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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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Active Optical Control with Machine Learning: A Proof of Concept for the Vera C. Rubin Observatory
Abstract The Active Optics System of the Vera C. Rubin Observatory (Rubin) uses information provided by four wave front sensors to determine deviations between the reconstructed wave front and the ideal wave front. The observed deviations are used to adjust the control parameters of the optical system to maintain image quality across the 3.°5 field of view. The baseline approach from the project is to obtain amplitudes of the Zernike polynomials describing the distorted wave front from out-of-focus images collected by the wave front sensors. These Zernike amplitudes are related via an “influence matrix” to the control parameters necessary to correct the wave front. In this paper, we use deep-learning methods to extract the control parameters directly from the images captured by the wave front sensors. Our neural net model uses anti-aliasing pooling to boost performance, and a domain-specific loss function to aid learning and generalization. The accuracy of the control parameters derived from our model exceeds Rubin requirements even in the presence of full-moon background levels and mis-centering of reference stars. Although the training process is time consuming, model evaluation requires only a few milliseconds. This low latency should allow for the correction of the optical configuration during the readout and slew interval between successive exposures.
Detecting low-energy interactions and the effects of energy accumulation in materials
Elusive as dark matter particles are, they are not the only entities that can produce small energy releases deep inside the most sensitive detectors. Cosmogenic and residual radioactivity as well as other factors can produce and slowly accumulate long-living excitations and defect configurations in materials. Unsteady and avalanche-like releases of accumulated energy can limit the dynamic range of detectors and the sensitivity of experiments. This type of mechanism, while not widely discussed in the dark matter and neutrino detectors community, got a lot of attention in discussions about systems with energy flow in the context of nonequilibrium thermodynamic. Here this paper explores the avalanche hypothesis using published data on low-energy background in detectors and available condensed-matter physics information on excitations, defects, and energetic molecules which can be produced in detector materials and examine ways to use these models to understand the origin of low-energy background in dark matter and other detectors and for suppression of these backgrounds.
K-space algorithmic reconstruction (KAREN): a robust statistical methodology to separate Bragg and diffuse scattering
Diffuse scattering occurring in the Bragg diffraction pattern of a long-range-ordered structure represents local deviation from the governing regular lattice. However, interpreting the real-space structure from the diffraction pattern presents a significant challenge because of the dramatic difference in intensity between the Bragg and diffuse components of the total scattering function. In contrast to the sharp Bragg diffraction, the diffuse signal has generally been considered to be a weak expansive or continuous background signal. In this paper, using 1D and 2D models, it is demonstrated that diffuse scattering in fact consists of a complex array of high-frequency features that must not be averaged into a low-frequency background signal. To evaluate the actual diffuse scattering effectively, an algorithm has been developed that uses robust statistics and traditional signal processing techniques to identify Bragg peaks as signal outliers which can be removed from the overall scattering data and then replaced by statistically valid fill values. This method, described as a 'K-space algorithmic reconstruction' (KAREN), can identify Bragg reflections independent of prior knowledge of a system's unit cell. KAREN does not alter any data other than that in the immediate vicinity of the Bragg reflections, and reconstructs the diffuse component surrounding the Bragg peaks without introducing discontinuities which induce Fourier ripples or artifacts from underfilling `punched' voids. The KAREN algorithm for reconstructing diffuse scattering provides demonstrably better resolution than can be obtained from previously described punch-and-fill methods. The superior structural resolution obtained using the KAREN method is demonstrated by evaluating the complex ordered diffuse scattering observed from the neutron diffraction of a single plastic crystal of CBr 4 using pair distribution function analysis.
Biological indicators for monitoring water quality of MTF canals system
Biological models, diversity indexes, were developed to predict environmental effects of NASA's Mississippi test facility (MTF) chemical operations on canal systems in the area. To predict the effects on local streams, a physical model of unpolluted streams was established. The model is fed by artesian well water free of background levels of pollutants. The species diversity and biota composition of unpolluted MTF stream was determined; resulting information will be used to form baseline data for future comparisons. Biological modeling was accomplished by adding controlled quantities or kinds of chemical pollutants and evaluating the effects of these chemicals on the biological life of the stream.
