Can winds driven by active galactic nuclei account for the extragalactic gamma-ray and neutrino backgrounds?

Various observations are revealing the widespread occurrence of fast and powerful winds in active galactic nuclei (AGNs) that are distinct from relativistic jets, likely launched from accretion disks and interacting strongly with the gas of their host galaxies. During the interaction, strong shocks are expected to form that can accelerate non-thermal particles to high energies. Such winds have been suggested to be responsible for a large fraction of the observed extragalactic gamma-ray background (EGB) in the GeV-TeV range and the diffuse neutrino background in the PeV range, via the decay of neutral and charged pions generated in inelastic $pp$ collisions between protons accelerated by the forward shock and the ambient gas. However, previous studies did not properly account for processes such as adiabatic losses that may reduce the gamma-ray and neutrino fluxes significantly. We evaluate the production of gamma-rays and neutrinos by AGN-driven winds in some detail by modeling their hydrodynamic and thermal evolution, including the effects of their two-temperature structure. We find that they can only account for less than $\sim 30$% of the EGB flux, as otherwise the model would violate the independent upper limit derived from the diffuse isotropic gamma-ray background. If the neutrino spectral index is steep with $\Gamma\gtrsim 2.2$, a severe tension with the isotropic gamma-ray background would arise as long as the winds contribute more than $20$% of the IceCube neutrino flux in the $10-100$TeV range. Nevertheless, at energies $\gtrsim100$~TeV, we find that the IceCube neutrino flux may still be accountable by AGN-driven winds if the spectral index is as small as $\Gamma\sim2.0-2.1$. The detectability of gamma-ray point sources also provides important constraints on such scenarios.Comment: 17 pages, 10 figures, to appear in Ap

Molecular Dynamics Simulation of Macromolecules Using Graphics Processing Unit

Molecular dynamics (MD) simulation is a powerful computational tool to study the behavior of macromolecular systems. But many simulations of this field are limited in spatial or temporal scale by the available computational resource. In recent years, graphics processing unit (GPU) provides unprecedented computational power for scientific applications. Many MD algorithms suit with the multithread nature of GPU. In this paper, MD algorithms for macromolecular systems that run entirely on GPU are presented. Compared to the MD simulation with free software GROMACS on a single CPU core, our codes achieve about 10 times speed-up on a single GPU. For validation, we have performed MD simulations of polymer crystallization on GPU, and the results observed perfectly agree with computations on CPU. Therefore, our single GPU codes have already provided an inexpensive alternative for macromolecular simulations on traditional CPU clusters and they can also be used as a basis to develop parallel GPU programs to further speedup the computations.Comment: 21 pages, 16 figure

Boundary two-parameter eight-state supersymmetric fermion model and Bethe ansatz solution

The recently introduced two-parameter eight-state $U_q[gl(3|1)]$ supersymmetric fermion model is extended to include boundary terms. Nine classes of boundary conditions are constructed, all of which are shown to be integrable via the graded boundary quantum inverse scattering method. The boundary systems are solved by using the coordinate Bethe ansatz and the Bethe ansatz equations are given for all nine cases.Comment: 11 pages, RevTex; some typos correcte

Discovery of the transient magnetar 3XMM J185246.6+003317 near supernova remnant Kesteven 79 with XMM-Newton

