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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Search for electroweak-scale dijet resonances using trigger-level analysis with the ATLAS detector in 132 fb −1 of 𝑝⁢𝑝 collisions at $\sqrt{𝑠}$ = 13 TeV

This article reports on a search for dijet resonances using 132 fb −1 of 𝑝⁢𝑝 collision data recorded at $\sqrt{𝑠}$ = 13 TeV by the ATLAS detector at the Large Hadron Collider. The search is performed solely on jets reconstructed within the ATLAS trigger to overcome bandwidth limitations imposed on conventional single-jet triggers, which would otherwise reject data from decays of sub-TeV dijet resonances. Collision events with two jets satisfying transverse momentum thresholds of 𝑝 T ≥ 85 GeV and jet rapidity separation of |𝑦*| <0.6 are analysed for dijet resonances with invariant masses from 375 to 1800 GeV. A data-driven background estimate is used to model the dijet mass distribution from multijet processes. No significant excess above the expected background is observed. Upper limits are set at 95% confidence level on coupling values for a benchmark leptophobic axial-vector 𝑍′ model and on the production cross section for a new resonance contributing a Gaussian-distributed line-shape to the dijet mass distribution.

hadron colliders↗
DOE OSTI2018

Zeptocalorimetry

Here we present the development of a Zeptocalorimeter. The motivation for designing and implementing such a device is driven, ultimately, by its anticipated exceptional sensitivity (10-21 J/K, at 2K). Such a device would be highly valuable in detecting minute quantities of mass for threat detection, studying fundamental phonon physics, and detecting energetic dissipation events at the attojoule level. To date, the most sensitive calorimeter demonstrated in the literature at 2K has been developed by the Roukes group at Caltech, where they achieved an addendum heat capacity of 10 -15 J/K with a 1/1000 sensitivity to external stimuli. To obtain such a low value of heat capacity requires a very small thermal mass, and thus, one of the greatest challenges in this project is the fabrication of this device, which requires numerous precision nanofabrication techniques. Furthermore, the heat capacity measurement of this device, as performed from room temperature to cryogenic temperatures, is equally challenging, as the transient signals used to determine the platform's thermal time constant require careful attention to the mitigation of feedthrough capacitance and delicate amplifier offsets. In this report we describe in detail the fabrication process flow for developing the calorimeter, including the layout and device design for obtaining a single lumped RC thermal resistance and capacitance, so that the device can be used for quantitative measurements of nanoscale materials with a suitable thermal link. The measurement method and experimental setup are also given, where we explain the heater and thermometer calibration methods, the thermal resistance measurements, the transient measurements, and lastly the cryogenic setup with intermediate frequency cabling and the thermal sinking of those lines.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

THREE-DIMENSIONAL SIMULATIONS OF TEARING AND INTERMITTENCY IN CORONAL JETS

Observations of coronal jets increasingly suggest that local fragmentation and intermittency play an important role in the dynamics of these events. In this work, we investigate this fragmentation in high-resolution simulations of jets in the closed-field corona. We study two realizations of the embedded-bipole model, whereby impulsive helical outflows are driven by reconnection between twisted and untwisted field across the domed fan plane of a magnetic null. We find that the reconnection region fragments following the onset of a tearing-like instability, producing multiple magnetic null points and flux-rope structures within the current layer. The flux ropes formed within the weak-field region in the center of the current layer are associated with “blobs” of density enhancement that become filamentary threads as the flux ropes are ejected from the layer, whereupon new flux ropes form behind them. This repeated formation and ejection of flux ropes provides a natural explanation for the intermittent outflows, bright blobs of emission, and filamentary structure observed in some jets. Additional observational signatures of this process are discussed. Essentially all jet models invoke reconnection between regions of locally closed and locally open field as the jet-generation mechanism. Therefore, we suggest that this repeated tearing process should occur at the separatrix surface between the two flux systems in all jets. A schematic picture of tearing-mediated jet reconnection in three dimensions is outlined.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Quantifying aerosol size distributions and their temporal variability in the Southern Great Plains, USA

