Multiplicity dependence of inclusive J/ψ production at midrapidity in pp collisions at s = 13 TeV
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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Results for “MULTIPLE PRODUCTION”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Direct-photon production in inelastic and high-multiplicity proton–proton collisions at $\sqrt{s}$ = 13 TeV
In this letter, we present the first measurement of direct photons at the transverse momentum of 1 < 𝑝 T < 6 GeV/𝑐 at midrapidity 𝜂 < 0.8 in inelastic and high-multiplicity proton–proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The fraction of virtual direct photons in the inclusive virtual photon spectrum is obtained from a fit to the dielectron invariant mass spectrum. In the limit of zero invariant mass, this fraction is equal to the relative contribution of real direct photons in the inclusive real photon spectrum. Contributions from decays of light- flavour neutral mesons are estimated using independent measurements in proton–proton collisions at the same energy and the same event class. For the first time at the LHC energies, a direct-photon signal is observed at low 𝑝T in both inelastic and high-multiplicity event classes, with a significance of 3.2𝜎 and 1.9𝜎 in terms of standard deviations, correspondingly. The yield of direct photons in inelastic pp collisions is compared to perturbative QCD calculations. The integrated photon yield is studied as a function of charged-particle multiplicity and is compared to the results from other experiments and theoretical calculations. The results show a significant increase of direct- photon yield with charged-particle multiplicity.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Fusion of Multiple Models for Improving Gross Primary Production Estimation With Eddy Covariance Data Based on Machine Learning
Abstract Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.
Environmental Sciences & Ecology↗
Comparison of methane emission estimates from multiple measurement techniques at natural gas production pads
This study presents the results of a campaign that estimated methane emissions at 268 gas production facilities in the Fayetteville shale gas play using onsite measurements (261 facilities) and two downwind methods - the dual tracer flux ratio method (Tracer Facility Estimate - TFE, 17 facilities) and the EPA Other Test Method 33a (OTM33A Facility Estimate - OFE, 50 facilities). A study onsite estimate (SOE) for each facility was developed by combining direct measurements and simulation of unmeasured emission sources, using operator activity data and emission data from literature. The SOE spans 0-403 kg/h and simulated methane emissions from liquid unloadings account for 88% of total emissions estimated by the SOE, with 76% (95% CI [51%-92%]) contributed by liquid unloading at two facilities. TFE and SOE show overlapping 95% CI between individual estimates at 15 of 16 (94%) facilities where the measurements were paired, while OFE and SOE show overlapping 95% CI between individual estimates at 28 of 43 (65%) facilities. However, variance-weighted least-squares (VWLS) regressions performed on sets of paired estimates indicate statistically significant differences between methods. The SOE represents a lower bound of emissions at facilities where onsite direct measurements of continuously emitting sources are the primary contributor to the SOE, a sub-selection of facilities which minimizes expected inter-method differences for intermittent pneumatic controllers and the impact of episodically-emitting unloadings. At 9 such facilities, VWLS indicates that TFE estimates systematically higher emissions than SOE (TFE-to-SOE ratio = 1.6, 95% CI [1.2 to 2.1]). At 20 such facilities, VWLS indicates that OFE estimates systematically lower emissions than SOE (OFE-to-SOE ratio of 0.41 [0.26 to 0.90]). Given that SOE at these facilities is a lower limit on emissions, these results indicate that OFE is likely a less accurate method than SOE or TFE for this type of facility.
03 NATURAL GAS↗
Understanding Decision-Relevant Regional Data Products: Workshop Report
A broad community of climate adaptation practitioners, stakeholders and policymakers rely on historical reconstructions and future projections of local to regional climate. To be of value to these users, climate data must be credible, salient, and authoritative (Cash et al. 2002). Namely, data must be consistent with our physical understanding of the global Earth system, must be relevant for informing the decision-making process, and must be backed by expert judgment. As more and more data products have become available, multiple challenges have emerged around the production, evaluation, selection, and use of these data products. Consequently, to ensure crucial decisions leverage the best possible historical and future physical climate data, there is a pressing need to develop a coordinated national climate data strategy that is inclusive of all relevant communities of practice.
