Precision measurement of the electron energy-loss function in tritium and deuterium gas for the KATRIN experiment

The KATRIN experiment is designed for a direct and model-independent determination of the effective electron anti-neutrino mass via a high-precision measurement of the tritium $$\upbeta $$ β -decay endpoint region with a sensitivity on $$m_\nu $$ m ν of 0.2 $$\hbox {eV}/\hbox {c}^2$$ eV / c 2 (90% CL). For this purpose, the $$\upbeta $$ β -electrons from a high-luminosity windowless gaseous tritium source traversing an electrostatic retarding spectrometer are counted to obtain an integral spectrum around the endpoint energy of 18.6 keV. A dominant systematic effect of the response of the experimental setup is the energy loss of $$\upbeta $$ β -electrons from elastic and inelastic scattering off tritium molecules within the source. We determined the energy-loss function in-situ with a pulsed angular-selective and monoenergetic photoelectron source at various tritium-source densities. The data was recorded in integral and differential modes; the latter was achieved by using a novel time-of-flight technique. We developed a semi-empirical parametrization for the energy-loss function for the scattering of 18.6-keV electrons from hydrogen isotopologs. This model was fit to measurement data with a 95% $$\hbox {T}_2$$ T 2 gas mixture at 30 K, as used in the first KATRIN neutrino-mass analyses, as well as a $$\hbox {D}_2$$ D 2 gas mixture of 96% purity used in KATRIN commissioning runs. The achieved precision on the energy-loss function has abated the corresponding uncertainty of $$\sigma (m_\nu ^2)< {{10}^{-2}}{\hbox {eV}^{2}}$$ σ ( m ν 2 ) < 10 - 2 eV 2 [1] in the KATRIN neutrino-mass measurement to a subdominant level.

A Novel Deeplabv3+ Network for SAR Imagery Semantic Segmentation Based on the Potential Energy Loss Function of Gibbs Distribution

Synthetic aperture radar (SAR) provides rich information about the Earth’s surface under all-weather and day-and-night conditions, and is applied in many relevant fields. SAR imagery semantic segmentation, which can be a final product for end users and a fundamental procedure to support other applications, is one of the most difficult challenges. This paper proposes an encoding-decoding network based on Deeplabv3+ to semantically segment SAR imagery. A new potential energy loss function based on the Gibbs distribution is proposed here to establish the semantic dependence among different categories through the relationship among different cliques in the neighborhood system. This paper introduces an improved channel and spatial attention module to the Mobilenetv2 backbone to improve the recognition accuracy of small object categories in SAR imagery. The experimental results show that the proposed method achieves the highest mean intersection over union (mIoU) and global accuracy (GA) with the least running time, which verifies the effectiveness of our method.

Inelastic mean free path of swift electrons and stopping power in Ta2O5

Energy Loss Function (ELF) of 2 5 Ta O derived from optical limitand extended to the total part of momentum and their energyexcitation region ELF plays an important function in calculatingenergy loss of electron in materials. The parameter Inelastic MeanFree Path (IMFP) is most important in quantitative surface sensitiveelectron spectroscopies, defined as the average distance that anelectron with a given energy travels between successive inelasticcollisions. The stopping cross section and single differential crosssectionSDCS are also calculated and gives good agreement withprevious work.

Energy-loss Function for Lead

We study the energy-loss function for lead in the framework of the time-dependent density functional theory, using the full-potential linearized augmented plane-wave plus local orbitals method. The ab initio calculations are performed in the adiabatic local density approximation. The comparison between the obtained energy-loss function for zero momentum transfer with those from reflection electron energy loss spectroscopy measurements and from first-principles calculations shows good agreement.