A quality-controlled, 5-year dataset of aerosol number size distributions (particles with diameters (Dp) from 7 nm through 14 µm) was developed using observations from a scanning mobility particle sizer, aerodynamic particle sizer, and a condensation particle counter at the Department of Energy's Southern Great Plains (SGP) site. This data set was used for two purposes. First, typical characteristics of the aerosol size distribution (number, surface area, and volume) were calculated for the SGP site, both for the entire dataset and on a seasonal basis, and size distribution lognormal fit parameters are provided. While the median size distributions generally had similar shapes (four lognormal modes) in all the seasons, there were some significant differences between seasons. These differences were most significant in the smallest particles(Dp<30 nm) and largest particles (Dp>800 nm).Second, power spectral analysis was conducted on this long-term dataset to determine key temporal cycles of total aerosol concentrations, as well as aerosol concentrations in specified size ranges. The strongest cyclic signal was associated with a diurnal cycle in total aerosol number concentrations that was driven by the number concentrations of the smallest particles(Dp<30 nm). This diurnal cycle in the smallest particles occurred in all seasons in ~50% of the observations,suggesting a persistent influence of new particle formation events on the number concentrations observed at the SGP site. This finding is in contrast with earlier studies that suggest new particle formation is observed primarily in the springtime at this site. The timing of peak concentrations associated with this diurnal cycle was shifted by several hours depending on the season,which was consistent with seasonal differences in insolation and boundary layer processes. Significant diurnal cycles in number concentrations were also found for particles with Dp between 140 and 800 nm, with peak concentrations occurring in the overnight hours, which were primarily associated with both nitrate and organic aerosol cycles. Weaker cyclic signals were observed for longer timescales (days to weeks) and are hypothesized to be related to the timescales of synoptic weather variability. The strongest periodic signals (3.5–5 and 7 d cycles) for these longer timescales varied depending on the season, with no cyclic signals and the lowest variability in the summer.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Magnetic Roots and the Driving of Extended Coronal Heating

We report results from a continuation of a previous study, in which we found large bright coronal loops within active regions and extending from active regions that have one end rooted near an island of included magnetic polarity that is a site of enhanced coronal heating and microflares. This suggested that magnetic activity such as microflaring results in enhanced heating in both the compact core field around the island and in the large loops extending from it. We might expect that the intensity variations due to enhanced heating in the compact and extended structures would be correlated. However, although some ex- tended loops do respond to the largest events taking place in the core fields near their feet, they do not show a clear response to most smaller individual events nor to the overall envelope of coronal heating activity in the core fields at their feet as determined from longer-term observations. Thus, while it is clear that the extended loops' heating is being driven from their ends at the magnetic islands, much of this heating is apparently by some form of footpoint activity that is not strongly coupled to the heating in the footpoint core fields. One possibility is that the remote heating in the extended loops is driven by reconnection at the magnetic null over the island, and that this reconnection is driven mainly by core-field activity that produces little coronal heating within the core field itself, perhaps in the manner of the numerical simulations by Karpen, Antiochos, and DeVore.

Porter, Jason G.↗
NASA NTRS2004

Solar Magnetic Explosions, Spicules, and the Heliosphere

We present an example of each of the following observed characteristics of the magnetic origins of quiet-region coronal heating, spicules, macrospicules, and coronal mass ejections (CMEs). (1) In quiet regions, the luminosity of the corona is roughly proportional to the edge length of the underlying photospheric magnetic network. (2) Spicules and EUV explosive events are concentrated at the edges of the magnetic network. (3) Many macrospicules have the magnetic structure of a surge rooted around an inclusion of opposite-polarity magnetic flux. (4) CMEs and eruptive flares are driven by explosions of sheared magnetic fields rooted along polarity dividing lines (neutral lines) in the photospheric magnetic flux. These characteristics together suggest that the mainstay of the heliosphere, the corona/solar wind rooted in quiet regions and coronal holes, may be driven by myriads of tiny magnetic explosions at the network edges, explosions like those that drive CMEs but of vastly smaller scale. If so, the steady solar wind and the CMEs that disrupt it both have the same root cause: explosions of initially-closed, strongly-sheared, bipolar magnetic fields. The photospheric vector magnetograms, chromospheric filtergrams, EUV spectra, and coronal images from Solar-B are expected to have sufficient sensitivity, spatial resolution, and cadence to test this scenario for coronal heating in quiet regions and coronal holes. This work was supported by NASA/OSS through its Solar and Heliospheric Physics SR and T Program and Sun-Earth Connection GI Program.

