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NASA NTRS2012

A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

Lau, William K. M.↗

DOE OSTI2023

Multi-dimensional incoherent Thomson scattering system in PHAse Space MApping (PHASMA) facility

A multi-dimensional incoherent Thomson scattering diagnostic system capable of measuring electron temperature anisotropies at the level of the electron velocity distribution function (EVDF) is implemented on the PHAse Space MApping facility to investigate electron energization mechanisms during magnetic reconnection. This system incorporates two injection paths (perpendicular and parallel to the axial magnetic field) and two collection paths, providing four independent EVDF measurements along four velocity space directions. For strongly magnetized electrons, a 3D EVDF comprised of two characteristic electron temperatures perpendicular and parallel to the local magnetic field line is reconstructed from the four measured EVDFs. As a result, validation of isotropic electrons in a single magnetic flux rope and a steady-state helicon plasma is presented.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Local structure, bonding, and asymmetry of $\mathrm{((NH_2)_2CH)PbBr_3}$, $\mathrm{CsPbBr_3}$, and $\mathrm{(CH_3MH_3)PbBr_3}$

Here we report local structure measurements for CsPbBr 3 and ((NH 2 ) 2 CH)PbBr 3 (FAPbBr 3 ) and compare them with recent results for (CH 3 NH 3 )PbBr 3 (MAPbBr 3 ). The Pb-Br bonding is similar for all three systems; the effective spring constants, κ, are comparable (ranging from 1.20 to 1.95 eV/Å 2 ), but small in magnitude indicating very soft materials. However, there are also important differences between the three systems. Static disorder is very small for CsPbBr3 but increases somewhat with the size of the organic molecular ions MA + and FA + . At room temperature, dynamic disorder dominates in all compounds. The thermal disorder of the Pb-Br pair distribution function (PDF), i.e., the Debye-Waller factor σ 2 follows a correlated Debye or Einstein model up to 300 K in CsPbBr 3 (orthorhombic phase), but for FAPbBr 3 and MAPbBr 3 , there is a break in the σ 2 (T) curve at the orthorhombic-tetragonal transition (o-t) near 150 K, indicating a small change in the spring constant κ. κ increases for MAPbBr 3 but decreases in FAPbBr 3 at this transition. These changes are attributed to changes in the H-bonding between Br - and MA + or FA + at this transition, as a result of librations or rotations of these molecular cations. In addition, the Pb-Br PDF becomes asymmetric at a relatively low temperature for FAPbBr 3 and MAPbBr 3 , while this effect is significantly smaller for CsPbBr 3 . Finally, we address the question of a model to explain the asymmetric PDF. Two main models are discussed in the literature, an anharmonic pair potential and a split-pair distribution, possibly driven by the presence of a lone pair on the Pb ion. We show that the fourth cumulant C 4 can differentiate between these two models and other possible models. Experimentally C 4 is positive at 250 K and above, for all three systems and that is inconsistent with a split-peak model, for which C 4 is negative for splittings larger than 0.12 Å.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1994

A time-dependent gyro-kinetic model of thermal ion upflows in the high-latitude F region