Digital simulation for post-docking response
The digital program, 2BODY, which simulates the translational and rotational motion of two connected rigid bodies and provides both digital and plot output is described. Relative rotation of the bodies at the connection is allowed, thereby providing a model suitable for studying system stability and response during a soft-dock regime. A users manual for the program is given as well as all the details and background pertaining to the equations of motion and mathematical models, integration scheme, and input/output routines.
Signal dispersion within a hippocampal neural network
A model network is described, representing two neural populations coupled so that one population is inhibited by activity it excites in the other. Parameters and operations within the model represent EPSPs, IPSPs, neural thresholds, conduction delays, background activity and spatial and temporal dispersion of signals passing from one population to the other. Simulations of single-shock and pulse-train driving of the network are presented for various parameter values. Neuronal events from 100 to 300 msec following stimulation are given special consideration in model calculations.
Mechanisms of Diurnal Precipitation over the United States Great Plains: A Cloud-Resolving Model Simulation
The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.
Islands in the fluid: islands are common in cosmology
We discuss the possibility of entanglement islands in cosmological spacetimes with a general perfect fluid with an equation of state w. We find that flat universes with time-symmetric slices where the Hubble parameter vanishes always have islands on that slice. We then move away from such slices, considering still universes with a general perfect fluid. Under the local thermal equilibrium assumption, the comoving entropy density s c is constant. As a result, the conditions for an island become an inequality between the energy density (or Hubble parameter) and the temperature at some time of normalization. The consequences are that islands can exist for practically all fluids that are not radiation, i.e. w ≠ 1/3. We also discuss the ramifications of our results for universes with spatial curvature. Finally, we show that islands occur in the Simple Harmonic Universe model which has no classical singularity at the background level, in contrast to all previous examples where islands occurred only in space-times with singularities.
Dark Energy Survey Year 3: Blue Shear
Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this blue cosmic shear sample are stable to IA model choice, unlike passive galaxies in the full DES Y3 sample, the goodness-of-fit is improved and the $\Omega_{m}$ and $S_8$ better agree with the cosmic microwave background. Mitigating IA with sample selection, instead of flexible model choices, can reduce uncertainty in $S_8$ by a factor of 1.5.
Towards Neutron Transformation Searches
To probe the origins of the baryon asymmetry, baryon number violation, the last unconfirmed Sakharov condition, must be definitively observed experimentally. Similarly, the nature of dark matter is currently unknown, and calls out for new candidates to be investigated. Each of these issues can be considered through the study of neutron transformations.Some rare baryon number violating processes, such as neutron-antineutron transformations, are expected to probe baryogenesis. Here, I show progress on this discovery target through construction of more accurate Monte Carlo models, the design of future detectors, creation of more complete atmospheric neutrino background simulations, and use of automated analysis techniques within the the NNBAR/HIBEAM experimental program at the European Spallation Source (ESS) and the Deep Underground Neutrino Experiment (DUNE). First simulation-based sensitivities for these experiments will be discussed. Modeling of rare neutron-antineutron transformation and subsequent annihilation will be discussed at length for multiple nuclei useful to these and other collaborations. To go along with this work, more comprehensive lepton-scattering nuclear models must be integrated into neutrino event generators for proper atmospheric neutrino background simulations. I discuss the first furnishing of these backgrounds for DUNE, and I highlight a potential path forward for the community in this vein using precisionmore » electron scattering modeling as a facsimile.Aspects of other potentially related neutron – mirror-neutron oscillations pertinent to dark matter and the neutron lifetime anomaly will also be considered for the ESS HIBEAM experiment. Here, I will present the first experimental sensitivity calculations for a broad range of modular experimental setups which will serve as research and design stepping stones toward NNBAR while producing a multitude of physics results over short time scales.« less
Holographic open quantum systems: toy models and analytic properties of thermal correlators
We present a unified picture of open quantum systems, the theory of a system probing a noisy thermal environment, distilling lessons learnt from previous holographic analyses. Our treatment is applicable both when the system is coupled to short-lived (Markovian), and long-lived (non-Markovian) environmental degrees of freedom. The thermal environment is modeled using an asymptotically AdS black hole, and the systems of interest are simple probe field theories. The effective stochastic dynamics of the system is governed by real-time thermal correlators, which we compute using the gravitational Schwinger-Keldysh (grSK) geometry. We describe the structure of arbitrary tree-level contact and exchange Witten diagrams in the grSK geometry. In particular, we argue, that all such diagrams reduce to integrals supported on a single copy of the exterior of the black hole. The integrand is obtained as a multiple discontinuity of a function comprising ingoing boundary-bulk propagators, monodromy functions which appear as radial Boltzmann weights, and vertex factors. These results allow us to deduce the analytic structure of real-time thermal n-point functions in holographic CFTs. We illustrate the general statements by a two-dimensional toy model, dual to fields in the BTZ background, which we argue captures many of the essential features of generic open holographic QFTs.
