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All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Light Cone Dynamics and EMC Effects in the Extraction of F{sub 2n} at Large Bjorken x

We discuss theoretical issues related to the extraction of deep inelastic (DIS) structure function of neutron from inclusive DIS scattering off the deuteron at large Bjorken x. Theoretical justification is given to the consideration of only pn component of the deuteron wave function and consistency with both the baryonic number and light-cone momentum conservation sum rules. Next we discuss the EMC type effects and argue that in all cases relevant to the nuclear DIS reactions at large x the main issue is the medium modification of the properties of bound nucleon rather than the non-nucleonic components like pions. We give brief description of the color screening model of EMC and within this model we estimate uncertainties in the extraction of the neutron DIS structure function at large x. We emphasize also that these uncertainties are rather ''model independent'' since any theoretical framework accounting for the medium modification is proportional to the magnitude of the virtuality of bound nucleon which increases with an increase of x.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Adjusting solar-induced fluorescence to nadir-viewing provides a better proxy for GPP

Solar-induced fluorescence (SIF) provides key information for inferring terrestrial gross primary productivity (GPP). However, there is little research on analyzing the performance of nadir-adjusted SIF (SIF nadir ) on GPP, compared to total SIF emitted by all leaves (SIF total ) for reducing the viewing angle effects and estimating GPP. Besides, there have been controversial opinions on whether SIF total is better correlated to GPP than raw SIF observations (SIF obs ). Here we systematically analyzed the relationship between raw/nadir/total SIF (i.e., SIF obs , SIF nadir and SIF total ) and GPP and investigated the underlying mechanism, using multi-angular field measurements and eddy covariance data in wheat and corn crops at sub-daily scale. We further compared the performance of SIF obs , SIF nadir and SIF total in estimating GPP using the TROPOspheric Monitoring Instrument (TROPOMI) SIF and concurrent AmeriFlux measurements at daily scale. Furthermore, the results indicate that diurnal SIF nadir has stronger correlations to GPP than SIF obs for field measurements, with the increase of mean coefficient of determination (R 2 ) by 0.05–0.07 for far-red band and 0.11–0.20 for red band. SIF nadir shows comparable performance with SIF total for both far-red and red bands. Although the viewing angle effects dominate the difference in estimating GPP between SIF nadir and SIF obs , the correlation between light use efficiency (LUE) and fesc further determines the different performance of SIF nadir and SIF total in estimating GPP. TROPOMI-based analysis further confirms that SIF nadir overall has higher correlations to AmeriFlux GPP than SIF obs for different plant functional types and shows similar performance with SIF total . Compared to SIF total , the estimation of SIF nadir independent of viewing angle effects does not require any canopy structure parameters, and thus offers promising potential for reliably estimating regional and global GPP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Cool core bias in Sunyaev–zel’dovich galaxy cluster surveys

Sunyaev–Zel’dovich (SZ) surveys find massive clusters of galaxies by measuring the inverse Compton scattering of cosmic microwave background off of intra-cluster gas. The cluster selection function from such surveys is expected to be nearly independent of redshift and cluster astrophysics. In this work, we estimate the effect on the observed SZ signal of centrally peaked gas density profiles (cool cores) and radio emission from the brightest cluster galaxy by creating mock observations of a sample of clusters that span the observed range of classical cooling rates and radio luminosities. For each cluster, we make simulated SZ observations by the South Pole Telescope and characterize the cluster selection function, but note that our results are broadly applicable to other SZ surveys. We find that the inclusion of a cool core can cause a change in the measured SPT significance of a cluster between 0.01 and 10% at z>0.3, increasing with cuspiness of the cool core and angular size on the sky of the cluster (i.e., decreasing redshift, increasing mass). We provide quantitative estimates of the bias in the SZ signal as a function of a gas density cuspiness parameter, redshift, mass, and the 1.4 GHz radio luminosity of the central active galactic nuclei. Based on this work, we estimate that, for the Phoenix cluster (one of the strongest cool cores known), the presence of a cool core is biasing the SZ significance high by ∼6%. The ubiquity of radio galaxies at the centers of cool core clusters will offset the cool core bias to varying degrees.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Dynamically accumulated dose and 4D accumulated dose for moving tumors