Ample evidence supports the significance of the high-latitude ionospheric contribution to magnetospheric plasma. Assuming flux conservation along a flux tube, the upward field-aligned ion flows observed in the magnetosphere require high-latitude ionospheric field-aligned ion upflows of the order of 10(exp 8) to 10(exp 9)/sq cm/s. Since radar and satellite observations of high-latitude F region flows at times exceed this flux requirement by an order of magnitude, the thermal ionospheric upflows are not simply the ionospheric response to a magnetospheric flux requirement. Several ionospheric ion upflow mechanisms have been proposed, but simulations based on fluid theory do not reproduce all the observed features of ionospheric ion upflows. Certain asymmetries in the statistical morphology of high-latitude F region ion upflows suggest that the ion upflows may be generated by ion-neutral frictional heating. We developed a single-component (O(+)), time-dependent gyro-kinetic model of the high-latitude F region response to frictional heating in which the neutral exobase is a discontinuous boundary between fully collisional and collisionless plasmas. The concept of a discontinuous neutreal exobase and the assumption of a constant and uniform polarization electric field reduce the ion velocity distribution function, from which we can compute the ion density, parallel velocity, parallel and perpendicular temperature, and parallel flux. Using our model, we simulated the response of a convecting flux tube between 500 km and 2500 km to various frictional heating inputs; the results were both qualitatively and quantitatively different from fluid model results, which may indicate an inadequacy of the fluid theory approach. The gyro-kinetic frictional heating model responses to the various simulations were qualitatively similar: (1) initial perturbations of all the modeled parameters propagated rapidly up the flux tube, (2) transient values of the ion parallel velocity, temperature, and flux exceeded 3 km/s, 2 x 10(exp 4) K, and 10(exp 9)/sq cm/s, respectively, (3) a second transient regime developed wherein the parallel temperature drops to very low values (a few hundred Kelvins), and (4) well after heating ceased, large parallel temperatures and large downward parallel velocities and fluxes developed as the flux tube slowly returned to diffusive equilibrium. The ion velocity distributions during the simulation are often non-Maxwellian and are sometimes composed of two distinct ion populations.

Loranc, M.↗

DOE OSTI2022

Plasma diagnostics and modeling of lithium-containing plasmas

Thin-film deposition from chemically reactive multi-component plasmas is complex, and the lack of electron collision cross-sections for even the most common metalorganic precursors and their fragments complicates their modeling based on fundamental plasma physics. This study focuses on understanding the plasma physics and chemistry in argon (Ar) plasmas containing lithium bis (trimethylsilyl) amide used to deposit Li x Si y thin films. These films are emerging as potential solid electrolytes for lithium-ion batteries, and the Li-to-Si ratio is a crucial parameter to enhance their ionic conductivity. We deposited Li x Si y films in an axial flow-through plasma reactor and studied the factors that determine the variation of the Li-to-Si ratio in films deposited at various points on a substrate spanning the entire reactor axis. While the Li-to-Si ratio is 1:2 in the precursor, the Li-to-Si ratio is as high as 3:1 in films deposited near the plasma entrance and decreases to 1:1 for films deposited downstream. Optical emission from the plasma is dominated by Li emission near the entrance, but Li emission disappears downstream, which we attribute to the complete consumption of the precursor. We hypothesized that the axially decreasing precursor concentration affects the electron energy distribution function in a way that causes different dissociation efficiencies for the production of Li and Si. We used Li line intensities to estimate the local precursor concentration and Ar line ratios to estimate the local reduced electric field to test this hypothesis. This analysis suggests that the mean electron energy increases along the reactor axis with decreasing precursor concentration. As a result, the decreasing Li-to-Si ratio with axially decreasing precursor concentration may be explained by Li release from the precursor having lower threshold energy than Si release.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

bnl/pub-Maffettone_2020_08

The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Maffettone, PhillipM [Brookhaven National Lab. (BN↗

DOE OSTI2021

Crystallography companion agent for high-throughput materials discovery

The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time-consuming, error-prone and impossible to scale. With the advent of autonomous robotic scientists or self-driving laboratories, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which outputs probabilistic classifications—rather than absolutes—to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering substantial time savings. It is demonstrated on a diverse set of organic and inorganic materials characterization challenges. This method is directly applicable to inverse design approaches and robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Continuum electromagnetic gyrokinetic simulations of turbulence in the tokamak scrape-off layer and laboratory devices