Optical Design and Characterization of 40-GHz Detector and Module for the BICEP Array
Families of cosmic inflation models predict a primordial gravitational-wave background that imprints B-mode polarization pattern in the cosmic microwave background (CMB). High-sensitivity instruments with wide frequency coverage and well-controlled systematic errors are needed to constrain the faint B-mode amplitude. We have developed antenna-coupled transition edge sensor arrays for high-sensitivity polarized CMB observations over a wide range of millimeter-wave bands. BICEP array, the latest phase of the BICEP/Keck experiment series, is a multi-receiver experiment designed to search for inflationary B-mode polarization to a precision σ(r) between 0.002 and 0.004 after 3 full years of observations, depending on foreground complexity and the degree of lensing removal. We describe the electromagnetic design and measured performance of BICEP array’s low-frequency 40-GHz detector, their packaging in focal plane modules, and optical characterization including efficiency and beam matching between polarization pairs. We summarize the design and simulated optical performance, including an approach to improve the optical efficiency due to mismatch losses. Here, we report the measured beam maps for a new broadband corrugation design to minimize beam differential ellipticity between polarization pairs caused by interactions with the module housing frame, which helps minimize polarized beam mismatch that converts CMB temperature to polarization (T→P) anisotropy in CMB maps.
Jet-associated deuteron production in pp collisions at $\sqrt{s}$ =13 TeV
Deuteron production in high-energy collisions is sensitive to the space–time evolution of the collision system, and is typically described by a coalescence mechanism. For the first time, we present results on jet-associated deuteron production in pp collisions at $\sqrt{s}$ =13 TeV, providing an opportunity to test the established picture for deuteron production in events with a hard scattering. Using a trigger particle with high transverse-momentum (p T > GeV/c) as a proxy for the presence of a jet at midrapidity, we observe a measurable population of deuterons being produced around the jet proxy. The associated deuteron yield measured in a narrow angular range around the trigger particle differs by 2.4–4.8 standard deviations from the uncorrelated background. The data are described by PYTHIA model calculations featuring baryon coalescence.
Divergent urbanization-induced impacts on global surface urban heat island trends since 1980s
Urbanization experiences different speeds and forms under diverse development stages across the globe. However, urbanization-induced impacts on long-term surface urban heat island intensity (I s ) trends across global cities and the regulators of such impacts remain understudied. Here we estimate interannual trends in daytime I s (i.e., urban-rural differences in surface temperatures) across 511 major cities for 1985 –2020 using annual averages calculated by using reconstructed land surface temperature data derived from more than >250,000 Landsat thermal images. Our study reveals that the global mean I s growth rate is 0.156 °C/decade. We further examine I s change associated with per 1% impervious land growth (denoted as ß) in each city throughout the research period and during different periods. The global mean ß is 0.018 ± 0.025 °C/% (mean ± 1 standard deviation) for the whole period, with greater values in humid than in arid climates; and the ß may change during different periods, e.g., it has more than tripled when urban impervious land exceeds 30%, indicating the spatiotemporally divergent impacts of urbanization on Is trends across global cities. The spatial variations in ß across global cities are well correlated with rural vegetation abundance and precipitation but not with urban population. Among these three factors, rural vegetation abundance possesses the greatest standardized regression coefficient of partial least-squares model, signifying the critical role of biome background in regulating ß. Furthermore, the finding implies that future urbanization over densely vegetated regions should be more carefully and strategically planned due to the greater urbanization-induced surface warming effect.