Purpose: The purpose of this work was to investigate the relationship between dynamically accumulated dose (dynamic dose) and 4D accumulated dose (4D dose) for irradiation of moving tumors, and to quantify the dose uncertainty induced by tumor motion. Methods: The authors established that regardless of treatment modality and delivery properties, the dynamic dose will converge to the 4D dose, instead of the 3D static dose, after multiple deliveries. The bounds of dynamic dose, or the maximum estimation error using 4D or static dose, were established for the 4D and static doses, respectively. Numerical simulations were performed (1) to prove the principle that for each phase, after multiple deliveries, the average number of deliveries for any given time converges to the total number of fractions (K) over the number of phases (N); (2) to investigate the dose difference between the 4D and dynamic doses as a function of the number of deliveries for deliveries of a 'pulsed beam'; and (3) to investigate the dose difference between 4D dose and dynamic doses as a function of delivery time for deliveries of a 'continuous beam.' A Poisson model was developed to estimate the mean dose error as a function of number of deliveries or delivered time for both pulsed beam and continuous beam. Results: The numerical simulations confirmed that the number of deliveries for each phase converges to K/N, assuming a random starting phase. Simulations for the pulsed beam and continuous beam also suggested that the dose error is a strong function of the number of deliveries and/or total deliver time and could be a function of the breathing cycle, depending on the mode of delivery. The Poisson model agrees well with the simulation. Conclusions: Dynamically accumulated dose will converge to the 4D accumulated dose after multiple deliveries, regardless of treatment modality. Bounds of the dynamic dose could be determined using quantities derived from 4D doses, and the mean dose difference between the dynamic dose and 4D dose as a function of number of deliveries and/or total deliver time was also established.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗
DOE OSTI2016

LOW-METALLICITY YOUNG CLUSTERS IN THE OUTER GALAXY. I. Sh 2-207

To study star formation in low-metallicity environments ([M/H] ∼ −1 dex), we obtained deep near-infrared (NIR) images of Sh 2-207 (S207), which is an H ii region in the outer Galaxy with a spectroscopically determined metallicity of [O/H] ≃ −0.8 dex. We identified a young cluster in the western region of S207 with a limiting magnitude of K{sub S} = 19.0 mag (10σ) that corresponds to a mass detection limit of ≲0.1 M{sub ⊙} and enables the comparison of star-forming properties under low metallicity with those of the solar neighborhood. From the fitting of the K-band luminosity function (KLF), the age and distance of the S207 cluster are estimated at 2–3 Myr and ∼4 kpc, respectively. The estimated age is consistent with the suggestion of small extinctions of stars in the cluster (A{sub V} ∼ 3 mag) and the non-detection of molecular clouds. The reasonably good fit between the observed KLF and the model KLF suggests that the underlying initial mass function (IMF) of the cluster down to the detection limit is not significantly different from the typical IMFs in the solar metallicity. From the fraction of stars with NIR excesses, a low disk fraction (<10%) in the cluster with a relatively young age is suggested, as we had previously proposed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate

Abstract The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long‐term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature ( Tmax ) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high‐emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH given Tmax with quantile regression models, using functions of temperature for each city in July for three time periods (1990–2005, 2026–2035, and 2071–2080). Quality‐of‐fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile of Tmax increases from 1990–2005 to 2071–2080, while mean RH decreases modestly. Conditional upon a fixed quantile of Tmax , the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixed Tmax , the high quantiles of RH (and thus of HI and dew point) increase from 1990–2005 to 2071–2080 in all four cities. This result suggests that the heat stress of a day at a given Tmax will increase in a warming climate due to the increase of RH.

