Dynamics of neutrino-driven winds: inclusion of accurate weak interaction rates in strong magnetic fields

Solving Newtonian steady-state wind equations with accurate weak interaction rates and magnetic fields (MFs) of young neutron stars considered, we study the dynamics and nucleosynthesis of neutrino-driven winds (NDWs) from proto neutron stars (PNSs). For a typical 1.4 M$_{\odot}$ PNS model, we find the nucleosynthesis products are closely related to the luminosity of neutrinos and anti-neutrinos. The lower the luminosity is, the larger effect to the NDWs caused by weak interactions and MFs is. At a high anti-neutrino luminosity of typically $8\times 10^{51}$ erg s$^{-1}$, neutrinos and anti-neutrinos dominate the processes in a NDW and the MFs hardly change the wind's properties. While at a low anti-neutrino luminosity of $10^{51}$ erg s$^{-1}$ at the late stage of a NDW, the mass of product and nucleosynthesis are changed significantly in the strong MFs, they are less important than those in the early stage when the anti-neutrino luminosity is high. Therefore for the most models considered for the NDWs from PNSs, based on our calculations the influences of MFs and the net weak interactions on the nucleosynthesis is not significant.Comment: 8 pages, 3 figures, accepted for publication in RA

Predicting the epidemic threshold of the susceptible-infected-recovered model

Researchers have developed several theoretical methods for predicting epidemic thresholds, including the mean-field like (MFL) method, the quenched mean-field (QMF) method, and the dynamical message passing (DMP) method. When these methods are applied to predict epidemic threshold they often produce differing results and their relative levels of accuracy are still unknown. We systematically analyze these two issues---relationships among differing results and levels of accuracy---by studying the susceptible-infected-recovered (SIR) model on uncorrelated configuration networks and a group of 56 real-world networks. In uncorrelated configuration networks the MFL and DMP methods yield identical predictions that are larger and more accurate than the prediction generated by the QMF method. When compared to the 56 real-world networks, the epidemic threshold obtained by the DMP method is closer to the actual epidemic threshold because it incorporates full network topology information and some dynamical correlations. We find that in some scenarios---such as networks with positive degree-degree correlations, with an eigenvector localized on the high $k$-core nodes, or with a high level of clustering---the epidemic threshold predicted by the MFL method, which uses the degree distribution as the only input parameter, performs better than the other two methods. We also find that the performances of the three predictions are irregular versus modularity

The Software Correlator of the Chinese VLBI Network

The software correlator of the Chinese VLBI Network (CVN) has played an irreplaceable role in the CVN routine data processing, e.g., in the Chinese lunar exploration project. This correlator will be upgraded to process geodetic and astronomical observation data. In the future, with several new stations joining the network, CVN will carry out crustal movement observations, quick UT1 measurements, astrophysical observations, and deep space exploration activities. For the geodetic or astronomical observations, we need a wide-band 10-station correlator. For spacecraft tracking, a realtime and highly reliable correlator is essential. To meet the scientific and navigation requirements of CVN, two parallel software correlators in the multiprocessor environments are under development. A high speed, 10-station prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm on a computer cluster platform is being developed. Another real-time software correlator for spacecraft tracking adopts the thread-parallel technology, and it runs on the SMP (Symmetric Multiple Processor) servers. Both correlators have the characteristic of flexible structure and scalability

Plasmoid ejection and secondary current sheet generation from magnetic reconnection in laser-plasma interaction

Reconnection of the self-generated magnetic fields in laser-plasma interaction was first investigated experimentally by Nilson {\it et al.} [Phys. Rev. Lett. 97, 255001 (2006)] by shining two laser pulses a distance apart on a solid target layer. An elongated current sheet (CS) was observed in the plasma between the two laser spots. In order to more closely model magnetotail reconnection, here two side-by-side thin target layers, instead of a single one, are used. It is found that at one end of the elongated CS a fan-like electron outflow region including three well-collimated electron jets appears. The ($>1$ MeV) tail of the jet energy distribution exhibits a power-law scaling. The enhanced electron acceleration is attributed to the intense inductive electric field in the narrow electron dominated reconnection region, as well as additional acceleration as they are trapped inside the rapidly moving plasmoid formed in and ejected from the CS. The ejection also induces a secondary CS

Manipulation of Tribological Properties of Metals by Ultrashort Pulsed Laser Micro-/Nanostructuring

Surface texturing as a means for controlling tribological properties of mechanical components is well known for many years. Various technologies have been developed for surface texturing. Among them, ultrashort pulsed laser surface texturing is one of the most promising ways to achieve micromachining in the field of tribological applications. Ultrashort pulsed laser technology can produce various micro-/nanostructures on the material surfaces to modulate their tribological properties. The aim of this chapter is to introduce the recent progress on ultrashort pulsed laser-induced frictional property change of metals and to demonstrate the potential applications of ultrashort pulsed laser-induced frictional property change of metal in various fields