARTS (Accurate/Advanced Radiotherapy System) optimization module based on the tumor configuration. The weight of the emitter was decided by the grid intensity. The direction of the emitter was decided by the combination of the virtual source and the emitter emitting position. The photon energy spectrum unfolded from the accelerator measurement data was adjusted by compensating the contaminated electron source. For verification, measured data and realistic clinical IMRT plan were compared with DPM dose calculation. Results: The regular field was verified by comparing with the measured data. It was illustrated that the differences were acceptable (<2% inside the field, 2–3mm in the penumbra). The dose calculation of irregular field by DPM simulation was also compared with that of FSPB (Finite Size Pencil Beam) and the passing rate of gamma analysis was 95.1% for peripheral lung cancer. The regular field and the irregular rotational field were all within the range of permitting error. The computing time of regular fields were less than 2h, and the test of peripheral lung cancer was 160min. Through parallel processing, the adapted DPM could complete the calculation of IMRT plan within half an hour. Conclusion: The adapted parallelized DPM code with irradiation source model is faster than classic Monte Carlo codes. Its computational accuracy and speed satisfy the clinical requirement, and it is expectable to be a Monte Carlo dose verification tool for IMRT Plan. Strategic Priority Research Program of the China Academy of Science(XDA03040000); National Natural Science Foundation of China (81101132)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Measurement of the photon electroproduction cross section at JLAB with the goal of performing a Rosenbluth separation of the DVCS contribution

The study of the inner structure of hadrons allows us to understand the nature of the interactions between partons, quarks and gluons, described by Quantum Chromodynamics. The elastic scattering reactions, which have been studied in order to measure the nucleon form factors, are included in this frame. The inelastic scattering reactions are also included in this frame, they allow us to obtain information about the nucleon structure thanks to the development of the parton distribution functions (PDFs). While through elastic scattering we can obtain information about the charge distribution of the nucleon, and hence, about the spatial distribution of the partons, through inelastic scattering we obtain information about the momentum distributions of partons, by employing the PDFs. However, we can study the exclusive inelastic scattering reactions, such as the Deeply Virtual Compton Scattering (DVCS), wich allow us to access to the spatial and momentum distributions simultaneously. This is possible thanks to the generalized parton distributions (GPDs), which allow us to correlate both types of distributions. The process known as DVCS is the easiest way to access the GPDs. This process can be expressed as the scattering of an electron by a proton by means of a virtual photon with the result of the scattered initial particles plus a real photon. We find a process competing with DVCS known as Bethe-Heitler (BH), in which the real photon is radiated by the lepton rather than the quark. Due to the small cross section of DVCS, of the order of nb, in order to conduct these kind of experiments it is necessary to make use of facilities capable of providing high beam intensities. One of these facilities is the Thomas Jefferson National Accelerator Facility , where the experiment JLab E07-007, "Complete Separation of Virtual Photon and π⁰ Electroproduction Observables of Unpolarized Protons", took place during the months of October to December of 2010. The main goal of this experiment is the isolation of the contribution from the term coming form the DVCS from the interference term, resulting from the BH contribution. This isolation is known as "Rosenbluth Separation". The work presented in this thesis focuses on the analysis of the data stored by the electromagnetic calorimeter, employed for the detection of real photons. There is also a a theoretical introduction to the study of the nucleon structure, reviewing the concepts of form factors and parton distributions through elastic and inelastic processes. The computation of the photon leptoproduction cross section is described in detail, as well as the goals of experiment E07-007. This thesis also describes the analysis of the data stored by the electromagnetic calorimeter, with the purpose of obtaining the kinematic variables of the real photons resulting from DVCS reactions. Finally, it describes the selection of events from stored data, the applied cuts to kinematical variables and the background subtraction. Also, the process of extraction of the necessary observables for computing the photon leptoproduction cross section is described, along with the main steps followed to perform the Monte Carlo simulation used in this computation. The resulting cross sections are shown at the end of this thesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1990

Interpretation of satellite-measured bidirectional reflectance from Cirrus cloudy atmospheres

The interpretation of the observed bidirectional reflectance from cirrus cloudy atmospheres is presented. A theoretical model was developed for the computation of the transfer of solar radiation in an anisotropic medium with particular applications to oriented ice crystals in cirrus clouds. In this model, the adding principle for radiative transfer was used with modifications to account for the anisotropy of scattering particles and the associated scattering phase matrix. The single-scattering properties, including the phase function, single-scattering albedo, and extinction cross sections, were used for randomly and horizontally oriented hexagonal ice crystals in radiative transfer computations. The radiative transfer model developed for the cirrus clouds was modified to account for the scattering contributions from the atmosphere and the surface. In order to test the relevance and significance of the ice crystal model for the interpretation of observed bidirectional reflectance from satellites, visible radiances collected on the half hour by the GOES series were selected. The data are calibrated and corrected with the proper filter functions, then navigated to match selected landmark data. A number of clear and cloudy cases during the cirrus IFO of the Fire experiment were chosen for theoretical analyses. The cloud particle shape and size distributions that were taken during satellite overpasses are used in radiative transfer calculations. The sensitivities of the shape, orientation, and size distribution of ice crystals on the reflected intensities at the top of the atmosphere are investigated. Finally, the relative importance of these cloud microphysical properties in the interpretation of satellite bidirectional reflectance are assessed and presented.

Takano, Y.↗

NASA NTRS1994

Test/score/report: Simulation techniques for automating the test process

A Test/Score/Report capability is currently being developed for the Transportable Payload Operations Control Center (TPOCC) Advanced Spacecraft Simulator (TASS) system which will automate testing of the Goddard Space Flight Center (GSFC) Payload Operations Control Center (POCC) and Mission Operations Center (MOC) software in three areas: telemetry decommutation, spacecraft command processing, and spacecraft memory load and dump processing. Automated computer control of the acceptance test process is one of the primary goals of a test team. With the proper simulation tools and user interface, the task of acceptance testing, regression testing, and repeatability of specific test procedures of a ground data system can be a simpler task. Ideally, the goal for complete automation would be to plug the operational deliverable into the simulator, press the start button, execute the test procedure, accumulate and analyze the data, score the results, and report the results to the test team along with a go/no recommendation to the test team. In practice, this may not be possible because of inadequate test tools, pressures of schedules, limited resources, etc. Most tests are accomplished using a certain degree of automation and test procedures that are labor intensive. This paper discusses some simulation techniques that can improve the automation of the test process. The TASS system tests the POCC/MOC software and provides a score based on the test results. The TASS system displays statistics on the success of the POCC/MOC system processing in each of the three areas as well as event messages pertaining to the Test/Score/Report processing. The TASS system also provides formatted reports documenting each step performed during the tests and the results of each step. A prototype of the Test/Score/Report capability is available and currently being used to test some POCC/MOC software deliveries. When this capability is fully operational it should greatly reduce the time necessary to test a POCC/MOC software delivery, as well as improve the quality of the test process.

Hageman, Barbara H.↗

DOE OSTI2016

SU-F-T-580: New Tumor Modeling Using 3D Gel Dosimeter for Brain Stereoctactic Radiotherpy (SRT)

Purpose: The purpose of this study is to develop new tumor model using 3D printing with 3D dosimeter for brain stereoctactic radiotherpy (SRT). Methods: BANG{sup 3} polymer gel was prepared and the gel-filled glass vials were irradiated with a 6 MV photon beam to acquire the calibration curve that present the change of R2 (1/T{sub 2}) value with dose. Graded doses from 0 to 12 Gy with an interval of 2 Gy were delivered. A kit for calibration of gel dosimeter and an 2 tumor model phantoms with a spherical shape were produced using a 3D printer with a polylactic acid after its 3D images were created using Autodesk software. 3D printed tumor phantoms and EBT3 films were irradiated to compare with treatment plan. After irradiation, vials for calibration and tumor model phantoms were scanned at 9.4T MRI. The spin-spin relaxation times (T{sub 2}) according to the each dose were calculated to evaluate the dose response. Acquired images were analyzed using an ImageJ. Scanned MRI images of tumor models were transferred treatment planning system and these were registered to the CT images. In all treatment plans, two arc plans (CW and CCW) were designed to deliver 50 Gy for 10 fractions. For first PTV, treatment plan was accurately designed that 95% of dose to cover 100% of PTV. But 2nd PTV was not intentionally cover 100% of PTV to evaluate the intensity of delivered tumor phantom with polymer gel. We compared the 3D dose distributions obtained from measurements with the 3D printed phantom and calculated with the TPS. Results: 3D printed phantom with a polymer gel was successfully produced. The dose distributions showed qualitatively good agreement among gel, film, and RTP data. Conclusion: A hybrid phantom represents a useful to validate the 3D dose distributions for patient-specific QA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Detection of Local/Regional Events in Kuwait Using Next-Generation Detection Algorithms

Seismic networks around the world use conventional triggering algorithms to detect seismic signals in order to locate local/regional seismic events. Kuwait National Seismological Network (KNSN) of Kuwait Institute of Scientific Research (KISR) is operating seven broad-band and short-period three-component stations in Kuwait. The network is equipped with Nanometrics digitizers and uses Antelope and Guralp acquisition software for processing and archiving the data. In this study, we selected 10 days of archived hourly-segmented continuous data of five stations (Figure 1) and 250 days of continuous recording at MIB. For the temporary deployment our selection criteria was based on KNSN catalog intensity for the period of time we test the method. An autonomous event detection and clustering framework is employed to test a more complete catalog of this short period of time. The goal is to illustrate the effectiveness of the technique and pursue the framework for longer period of time.