Moore, Ronald L.↗
NASA NTRS2018

Sun-to-Earth Propagation of the 2015 June 21 Coronal Mass Ejection Revealed by Optical, EUV, and Radio Observations

We investigate the propagation of the 2015 June 21 CME-driven shock as revealed by the type II bursts at metricand longer wavelengths and coronagraph observations. The CME was associated with the second largest geomagneticstorm of solar cycle 24 and a large solar energetic particle (SEP) event. The eruption consisted of twoM-class flares, with the first one being confined, with no metric or interplanetary radio bursts. However, therewas intense microwave burst, indicating accelerated particles injected toward the Sun. The second flare was eruptive that resulted in a halo CME. The CME was deflected primarily by an equatorial coronal hole that resulted in the modification of the intensity profile of the associated SEP event and the duration of the CME at Earth. The interplanetary type II burst was particularly intense and was visible from the corona all the way to the vicinity of the Wind spacecraft with fundamental-harmonic structure. We computed the shock speed using the type II drift rates at various heliocentric distances and obtained information on the evolution of the shock that matched coronagraph observations near the Sun and in-situ observations near Earth. The depth of the geomagnetic storm is consistent with the 1-AU speed of the CME and the magnitude of the southward component.

Gopalswamy, N.↗
DOE OSTI2016

Searching for Sterile Neutrinos with MINOS

This document presents the latest results for a 3+1 sterile neutrino search using the $10.56 \times 10^{20}$ protons-on-target data set taken from 2005 - 2012. By searching for oscillations driven by a large mass splitting, MINOS is sensitive to the existence of sterile neutrinos through any energy dependent deviations using a charged current sample, as well as looking at any relative deficit between neutral current events between the far and near detectors. This document will discuss the novel analysis that enabled a search for sterile neutrinos setting a limit in the previously unexplored regions in the parameter space $\{\Delta m^{2}_{41}, \sin^2\theta_{24}\}$. The results presented can be compared to the parameter space suggested by LSND and MiniBooNE and complements other previous experimental searches for sterile neutrinos in the electron neutrino appearance channel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Origin of Stabilization of Ligand-Centered Mixed Valence Ruthenium Azopyridine Complexes: DFT Insights for Neuromorphic Applications

Redox-driven conductance changes are critical processes in molecular- and coordination-complex-based memristive thin films and devices that are envisioned for neuromorphic technologies, but fundamental mechanisms of conductance switching are not fully understood. Here, we explore charge disproportionation (CD) processes in [Ru II L 2 ](PF 6 ) 2 molecular systems that intrinsically involve interfragment charge transfer (IFCT). Using a combination of ab initio molecular dynamics simulation (AIMD), time-dependent density functional theory (TD-DFT), and density functional theory (DFT) calculations, we investigate the electron transfer mechanisms and the roles of temperature and cell volumetric expansion in facilitating the counterion movements and electronic transitions required for low-cost IFCT and charge redistribution. A detailed analysis of the density of states and TD-DFT calculations highlights that unpaired electrons play a crucial role in low-energy transitions, with the azo (N=N) groups of the ligand serving as the primary sites for electronic transport between molecular fragments, further stabilizing the asymmetric state. Localization of added electrons on azo ligands occurs with negligible change at the Ru centers, supported by atomic volume expansions up to +4.74 bohr 3 , and goes along with a progressive reduction of the HOMO−LUMO gap across redox states, suggesting enhanced conductivity. The TD-DFT analysis reveals a dominant IFCT excitation at 2082.76 nm in the doubly reduced (22) state, while a stabilization energy of 1.20 eV of the asymmetric (13) state relative to the symmetric (22) state is predicted by constrained DFT. Periodic DFT and AIMD simulations emulating a molecular film show that the stabilization of the asymmetric state, relative to a symmetric one, translates in net charge separation values (order of ∼0.33 e) that are strongly linked to increased counterion mobility (average counterion displacements exceeding 0.7 Å per atom during CD events) and the involvement of azo groups in electron redistribution. These findings, which align with previously reported experimental and computational data, provide key insights into the IFCT mechanisms and electronic transport facilitated by azo groups, with important implications for redox-driven memristive and neuromorphic technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Impacts of ENSO events on cloud radiative effects in preindustrial conditions: Changes in cloud fraction and their dependence on interactive aerosol emissions and concentrations

