4,733 research outputs found
Charmed Baryon Weak Decays with SU(3) Flavor Symmetry
We study the semileptonic and non-leptonic charmed baryon decays with
flavor symmetry, where the charmed baryons can be , , , or . With denoted as the baryon
octet (decuplet), we find that the
decays are forbidden, while the ,
, and decays are the only existing Cabibbo-allowed modes
for , , and , respectively. We predict the rarely studied
decays, such as and . For the observation, the doubly and triply charmed baryon decays of
, ,
, and 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 LaOsSb: Multiband s-wave superconductivity
We measured the magnetic penetration depth in single crystals of
LaOsSb (=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 which is significantly smaller than the BCS value of 1.76. In
addition, the normalized superfluid density shows an unusually long
suppression near , and are best fit by a two-band s-wave model.Comment: 5 pages, 2 figure
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