58 GEOSCIENCES↗

DOE OSTI2022

Journal paper

Laser technology is being widely studied for controlled energy deposition for a range of applications, including flow control, ignition, combustion, and diagnostics. The absorption and scattering of laser radiation by liquid droplets in aerosols affects propagation of the laser beam in the atmosphere, while the ignition and combustion characteristics in combustion chambers are influenced by the evaporation rate of the sprayed fuel. In this work, we present a mathematical model built on OpenFOAM for laser heating and evaporation of a single droplet in the diffusion-dominated regime taking into account absorption of the laser radiation, evaporation process, and vapor flow dynamics. The developed solver is validated against available experimental and numerical data for heating and evaporation of ethanol and water droplets. The two main regimes—continuous and pulsed laser heating—are explored. For continuous laser heating, the peak temperature is higher for larger droplets. For pulsed laser heating, when the peak irradiance is close to transition to the boiling regime, the temporal dynamics of the droplet temperature does not depend on the droplet size. With the empirical normalization of time, the dynamics of the droplet shrinkage and cooling are found to be independent of droplet sizes and peak laser intensities.

42 ENGINEERING↗

DOE OSTI2026

BM3DORNL

BM3DORNL is a high-performance, open-source library for removing streak and ring artifacts from computed-tomography (CT) data, developed for neutron imaging at Oak Ridge National Laboratory's Spallation Neutron Source (VENUS beamline) and applicable to X-ray CT as well. Ring artifacts — concentric rings in reconstructed slices caused by detector pixel-to-pixel response non-uniformities — appear as vertical streaks in the sinogram and degrade both image quality and quantitative analysis. BM3DORNL operates in the sinogram domain using an adaptation of the BM3D (block-matching and 3D collaborative filtering) algorithm (Dabov et al., 2007). It provides a dedicated streak-removal mode, a true multi-scale BM3D variant (after Mäkinen et al., 2021) that suppresses wide streaks single-scale methods miss, and an alternative Fourier–SVD method (~2.6× faster) combining FFT-based energy detection with rank-1 SVD. The computationally intensive core is implemented in Rust with parallel (Rayon) block matching, integral-image pre-screening, and optimized transforms, and is exposed through a simple Python API (with an optional GUI) so it integrates directly into existing tomography reconstruction pipelines. It processes both 2D sinograms and 3D sinogram stacks, is pip-installable for Linux and macOS, and is documented at https://bm3dornl.readthedocs.io.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗

NASA NTRS2023

Simulation of the Solar Energetic Particle Event on 2020 May 29 Observed by Parker Solar Probe

This paper presents a stochastic three-dimensional focused transport simulation of solar energetic particles (SEPs) produced by a data-driven coronal mass ejection (CME) shock propagating through a data-driven model of coronal and heliospheric magnetic fields. The injection of SEPs at the CME shock is treated using diffusive shock acceleration of post-shock suprathermal solar wind ions. A time-backward stochastic simulation is employed to solve the transport equation to obtain the SEP time–intensity profile at any location, energy, and pitch angle. The model is applied to a SEP event on 2020 May 29, observed by STEREO-A close to ∼1 au and by Parker Solar Probe (PSP) when it was about 0.33 au away from the Sun. The SEP event was associated with a very slow CME with a plane-of-sky speed of 337 km s −1 at a height below 6 RS as reported in the SOHO/LASCO CME catalog. We compute the time profiles of particle flux at PSP and STEREO-A locations, and estimate both the spectral index of the proton energy spectrum for energies between ∼2 and 16 MeV and the equivalent path length of the magnetic field lines experienced by the first arriving SEPs. We find that the simulation results are well correlated with observations. The SEP event could be explained by the acceleration of particles by a weak CME shock in the low solar corona that is not magnetically connected to the observers.

Solar energetic particles↗

DOE OSTI2015

Improving Data Mobility & Management for International Cosmology

In February 2015 the third workshop in the CrossConnects series, with a focus on Improving Data Mobility & Management for International Cosmology, was held at Lawrence Berkeley National Laboratory. Scientists from fields including astrophysics, cosmology, and astronomy collaborated with experts in computing and networking to outline strategic opportunities for enhancing scientific productivity and effectively managing the ever-increasing scale of scientific data. While each field has unique details which depend on the instruments employed, the type and scale of the data, and the structure of scientific collaborations, several important themes emerged from the workshop discussions. Findings, as well as a set of recommendations, are contained in their respective sections in this report.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Automated Labeling of Electron Microscopy Images Using Deep Learning