Yuan, Jiacan↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2015

Effect of van der Waals interactions on the structural and binding properties of GaSe

The influence of van der Waals interactions on the lattice parameters, band structure, elastic moduli and binding energy of layered GaSe compound has been studied using projector-augmented wave method within density functional theory. We employed the conventional local/semilocal exchange-correlation functionals and recently developed van der Waals functionals which are able to describe dispersion forces. It is found that application of van der Waals density functionals allows to substantially increase the accuracy of calculations of the lattice constants a and c and interlayer distance in GaSe at ambient conditions and under hydrostatic pressure. The pressure dependences of the a-parameter, Ga–Ga, Ga–Se bond lengths and Ga–Ga–Se bond angle are characterized by a relatively low curvature, while c(p) has a distinct downward bowing due to nonlinear shrinking of the interlayer spacing. From the calculated binding energy curves we deduce the interlayer binding energy of GaSe, which is found to be in the range 0.172–0.197 eV/layer (14.2–16.2 meV/Å{sup 2}). - Highlights: • Effects of van der Waals interactions are analyzed using advanced density functionals. • Calculations with vdW-corrected functionals closely agree with experiment. • Interlayer binding energy of GaSe is estimated to be 14.2–16.2 meV/Å{sup 2}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

A REDSHIFT SURVEY OF HERSCHEL FAR-INFRARED SELECTED STARBURSTS AND IMPLICATIONS FOR OBSCURED STAR FORMATION

We present Keck spectroscopic observations and redshifts for a sample of 767 Herschel-SPIRE selected galaxies (HSGs) at 250, 350, and 500 {mu}m, taken with the Keck I Low Resolution Imaging Spectrometer and the Keck II DEep Imaging Multi-Object Spectrograph. The redshift distribution of these SPIRE sources from the Herschel Multitiered Extragalactic Survey peaks at z = 0.85, with 731 sources at z < 2 and a tail of sources out to z {approx} 5. We measure more significant disagreement between photometric and spectroscopic redshifts (({Delta}z/(1 + z{sub spec})) = 0.29) than is seen in non-infrared selected samples, likely due to enhanced star formation rates and dust obscuration in infrared-selected galaxies. The infrared data are used to directly measure integrated infrared luminosities and dust temperatures independent of radio or 24 {mu}m flux densities. By probing the dust spectral energy distribution (SED) at its peak, we estimate that the vast majority (72%-83%) of z < 2 Herschel-selected galaxies would drop out of traditional submillimeter surveys at 0.85-1 mm. We find that dust temperature traces infrared luminosity, due in part to the SPIRE wavelength selection biases, and partially from physical effects. As a result, we measure no significant trend in SPIRE color with redshift; if dust temperature were independent of luminosity or redshift, a trend in SPIRE color would be expected. Composite infrared SEDs are constructed as a function of infrared luminosity, showing the increase in dust temperature with luminosity, and subtle change in near-infrared and mid-infrared spectral properties. Moderate evolution in the far-infrared (FIR)/radio correlation is measured for this partially radio-selected sample, with q{sub IR}{proportional_to}(1 + z){sup -0.30{+-}0.02} at z < 2. We estimate the luminosity function and implied star formation rate density contribution of HSGs at z < 1.6 and find overall agreement with work based on 24 {mu}m extrapolations of the LIRG, ULIRG, and total infrared contributions. This work significantly increased the number of spectroscopically confirmed infrared-luminous galaxies at z >> 0 and demonstrates the growing importance of dusty starbursts for galaxy evolution studies and the build-up of stellar mass throughout cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Maps of the Magellanic clouds from combined South Pole Telescope and Planck data