The impacts of the El Niño–Southern Oscillation (ENSO) events on shortwave and longwave cloud radiative effects (CRE SW and CRE LW ) and the underlying changes in cloud fraction as well as aerosol emissions, wet scavenging and transport are quantified using three 150-year simulations in preindustrial conditions by the CESM model. Compared to recent observations from Clouds and the Earth’s Radiant Energy System (CERES), the model simulation successfully reproduced larger variations of CRE SW over the tropical western and central Pacific, Indonesian regions, and the eastern Pacific Ocean, as well as large variations of CRE LW located mainly within the tropics. The ENSO cycle is found to dominate interannual variations of cloud radiative effects, especially over the tropics. Relative to those during La Niña events, simulated cooling (warming) effects from CRE SW (CRE LW ) during El Niño events are stronger over the tropical western and central Pacific Ocean, with the largest difference exceeding 40 Wm –2 (30 Wm –2 ), with weaker effects of 10–30 Wm –2 over Indonesian regions and the subtropical Pacific Ocean. Here, sensitivity tests show that variations of cloud radiative effects are mainly driven by ENSO-related changes in cloud fraction. The variations in medium and high cloud fractions each account for about 20–50% of the interannual variations of CRE SW over the tropics and almost all of the variations of CRE LW between 60°S and 60°N. The variation of low cloud fraction contributes most interannual variations of CRESW over the mid-latitude oceans. Variations in natural aerosol concentrations considering emissions, wet scavenging and transport explained 10–30% of the interannual variations of both CRE SW and CRE LW over the tropical Pacific, Indonesian regions and the tropical Indian Ocean. Changes in wet scavenging of natural aerosol modulate the variations of cloud radiative effects. Because of increased (decreased) precipitation over the tropical western Pacific Ocean in El Niño (La Niña) events, increased (decreased) wet scavenging of natural aerosols dampens more than 4–6% of variations of cloud radiative effects averaged over the tropics. In contrast, increased surface winds cause feedbacks that increase sea spray emissions that enhance the variations by 3–4% averaged over the tropics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Advancing Open Science in Atmospheric Research: Integrating Data Usability and Machine Learning

In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences." "In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences.

Jennifer Wei↗
DOE OSTI2019

Multivariate Pointwise Information-Driven Data Sampling and Visualization

With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Hurricanes and turbulent floods threaten arsenic-contaminated coastal soils and vulnerable communities

Coastal environments, particularly those adjacent to Superfund sites, are at increased risk of contaminant release during natural disasters, posing serious threats to nearby communities. To investigate this issue, we employed an advanced laboratory flood simulator to impose arsenic-contaminated sediments to turbulent flooding events. We further monitored changes in arsenic collocation and solid-phase speciation using advanced synchrotron radiation-based techniques to understand the impacts of flooding on arsenic mobility. Our results demonstrate that turbulent conditions significantly enhance the resuspension of arsenic-rich sediments, resulting in increased arsenic release into the water. This mobilization is driven by the erosion of the reduced sediments and the redox-mediated transformation and dissolution of Fe and Mn (oxyhydr) oxides, which promote the release of As(III). We found that arsenic speciation on resuspended particles is closely tied to shear stress, with As(V) prevailing at low stress and the more toxic As(III) dominating at higher stress levels. In the post-erosion phase, solid-phase As(III) decreased while dissolved As(III) increased, indicating ongoing desorption. The persistence of multiple arsenic species on resuspended particles marks them as potential long-range transport vectors. Thus, the environmental impact of flooding and sediment resuspension extends beyond the event itself, raising longer-term concerns for arsenic mobility. Our comprehensive geospatial analysis revealed substantial overlap between arsenic-contaminated soils and regions at high risk of flooding and hurricanes across the conterminous United States. This overlap disproportionately impacts economically disadvantaged and marginalized communities. Approximately 40 million Americans reside within 10 kilometers of these high-risk contaminated zones, with nearly 28 million exposed to hurricane threats and around 18 million vulnerable to flooding risks. Alarmingly, over 40% of those affected by hurricanes and 33% of those impacted by flooding belong to underrepresented minority and low-income populations. These findings highlight the urgent need for targeted mitigation strategies to protect public health and address environmental justice concerns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Role of underlying surface, rainstorm and antecedent wetness condition on flood responses in small and medium sized watersheds in the Yangtze River Delta region, China