Arctic warming by abundant fine sea salt aerosols from blowing snow
Abstract The Arctic warms nearly four times faster than the global average, and aerosols play an increasingly important role in Arctic climate change. In the Arctic, sea salt is a major aerosol component in terms of mass concentration during winter and spring. However, the mechanisms of sea salt aerosol production remain unclear. Sea salt aerosols are typically thought to be relatively large in size but low in number concentration, implying that their influence on cloud condensation nuclei population and cloud properties is generally minor. Here we present observational evidence of abundant sea salt aerosol production from blowing snow in the central Arctic. Blowing snow was observed more than 20% of the time from November to April. The sublimation of blowing snow generates high concentrations of fine-mode sea salt aerosol (diameter below 300 nm), enhancing cloud condensation nuclei concentrations up to tenfold above background levels. Using a global chemical transport model, we estimate that from November to April north of 70° N, sea salt aerosol produced from blowing snow accounts for about 27.6% of the total particle number, and the sea salt aerosol increases the longwave emissivity of clouds, leading to a calculated surface warming of +2.30 W m −2 under cloudy sky conditions.
Erosion and impurity transport for the edge localized mode suppression window in KSTAR
A 3D analysis of plasma wall interactions and global impurity transport for the edge localized mode suppression window in KSTAR during H-Mode discharges has shown that carbon erosion at the divertor plates is a strong function of the resonant magnetic perturbation (n = 1) coil current and relative phasing. The Generalized Perturbation Equilibrium Code was used to determine a realistic initial perturbed plasma equilibrium, and EMC3-EIRENE was used to calculate the resulting scrape-off layer plasma used in this study as a fixed background for the ERO2.0 plasma–material interaction model. The resulting transport leads to deposition of impurities along the targets positioned at the high-field side of the device. An attempt at calculating the resulting effective charge state has demonstrated a similar dependence on the perturbation coil current and has been able to determine a window for the experimentally observed values of Zeff by including contributions of all ionized carbon charge states and deuterium.
Constraining dark matter microphysics with the annihilation signal from subhalos
In the cold dark matter scenario, galactic dark matter halos are populated with a large number of smaller subhalos. Previous work has shown that dark matter annihilations in subhalos can generate a distinctive, non-Poisson signal in the gamma-ray photon counts probability distribution function (PDF). Here we show that the gamma-ray PDF also carries information about the velocity dependence of the dark matter annihilation cross section. After calculating the PDF assuming s-wave and Sommerfeld-enhanced annihilation, we perform a mock data analysis to illustrate how current and future observations can constrain the microphysics of the dark matter annihilation. We find that, with current Fermi data, and assuming a dark matter annihilation cross section roughly at the limit of current bounds from annihilation in dwarf spheroidal galaxies, one can potentially distinguish the non-Poissonian fluctuations expected from dark matter annihilation in subhalos from Poisson sources, as well as from dark matter models with an incorrect velocity-dependence. Here we explore how robust these results are to assumptions about the modeling of the galactic gamma-ray background, but further work is needed to determine the impact of realistic astrophysical source populations on our results. We also point out a four-parameter degeneracy between the velocity dependence of the dark matter annihilation, the minimum subhalo mass, the power law index of the subhalo mass function, and the normalization of the dark matter signal. This degeneracy can be broken with priors from N-body simulations or from observational constraints on the subhalo mass function.