Charmed Baryon Weak Decays with SU(3) Flavor Symmetry

We study the semileptonic and non-leptonic charmed baryon decays with $SU(3)$ flavor symmetry, where the charmed baryons can be ${\bf B}_{c}=(\Xi_c^0,\Xi_c^+,\Lambda_c^+)$, ${\bf B}'_{c}=(\Sigma_c^{(++,+,0)},\Xi_{c}^{\prime(+,0)},\Omega_c^0)$, ${\bf B}_{cc}=(\Xi_{cc}^{++},\Xi_{cc}^+,\Omega_{cc}^+)$, or ${\bf B}_{ccc}=\Omega^{++}_{ccc}$. With ${\bf B}_n^{(\prime)}$ denoted as the baryon octet (decuplet), we find that the ${\bf B}_{c}\to {\bf B}'_n\ell^+\nu_\ell$ decays are forbidden, while the $\Omega_c^0\to \Omega^-\ell^+\nu_\ell$, $\Omega_{cc}^+\to\Omega_c^0\ell^+\nu_\ell$, and $\Omega_{ccc}^{++}\to \Omega_{cc}^+\ell^+\nu_\ell$ decays are the only existing Cabibbo-allowed modes for ${\bf B}'_{c}\to {\bf B}'_n\ell^+\nu_\ell$, ${\bf B}_{cc}\to {\bf B}'_c\ell^+\nu_\ell$, and ${\bf B}_{ccc}\to {\bf B}_{cc}^{(\prime)}\ell^+\nu_\ell$, respectively. We predict the rarely studied ${\bf B}_{c}\to {\bf B}_n^{(\prime)}M$ decays, such as ${\cal B}(\Xi_c^0\to\Lambda^0\bar K^0,\,\Xi_c^+\to\Xi^0\pi^+)=(8.3\pm 0.9,8.0\pm 4.1)\times 10^{-3}$ and ${\cal B}(\Lambda_c^+\to \Delta^{++}\pi^-,\,\Xi_c^0\to\Omega^- K^+)=(5.5\pm 1.3,4.8\pm 0.5)\times 10^{-3}$. For the observation, the doubly and triply charmed baryon decays of $\Omega_{cc}^{+}\to \Xi_c^+\bar K^0$, $\Xi_{cc}^{++}\to (\Xi_c^+\pi^+$, $\Sigma_c^{++}\bar K^0)$, and $\Omega_{ccc}^{++}\to (\Xi_{cc}^{++}\bar K^0,\Omega_{cc}^+\pi^+,\Xi_c^+ D^+)$ are the favored Cabibbo-allowed decays, which are accessible to the BESIII and LHCb experiments.Comment: 29 pages, no figure, a typo in the table correcte

A high flux source of cold strontium atoms

We describe an experimental apparatus capable of achieving a high loading rate of strontium atoms in a magneto-optical trap operating in a high vacuum environment. A key innovation of this setup is a two dimensional magneto-optical trap deflector located after a Zeeman slower. We find a loading rate of 6x10^9/s whereas the lifetime of the magnetically trapped atoms in the 3P2 state is 54s.Comment: 12 pages, 16 figure

Optical Properties of Organometallic Perovskite: An ab initio Study using Relativistic GW Correction and Bethe-Salpeter Equation

In the development of highly efficient photovoltaic cells, solid perovskite systems have demonstrated unprecedented promise, with the figure of merit exceeding nineteen percent of efficiency. In this paper, we investigate the optical and vibrational properties of organometallic cubic perovskite CH3NH3PbI3 using first-principles calculations. For accurate theoretical description, we go beyond conventional density functional theory (DFT), and calculated optical conductivity using relativist quasi-particle (GW) correction. Incorporating these many-body effects, we further solve Bethe-Salpeter equations (BSE) for excitons, and found enhanced optical conductivity near the gap edge. Due to the presence of organic methylammonium cations near the center of the perovskite cell, the system is sensitive to low energy vibrational modes. We estimate the phonon modes of CH3NH3PbI3 using small displacement approach, and further calculate the infrared absorption (IR) spectra. Qualitatively, our calculations of low-energy phonon frequencies are in good agreement with our terahertz measurements. Therefore, for both energy scales (around 2 eV and 0-20 meV), our calculations reveal the importance of many-body effects and their contributions to the desirable optical properties in the cubic organometallic perovskites system.Comment: 5 pages, 4 figure

A Statistical Analysis of Industrial Penetration and Internet Intensity in Taiwan

This paper investigates the effect of industrial penetration (geographic concentration of industries) and internet intensity (the proportion of enterprises that use the internet) for Taiwan manufacturing firms, and analyses whether the relationships are substitutes or complements. The sample observations are based on 153,081 manufacturing plants, and covers 26 two-digit industry categories and 358 geographical townships in Taiwan. The Heckman selection model is used to accommodate sample selectivity for unobservable data for firms that use the internet. The empirical results from two-stage estimation show that: (1) a higher degree of industrial penetration will not affect the probability that firms will use the internet, but will affect the total expenditure on internet intensity; (2) for two-digit SIC industries, industrial penetration generally decreases the total expenditure on internet intensity; and (3) industrial penetration and internet intensity are substitutes