Here, we present algorithms and results from Gkeyll, a full-f continuum, electromagnetic gyrokinetic code, designed to study turbulence in the edge region of fusion devices. The edge is computationally very challenging, requiring robust algorithms that can handle large-amplitude fluctuations and stable interactions with plasma sheaths. We present an energy-conserving high-order discontinuous Galerkin scheme that solves gyrokinetic equations in Hamiltonian form. Efficiency is improved by a careful choice of basis functions and automatically generated computation kernels. Previous verification tests were performed in the straight-field-line large plasma device [Shi et al., J. Plasma Phys. 83, 905830304 (2017)] and the Texas Helimak, a simple magnetized torus [Bernard et al., Phys. Plasmas 26, 042301 (2019)], including the effect of end-plate biasing on turbulence. Results for the scrape-off layer for NSTX parameters with a model helical magnetic geometry with bad curvature have been obtained [Shi et al., Phys. Plasmas 26, 012307 (2019)]. In this paper, we present algorithms for the two formulations of electromagnetic gyrokinetics: the Hamiltonian and the symplectic. We describe each formulation and show results of benchmark tests. Although our scheme works for the Hamiltonian formulation, the presence of spurious numerical modes for high-β and large $k^2_⊥ρ^2_s$ regimes shows that the symplectic formulation is more robust. We then review our recent algorithm for the symplectic formulation [Mandell et al., J. Plasma Phys. 86, 905860109 (2020)], along with example application of this new capability. Maintaining positivity of the distribution function can be challenging, and we describe a new and novel exponential recovery based algorithm to address this.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Learning functional priors and posteriors from data and physics

In this work, we develop a new Bayesian framework based on deep neural networks to be able to extrapolate in space-time using historical data and to quantify uncertainties arising from both noisy and gappy data in physical problems. Specifically, the proposed approach has two stages: (1) prior learning and (2) posterior estimation. At the first stage, we employ the physics-informed Generative Adversarial Networks (PI-GAN) to learn a functional prior either from a prescribed function distribution, e.g., Gaussian process, or from historical data and physics. At the second stage, we employ the Hamiltonian Monte Carlo (HMC) method to estimate the posterior in the latent space of PI-GANs. In addition, we use two different approaches to encode the physics: (1) automatic differentiation, used in the physicsinformed neural networks (PINNs) for scenarios with explicitly known partial differential equations (PDEs), and (2) operator regression using the deep operator network (DeepONet) for PDE-agnostic scenarios. We then test the proposed method for (1) meta-learning for one-dimensional regression, and forward/inverse PDE problems (combined with PINNs); (2) PDE-agnostic physical problems (combined with DeepONet), e.g., fractional diffusion as well as saturated stochastic (100-dimensional) flows in heterogeneous porous media; and (3) spatial-temporal regression problems, i.e., inference of a marine riser displacement field using experimental data from the Norwegian Deepwater Programme (NDP). The results demonstrate that the proposed approach can provide accurate predictions as well as uncertainty quantification given very limited scattered and noisy data, since historical data could be available to provide informative priors. In summary, the proposed method is capable of learning flexible functional priors, e.g., both Gaussian and non-Gaussian process, and can be readily extended to big data problems by enabling mini-batch training using stochastic HMC or normalizing flows since the latent space is generally characterized as low dimensional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2007

Comparison of Integrated Radiation Transport Models with TEPC Measurements for the Average Quality Factors in Spaceflights

The purpose of this work is to test our theoretical model for the interpretation of radiation data measured in space. During the space missions astronauts are exposed to the complex field of radiation type and kinetic energies from galactic cosmic rays (GCR), trapped protons, and sometimes solar particle events (SPEs). The tissue equivalent proportional counter (TEPC) is a simple time-dependent approach for radiation monitoring for astronauts on board the International Space Station. Another and a newer approach to Microdosimetry is the use of silicon-on-insulator (SOI) technology launched on the MidSTAR-1 mission in low Earth orbit (LEO). In the radiation protection practice, the average quality factor of a radiation field is defined as a function of linear energy transfer (LET), Q(sub ave)(LET). However, TEPC measures the average quality factor as a function of the lineal energy y, Q(sub ave)(y), defined as the average energy deposition in a volume divided by the average chord length of the volume. Lineal energy, y, deviates from LET due to energy straggling, delta-ray escape or entry, and nuclear fragments produced in the detector volume. Monte Carlo track structure simulation was employed to obtain the response of a TEPC irradiated with charged particle for an equivalent site diameter of 1 micron of wall-less counter. The calculated data of the energy absorption in the wall-less counter were compiled for various y values for several ion types at various discrete projectile energy levels. For the simulation of TEPC response from the mixed radiation environments inside a spacecraft, such as, Space Shuttle and International Space Station, the complete microdosimetric TEPC response, f( y, E, Z), were calculated with the Monte Carlo theoretical results by using the first order Lagrangian interpolation for a monovariate function at a given y value (y = 0.1 keV/micron 5000 keV/micron) at any projectile energy level (E = 0.01 MeV/u to 50,000 MeV/u) of each specific radiation type (Z = 1 to 28). Because the anomalous response has been observed at large event sizes in the experiment due to the escape of energy out of sensitive volume by delta-rays and the entry of delta-rays from the high-density wall into the low-density gas-volume cavity, Monte Carlo simulation was also made for the response of a walled-TEPC with wall thickness 2 mm and density 1 g/cm(exp 3). The radius of cavity was set to 6.35 mm and a gas density 7.874 x 10(exp -5) g/cm(exp 3). The response of the walled- and the wall-less counters were compared. The average quality factor Q(sub ave)(y) for trapped protons on STS-89 demonstrated the good agreement between the model calculations and flight TEPC data as shown. Using an integrated space radiation model (this includes the transport codes HZETRN and BRYNTRN, the quantum nuclear interaction model QMSFRG) and the resultant response distribution functions of walled-TEPC from Monte-Carlo track simulations, we compared model calculations with walled-TEPC measurements from NASA missions in LEO and made predictions for the lunar and the Mars missions. The Q(sub ave)(y) values for the trapped or the solar protons ranged from 1.9-2.5. This over-estimates the Qave(LET) values which ranged from 1.4-1.6. Both quantities increase with shield thickness due to nuclear fragmentation. The Q(sub ave)(LET) for the complete GCR spectra was found to be 3.5-4.5, while flight TEPCs measured 2.9-3.4 for Q(sub ave)(y). The GCR values are decreasing with the shield thickness. Our analysis for a proper interpretation of data supports the use of TEPCs for monitoring space radiation environment.

Kim, Myung-Hee Y.↗

DOE OSTI2022

Presentation of gas-phase-reactant-accessible single-rhodium-atom catalysts for CO oxidation, via MOF confinement of an Anderson polyoxometalate

Geometric or electronic confinement of guests within nanoporous hosts holds promise for imparting catalytic functionality, including single-metal-atom catalytic functionality, to existing materials. When the nanoporous host is a metal–organic framework (MOF), single-metal-ion catalysts have typically been installed by grafting to an open site on an inorganic node, with the node effectively becoming the support for the catalyst. This approach, however, imposes compositional constraints, as the node not only needs to be receptive to grafting, but also must be capable of stabilizing the framework against solvent evacuation, chemical exposure, and heating. Here, we show that disk-like, Anderson polyoxometalate clusters (RhMo 6 O 24 n- and Mo 7 O 24 m- ; POMs) can be confined in pore-specific and orientation-specific fashion within the hierarchically porous, Zr(IV)-based MOF, NU1K. Self-limiting loading of one cluster per pore, and associated nano-confinement, serve to isolate each POM and prevent consolidation caused by sintering. Additionally, the oriented confinement serves to expose individual rhodium atoms to candidate gas-phase reactants, while enabling the rhodium atom to employ a well-defined oxy-molybdenum cluster, rather than a MOF node, as a support. Synchrotron-based difference-electron-density maps and differential pair-distribution-function analyses of scattered X-rays establish cluster siting and orientation and confirm isolation. Nanoconfined (i.e., MOF- and POM-confined) single-rhodium(III)-atoms are catalytically competent for an illustrative gas-phase reaction, CO oxidation by O 2 , with the MOF-isolated POM enormously outperforming nonporous, MOF-free, solid (NH 4 ) 3 [H 6 RhMo 6 O 24 ]·6H 2 O. This paper highlights the value of MOF-based nano-confinement and oriented isolation of planar POMs as a means of uniformly presenting and stabilizing potent single-metal-atom catalysts, in reactant-accessible form, on well-defined supports.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Experimental Verification of Ir 5d Orbital States and Atomic Structures in Highly Active Amorphous Iridium Oxide Catalysts

In iridium oxide catalysts, the electronic states whose energies are in the range of energetics and charge transfer kinetics of the oxygen evolution reaction (OER) originate from the Ir 5d orbital states. However, the understanding of the atomic structures and orbital states underlying catalytic reactivity in amorphous iridium oxide oxygen evolving catalysts (Ir-OECs) is incomplete compared to that of crystalline oxides, owing to a lack of direct experimental verification. Here, we present experimental approaches using resonant inelastic X-ray scattering (RIXS) to directly access Ir 5d orbital excitations at the Ir L 3 edge and atomic pair distribution function (PDF) measurements to characterize electronic and coordination structures at the atomic scale. The so-called iridium blue layer (IrBL) and IrO x were formed from the organometallic precursor complex [Cp*Ir(H 2 O) 3 ]SO 4 and the inorganic precursor IrCl 3 , respectively. Ex situ IrBL and IrO x films for RIXS and PDF measurements were prepared by conditioning electrodeposited films at a low voltage. The incident energy RIXS profile of IrO x exhibited extra weak resonantly enhanced excitation below 2 eV energy loss. The feature was clearly different from a single high-energy excitation above 3 eV of IrBL related to the interband transition between π- and σ-antibonding states. The atomic structure refinement based on PDF measurements revealed the atomic structure domains to have edge- and corner-shared IrO 6 octahedra with trigonal-type distortion. Furthermore, density functional theory calculations guided by the refined atomic structures shed light on the electronic structure corresponding to experimental results, including insulating and metallic phases in ex situ IrBL and IrO x films, respectively. Our study establishes different Ir 5d orbital states and atomic structures in two amorphous Ir oxide OER catalysts in their reduction states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Gluon helicity in the nucleon from lattice QCD and machine learning

We present the first lattice QCD determination of the light cone gluon helicity correlation parton distribution function (PDF) with numerical evidence toward disfavoring negative gluon polarization in the nucleon. We present a solution for eliminating an inevitable contamination term that dominates the Euclidean correlations and makes determining gluon helicity PDF unfeasible. The proposed synergy between lattice QCD and artificial intelligence offers a superior platform to alleviate the defining challenge of extracting quark and gluon PDFs from the lattice data that are available in a limited domain due to a finite range of accessible hadron momenta. We suggest a systematically improvable method to extract PDFs from the lattice data, independent of inadequate parametrizations. The result of the gluon helicity will improve our understanding of the role of spin in the strong interaction and the nucleon-spin structure.

Lattice QCD↗

DOE OSTI2023

Gluon transverse-momentum-dependent distributions from large-momentum effective theory

We demonstrate that gluon transverse-momentum-dependent parton distribution functions (TMDPDFs) can be extracted from lattice calculations of appropriate Euclidean correlations in large-momentum effective theory (LaMET). Based on perturbative calculations of gluon unpolarized and helicity TMDPDFs, we present a matching formula connecting them and their LaMET counterparts, where the latter are renormalized in a scheme facilitating lattice calculations and converted to the $\overline{MS}$ scheme. The hard matching kernel is given up to one-loop level. We also show that the perturbative result is independent of the prescription used for the pinch-pole singularity in the relevant correlations. Our results offer a guidance for the extraction of gluon TMDPDFs from lattice simulations, and have the potential to greatly facilitate perturbative calculations of the hard matching kernel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Fresh look at the nuclear transparency using the generalized parton distributions

Color transparency (CT) is a fundamental phenomenon in QCD in which hadrons produced in high-energy exclusive processes traverse nuclear matter with minimal interactions. Nuclear transparency, which quantifies this attenuation suppression, is a quantity with high sensitivity to CT effects and provides critical insights into QCD dynamics in nuclear environments. In this study, we revisit nuclear transparency using the framework of generalized parton distributions (GPDs). By constructing nuclear GPDs (nGPDs) through the incorporation of nuclear parton distribution functions, we calculate the nuclear transparency 𝑇⁡(𝑄 2 ) for the carbon nucleus as a function of momentum transfer 𝑄 2 considering various definitions and compare the results obtained with available experimental data. Our finding highlights the importance of choosing a physically motivated definition of nuclear transparency. Moreover, we emphasize that a more reliable determination of nGPDs requires a dedicated global analysis incorporating nuclear data. Such an approach is essential for improving the theoretical understanding of CT and for achieving consistency with experimental observations in the high-𝑄 2 regime.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Effects of threshold resummation for large-x PDF in large momentum effective theory

