A study of the correlations between jet quenching observables at RHIC

Focusing on four types of correlation plots, $R_{\rm AA}$ vs. $v_2$, $R_{\rm AA}$ vs. $I_{\rm AA}$, $I_{\rm AA}$ vs. $v_2^{I_{\rm AA}}$ and $v_2$ vs.\ $v_2^{I_{\rm AA}}$, we demonstrate how the centrality dependence of \emph{correlations} between multiple jet quenching observables provide valuable insight into the energy loss mechanism in a quark-gluon plasma. In particular we find that a qualitative energy loss model gives a good description of $R_{\rm AA}$ vs.\ $v_2$ only when we take $\Delta E\sim l^3$ and a medium geometry generated by a model of the Color Glass Condensate. This same $\Delta E\sim l^3$ model also qualitatively describes the trigger $p_T$ dependence of $R_{\rm AA}$ vs.\ $I_{\rm AA}$ data and makes novel predictions for the centrality dependence for this $R_{\rm AA}$ vs.\ $I_{\rm AA}$ correlation. Current data suggests, albeit with extremely large uncertainty, that $v_2^{I_{\rm AA}}\gg v_2$, a correlation that is difficult to reproduce in current energy loss models.Comment: 6 pages, 6 figure

Interaction of cosmic background neutrinos with matter of periodic structure

We study coherent interaction of cosmic background neutrinos(CBNs) with matter of periodic structure. The mixing and small masses of neutrinos discovered in neutrino oscillation experiments indicate that CBNs which have very low energy today should be in mass states and can transform from one mass state to another in interaction with electrons in matter. We show that in a coherent scattering process a periodic matter structure designed to match the scale of the mass square difference of neutrinos can enhance the conversion of CBNs from one mass state to another. Energy of CBNs can be released in this scattering process and momentum transfer from CBNs to electrons in target matter can be obtained.Comment: 6 pages, 5 figures, publication versio

Deep Learning for Single Image Super-Resolution: A Brief Review

Single image super-resolution (SISR) is a notoriously challenging ill-posed problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions. To solve the SISR problem, recently powerful deep learning algorithms have been employed and achieved the state-of-the-art performance. In this survey, we review representative deep learning-based SISR methods, and group them into two categories according to their major contributions to two essential aspects of SISR: the exploration of efficient neural network architectures for SISR, and the development of effective optimization objectives for deep SISR learning. For each category, a baseline is firstly established and several critical limitations of the baseline are summarized. Then representative works on overcoming these limitations are presented based on their original contents as well as our critical understandings and analyses, and relevant comparisons are conducted from a variety of perspectives. Finally we conclude this review with some vital current challenges and future trends in SISR leveraging deep learning algorithms.Comment: Accepted by IEEE Transactions on Multimedia (TMM

Space Charge Behaviour in Oil-Paper Insulation with Different Aging Condition

Oil-paper insulation system is widely used in power transformers and cables. The dielectric properties of oilpaper insulation play an important role in the reliable operation of power equipment. Oil-paper insulation degrades under a combined stress of thermal (the most important factor), electrical, mechanical, and chemical stresses during routine operations, which has great effect on the dielectric properties of oil-paper insulation [1]. Space charge in oil-paper insulation has a close relation to its electrical performance [1]. In this paper, space charge behaviour of oil-paper insulation sample with three different ageing conditions (aged for 0, 35 and 77 days) was investigated using the pulsed electroacoustic (PEA) technique. The influence of aging on the space charge dynamics behaviour was analysed. Results show that aging has great effect on the space charge dynamics of oil-paper insulation. The homocharge injection takes place under all three aging conditions above. Positive charges tend to accumulate in the sample, and increase with the oil-paper insulation sample deterioration. The time to achieve the maximum injection charge density is 30s, 2min and 10min for oil-paper insulation sample aged for 0, 35 and 77 days, respectively. The maximum charge density injected in the sample aged for 77 days is more than two times larger than the initial sample. In addition, the charge decay speed becomes much slower with the aging time increase. There is an exponential relationship between the total charge amount and the decay time. The decay time constant ? increases with the increasing deterioration condition of the oil-paper insulation sample. The ? value may be used to reflect the aging status of oil-paper insulation

Gravitational Thermodynamics of Space-time Foam in One-loop Approximation

We show from one-loop quantum gravity and statistical thermodynamics that the thermodynamics of quantum foam in flat space-time and Schwarzschild space-time is exactly the same as that of Hawking-Unruh radiation in thermal equilibrium. This means we show unambiguously that Hawking-Unruh thermal radiation should contain thermal gravitons or the contribution of quantum space-time foam. As a by-product, we give also the quantum gravity correction in one-loop approximation to the classical black hole thermodynamics.Comment: 7 pages, revte

Non-standard interactions of solar neutrinos in dark matter experiments

Non-standard neutrino interactions (NSI) affect both their propagation through matter and their detection, with bounds on NSI parameters coming from various astrophysical and terrestrial neutrino experiments. In this paper, we show that NSI can be probed in future direct dark matter detection experiments through both elastic neutrino-electron scattering and coherent neutrino-nucleus scattering, and that these channels provide complementary probes of NSI. We show NSI can increase the event rate due to solar neutrinos, with a sharp increase for lower nuclear recoil energy thresholds that are within reach for upcoming detectors. We also identify an interference range of NSI parameters for which the rate is reduced by approximately 40\%. Finally, we show that the "dark side" solution for the solar neutrino mixing angle may be discovered at forthcoming direct detection experiments.Comment: 12 pages, 5 figure

Representation of SO(3) Group by a Maximally Entangled State

A representation of the SO(3) group is mapped into a maximally entangled two qubit state according to literatures. To show the evolution of the entangled state, a model is set up on an maximally entangled electron pair, two electrons of which pass independently through a rotating magnetic field. It is found that the evolution path of the entangled state in the SO(3) sphere breaks an odd or even number of times, corresponding to the double connectedness of the SO(3) group. An odd number of breaks leads to an additional $\pi$ phase to the entangled state, but an even number of breaks does not. A scheme to trace the evolution of the entangled state is proposed by means of entangled photon pairs and Kerr medium, allowing observation of the additional $\pi$ phase.Comment: 4 pages, 3 figure

1-D Air-snowpack modeling of atmospheric nitrous acid at South Pole during ANTCI 2003

A 1-D air-snowpack model of HONO has been developed and constrained by observed chemistry and meteorology data. The 1-D model includes molecular diffusion and mechanical dispersion, windpumping in snow, gas phase to quasi-liquid layer phase HONO transfer and quasi-liquid layer nitrate and interstitial air HONO photolysis. Photolysis of nitrate is important as a dominant HONO source inside the snowpack, however, the observed HONO emission from the snowpack was triggered mainly by the equilibrium between quasi liquid layer nitrite and firn air HONO deep down the snow surface (i.e. 30 cm below snow surface). The high concentration of HONO in the firn air is subsequently transported above the snowpack by diffusion and windpumping. The model uncertainties come mainly from lack of measurements and the interpretation of the QLL properties based on the bulk snow measurements. One critical factor is the ionic strength of QLL nitrite, which is estimated here by the bulk snow pH, nitrite concentration, and QLL to bulk snow volume ratio

A transient plasticity study and low cycle fatigue analysis of the Space Station Freedom photovoltaic solar array blanket

The Space Station Freedom photovoltaic solar array blanket assembly is comprised of several layers of materials having dissimilar elastic, thermal, and mechanical properties. The operating temperature of the solar array, which ranges from -75 to +60 C, along with the material incompatibility of the blanket assembly components combine to cause an elastic-plastic stress in the weld points of the assembly. The weld points are secondary structures in nature, merely serving as electrical junctions for gathering the current. The thermal mechanical loading of the blanket assembly operating in low earth orbit continually changes throughout each 90 min orbit, which raises the possibility of fatigue induced failure. A series of structural analyses were performed in an attempt to predict the fatigue life of the solar cell in the Space Station Freedom photovoltaic array blanket. A nonlinear elastic-plastic MSC/NASTRAN analysis followed by a fatigue calculation indicated a fatigue life of 92,000 to 160,000 cycles for the solar cell weld tabs. Additional analyses predict a permanent buckling phenomenon in the copper interconnect after the first loading cycle. This should reduce or eliminate the pulling of the copper interconnect on the joint where it is welded to the silicon solar cell. It is concluded that the actual fatigue life of the solar array blanket assembly should be significantly higher than the calculated 92,000 cycles, and thus the program requirement of 87,500 cycles (orbits) will be met. Another important conclusion that can be drawn from the overall analysis is that, the strain results obtained from the MSC/NASTRAN nonlinear module are accurate to use for low-cycle fatigue analysis, since both thermal cycle testing of solar cells and analysis have shown higher fatigue life than the minimum program requirement of 87,500 cycles

Coherence-Pattern Guided Compressive Sensing with Unresolved Grids

Highly coherent sensing matrices arise in discretization of continuum imaging problems such as radar and medical imaging when the grid spacing is below the Rayleigh threshold. Algorithms based on techniques of band exclusion (BE) and local optimization (LO) are proposed to deal with such coherent sensing matrices. These techniques are embedded in the existing compressed sensing algorithms such as Orthogonal Matching Pursuit (OMP), Subspace Pursuit (SP), Iterative Hard Thresholding (IHT), Basis Pursuit (BP) and Lasso, and result in the modified algorithms BLOOMP, BLOSP, BLOIHT, BP-BLOT and Lasso-BLOT, respectively. Under appropriate conditions, it is proved that BLOOMP can reconstruct sparse, widely separated objects up to one Rayleigh length in the Bottleneck distance {\em independent} of the grid spacing. One of the most distinguishing attributes of BLOOMP is its capability of dealing with large dynamic ranges. The BLO-based algorithms are systematically tested with respect to four performance metrics: dynamic range, noise stability, sparsity and resolution. With respect to dynamic range and noise stability, BLOOMP is the best performer. With respect to sparsity, BLOOMP is the best performer for high dynamic range while for dynamic range near unity BP-BLOT and Lasso-BLOT with the optimized regularization parameter have the best performance. In the noiseless case, BP-BLOT has the highest resolving power up to certain dynamic range. The algorithms BLOSP and BLOIHT are good alternatives to BLOOMP and BP/Lasso-BLOT: they are faster than both BLOOMP and BP/Lasso-BLOT and shares, to a lesser degree, BLOOMP's amazing attribute with respect to dynamic range. Detailed comparisons with existing algorithms such as Spectral Iterative Hard Thresholding (SIHT) and the frame-adapted BP are given