Industrial Penetration and Internet Intensity

This paper investigates the effect of industrial penetration and internet intensity for Taiwan manufacturing firms, and analyses whether the relationships are substitutes or complements. The sample observations are based on 153,081 manufacturing plants, and covers 26 two-digit industry categories and 358 geographical townships in Taiwan. The Heckman selection model is used to accommodate sample selectivity for unobservable data for firms that use the internet. The empirical results from two-stage estimation show that: (1) a higher degree of industrial penetration will not affect the probability that firms will use the internet, but will affect the total expenditure on internet intensity; (2) for two-digit industries, industrial penetration generally decreases the total expenditure on internet intensity; and (3) industrial penetration and internet intensity are substitutes

Testing Co-Volatility Spillovers for Natural Gas Spot, Futures and ETF Spot using Dynamic Conditional Covariances

There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices

Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice

Energy and agricultural commodities and markets have been examined extensively, albeit separately, for a number of years. In the energy literature, the returns, volatility and volatility spillovers (namely, the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset), among alternative energy commodities, such as oil, gasoline and ethanol across different markets, have been analysed using a variety of univariate and multivariate models, estimation techniques, data sets, and time frequencies. A similar comment applies to the separate theoretical and empirical analysis of a wide range of agricultural commodities and markets. Given the recent interest and emphasis in bio-fuels and green energy, especially bio-ethanol, which is derived from a range of agricultural products, it is not surprising that there is a topical and developing literature on the spillovers between energy and agricultural markets. Modelling and testing spillovers between the energy and agricultural markets has typically been based on estimating multivariate conditional volatility models, specifically the Baba, Engle, Kraft, and Kroner (BEKK) and dynamic conditional correlation (DCC) models. A serious technical deficiency is that the Quasi-Maximum Likelihood Estimates (QMLE) of a Full BEKK matrix, which is typically estimated in examining volatility spillover effects, has no asymptotic properties, except by assumption, so that no valid statistical test of volatility spillovers is possible. Some papers in the literature have used the DCC model to test for volatility spillovers. However, it is well known in the financial econometrics literature that the DCC model has no regularity conditions, and that the QMLE of the parameters of DCC has no asymptotic properties, so that there is no valid statistical testing of volatility spillovers. The purpose of the paper is to evaluate the theory and practice in testing for volatility spillovers between energy and agricultural markets using the multivariate Full BEKK and DCC models, and to make recommendations as to how such spillovers might be tested using valid statistical techniques. Three new definitions of volatility and covolatility spillovers are given, and the different models used in empirical applications are evaluated in terms of the new definitions and statistical criteria

Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice

Energy and agricultural commodities and markets have been examined extensively, albeit separately, for a number of years. In the energy literature, the returns, volatility and volatility spillovers (namely, the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset), among alternative energy commodities, such as oil, gasoline and ethanol across different markets, have been analysed using a variety of univariate and multivariate models, estimation techniques, data sets, and time frequencies. A similar comment applies to the separate theoretical and empirical analysis of a wide range of agricultural commodities and markets. Given the recent interest and emphasis in bio-fuels and green energy, especially bio-ethanol, which is derived from a range of agricultural products, it is not surprising that there is a topical and developing literature on the spillovers between energy and agricultural markets. Modelling and testing spillovers between the energy and agricultural markets has typically been based on estimating multivariate conditional volatility models, specifically the Baba, Engle, Kraft, and Kroner (BEKK) and dynamic conditional correlation (DCC) models. A serious technical deficiency is that the Quasi-Maximum Likelihood Estimates (QMLE) of a Full BEKK matrix, which is typically estimated in examining volatility spillover effects, has no asymptotic properties, except by assumption, so that no valid statistical test of volatility spillovers is possible. Some papers in the literature have used the DCC model to test for volatility spillovers. However, it is well known in the financial econometrics literature that the DCC model has no regularity conditions, and that the QMLE of the parameters of DCC has no asymptotic properties, so that there is no valid statistical testing of volatility spillovers. The purpose of the paper is to evaluate the theory and practice in testing for volatility spillovers between energy and agricultural markets using the multivariate Full BEKK and DCC models, and to make recommendations as to how such spillovers might be tested using valid statistical techniques. Three new definitions of volatility and covolatility spillovers are given, and the different models used in empirical applications are evaluated in terms of the new definitions and statistical criteria

Penetration depth study of LaOs4_4Sb12_{12}: Multiband s-wave superconductivity

We measured the magnetic penetration depth $\lambda(T)$ in single crystals of LaOs$_{4}$Sb$_{12}$ ($T_c$=0.74 K) down to 85 mK using a tunnel diode oscillator technique. The observed low-temperature exponential dependence indicates a s-wave gap. Fitting the low temperature data to BCS s-wave expression gives the zero temperature gap value $\Delta (0)= (1.34 \pm 0.07) k_B T_c$ which is significantly smaller than the BCS value of 1.76$k_B T_c$. In addition, the normalized superfluid density $\rho(T)$ shows an unusually long suppression near $T_c$, and are best fit by a two-band s-wave model.Comment: 5 pages, 2 figure