Power-law Behavior of High Energy String Scatterings in Compact Spaces

We calculate high energy massive scattering amplitudes of closed bosonic string compactified on the torus. We obtain infinite linear relations among high energy scattering amplitudes. For some kinematic regimes, we discover that some linear relations break down and, simultaneously, the amplitudes enhance to power-law behavior due to the space-time T-duality symmetry in the compact direction. This result is consistent with the coexistence of the linear relations and the softer exponential fall-off behavior of high energy string scattering amplitudes as we pointed out prevously. It is also reminiscent of hard (power-law) string scatterings in warped spacetime proposed by Polchinski and Strassler.Comment: 6 pages, no figure. Talk presented by Jen-Chi Lee at Europhysics Conference (EPS2007), Manchester, England, July 19-25, 2007. To be published by Journal of Physics: Conference Series

350 Micron Observations of Ultraluminous Infrared Galaxies at Intermediate Redshifts

We present 350micron observations of 36 ultraluminous infrared galaxies (ULIRGs) at intermediate redshifts (0.089 <= z <= 0.926) using the Submillimeter High Angular Resolution Camera II (SHARC-II) on the Caltech Submillimeter Observatory (CSO). In total, 28 sources are detected at S/N >= 3, providing the first flux measurements longward of 100micron for a statistically significant sample of ULIRGs in the redshift range of 0.1 < z < 1.0. Combining our 350micron flux measurements with the existing IRAS 60 and 100micron data, we fit a single-temperature model to the spectral energy distribution (SED), and thereby estimate dust temperatures and far-IR luminosities. Assuming an emissivity index of beta = 1.5, we find a median dust temperature and far-IR luminosity of Td = 42.8+-7.1K and log(Lfir/Lsolar) = 12.2+-0.5, respectively. The far-IR/radio correlation observed in local star-forming galaxies is found to hold for ULIRGs in the redshift range 0.1 < z < 0.5, suggesting that the dust in these sources is predominantly heated by starbursts. We compare the far-IR luminosities and dust temperatures derived for dusty galaxy samples at low and high redshifts with our sample of ULIRGs at intermediate redshift. A general Lfir-Td relation is observed, albeit with significant scatter, due to differing selection effects and variations in dust mass and grain properties. The relatively high dust temperatures observed for our sample compared to that of high-z submillimeter-selected starbursts with similar far-IR luminosities suggest that the dominant star formation in ULIRGs at moderate redshifts takes place on smaller spatial scales than at higher redshifts.Comment: (24 pages in preprint format, 1 table, 7 figures, accepted for publication in ApJ

Cooperative emission of a pulse train in an optically thick scattering medium

An optically thick cold atomic cloud emits a coherent flash of light in the forward direction when the phase of an incident probe field is abruptly changed. Because of cooperativity, the duration of this phenomena can be much shorter than the excited lifetime of a single atom. Repeating periodically the abrupt phase jump, we generate a train of pulses with short repetition time, high intensity contrast and high efficiency. In this regime, the emission is fully governed by cooperativity even if the cloud is dilute.Comment: 5 pages, 3 figure

A self-learning particle swarm optimizer for global optimization problems

Copyright @ 2011 IEEE. All Rights Reserved. This article was made available through the Brunel Open Access Publishing Fund.Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex situations. This paper presents a novel algorithm, called self-learning particle swarm optimizer (SLPSO), for global optimization problems. In SLPSO, each particle has a set of four strategies to cope with different situations in the search space. The cooperation of the four strategies is implemented by an adaptive learning framework at the individual level, which can enable a particle to choose the optimal strategy according to its own local fitness landscape. The experimental study on a set of 45 test functions and two real-world problems show that SLPSO has a superior performance in comparison with several other peer algorithms.This work was supported by the Engineering and Physical Sciences Research Council of U.K. under Grants EP/E060722/1 and EP/E060722/2

The infrared conductivity of Nax_xCoO2_2: evidence of gapped states

We present infrared ab-plane conductivity data for the layered cobaltate Na$_x$CoO$_2$ at three different doping levels ($x=0.25, 0.50$, and 0.75). The Drude weight increases monotonically with hole doping, $1-x$. At the lowest hole doping level $x$=0.75 the system resembles the normal state of underdoped cuprate superconductors with a scattering rate that varies linearly with frequency and temperature and there is an onset of scattering by a bosonic mode at 600 \cm. Two higher hole doped samples ($x=0.50$ and 0.25) show two different-size gaps (110 \cm and 200 \cm, respectively) in the optical conductivities at low temperatures and become insulators. The spectral weights lost in the gap region of 0.50 and 0.25 samples are shifted to prominent peaks at 200 \cm and 800 \cm, respectively. We propose that the two gapped states of the two higher hole doped samples ($x$=0.50 and 0.25) are pinned charge ordered states.Comment: 4 pages, 3 figure

Transient analysis using conical shell elements

The use of the NASTRAN conical shell element in static, eigenvalue, and direct transient analyses is demonstrated. The results of a NASTRAN static solution of an externally pressurized ring-stiffened cylinder agree well with a theoretical discontinuity analysis. Good agreement is also obtained between the NASTRAN direct transient response of a uniform cylinder to a dynamic end load and one-dimensional solutions obtained using a method of characteristics stress wave code and a standing wave solution. Finally, a NASTRAN eigenvalue analysis is performed on a hydroballistic model idealized with conical shell elements

Rainfall frequency analysis for ungauged regions using remotely sensed precipitation information

Rainfall frequency analysis, which is an important tool in hydrologic engineering, has been traditionally performed using information from gauge observations. This approach has proven to be a useful tool in planning and design for the regions where sufficient observational data are available. However, in many parts of the world where ground-based observations are sparse and limited in length, the effectiveness of statistical methods for such applications is highly limited. The sparse gauge networks over those regions, especially over remote areas and high-elevation regions, cannot represent the spatiotemporal variability of extreme rainfall events and hence preclude developing depth-duration-frequency curves (DDF) for rainfall frequency analysis. In this study, the PERSIANN-CDR dataset is used to propose a mechanism, by which satellite precipitation information could be used for rainfall frequency analysis and development of DDF curves. In the proposed framework, we first adjust the extreme precipitation time series estimated by PERSIANN-CDR using an elevation-based correction function, then use the adjusted dataset to develop DDF curves. As a proof of concept, we have implemented our proposed approach in 20 river basins in the United States with different climatic conditions and elevations. Bias adjustment results indicate that the correction model can significantly reduce the biases in PERSIANN-CDR estimates of annual maximum series, especially for high elevation regions. Comparison of the extracted DDF curves from both the original and adjusted PERSIANN-CDR data with the reported DDF curves from NOAA Atlas 14 shows that the extreme percentiles from the corrected PERSIANN-CDR are consistently closer to the gauge-based estimates at the tested basins. The median relative errors of the frequency estimates at the studied basins were less than 20% in most cases. Our proposed framework has the potential for constructing DDF curves for regions with limited or sparse gauge-based observations using remotely sensed precipitation information, and the spatiotemporal resolution of the adjusted PERSIANN-CDR data provides valuable information for various applications in remote and high elevation areas