β\beta-Decay Spectrum, Response Function and Statistical Model for Neutrino Mass Measurements with the KATRIN Experiment

The objective of the Karlsruhe Tritium Neutrino (KATRIN) experiment is to determine the effective electron neutrino mass $m(\nu_\text{e})$ with an unprecedented sensitivity of $0.2\,\text{eV}$ (90\% C.L.) by precision electron spectroscopy close to the endpoint of the $\beta$ decay of tritium. We present a consistent theoretical description of the $\beta$ electron energy spectrum in the endpoint region, an accurate model of the apparatus response function, and the statistical approaches suited to interpret and analyze tritium $\beta$ decay data observed with KATRIN with the envisaged precision. In addition to providing detailed analytical expressions for all formulae used in the presented model framework with the necessary detail of derivation, we discuss and quantify the impact of theoretical and experimental corrections on the measured $m(\nu_\text{e})$. Finally, we outline the statistical methods for parameter inference and the construction of confidence intervals that are appropriate for a neutrino mass measurement with KATRIN. In this context, we briefly discuss the choice of the $\beta$ energy analysis interval and the distribution of measuring time within that range.Comment: 27 pages, 22 figures, 2 table

A pulsed, mono-energetic and angular-selective UV photo-electron source for the commissioning of the KATRIN experiment

The KATRIN experiment aims to determine the neutrino mass scale with a sensitivity of 200 meV/c^2 (90% C.L.) by a precision measurement of the shape of the tritium $\beta$-spectrum in the endpoint region. The energy analysis of the decay electrons is achieved by a MAC-E filter spectrometer. To determine the transmission properties of the KATRIN main spectrometer, a mono-energetic and angular-selective electron source has been developed. In preparation for the second commissioning phase of the main spectrometer, a measurement phase was carried out at the KATRIN monitor spectrometer where the device was operated in a MAC-E filter setup for testing. The results of these measurements are compared with simulations using the particle-tracking software "Kassiopeia", which was developed in the KATRIN collaboration over recent years.Comment: 19 pages, 16 figures, submitted to European Physical Journal

Orbital electron capture by the nucleus

The theory of nuclear electron capture is reviewed in the light of current understanding of weak interactions. Experimental methods and results regarding capture probabilities, capture ratios, and EC/Beta(+) ratios are summarized. Radiative electron capture is discussed, including both theory and experiment. Atomic wave function overlap and electron exchange effects are covered, as are atomic transitions that accompany nuclear electron capture. Tables are provided to assist the reader in determining quantities of interest for specific cases

The role of carbonaceous deposits in the activity and stability of Ni-based catalysts applied in the dry reforming of methane

Highly stable Ni catalysts with varying Ni contents up to 50 mol% originating from hydrotalcite-like precursors were applied in the dry reforming of methane at 800 and 900 °C. The integral specific rate of methane conversion determined after 10 h on stream was 3.8 mmol s-1 gcat-1 at 900 °C. Due to the outstanding high activity, a catalyst mass of just 10 mg had to be used to avoid operating the reaction in thermodynamic equilibrium. The resulting WHSV was as high as 1.44 × 106 ml gcat-1 h-1. The observed axial temperature distribution with a pronounced cold spot was analyzed by computational fluid dynamics simulations to verify the strong influence of this highly endothermic reaction. Transmission electron microscopy and temperature-programmed oxidation experiments were used to probe the formation of different carbon species, which was found to depend on the catalyst composition and the reaction temperature. Among the formed carbon species, multi-walled carbon nanofibers were detrimental to the long-term stability at 800 °C, whereas their formation was suppressed at 900 °C. The formation of graphitic carbon at 900 °C originating from methane pyrolysis played a minor role. The methane conversion after 100 h of dry reforming at 900 °C compared to the initial one amounted to 98% for the 25 mol% Ni catalyst. The oxidative regeneration of the catalyst was achieved in the isothermal mode using only carbon dioxide in the feed

Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Implications of Recent Measurements of Hadronic Charmless B Decays