54 ENVIRONMENTAL SCIENCES↗
Tracing CP Violation in the Production of Top Quartk Pairs by Multiple TeV Proton-proton Collisions
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Brandenburg, A.↗
Multiplicity dependence of $\pi$, K, and p production in pp collisions at $\sqrt{s}$ = 13 TeV
This paper presents the measurements of π ± , K ± , p and $\bar{p}$ transverse momentum (p T ) spectra as a function of charged-particle multiplicity density in proton–proton (pp) collisions at $\sqrt{s}$ = 13TeV with the ALICE detector at the LHC. Such study allows us to isolate the center-of-mass energy dependence of light-flavour particle production. The measurements reported here cover a p T range from 0.1 to 20 GeV / c and are done in the rapidity interval | y| < 0.5. The p T -differential particle ratios exhibit an evolution with multiplicity, similar to that observed in pp collisions at $\sqrt{s}$ = 7 TeV, which is qualitatively described by some of the hydrodynamical and pQCD-inspired models discussed in this paper. Furthermore, the p T -integrated hadron-to-pion yield ratios measured in pp collisions at two different center-of-mass energies are consistent when compared at similar multiplicities. This also extends to strange and multi-strange hadrons, suggesting that, at LHC energies, particle hadrochemistry scales with particle multiplicity the same way under different collision energies and colliding systems.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication
We investigate outer-product--parallel, inner-product--parallel, and row-by-row-product--parallel formulations of sparse matrix-matrix multiplication (SpGEMM) on distributed memory architectures. For each of these three formulations, we propose a hypergraph model and a bipartite graph model for distributing SpGEMM computations based on one-dimensional (1D) partitioning of input matrices. Here, we also propose a communication hypergraph model for each formulation for distributing communication operations. The computational graph and hypergraph models adopted in the first phase aim at minimizing the total message volume and balancing the computational loads of processors, whereas the communication hypergraph models adopted in the second phase aim at minimizing the total message count and balancing the message volume loads of processors. That is, the computational partitioning models reduce the bandwidth cost and the communication hypergraph models reduce the latency cost. Our extensive parallel experiments on up to 2048 processors for a wide range of realistic SpGEMM instances show that although the outer-product--parallel formulation scales better, the row-by-row-product--parallel formulation is more viable due to its significantly lower partitioning overhead and competitive scalability. For computational partitioning models, our experimental findings indicate that the proposed bipartite graph models are attractive alternatives to their hypergraph counterparts because of their lower partitioning overhead. Finally, we show that by reducing the latency cost besides the bandwidth cost through using the communication hypergraph models, the parallel SpGEMM time can be further improved up to 32%.
97 MATHEMATICS AND COMPUTING↗
Sensor-Enabled Alleviation of Product Inhibition in Chorismate Pyruvate-Lyase
Product inhibition is a frequent bottleneck in industrial enzymes, and testing mutations to alleviate product inhibition via traditional methods remains challenging as many variants need to be tested against multiple substrate and product concentrations. Further, traditional screening methods are conducted in vitro, and resulting enzyme variants may perform differently in vivo in the context of whole-cell metabolism and regulation. In this study, we address these two problems by establishing a high-throughput screening method to alleviate product inhibition in an industrially relevant enzyme, chorismate pyruvate-lyase (UbiC). First, we engineered a highly specific, genetically encoded biosensor for 4-hydroxybenzoate (4HB) in an industrially relevant host, Pseudomonas putida KT2440. We subsequently applied the biosensor to detect the activity of a heterologously expressed UbiC that converts chorismate into 4HB and pyruvate. By using benzoate as a product surrogate that inhibits UbiC without activating the biosensor, we were able to efficiently create and screen a diversified library for UbiC variants with reduced product inhibition. Introduction of the improved UbiC enzyme variant into an experimental production strain for the industrial precursor cis,cis-muconic acid (muconate), enabled a >2-fold yield improvement for glucose to muconate conversion when the new UbiC variant was expressed from a plasmid and a 60% yield increase when the same UbiC variant was genomically integrated into the strain. Overall, this work demonstrates that by coupling a library of enzyme variants to whole-cell catalysis and biosensing, variants with reduced product inhibition can be identified, and that this improved enzyme can result in increased titers of a downstream molecule of interest.
09 BIOMASS FUELS↗
Concept Overview & Preliminary Analysis
'H2@Scale' is an opportunity for wide-scale use of hydrogen as an intermediate that carries energy from various production options to multiple uses. It is based on identifying and developing opportunities for low-cost hydrogen production and investigating opportunities for using that hydrogen across the electricity, industrial, and transportation sectors. One of the key production opportunities is use of low-cost electricity that may be generated under high penetrations of variable renewable generators such as wind and solar photovoltaics. The technical potential demand for hydrogen across the sectors is 60 million metric tons per year. The U.S. has sufficient domestic renewable resources so that each could meet that demand and could readily meet the demand using a portfolio of generation options. This presentation provides an overview of the concept and the technical potential demand and resources. It also motivates analysis and research on H2@Scale.
30 DIRECT ENERGY CONVERSION↗
Carbon Dioxide Utilization Life Cycle Analysis Guidance for the U.S. DOE Office of Fossil Energy and Carbon Management (Version 2.0)
Capturing carbon dioxide (CO 2 ) and placing it in permanent storage in geologic formations is an option for reducing CO 2 emissions, but it may not be a viable one for all CO 2 emitters. For some, the added cost of capture may be too high to implement, or the geology near the source may not be suitable for storage. In these circumstances, other options will be needed. Carbon use and reuse, or CO 2 utilization (CO2U), is an alternative approach that seeks beneficial uses for captured CO 2 , such as using it as a feedstock in the production of fuels, chemicals, and building materials. These uses would give CO 2 value that could be used by suppliers (emitters) to offset capture costs. One of the principal features and challenges associated with CO2U is that the products derived from CO 2 must have lower carbon footprints than their conventional counterparts. Previous assessments of CO2U alternatives have focused on the carbon content of utilization products as an indicator of CO 2 equivalent (CO 2 e) emissions reduction potential. However, embodied emissions are—at best—only weakly correlated with the amount of carbon contained in any physical product. Therefore, the most attractive CO2U options will both displace the carbon in an existing product and improve the overall carbon efficiency of the manufacturing process. Research to overcome barriers will include identifying existing co-feeds and available low-carbon energy sources to enable the conversion of CO 2 to value-added products under favorable processing conditions. New discoveries in the fields of nano- and bio-technology will be applied to efficiently utilize CO 2 in new applications. Development of advanced materials and processes, integrating CO 2 capture with utilization processes (e.g., algae), exploring a diverse slate of products from CO 2 to effectively offset capture costs and developing processes based on waste energy are means to overcome these barriers. The research will lead to the development of advanced catalysts, materials, and equipment that can be used to convert CO 2 into useful products. The result will be multiple flexible and adaptable technology platforms that can be used to produce suites of products spanning multiple utilization pathways.
54 ENVIRONMENTAL SCIENCES↗
Vegetation clumping modulates global photosynthesis through adjusting canopy light environment
Abstract The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within‐canopy light environment and photosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9%–15% and 23%–34% less direct and diffuse radiation, respectively, while shaded canopy absorbed 3%–18% more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption, and sunlit–shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity ( V cmax ), which together decreased photosynthesis in sunlit canopy by 5.9–7.2 PgC year −1 while enhanced photosynthesis by 6.9–8.2 PgC year −1 in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year −1 net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.
59 BASIC BIOLOGICAL SCIENCES↗
ISRU System Model Tool: From Excavation to Oxygen Production
In the late 80's, conceptual designs for an in situ oxygen production plant were documented in a study by Eagle Engineering [1]. In the "Summary of Findings" of this study, it is clearly pointed out that: "reported process mass and power estimates lack a consistent basis to allow comparison." The study goes on to say: "A study to produce a set of process mass, power, and volume requirements on a consistent basis is recommended." Today, approximately twenty years later, as humans plan to return to the moon and venture beyond, the need for flexible up-to-date models of the oxygen extraction production process has become even more clear. Multiple processes for the production of oxygen from lunar regolith are being investigated by NASA, academia, and industry. Three processes that have shown technical merit are molten regolith electrolysis, hydrogen reduction, and carbothermal reduction. These processes have been selected by NASA as the basis for the development of the ISRU System Model Tool (ISMT). In working to develop up-to-date system models for these processes NASA hopes to accomplish the following: (1) help in the evaluation process to select the most cost-effective and efficient process for further prototype development, (2) identify key parameters, (3) optimize the excavation and oxygen production processes, and (4) provide estimates on energy and power requirements, mass and volume of the system, oxygen production rate, mass of regolith required, mass of consumables, and other important parameters. Also, as confidence and high fidelity is achieved with each component's model, new techniques and processes can be introduced and analyzed at a fraction of the cost of traditional hardware development and test approaches. A first generation ISRU System Model Tool has been used to provide inputs to the Lunar Architecture Team studies.
Santiago-Maldonado, Edgardo↗
Aldol condensation of mixed oxygenates on TiO 2
Kinetic studies of aldol condensation of mixtures on TiO 2 reveal strong suppression of acetone self-condensation in the presence of acetaldehyde.