© 2018 IEEE. Searching for scientific data requires metadata providing a relevant context. Today, generating metadata is a time and labor intensive manual process that is often neglected, and important datasets are not accessible through search. We investigate the use of machine learning to generalize metadata from a subset of labeled data, thus increasing the availability of meaningful metadata for search. Specifically, we consider electron microscopy images collected at the National Center for Electron Microscopy (NCEM) at the Lawrence Berkeley National Laboratory (LBNL) and use deep learning to discern characteristics from a small subset of labeled images and transfer labels to the entire image corpus. Relatively small training set sizes and a minimum resolution of 512\times 512 pixels required by the application domain pose unique challenges. We overcome these challenges by using a simple yet powerful convolutional network architecture that limits the number of free parameters to lower the required amount of computational power and reduce the risk of overfitting. We achieve a classification accuracy of approximately 80% in discerning between images recorded in two operating modes of the electron microscope-transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM). We use transfer learning-i.e., re-using the pre-trained convolution layers from the TEM vs. STEM classification problem-to generalize labels and achieve an accuracy of approximately 70 % despite current experiments being limited to small training data sets. We present these predictions as suggestions to domain scientists through a web-based tool to accelerate the labeling process with the goal of further validating our approach and improving the accuracy of automatically created labels.

Weber, Gunther H↗

DOE OSTI2013

Summer Student Internship working on the GPU

This summer internship consisted of learning computer programming skills and languages including Thrust, CUDA, C++, C and Linux. The application of this programming is for use in GPU, graphics processing units, that are processors that perform math intensive calculations rapidly in three dimensions typically in advanced video games (“NVIDIA GeForce…”). Our goal is to apply this technology towards exa-scale computing on the LANL supercomputing infrastructure. My mentors use these machines to do computations. The completed algorithms include KD tree and Top K. In order to access the GPU, CUDA was used. CUDA is a parallel computer architecture for general computing on the GPUs. There are different means by which to access CUDA. The first approach uses libraries, like Thrust, Linear Algebra, and Signal and Image Processing. Another approach parallelizes loops in Fortran or C and in the last approach people develop custom parallel algorithms using familiar language (“What is CUDA”). The algorithms I worked on this summer use the first approach of using the thrust library of parallel algorithms and data structures.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (4th Annual Report)

Nuclear plant sites collect and store large volumes of data collected from various equipment and systems. These datasets typically include plant process parameters, maintenance records, technical logs, online monitoring data, and equipment failure data. The collection of such data affords an opportunity to leverage data-driven machine learning and artificial intelligence technologies to provide diagnostic and prognostic capabilities within the nuclear power industry to reduce operating and maintenance costs. In this way, nuclear energy can become more economically competitive with other energy sources, and premature closures can be avoided. From a maintenance standpoint, savings can be achieved by leveraging machine learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose and predict potential faults within the system. Improved model accuracy can lead to reductions in unnecessary maintenance and more efficient planning of future maintenance, thus lowering the costs associated with parts, labor, and unnecessary planned, forced, or extended outages. From an operations perspective, cost savings can be generated by shifting from route-based monitoring to wireless technologies for online monitoring, and by transitioning from onsite- to cloud-based computing and storage services. Wireless monitoring would reduce the operator manhours required for taking routine measurements, while cloud computing services would generate cost savings by reducing the amount of hardware needing to be purchased and maintained—all while scaling to both computational and storage demands. This report summarizes this project’s effort to shift from costly, labor-intensive preventative maintenance to cheaper predictive maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Line Ratios for Solar Wind Charge Exchange with Comets

Charge exchange (CX) has emerged in X-ray emission modeling as a significant process that must be considered in many astrophysical environments—particularly comets. Comets host an interaction between solar wind ions and cometary neutrals to promote solar wind charge exchange (SWCX). X-ray observatories provide astronomers and astrophysicists with data for many X-ray emitting comets that are impossible to accurately model without reliable CX data. Here, we utilize a streamlined set of computer programs that incorporate the multi-channel Landau–Zener theory and a cascade model for X-ray emission to generate cross sections and X-ray line ratios for a variety of bare and non-bare ion single electron capture (SEC) collisions. Namely, we consider collisions between the solar wind constituent bare and H-like ions of C, N, O, Ne, Na, Mg, Al, and Si and the cometary neutrals H{sub 2}O, CO, CO{sub 2}, OH, and O. To exemplify the application of this data, we model the X-ray emission of Comet C/2000 WM1 (linear) using the CX package in SPEX and find excellent agreement with observations made with the XMM-Newton RGS detector. Our analyses show that the X-ray intensity is dominated by SWCX with H, while H{sub 2}O plays a secondary role. This is the first time, to our knowledge, that CX cross sections have been implemented into a X-ray spectral fitting package to determine the H to H{sub 2}O ratio in cometary atmospheres. The CX data sets are incorporated into the modeling packages SPEX and Kronos .

79 ASTRONOMY AND ASTROPHYSICS↗