Exotic mesons from quantum chromodynamics with improved gluon and quark actions on the anisotropic lattice

Hybrid (exotic) mesons, which are important predictions of quantum chromodynamics (QCD), are states of quarks and anti-quarks bound by excited gluons. First principle lattice study of such states would help us understand the role of ``dynamical'' color in low energy QCD and provide valuable information for experimental search for these new particles. In this paper, we apply both improved gluon and quark actions to the hybrid mesons, which might be much more efficient than the previous works in reducing lattice spacing error and finite volume effect. Quenched simulations were done at $\beta=2.6$ and on a $\xi=3$ anisotropic $12^3\times36$ lattice using our PC cluster. We obtain $2013 \pm 26 \pm 71$ MeV for the mass of the $1^{-+}$ hybrid meson ${\bar q}qg$ in the light quark sector, and $4369 \pm 37 \pm 99$Mev in the charm quark sector; the mass splitting between the $1^{-+}$ hybrid meson ${\bar c}c g$ in the charm quark sector and the spin averaged S-wave charmonium mass is estimated to be $1302 \pm 37 \pm 99$ MeV. As a byproduct, we obtain $1438 \pm 32 \pm 57$ MeV for the mass of a P-wave $1^{++}$ ${\bar u}u$ or ${\bar d}d$ meson and $1499 \pm 28 \pm 65$ MeV for the mass of a P-wave $1^{++}$ ${\bar s}s$ meson, which are comparable to their experimental value 1426 MeV for the $f_1(1420)$ meson. The first error is statistical, and the second one is systematical. The mixing of the hybrid meson with a four quark state is also discussed.Comment: 12 pages, 3 figures. Published versio

Cooperative and Distributed Localization for Wireless Sensor Networks in Multipath Environments

We consider the problem of sensor localization in a wireless network in a multipath environment, where time and angle of arrival information are available at each sensor. We propose a distributed algorithm based on belief propagation, which allows sensors to cooperatively self-localize with respect to one single anchor in a multihop network. The algorithm has low overhead and is scalable. Simulations show that although the network is loopy, the proposed algorithm converges, and achieves good localization accuracy

Helicity Observation of Weak and Strong Fields

We report in this letter our analysis of a large sample of photospheric vector magnetic field measurements. Our sample consists of 17200 vector magnetograms obtained from January 1997 to August 2004 by Huairou Solar Observing Station of the Chinese National Astronomical Observatory. Two physical quantities, $\alpha$ and current helicity, are calculated and their signs and amplitudes are studied in a search for solar cycle variations. Different from other studies of the same type, we calculate these quantities for weak ($100G1000G$) fields separately. For weak fields, we find that the signs of both $\alpha$ and current helicity are consistent with the established hemispheric rule during most years of the solar cycle and their magnitudes show a rough tendency of decreasing with the development of solar cycle. Analysis of strong fields gives an interesting result: Both $\alpha$ and current helicity present a sign opposite to that of weak fields. Implications of these observations on dynamo theory and helicity production are also briefly discussed.Comment: accepted for publication in ApJ Lette

Distributed Local Linear Parameter Estimation using Gaussian SPAWN

We consider the problem of estimating local sensor parameters, where the local parameters and sensor observations are related through linear stochastic models. Sensors exchange messages and cooperate with each other to estimate their own local parameters iteratively. We study the Gaussian Sum-Product Algorithm over a Wireless Network (gSPAWN) procedure, which is based on belief propagation, but uses fixed size broadcast messages at each sensor instead. Compared with the popular diffusion strategies for performing network parameter estimation, whose communication cost at each sensor increases with increasing network density, the gSPAWN algorithm allows sensors to broadcast a message whose size does not depend on the network size or density, making it more suitable for applications in wireless sensor networks. We show that the gSPAWN algorithm converges in mean and has mean-square stability under some technical sufficient conditions, and we describe an application of the gSPAWN algorithm to a network localization problem in non-line-of-sight environments. Numerical results suggest that gSPAWN converges much faster in general than the diffusion method, and has lower communication costs, with comparable root mean square errors

Evolutionary History of the Photolyase/Cryptochrome Superfamily in Eukaryotes

Background Photolyases and cryptochromes are evolutionarily related flavoproteins, which however perform distinct physiological functions. Photolyases (PHR) are evolutionarily ancient enzymes. They are activated by light and repair DNA damage caused by UV radiation. Although cryptochromes share structural similarity with DNA photolyases, they lack DNA repair activity. Cryptochrome (CRY) is one of the key elements of the circadian system in animals. In plants, CRY acts as a blue light receptor to entrain circadian rhythms, and mediates a variety of light responses, such as the regulation of flowering and seedling growth. Results We performed a comprehensive evolutionary analysis of the CRY/PHR superfamily. The superfamily consists of 7 major subfamilies: CPD class I and CPD class II photolyases, (6-4) photolyases, CRY-DASH, plant PHR2, plant CRY and animal CRY. Although the whole superfamily evolved primarily under strong purifying selection (average omega = 0.0168), some subfamilies did experience strong episodic positive selection during their evolution. Photolyases were lost in higher animals that suggests natural selection apparently became weaker in the late stage of evolutionary history. The evolutionary time estimates suggested that plant and animal CRYs evolved in the Neoproterozoic Era (similar to 1000-541 Mya), which might be a result of adaptation to the major climate and global light regime changes occurred in that period of the Earth's geological history.published_or_final_versio

Distribution of Spectral Lags in Gamma Ray Bursts

Using the data acquired in the Time To Spill (TTS) mode for long gamma-ray bursts (GRBs) collected by the Burst and Transient Source Experiment on board the Compton Gamma Ray Observatory (BATSE/CGRO), we have carefully measured spectral lags in time between the low (25-55 keV) and high (110-320 keV) energy bands of individual pulses contained in 64 multi-peak GRBs. We find that the temporal lead by higher-energy gamma-ray photons (i.e., positive lags) is the norm in this selected sample set of long GRBs. While relatively few in number, some pulses of several long GRBs do show negative lags. This distribution of spectral lags in long GRBs is in contrast to that in short GRBs. This apparent difference poses challenges and constraints on the physical mechanism(s) of producing long and short GRBs. The relation between the pulse peak count rates and the spectral lags is also examined. Observationally, there seems to be no clear evidence for systematic spectral lag-luminosity connection for pulses within a given long GRB.Comment: 20 pages, 4 figure

Efficient Scheduling for SDMG CIOQ Switches

Combined input and output queuing (CIOQ) switches are being considered as high-performance switch architectures due to their ability to achieve 100% throughput and perfectly emulate output queuing (OQ) switch performance with a small speedup factor S. To realize a speedup factor S, a conventional CIOQ switch requires the switching fabric and memories to operate S times faster than the line rate. In this paper, we propose to use a CIOQ switch with space-division multiplexing expansion and grouped input/output ports (SDMG CIOQ switch for short) to realize speedup while only requiring the switching fabric and memories to operate at the line rate. The cell scheduling problem for the SDMG CIOQ switch is abstracted as a bipartite k-matching problem. Using fluid model techniques, we prove that any maximal size k-matching algorithm on an SDMG CIOQ switch with an expansion factor 2 can achieve 100% throughput assuming input line arrivals satisfy the strong law of large numbers (SLLN) and no input/output line is oversubscribed. We further propose an efficient and starvation-free maximal size k-matching scheduling algorithm, kFRR, for the SDMG CIOQ switch. Simulation results show that kFRR achieves 100% throughput for SDMG CIOQ switches with an expansion factor 2 under two SLLN traffic models, uniform traffic and polarized traffic, confirming our analysis