Floods are becoming more frequent and are hard to control due to the shortage of water conservancy projects in small and medium sized basins, especially in developing regions. Understanding the hydrologic responses and estimated flood characteristics to storm events can help to predict flood disasters and form better effective mitigation and adaptation strategies. Here, using observations of several representative watersheds and Artificial Neural Networks (ANN) and Principal Component Regression (PCR) models, we conducted data-driven analyses to examine the flood responding characteristics. We quantified the relative contributions of the influencing factors to the variation of each flood characteristic. Statistical analysis of the observations shows that the drainage area plays a key role in determining the distribution of lag time and peak discharge. Rainstorm variability has direct influence on floods, and typhoon-induced rainstorms with high total rainfall and rainfall intensity generate higher lag time, flood peak, unit discharge and runoff depth, but lower runoff coefficient. The ANN and PCR models accurately predicted the variations of flood features using the driving factors including physical geographical characteristics, rainstorm features, and antecedent condition. Physical geographic characteristics are key influential factors of lag time, flood peak and runoff coefficient, while the rainstorm features control the magnitude of unit discharge and runoff depth. These results indicate that floods are mainly affected by rainstorm features and physical geographic characteristics in the Yangtze River delta, and it might become more damaging with the increasing rainfall extremes and sprawling impervious surfaces in a changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Marine phytoplankton downregulate core photosynthesis and carbon storage genes upon rapid mixed layer shallowing

Marine phytoplankton are a diverse group of photoautotrophic organisms and key mediators in the global carbon cycle. Phytoplankton physiology and biomass accumulation are closely tied to mixed layer depth, but the intracellular metabolic pathways activated in response to changes in mixed layer depth remain less explored. Here, metatranscriptomics was used to characterize the phytoplankton community response to a mixed layer shallowing (from 233 to 5 m) over the course of two days during the late spring in the Northwest Atlantic. Most phytoplankton genera downregulated core photosynthesis, carbon storage, and carbon fixation genes as the system transitioned from a deep to a shallow mixed layer and shifted towards catabolism of stored carbon supportive of rapid cell growth. In contrast, phytoplankton genera exhibited divergent transcriptional patterns for photosystem light harvesting complex genes during this transition. Active virus infection, taken as the ratio of virus to host transcripts, increased in the Bacillariophyta (diatom) phylum and decreased in the Chlorophyta (green algae) phylum upon mixed layer shallowing. A conceptual model is proposed to provide ecophysiological context for our findings, in which integrated light limitation and lower division rates during transient deep mixing are hypothesized to disrupt resource-driven, oscillating transcript levels related to photosynthesis, carbon fixation, and carbon storage. Our findings highlight shared and unique transcriptional response strategies within phytoplankton communities acclimating to the dynamic light environment associated with transient deep mixing and shallowing events during the annual North Atlantic bloom.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Statistically-informed deep learning for gravitational wave parameter estimation

We introduce deep learning models to estimate the masses of the binary components of black hole mergers, $(m_1,m_2)$, and three astrophysical properties of the post-merger compact remnant, namely, the final spin, $a_\mathrm f$, and the frequency and damping time of the ringdown oscillations of the fundamental $\ell = m = 2$ bar mode, $(\omega_\mathrm R, \omega_\mathrm I)$. Our neural networks combine a modified WaveNet architecture with contrastive learning and normalizing flow. We validate these models against a Gaussian conjugate prior family whose posterior distribution is described by a closed analytical expression. Upon confirming that our models produce statistically consistent results, we used them to estimate the astrophysical parameters $(m_1,m_2, a_\mathrm f, \omega_\mathrm R, \omega_\mathrm I)$ of five binary black holes: GW150914, GW170104, GW170814, GW190521 and GW190630. We use PyCBC Inference to directly compare traditional Bayesian methodologies for parameter estimation with our deep learning based posterior distributions. Our results show that our neural network models predict posterior distributions that encode physical correlations, and that our data-driven median results and 90% confidence intervals are similar to those produced with gravitational wave Bayesian analyses. This methodology requires a single V100 NVIDIA GPU to produce median values and posterior distributions within two milliseconds for each event. Furthermore, this neural network, and a tutorial for its use, are available at the Data and Learning Hub for Science.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A cross-biome synthesis of soil respiration and its determinants under simulated precipitation changes

