Sensitivity of Neutrino Mass Experiments to the Cosmic Neutrino Background

The KATRIN neutrino experiment is a next-generation tritium beta decay experiment aimed at measuring the mass of the electron neutrino to better than 200 meV at 90% C.L. Due to its intense tritium source, KATRIN can also serve as a possible target for the process of neutrino capture, {\nu}e +3H \to 3He+ + e-. The latter process, possessing no energy threshold, is sensitive to the Cosmic Neutrino Background (C{\nu}B). In this paper, we explore the potential sensitivity of the KATRIN experiment to the relic neutrino density. The KATRIN experiment is sensitive to a C{\nu}B over-density ratio of 2.0x 10^9 over standard concordance model predictions (at 90% C.L.), addressing the validity of certain speculative cosmological models

Solving for Micro- and Macro- Scale Electrostatic Configurations Using the Robin Hood Algorithm

We present a novel technique by which highly-segmented electrostatic configurations can be solved. The Robin Hood method is a matrix-inversion algorithm optimized for solving high density boundary element method (BEM) problems. We illustrate the capabilities of this solver by studying two distinct geometry scales: (a) the electrostatic potential of a large volume beta-detector and (b) the field enhancement present at surface of electrode nano-structures. Geometries with elements numbering in the O(10^5) are easily modeled and solved without loss of accuracy. The technique has recently been expanded so as to include dielectrics and magnetic materials.Comment: 40 pages, 20 figure

Violation of the Leggett-Garg Inequality in Neutrino Oscillations

The Leggett-Garg inequality, an analogue of Bell's inequality involving correlations of measurements on a system at different times, stands as one of the hallmark tests of quantum mechanics against classical predictions. The phenomenon of neutrino oscillations should adhere to quantum-mechanical predictions and provide an observable violation of the Leggett-Garg inequality. We demonstrate how oscillation phenomena can be used to test for violations of the classical bound by performing measurements on an ensemble of neutrinos at distinct energies, as opposed to a single neutrino at distinct times. A study of the MINOS experiment's data shows a greater than $6{\sigma}$ violation over a distance of 735 km, representing the longest distance over which either the Leggett-Garg inequality or Bell's inequality has been tested.Comment: Updated to match published version. 6 pages, 2 figure

New approach to 3D electrostatic calculations for micro-pattern detectors

We demonstrate practically approximation-free electrostatic calculations of micromesh detectors that can be extended to any other type of micropattern detectors. Using newly developed Boundary Element Method called Robin Hood Method we can easily handle objects with huge number of boundary elements (hundreds of thousands) without any compromise in numerical accuracy. In this paper we show how such calculations can be applied to Micromegas detectors by comparing electron transparencies and gains for four different types of meshes. We demonstrate inclusion of dielectric material by calculating the electric field around different types of dielectric spacers

Principal components technique analysis for vegetation and land use discrimination

Automatic pre-processing technique called Principal Components (PRINCO) in analyzing LANDSAT digitized data, for land use and vegetation cover, on the Brazilian cerrados was evaluated. The chosen pilot area, 223/67 of MSS/LANDSAT 3, was classified on a GE Image-100 System, through a maximum-likehood algorithm (MAXVER). The same procedure was applied to the PRINCO treated image. PRINCO consists of a linear transformation performed on the original bands, in order to eliminate the information redundancy of the LANDSAT channels. After PRINCO only two channels were used thus reducing computer effort. The original channels and the PRINCO channels grey levels for the five identified classes (grassland, "cerrado", burned areas, anthropic areas, and gallery forest) were obtained through the MAXVER algorithm. This algorithm also presented the average performance for both cases. In order to evaluate the results, the Jeffreys-Matusita distance (JM-distance) between classes was computed. The classification matrix, obtained through MAXVER, after a PRINCO pre-processing, showed approximately the same average performance in the classes separability

Atmospheric correction analysis on LANDSAT data over the Amazon region

The Amazon Region natural resources were studied in two ways and compared. A LANDSAT scene and its attributes were selected, and a maximum likelihood classification was made. The scene was atmospherically corrected, taking into account Amazonic peculiarities revealed by (ground truth) of the same area, and the subsequent classification. Comparison shows that the classification improves with the atmospherically corrected images