The phase relation between sunspot numbers and soft X-ray flares

To better understand long-term flare activity, we present a statistical study on soft X-ray flares from May 1976 to May 2008. It is found that the smoothed monthly peak fluxes of C-class, M-class, and X-class flares have a very noticeable time lag of 13, 8, and 8 months in cycle 21 respectively with respect to the smoothed monthly sunspot numbers. There is no time lag between the sunspot numbers and M-class flares in cycle 22. However, there is a one-month time lag for C-class flares and a one-month time lead for X-class flares with regard to sunspot numbers in cycle 22. For cycle 23, the smoothed monthly peak fluxes of C-class, M-class, and X-class flares have a very noticeable time lag of one month, 5 months, and 21 months respectively with respect to sunspot numbers. If we take the three types of flares together, the smoothed monthly peak fluxes of soft X-ray flares have a time lag of 9 months in cycle 21, no time lag in cycle 22 and a characteristic time lag of 5 months in cycle 23 with respect to the smoothed monthly sunspot numbers. Furthermore, the correlation coefficients of the smoothed monthly peak fluxes of M-class and X-class flares and the smoothed monthly sunspot numbers are higher in cycle 22 than those in cycles 21 and 23. The correlation coefficients between the three kinds of soft X-ray flares in cycle 22 are higher than those in cycles 21 and 23. These findings may be instructive in predicting C-class, M-class, and X-class flares regarding sunspot numbers in the next cycle and the physical processes of energy storage and dissipation in the corona.Comment: 8 pages, 3 figures, Accepted for publication in Astrophysics & Space Scienc

A Lattice Study of the Magnetic Moment and the Spin Structure of the Nucleon

Using an approach free from momentum extrapolation, we calculate the nucleon magnetic moment and the fraction of the nucleon spin carried by the quark angular momentum in the quenched lattice QCD approximation. Quarks with three values of lattice masses, 210, 124 and 80 MeV, are formulated on the lattice using the standard Wilson approach. At every mass, 100 gluon configurations on 16^3 x 32 lattice with \beta=6.0 are used for statistical averaging. The results are compared with the previous calculations with momentum extrapolation. The contribution of the disconnected diagrams is studied at the largest quark mass using noise theory technique.Comment: 14 pages, 3 figures, Talk given at Lattice2001, Berlin, German

Merger of binary neutron stars of unequal mass in full general relativity

We present results of three dimensional numerical simulations of the merger of unequal-mass binary neutron stars in full general relativity. A $\Gamma$-law equation of state $P=(\Gamma-1)\rho\epsilon$ is adopted, where $P$, $\rho$, \varep, and $\Gamma$ are the pressure, rest mass density, specific internal energy, and the adiabatic constant, respectively. We take $\Gamma=2$ and the baryon rest-mass ratio $Q_M$ to be in the range 0.85--1. The typical grid size is $(633,633,317)$ for $(x,y,z)$ . We improve several implementations since the latest work. In the present code, the radiation reaction of gravitational waves is taken into account with a good accuracy. This fact enables us to follow the coalescence all the way from the late inspiral phase through the merger phase for which the transition is triggered by the radiation reaction. It is found that if the total rest-mass of the system is more than $\sim 1.7$ times of the maximum allowed rest-mass of spherical neutron stars, a black hole is formed after the merger irrespective of the mass ratios. The gravitational waveforms and outcomes in the merger of unequal-mass binaries are compared with those in equal-mass binaries. It is found that the disk mass around the so formed black holes increases with decreasing rest-mass ratios and decreases with increasing compactness of neutron stars. The merger process and the gravitational waveforms also depend strongly on the rest-mass ratios even for the range $Q_M= 0.85$--1.Comment: 32 pages, PRD68 to be publishe

Automated Prediction of CMEs Using Machine Learning of CME – Flare Associations

YesIn this work, machine learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CMEs catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flares and CMEs data, which are later arranged in numerical training vectors and fed to machine learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Different properties are extracted from all the associated (A) and not-associated (NA) flares representing the intensity, flare duration, duration of decline and duration of growth. Cascade Correlation Neural Networks (CCNN) are used in our work. The flare properties are converted to numerical formats that are suitable for CCNN. The CCNN will predict if a certain flare is likely to initiate a CME after input of its properties. Intensive experiments using the Jack-knife techniques are carried out and it is concluded that our system provides an accurate prediction rate of 65.3%. The prediction performance is analysed and recommendation for enhancing the performance are provided

Search for Λc+→pK+π−\Lambda_c^+ \to p K^+ \pi^- and Ds+→K+K+π−D_s^+ \to K^+ K^+ \pi^- Using Genetic Programming Event Selection

We apply a genetic programming technique to search for the double Cabibbo suppressed decays $\Lambda_c^+ \to p K^+ \pi^-$ and $D_s^+ \to K^+ K^+ \pi^-$. We normalize these decays to their Cabibbo favored partners and find $\text{BR}($\Lambda_c^+ \to p K^+ \pi^-$)/\text{BR}($\Lambda_c^+ \to p K^- \pi^+$) = (0.05 \pm 0.26 \pm 0.02)$ and $\text{BR}($D_s^+ \to K^+ K^+ \pi^-$)/\text{BR}($D_s^+ \to K^+ K^- \pi^+$) = (0.52\pm 0.17\pm 0.11)$ where the first errors are statistical and the second are systematic. Expressed as 90% confidence levels (CL), we find $< 0.46$ and $< 0.78$ respectively. This is the first successful use of genetic programming in a high energy physics data analysis.Comment: 10 page

Measurements of Ξc+\Xi_c^{+} Branching Ratios

Using data collected by the fixed target Fermilab experiment FOCUS, we measure the branching ratios of the Cabibbo favored decays $\Xi_c^+ \to \Sigma^+K^-\pi^+$, $\Xi_c^+ \to \Sigma^+ \bar{K}^{*}(892)^0$, and $\Xi_c^+ \to \Lambda^0K^-\pi^+\pi^+$ relative to $\Xi_c^+ \to \Xi^-\pi^+\pi^+$ to be $0.91\pm0.11\pm0.04$, $0.78\pm0.16\pm0.06$, and $0.28\pm0.06\pm0.06$, respectively. We report the first observation of the Cabibbo suppressed decay $\Xi_c^+ \to \Sigma^+K^+K^-$ and we measure the branching ratio relative to $\Xi_c^+ \to \Sigma^+K^-\pi^+$ to be $0.16\pm0.06\pm0.01$. We also set 90% confidence level upper limits for $\Xi_c^+ \to \Sigma^+ \phi$ and $\Xi_c^+ \to \Xi^*(1690)^0(\Sigma^+ K^-) K^+$ relative to $\Xi_c^+ \to \Sigma^+K^-\pi^+$ to be 0.12 and 0.05, respectively. We find an indication of the decays $\Xi_c^+ \to \Omega^-K^{+}\pi^+$ and $\Xi_c^+ \to \Sigma^{*}(1385)^+ \bar{K}^0$ and set 90% confidence level upper limits for the branching ratios with respect to $\Xi_c^+ \to \Xi^-\pi^+\pi^+$ to be 0.12 and 1.72, respectively. Finally, we determine the 90% C.L. upper limit for the resonant contribution $\Xi_c^+ \to \Xi^{*}(1530)^0 \pi^+$ relative to $\Xi_c^+ \to \Xi^-\pi^+\pi^+$ to be 0.10.Comment: 14 pages, 8 figure