Soil respiration (R s ) is the second-largest terrestrial carbon (C) flux. Although R s has been extensively studied across a broad range of biomes, there is surprisingly little consensus on how the spatiotemporal patterns of Rs will be altered in a warming climate with changing precipitation regimes. Here, we present a global synthesis Rs data from studies that have manipulated precipitation in the field by collating studies from 113 increased precipitation treatments, 91 decreased precipitation treatments, and 14 prolonged drought treatments. Our meta-analysis indicated that when the increased precipitation treatments were normalized to 28% above the ambient level, the soil moisture, R s ,and the temperature sensitivity (Q 10 ) values increased by an average of 17%, 16%, and 6%, respectively, and the soil temperature decreased by -1.3%. The greatest increases in R s and Q 10 were observed in arid areas, and the stimulation rates decreased with increases in climate humidity. When the decreased precipitation treatments were normalized to 28% below the ambient level, the soil moisture and Rs values decreased by an average of -14% and -17%, respectively, and the soil temperature and Q 10 values were not altered. The reductions in soil moisture tended to be greater in more humid areas. Prolonged drought without alterations in the amount of precipitation reduced the soil moisture and Rs by -12% and -6%, respectively, but did not alter Q 10 . Overall, our synthesis suggests that soil moisture and Rs tend to be more sensitive to increased precipitation in more arid areas and more responsive to decreased precipitation in more humid areas. The responses of R s and Q 10 were predominantly driven by precipitation-induced changes in the soil moisture, whereas changes in the soil temperature had limited impacts. Finally, our synthesis of prolonged drought experiments also emphasizes the importance of the timing and frequency of precipitation events on ecosystem C cycles. Given these findings, we urge future studies to focus on manipulating the frequency, intensity, and seasonality of precipitation with an aim to improving our ability to predict and model feedback between R s and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-D-9A-01: Listmode-Driven Optimal Gating (OG) Respiratory Motion Management: Potential Impact On Quantitative PET Imaging

Purpose: To evaluate the potential impact of listmode-driven amplitude based optimal gating (OG) respiratory motion management technique on quantitative PET imaging. Methods: During the PET acquisitions, an optical camera tracked and recorded the motion of a tool placed on top of patients' torso. PET event data were utilized to detect and derive a motion signal that is directly coupled with a specific internal organ. A radioactivity-trace was generated from listmode data by accumulating all prompt counts in temporal bins matching the sampling rate of the external tracking device. Decay correction for 18F was performed. The image reconstructions using OG respiratory motion management technique that uses 35% of total radioactivity counts within limited motion amplitudes were performed with external motion and radioactivity traces separately with ordered subset expectation maximization (OSEM) with 2 iterations and 21 subsets. Standard uptake values (SUVs) in a tumor region were calculated to measure the effect of using radioactivity trace for motion compensation. Motion-blurred 3D static PET image was also reconstructed with all counts and the SUVs derived from OG images were compared with SUVs from 3D images. Results: A 5.7 % increase of the maximum SUV in the lesion was found for optimal gating image reconstruction with radioactivity trace when compared to a static 3D image. The mean and maximum SUVs on the image that was reconstructed with radioactivity trace were found comparable (0.4 % and 4.5 % increase, respectively) to the values derived from the image that was reconstructed with external trace. Conclusion: The image reconstructed using radioactivity trace showed that the blurring due to the motion was reduced with impact on derived SUVs. The resolution and contrast of the images reconstructed with radioactivity trace were comparable to the resolution and contrast of the images reconstructed with external respiratory traces. Research supported by Siemens.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