We report the serendipitous discovery with XMM-Newton that 3XMM J185246.6+003317 is an 11.56 s X-ray pulsar located 1' away from the southern boundary of supernova remnant Kes 79. The spin-down rate of 3XMM J185246.6+003317 is $<1.1\times 10^{-13}$ s s$^{-1}$, which, together with the long period P=11.558714(2) s, indicates a dipolar surface magnetic field of $1.7$ Myr, and a spin-down luminosity of $<2.8\times 10^{30}$ erg s$^{-1}$. The X-ray spectrum of the source is best-fitted with a resonant Compton scattering model, and can be also adequately described by a blackbody model. The observations covering a seven month span from 2008 to 2009 show variations in the spectral properties of the source, with the luminosity decreasing from $2.7\times 10^{34}$ erg s$^{-1}$ to $4.6 \times 10^{33}$ erg s$^{-1}$, along with a decrease of the blackbody temperature from $kT\approx 0.8$ keV to $\approx0.6$ keV. The X-ray luminosity of the source is higher than its spin-down luminosity, ruling out rotation as a power source. The combined timing and spectral properties, the non-detection of any optical or infrared counterpart, together with the lack of detection of the source in archival X-ray data prior to the 2008 XMM-Newton observation, point to this source being a newly discovered transient low-B magnetar undergoing an outburst decay during the XMM-Newton observations. The non-detection by Chandra in 2001 sets an upper limit $4\times 10^{32}$ erg s$^{-1}$ to the quiescent luminosity of 3XMM J185246.6+003317. Its period is the longest among currently known transient magnetars. The foreground absorption toward 3XMM J185246.6+003317 is similar to that of Kes 79, suggesting a similar distance of $\sim$7.1 kpc.Comment: 7 pages, 4 figures, 1 table; updated to match the published versio

The K giant stars from the LAMOST survey data I: identification, metallicity, and distance

We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2.5%. Applying the classification method to about 2 million LAMOST spectra observed during the pilot survey and the first year survey, we select 298,036 K giant candidates. The metallicities of the sample are also estimated with uncertainty of $0.13\sim0.29$\,dex based on the equivalent widths of Mg$_{\rm b}$ and iron lines. A Bayesian method is then developed to estimate the posterior probability of the distance for the K giant stars, based on the estimated metallicity and 2MASS photometry. The synthetic isochrone-based distance estimates have been calibrated using 7 globular clusters with a wide range of metallicities. The uncertainty of the estimated distance modulus at $K=11$\,mag, which is the median brightness of the K giant sample, is about 0.6\,mag, corresponding to $\sim30$% in distance. As a scientific verification case, the trailing arm of the Sagittarius stream is clearly identified with the selected K giant sample. Moreover, at about 80\,kpc from the Sun, we use our K giant stars to confirm a detection of stream members near the apo-center of the trailing tail. These rediscoveries of the features of the Sagittarius stream illustrate the potential of the LAMOST survey for detecting substructures in the halo of the Milky Way.Comment: 24 pages, 20 figures, submitted to Ap

A new tow-parameter integrable model of strongly correlated electrons with quantum superalgebra symmetry

A new two-parameter integrable model with quantum superalgebra $U_q[gl(3|1)]$ symmetry is proposed, which is an eight-state electron model with correlated single-particle and pair hoppings as well as uncorrelated triple-particle hopping. The model is solved and the Bethe ansatz equations are obtained.Comment: 6 pages, RevTe

Mass and Age of Red Giant Branch Stars Observed with LAMOST and \emph{Kepler}

Obtaining accurate and precise masses and ages for large numbers of giant stars is of great importance for unraveling the assemblage history of the Galaxy. In this paper, we estimate masses and ages of 6940 red giant branch (RGB) stars with asteroseismic parameters deduced from \emph{Kepler} photometry and stellar atmospheric parameters derived from LAMOST spectra. The typical uncertainties of mass is a few per cent, and that of age is $\sim$\,20 per cent. The sample stars reveal two separate sequences in the age -- [$\alpha$/Fe] relation -- a high--$\alpha$ sequence with stars older than $\sim$\,8\,Gyr and a low--$\alpha$ sequence composed of stars with ages ranging from younger than 1\,Gyr to older than 11\,Gyr. We further investigate the feasibility of deducing ages and masses directly from LAMOST spectra with a machine learning method based on kernel based principal component analysis, taking a sub-sample of these RGB stars as a training data set. We demonstrate that ages thus derived achieve an accuracy of $\sim$\,24 per cent. We also explored the feasibility of estimating ages and masses based on the spectroscopically measured carbon and nitrogen abundances. The results are quite satisfactory and significantly improved compared to the previous studies.Comment: accepted by MNRA