Oliphant, Brandon Elliott↗
Latest Development in Radiative Transfer Models and Retrieval Algorithms Using Principal Components
The radiative transfer model (RTMs) has a wide range of applications in satellite remote sensing and atmospheric radiation applications. However, millions of line-by-line (LBL) radiative transfer calculations at fine monochromatic frequencies are needed in order to properly calculate spectral contributions of water vapor and trace gases in the atmosphere in infrared and solar spectral regions. Therefore, fast and accurate RTMs are needed to efficiently process large amount of satellite data. A Principal Component-based Radiative Transfer Model (PCRTM) was first developed in 2004 at NASA Langley Research Centre to fulfil this need. By using PC-compression, one can reduce the data dimension significantly while maintaining original information content. The PCRTM can directly compute PC-scores and their derivatives with respect to retrieved parameters. The PCRTM can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra from 0.250 µm (400000 cm-1) to 2000 µm (50 cm-1) with several orders of magnitude faster speed as compared to a LBL RTM. It is also extremely accurate compared to LBL RTM benchmarks (0.03 K RMS error in IR and 0.05% in solar). The PCRTM model has been developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, FIRST, and CLARREO-IR in thermal IR spectral region and CLARREO-Solar, CPF, TEMPO, EMIT, OMI, and SCIAMACHY in solar spectral region. The PCRTM accuracy has been demonstrated via RTM intercomparisons and with real satellite observations from AIRS, CrIS, IASI, SCHIAMACHY, and EMIT etc. In this presentation, we will describe two PCRTM-based inversion algorithms to retrieve atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties from hyperspectral sounders such as AIRS, CrIS, IASI, and NAST-I. The first one is called Single Fieldof-view Sounder Atmospheric Product (SiFSAP) algorithm. It provides L2 products with 9-times higher area spatial resolution as compared to current cloud-clearing sounder algorithms. The SiFSAP L2 and L3 products are available at NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. The second inversion algorithm is called Climate Fingerprinting Atmospheric Product (ClimFiSP) algorithm. It is designed to produce high quality climate products (trends, anomalies, daily, and monthly profiles of temperature, water vapor, traces, clouds, and surface properties) from multiple satellite sensors such AIRS on Aqua and CrIS on multiple satellites. This product will be available at NASA GES DISC later this year. The PCRTMbased high fidelity simulators for CLARREO and CPF have been used for sensor performance trade studies, algorithm development, and inter-satellite calibrations. We have also used PCRTM generated TOA radiance spectra to train an AI-based algorithm and successfully retrieved cloud properties from EMIT solar hyperspectral imagers.
PCRTM↗
Assimilation of Blended Satellite Soil Moisture Data Products to Further Improve Noah-MP Model Skills
Microwave satellite remote sensing has enabled observations of soil moisture (SM) at the global scale, and multiple SM data products have been developed in the past decades. However, single-sensor-based measurements are insufficient for continuous spatiotemporal coverage. In the context of its climate program, the Climate Change Initiative, the European Space Agency (ESA) has developed robust, long term, global scale, multi instrument satellite derived time series of climate data record for key component of the climate system, including soil moisture (CCI), while the Soil Moisture Operational Product System (SMOPS) was specifically developed by National Oceanic and Atmospheric Administration (NOAA) to offer the real time blended SM datasets through merging all available individual products. Before combining, all individual SM data ingested into both SMOPS and CCI blended products are scaled to Global Land Data Assimilation System (GLDAS) 0-10 cm SM climatology. Benefiting from land surface model evolution and the availability of high-quality forcing data, GLDAS has become more comprehensive to track SM changes and dynamic trends. The development of GLDAS and the scaling procedure in CCI and SMOPS leave an open scientific and operational question: do the blended satellite SM data products have added value comparing to the GLDAS product? This study clearly reveals that both CCI and SMOPS can provide the reliable SM observations with independent information, although their climatology matches well with GLDAS. Relative to assimilation of GLDAS 0-10 cm SM data, Noah-MP model can be further improved by assimilating the blended satellite SM observations with respect to the quality-controlled in situ measurements. The strong consistency of results presented in this paper proves that the blended satellite SM data products are more useful than the GLDAS product in terms of improving Noah-MP model performance.
Jifu Yin↗
Measurement of the tt¯ production cross-section as a function of jet multiplicity and jet transverse momentum in 7 TeV proton-proton collisions with the ATLAS detector
The t t ¯<!-- ¯ --> production cross-section dependence on jet multiplicity and jet transverse momentum is reported for proton-proton collisions at a centre-of-mass energy of 7 TeV in the single-lepton channel. This data was collected with the ATLAS detector at the CERN Large Hadron Collider and comprise the full 2011 data sample corresponding to an integrated luminosity of 4.6 fb –1 . Differential cross-sections are presented as a function of the jet multiplicity for up to eight jets using jet transverse momentum thresholds of 25, 40, 60, and 80 GeV, and as a function of jet transverse momentum up to the fifth jet. The results are shown after background subtraction and corrections for all known detector effects, within a kinematic range closely matched to the experimental acceptance. Several QCD-based Monte Carlo models are compared with the results. Sensitivity to the parton shower modelling is found at the higher jet multiplicities, at high transverse momentum of the leading jet and in the transverse momentum spectrum of the fifth leading jet. As a result, the MC@NLO+HERWIG MC is found to predict too few events at higher jet multiplicities.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