Parton distribution functions (PDFs) at large x are challenging to extract from experimental data, yet they are essential for understanding hadron structure and searching for new physics beyond the Standard Model. Within the framework of the large momentum P z expansion of lattice quasi-PDFs, we investigate large x PDFs, where the matching coefficient is factorized into the hard kernel, related to the active quark momentum xP z , and the threshold soft function, associated with the spectator momentum (1 − x)P z . The renormalization group equation of the soft function enables the resummation of the threshold double logarithms α k ln 2k (1 − x), which is crucial for a reliable and controllable calculation of large x PDFs. Our analysis with pion valence PDFs indicates that perturbative matching breaks down when the spectator momentum (1 − x)P z approaches Λ QCD , but remains valid when both xP z and (1 − x)P z are much larger than Λ QCD . Additionally, we incorporate leading renormalon resummation within the threshold framework, demonstrating good perturbative convergence in the region where both spectator and active quark momenta are perturbative scales.

factorization↗

DOE OSTI2023

Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet and (ii) identifying the underlying hard process of the event. We propose applications of our machine learning-based jet identification in the key research areas at the future EIC and current Relativistic Heavy Ion Collider program, including enhancing constraints on (transverse momentum dependent) parton distribution functions, improving experimental access to transverse spin asymmetries, studying photon structure, and quantifying the modification of hadrons and jets in the cold nuclear matter environment in electron-nucleus collisions. We establish first benchmarks and contrast the estimated performance of flavor tagging at the EIC with that at the Large Hadron Collider. We perform studies relevant to aspects of detector design including particle identification, charge information, and minimum transverse momentum capabilities. Additionally, we study the impact of using full event information instead of using only information associated with the identified jet. These methods can be deployed either on suitably accurate Monte Carlo event generators, or, for several applications, directly on experimental data. We provide an outlook for ultimately connecting these machine learning-based methods with first principles calculations in quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2011

Characterizing Vegetation Cover in Global Savannas with an Annual Foliage Clumping Index Derived from the MODIS BRDF Product

The global savanna biome is characterized by enormous diversity in the physiognomy and spatial structure of the vegetation. The foliage clumping index can be calculated from bidirectional reflectance distribution function (BRDF) data. It measures the response of the darkspot reflectance to increased shadow associated with clumped vegetation and is related to leaf area index. Clumping index theoretically declines with increasing woody cover until the tree canopy begins to become uniform. In this study, clumping index is calculated for Moderate Resolution Imaging Spectroradiometer BRDF data for the Australian tropical savanna, the tropical savannas of South America, and the tropical savannas of east, west and southern Africa and compared with site-based measurements of tree canopy cover, and with area-based classifications of land cover. There were differences in sensitivity of clumping index between red and near-infrared reflectance channels, and between savanna systems with markedly different woody vegetation physiognomy. Clumping index was broadly related to foliage cover from historical site data in Australia and in West Africa and Kenya, but not in Southern Africa nor with detailed site-based demographic data in the cerrado of Brazil. However, clumping index decreased with proportion of woody cover in land cover datasets for east Africa, Australia and the Colombian Llanos. There was overlap in the range of clumping index values for forest, cerrado and campo land covers in Brazil. Clumping index was generally negatively correlated with percentage tree cover from the MODIS Vegetation Continuous Fields product, but regional differences in the relationship were evident. There were large differences in the frequency distributions of clumping index from savanna, woody savanna and grassland land cover classes between global ecoregions. The clumping index shows differing sensitivity to savanna woody cover for red and NIR reflectance, and requires regional calibration for application as a universal indicator.

Hill, Michael J.↗