Here, we present maps of the Large and Small Magellanic Clouds from combined South Pole Telescope (SPT) and Planck data. Both instruments are designed to make measurements of the cosmic microwave background but are sensitive to any source of millimeter-wave (mm-wave) emission. The Planck satellite observes in nine mm-wave bands, while the SPT data used in this work were taken with the three-band SPT-SZ camera. The SPT-SZ bands correspond closely to three of the nine Planck bands, namely those centered at 1.4, 2.1, and 3.0 mm. The angular resolution of the Planck data in these bands ranges from 5 to 10 arcmin, while the SPT resolution in these bands ranges from 1.0 to 1.7 arcmin. The combined maps take advantage of the high resolution of the SPT data and the long-timescale stability of the space-based Planck observations to deliver high signal-to-noise and robust brightness measurements on scales from the size of the maps down to ~1 arcmin. In each of the three bands, we first calibrate and color-correct the SPT data to match the Planck data, then we use noise estimates from each instrument and knowledge of each instrument's beam, or point-spread function, to make the inverse-variance-weighted combination of the two instruments' data as a function of angular scale. Furthermore, we create maps assuming a range of underlying emission spectra (for the color correction) and at a range of final resolutions. We perform several consistency tests on the combined maps and estimate the expected noise in measurements of features in the maps. Finally, we compare the maps of the Large Magellanic Cloud (LMC) from this work to maps from the Herschel HERITAGE survey, finding general consistency between the datasets. Furthermore, the broad wavelength coverage provides evidence of different emission mechanisms at work in different environments in the LMC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy-scale photosynthesis

The proliferation of digital cameras co-located with eddy covariance instrumentation provides new opportunities to better understand the relationship between canopy phenology and the seasonality of canopy photosynthesis. In this paper we analyze the abilities and limitations of canopy color metrics measured by digital repeat photography to track seasonal canopy development and photosynthesis, determine phenological transition dates, and estimate intra-annual and interannual variability in canopy photosynthesis. Here, we used 59 site-years of camera imagery and net ecosystem exchange measurements from 17 towers spanning three plant functional types (deciduous broadleaf forest, evergreen needleleaf forest, and grassland/crops) to derive color indices and estimate gross primary productivity (GPP). GPP was strongly correlated with greenness derived from camera imagery in all three plant functional types. Specifically, the beginning of the photosynthetic period in deciduous broadleaf forest and grassland/crops and the end of the photosynthetic period in grassland/crops were both correlated with changes in greenness; changes in redness were correlated with the end of the photosynthetic period in deciduous broadleaf forest. However, it was not possible to accurately identify the beginning or ending of the photosynthetic period using camera greenness in evergreen needleleaf forest. At deciduous broadleaf sites, anomalies in integrated greenness and total GPP were significantly correlated up to 60 days after the mean onset date for the start of spring. More generally, results from this work demonstrate that digital repeat photography can be used to quantify both the duration of the photosynthetically active period as well as total GPP in deciduous broadleaf forest and grassland/crops, but that new and different approaches are required before comparable results can be achieved in evergreen needleleaf forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Adversarial autoencoder ensemble for fast and probabilistic reconstructions of few-shot photon correlation functions for solid-state quantum emitters

Second-order photon correlation measurements [g (2) (τ) functions] are widely used to classify single-photon emission purity in quantum emitters or to measure the multiexciton quantum yield of emitters that can simultaneously host multiple excitations – such as quantum dots – by evaluating the value of g (2) (τ = 0). Accumulating enough photons to accurately calculate this value is time consuming and could be accelerated by fitting of few-shot photon correlations. Here, we develop an uncertainty-aware, deep adversarial autoencoder ensemble (AAE) that reconstructs noise-free g (2) (τ) functions from noise-dominated, few-shot inputs. The model is trained with simulated g (2) (τ) functions that are facilely generated by Poisson sampling time bins. The AAE reconstructions are performed orders-of-magnitude faster, with reconstruction errors and estimates of g (2) (τ = 0) that are lower in variance and similar in accuracy compared to Maximum likelihood estimation and Levenberg-Marquardt least-squares fitting approaches, for simulated and experimentally measured few-shot g (2) (τ) functions (~100 two-photon events) of InP/ZnS/ZnSe and CdS/CdSe/CdS quantum dots. The deep-ensemble model comprises eight individual autoencoders, allowing for probabilistic reconstructions of noise-free g (2) (τ) functions, and we show that the predicted variance scales inversely with number of shots, with comparable uncertainties to computationally intensive Markov chain Monte Carlo sampling. Furthermore, this work demonstrates the advantage of machine learning models to perform uncertainty-aware, fast, and accurate reconstructions of simple Poisson-distributed photon correlation functions, allowing for on-the-fly reconstructions and accelerated materials characterization of solid-state quantum emitters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Drift-flux Analysis in Horizontal Two-phase Flow

While the most detailed approach to model two-phase flows is the two-fluid model, the drift-flux model may also provide effective methods for estimating one-dimensional two-phase flow parameters. For example, in the current nuclear system analysis codes, the interfacial drag force is a function of the void fraction, drift velocity, and area-averaged relative velocity, which are estimated based on drift-flux approach. While correlations for these parameters exist for vertical two-phase flows, correlations for horizontal two-phase flows have not been developed. (authors)

42 ENGINEERING↗
DOE OSTI2014

SU-E-I-07: An Improved Technique for Scatter Correction in PET

Purpose: In positron emission tomography (PET), the single scatter simulation (SSS) algorithm is widely used for scatter estimation in clinical scans. However, bias usually occurs at the essential steps of scaling the computed SSS distribution to real scatter amounts by employing the scatter-only projection tail. The bias can be amplified when the scatter-only projection tail is too small, resulting in incorrect scatter correction. To this end, we propose a novel scatter calibration technique to accurately estimate the amount of scatter using pre-determined scatter fraction (SF) function instead of the employment of scatter-only tail information. Methods: As the SF depends on the radioactivity distribution and the attenuating material of the patient, an accurate theoretical relation cannot be devised. Instead, we constructed an empirical transformation function between SFs and average attenuation coefficients based on a serious of phantom studies with different sizes and materials. From the average attenuation coefficient, the predicted SFs were calculated using empirical transformation function. Hence, real scatter amount can be obtained by scaling the SSS distribution with the predicted SFs. The simulation was conducted using the SimSET. The Siemens Biograph™ 6 PET scanner was modeled in this study. The Software for Tomographic Image Reconstruction (STIR) was employed to estimate the scatter and reconstruct images. The EEC phantom was adopted to evaluate the performance of our proposed technique. Results: The scatter-corrected image of our method demonstrated improved image contrast over that of SSS. For our technique and SSS of the reconstructed images, the normalized standard deviation were 0.053 and 0.182, respectively; the root mean squared errors were 11.852 and 13.767, respectively. Conclusion: We have proposed an alternative method to calibrate SSS (C-SSS) to the absolute scatter amounts using SF. This method can avoid the bias caused by the insufficient tail information and therefore improve the accuracy of scatter estimation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Instantaneous Frequency and Damping from Transient Ring-Down Data

Broadband impact excitation in structural dynamics is a common technique used to detect and characterize nonlinearities in mechanical systems since it excites many frequencies of a structure at once and can be applied with a variety of boundary conditions. Non-stationary time signals from transient ring-down measurements require time-frequency analysis tools to observe variations in frequency and energy dissipation as the response evolves. This work uses the short-time Fourier transform to estimate the instantaneous frequency and damping ratio from either measured or simulated transient ring-down data. By combining the discrete Fourier transform with an expanding or contracting window function that moves along the time axis, the resulting spectrum is used to estimate the instantaneous frequencies, damping and complex Fourier coefficients. This method is demonstrated on a multi-degree-of-freedom beam with a cubic spring attachment, and investigates the amplitudefrequency dependence in connection to the undamped nonlinear normal modes. A second example shows the results from experiment ring-down response on a beam with a lap joint, and reveals how the system behaves as energy dissipates.