Implications of recent CLEO measurements of hadronic charmless B decays are discussed. (i) Employing the Bauer-Stech-Wirbel (BSW) model for form factors as a benchmark, the $B\to\pi^+\pi^-$ data indicate that the form factor $F_0^{B\pi}(0)$ is smaller than that predicted by the BSW model, whereas the data of $B\to\omega\pi, K^*\eta$ imply that the form factors $A_0^{B\omega}(0), A_0^{BK^*}(0)$ are greater than the BSW model's values. (ii) The tree-dominated modes $B\to\pi^+\pi^-, \rho^0\pi^\pm, \omega\pi^\pm$ imply that the effective number of colors N_c(LL) for (V-A)(V-A) operators is preferred to be smaller, while the current limit on $B\to\phi K$ shows that N_c(LR)>3. The data of $B\to K\eta'$ and $K^*\eta$ clearly indicate that $N_c(LR)\gg N_c(LL)$. (iii) In order to understand the observed suppression of $\pi^+\pi^-$ and non-suppression of $K\pi$ modes, both being governed by the form factor $F_0^{B\pi}$, the unitarity angle $\gamma$ is preferred to be greater than $90^\circ$. By contrast, the new measurement of $B^\pm\to\rho^0\pi^\pm$ no longer strongly favors $\cos\gamma<0$. (iv) The observed pattern K^-\pi^+\sim \ov K^0\pi^-\sim {2\over 3}K^-\pi^0 is consistent with the theoretical expectation: The constructive interference between electroweak and QCD penguin diagrams in the $K^-\pi^0$ mode explains why {\cal B}(B^-\to K^-\pi^0)>{1\over 2}{\cal B}(\ov B^0\to K^-\pi^+). (v) The observation \nc(LL)<3<\nc(LR) and our preference for \nc(LL)\sim 2 and \nc(LR)\sim 6 are justified by a recent perturbative QCD calculation of hadronic rare B decays in the heavy quark limit.Comment: 21 pages; CLEO measurements of several charmless B decay modes are updated. Discussion of the unitarity angle gamma in the \rho\pi mode is revise

Emerging Trade Patterns in a 3-Region Linear NEG Model: Three Examples

This chapter draws attention to a specific feature of a NEG model that uses linear (and not iso-elastic) demand functions, namely its ability to account for zero trade. Thus, it represents a suitable framework to study how changes in parameters that are typical for NEG models, such as trade costs and regional market size, not only shape the regional distribution of economic activity, but at the same time determine the emergence of additional trade links between formerly autarkic regions. We survey some related papers and present a three-region framework that potentially nests many possible trade patterns. To focus the analysis, we study in more detail three specific trade patterns frequently found in the EU trade network. We start with three autarkic regions; then we introduce the possibility that two regions trade with each other; and, finally, we allow for one region trading with the other two, but the latter are still not trading with each other. We find a surprising plethora of long-run equilibria each involving a specific regional distribution of economic activity and a specific pattern of trade links. We show how a reduction in trade costs shapes simultaneously industry location and the configuration of the trade network

Chirp mitigation of plasma-accelerated beams using a modulated plasma density

Plasma-based accelerators offer the possibility to drive future compact light sources and high-energy physics applications. Achieving good beam quality, especially a small beam energy spread, is still one of the major challenges. For stable transport, the beam is located in the focusing region of the wakefield which covers only the slope of the accelerating field. This, however, imprints a longitudinal energy correlation (chirp) along the bunch. Here, we propose an alternating focusing scheme in the plasma to mitigate the development of this chirp and thus maintain a small energy spread

The ZEUS Forward Plug Calorimeter with Lead-Scintillator Plates and WLS Fiber Readout

A Forward Plug Calorimeter (FPC) for the ZEUS detector at HERA has been built as a shashlik lead-scintillator calorimeter with wave length shifter fiber readout. Before installation it was tested and calibrated using the X5 test beam facility of the SPS accelerator at CERN. Electron, muon and pion beams in the momentum range of 10 to 100 GeV/c were used. Results of these measurements are presented as well as a calibration monitoring system based on a $^{60}$Co source.Comment: 38 pages (Latex); 26 figures (ps

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating