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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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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Angular power spectrum of the diffuse gamma-ray emission as measured by the Fermi Large Area Telescope and constraints on its dark matter interpretation

The isotropic gamma-ray background arises from the contribution of unresolved sources, including members of confirmed source classes and proposed gamma-ray emitters such as the radiation induced by dark matter annihilation and decay. Clues about the properties of the contributing sources are imprinted in the anisotropy characteristics of the gamma-ray background. We use 81 months of Pass 7 Reprocessed data from the Fermi Large Area Telescope to perform a measurement of the anisotropy angular power spectrum of the gamma-ray background. Here, we analyze energies between 0.5 and 500 GeV, extending the range considered in the previous measurement based on 22 months of data. We also compute, for the first time, the cross-correlation angular power spectrum between different energy bins. The derived angular spectra are compatible with being Poissonian, i.e. constant in multipole. Furthermore, the energy dependence of the anisotropy suggests that the signal is due to two populations of sources, contributing, respectively, below and above ~ 2 GeV . Finally, using data from state-of-the-art numerical simulations to model the dark matter distribution, we constrain the contribution from dark matter annihilation and decay in Galactic and extra-Galactic structures to the measured anisotropy. These constraints are competitive with those that can be derived from the average intensity of the isotropic gamma-ray background.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Possible interpretation of the newly observed Ω ( 2012 ) state

Inspired by the newly observed $Ω (2012)$ state at Belle II, we investigate the two-body strong decays of $Ω$ baryons up to $N = 2$ shell within the chiral quark model. Our results indicate that (i) the newly observed $Ω (2012)$ state could be assigned to the spin-parity $J^P = 3 / 2^-$ state |$70,^{2}10, 1, 1, \frac{3^-}{2}$$\rangle$ and the experimental data can be reasonably described. However, the spin-parity $J^P = 1 / 2^-$ state |$70,^{2}10, 1, 1, \frac{1^-}{2}$$\rangle$ and spin-parity $J^P = 3 / 2^+$ state |$56, ^{4}10, 2, 0, \frac{3^+}{2}$$\rangle$ cannot be completely excluded. (ii) The $D$-wave states in the $N = 2$ shell are most likely to be narrow states with a width of dozens of MeV and have a good potential to be observed in the $\Xi$$K$ and/or $\Xi(1530)K$ channels in future experiments. The $Ω(2250)$ resonance listed in PDG may be a good candidate for the $J^P$ = $5/2^+$ $1D$ wave state |$56$,$^{4}10$, $2, 2$, $5/2^+$ $\rangle$ .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Point-particle drag, lift, and torque closure models using machine learning: Hierarchical approach and interpretability

Developing deterministic neighborhood-informed point-particle closure models using machine learning has garnered interest recently from the dispersed multiphase flow community. The robustness of neural models for this complex multibody problem is hindered by the availability of particle-resolved data. Here, the present work addresses this unavoidable limitation of data paucity by implementing two strategies: (1) by using a rotation and reflection equivariant neural network and (2) by pursuing a physics-based hierarchical machine learning approach. The resulting machine-learned models are observed to achieve a maximum accuracy of 85% and 96% in the prediction of neighbor-induced force and torque fluctuations, respectively, for a wide range of Reynolds number and volume fraction conditions considered. Furthermore, we pursue force and torque network architectures that provide universal prediction spanning a wide range of Reynolds number (0.25 ≤ Re ≤250) and particle volume fraction (0 ≤ φ ≤0.4). The hierarchical nature of the approach enables improved prediction of quantities such as streamwise torque, by going beyond binary interactions to include trinary interactions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