42 ENGINEERING↗
DOE OSTI2019

Measurement of the Crab Nebula Spectrum Past 100 TeV with HAWC

In this study, we present TeV gamma-ray observations of the Crab Nebula, the standard reference source in ground-based gamma-ray astronomy, using data from the High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory. In this analysis we use two independent energy estimation methods that utilize extensive air shower variables such as the core position, shower angle, and shower lateral energy distribution. In contrast, the previously published HAWC energy spectrum roughly estimated the shower energy with only the number of photomultipliers triggered. This new methodology yields a much-improved energy resolution over the previous analysis and extends HAWC's ability to accurately measure gamma-ray energies well beyond 100 TeV. The energy spectrum of the Crab Nebula is well fit to a log-parabola shape $\left(\tfrac{{dN}}{{dE}}={\phi }_{0}{\left(E/7\mathrm{TeV}\right)}^{-\alpha -\beta \mathrm{ln}\left(E/7\mathrm{TeV}\right)}\right)$ with emission up to at least 100 TeV. For the first estimator, a ground parameter that utilizes fits to the lateral distribution function to measure the charge density 40 m from the shower axis, the best-fit values are ${\phi }_{o}=(2.35\pm {0.04}_{-0.21}^{+0.20})\times {10}^{-13}$ (TeV cm 2 s) -1 , $\alpha =2.79\pm {0.02}_{-0.03}^{+0.01}$, and $\beta =0.10\pm {0.01}_{-0.03}^{+0.01}$. For the second estimator, a neural network that uses the charge distribution in annuli around the core and other variables, these values are ${\phi }_{o}=(2.31\pm {0.02}_{-0.17}^{+0.32})\times {10}^{-13}$ (TeV cm 2 s) -1 , $\alpha =2.73\pm {0.02}_{-0.02}^{+0.03}$, and β = 0.06 ± 0.01 ± 0.02. The first set of uncertainties is statistical; the second set is systematic. Both methods yield compatible results. Finally, these measurements are the highest-energy observation of a gamma-ray source to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Multipoint Observations of Energetic Particle Injections and Substorm Activity During a Conjunction Between Magnetospheric Multiscale (MMS) and Van Allen Probes

Here, this study examines multipoint observations during a conjunction between Magnetospheric Multiscale (MMS) and Van Allen Probes on 7 April 2016 in which a series of energetic particle injections occurred. With complementary data from Time History of Events and Macroscale Interactions during Substorms, Geotail, and Los Alamos National Laboratory spacecraft in geosynchronous orbit (16 spacecraft in total), we develop new insights on the nature of energetic particle injections associated with substorm activity. Despite this case involving only weak substorm activity (maximum AE <300 nT) during quiet geomagnetic conditions in steady, below-average solar wind, a complex series of at least six different electron injections was observed throughout the system. Intriguingly, only one corresponding ion injection was clearly observed. All ion and electron injections were observed at <600 keV only. MMS reveals detailed substructure within the largest electron injection. A relationship between injected electrons with energy <60 keV and enhanced whistler mode chorus wave activity is also established from Van Allen Probes and MMS. Drift mapping using a simplified magnetic field model provides estimates of the dispersionless injection boundary locations as a function of universal time, magnetic local time, and L shell. The analysis reveals that at least five electron injections, which were localized in magnetic local time, preceded a larger injection of both electrons and ions across nearly the entire nightside of the magnetosphere near geosynchronous orbit. The larger ion and electron injection did not penetrate to L < 6.6, but several of the smaller electron injections penetrated to L < 6.6. Due to the discrepancy between the number, penetration depth, and complexity of electron versus ion injections, this event presents challenges to the current conceptual models of energetic particle injections.

58 GEOSCIENCES↗