Statistical Properties of Multiple Optical Emission Components in Gamma-Ray Bursts and Implications

Well-sampled optical lightcurves of 146 gamma-ray bursts (GRBs) are complied from the literature. Multiple optical emission components are extracted with power-law function fits to these lightcurves. We present a systematical analysis for statistical properties and their relations to prompt gamma-ray emission and X-ray afterglow for each component. We show that peak luminosity in the prompt and late flares are correlated and the evolution of the peak luminosity may signal the evolution of the accretion rate. No tight correlation between the shallow decay phase/plateau and prompt gamma-ray emission is found. Assuming that they are due to a long-lasting wind injected by a compact object, we show that the injected behavior favors the scenarios of a long-lasting wind after the main burst episode. The peak luminosity of the afterglow onset is tightly correlated with Eiso, and it is dimmer as peaking later. Assuming that the onset bump is due to the fireball deceleration by the external medium, we examine the Gamma_0-Eiso relation and find that it is confirmed with the current sample. Optical re-brightening is observed in 30 GRBs in our sample. It shares the same relation between the width and the peak time as found in the onset bump, but no clear correlation between the peak luminosity and Eiso as observed in the onset bumps is found. Although its peak luminosity also decays with time, the slope is much shallower than that of the onset peak. We get L t^{-1}_{p}$, being consistent with off-axis observations to an expanding external fireball in a wind-like circum medium. The late re-brightening may signal another jet component. Mixing of different emission components may be the reason for the observed chromatic breaks in different energy bands.Comment: 10 pages, 5 figures, to be published by IJMPD (Proceedings of "The Third Galileo - Xu Guangqi meeting", Beijing, October 11-15, 2011

Nuclear Hartree-Fock calculations on parallel computers

Hartree-Fock (HF) calculations have had remarkable success in describing large nuclei at high spin, temperature and deformation. To allow full range of possible deformations, the Skyrme HF equations can be discretized on a three-dimensional mesh. However, such calculations are currently limited by the computational resources provided by traditional supercomputers. To take advantage of recent developments in massively parallel computing technology, we have implemented the LLNL Skyrme-force static and rotational HF codes on Intel's DELTA and GAMMA systems at Caltech. We decomposed the HF code by assigning a portion of the mesh to each node, with nearest neighbor meshes assigned to nodes connected by communication· channels. This kind of decomposition is well-suited for the DELTA and the GAMMA architecture because the only non-local operations are wave function orthogonalization and the boundary conditions of the Poisson equation for the Coulomb field. Our first application of the HF code on parallel computers has been the study of identical superdeformed (SD) rotational bands in the Hg region. In the last ten years, many SD rotational bands have been found experimentally. One very surprising feature found in these SD rotational bands is that many pairs of bands in nuclei that differ by one or two mass units have nearly identical deexcitation gamma-ray energies. Our calculations of the five rotational bands in ^(192)Hg and ^(194)Pb show that the filling of specific orbitals can lead to bands with deexcitation gamma-ray energies differing by at most 2 keV in nuclei differing by two mass units and over a range of angular momenta comparable to that observed experimentally. Our calculations of SD rotational bands in the Dy region also show that twinning can be achieved by filling or emptying some specific orbitals. The interpretation of future precise experiments on atomic parity nonconservation (PNC) in terms of parameters of the Standard Model could be hampered by uncertainties in the atomic and nuclear structure. As a further application of the massively parallel HF calculations, we calculated the proton and neutron densities of the Cesium isotopes from A = 125 to A = 139. Based on our good agreement with experimental charge radii, binding energies, and ground state spins, we conclude that the uncertainties in the ratios of weak charges are less than 10^(-3), comfortably smaller than the anticipated experimental error.</p

Synthesis of chiral α-hydroxy acids via palladium-catalyzed C(sp^3)–H alkylation of lactic acid

Herein we report a Pd-catalyzed alkylation of lactic acid with the assistance of 8-aminoquinoline auxiliary. A wide range of alkyl iodides bearing β-hydrogen atoms are compatible with the reaction conditions, providing a practical and straightforward alternative to access chiral α-hydroxy acids (AHAs). The new reactions have been applied for the synthesis of isotope-labeled AHAs and a sugar-containing complex AHA

Δ\Delta contribution in e++e−→p+pˉe^+ + e^- \to p + \bar{p} at small ss

Two-photon annihilate contributions in the process $e^+ + e^- \to p + \bar{p}$ including $N$ and $\Delta$ intermediate are discussed in a simple hadronic model. The corrections to the unpolarized cross section and polarized observables $P_x,P_z$ are presented. The results show the two-photon annihilate correction to unpolarized cross section is small and its angle dependence becomes weak at small $s$ after considering the $N$ and $\Delta(1232)$ contributions simultaneously, while the correction to $P_z$ is enhanced.Comment: 5 page

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the 1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification