Transversity from two pion interference fragmentation

We present calculation on the azimuthal spin asymmetries for pion pair production in semi-inclusive deep inelastic scattering (SIDIS) process at both HERMES and COMPASS kinematics, with transversely polarized proton, deuteron and neutron targets. We calculate the asymmetry by adopting a set of parametrization of the interference fragmentation functions and two different models for the transversity. We find that the result for the proton target is insensitive to the approaches of the transversity but more helpful to understand the interference fragmentation functions. However, for the neutron target, which can be obtained through using deuteron and {$^3$He} targets, we find different predictions for different approaches to the transversity. Thus probing the two pion interference fragmentation from the neutron can provide us more interesting information on the transversity.Comment: 15 latex pages, 6 figures, to appear in PR

Outlier Detection Using Nonconvex Penalized Regression

This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the $n$ data points. We then apply a regularization favoring a sparse vector of mean shift parameters. The usual $L_1$ penalty yields a convex criterion, but we find that it fails to deliver a robust estimator. The $L_1$ penalty corresponds to soft thresholding. We introduce a thresholding (denoted by $\Theta$) based iterative procedure for outlier detection ($\Theta$-IPOD). A version based on hard thresholding correctly identifies outliers on some hard test problems. We find that $\Theta$-IPOD is much faster than iteratively reweighted least squares for large data because each iteration costs at most $O(np)$ (and sometimes much less) avoiding an $O(np^2)$ least squares estimate. We describe the connection between $\Theta$-IPOD and $M$-estimators. Our proposed method has one tuning parameter with which to both identify outliers and estimate regression coefficients. A data-dependent choice can be made based on BIC. The tuned $\Theta$-IPOD shows outstanding performance in identifying outliers in various situations in comparison to other existing approaches. This methodology extends to high-dimensional modeling with $p\gg n$, if both the coefficient vector and the outlier pattern are sparse

Terminal Proterozoic cyanobacterial blooms and phosphogenesis documented by the Doushantuo granular phosphorites II: Microbial diversity and C isotopes

An unprecedented period of phosphogenesis, along with massive deposition of black shales, major perturbations in the global carbon cycle and the rise of atmospheric oxygen, occurred in the terminal Proterozoic in the aftermath of the Marinoan glaciation. Although causal links between these processes have been postulated, evidence remains challenging. Correlated in situ micro-analyses of granular phosphorites from the Ediacaran Doushantuo Formation in Yichang, South China, suggested that cyanobacteria and associated extracellular polymeric substances (EPS) might have promoted aggregated granule growth and subsequent phosphatization (She et al., 2013). Here, we present new paleontological data for the Doushantuo phosphorites from Yichang, which, combined with Raman microspectroscopy and carbon isotope data, further document links between the biology of cyanobacteria and phosphogenesis. Mapping of microfossils in thin section shows that most phosphatic granules contain microfossils that are dominated by colonies of Myxococcoides, along with several filamentous genera generally considered to represent cyanobacterial sheaths. In addition, the phosphorites and associated rocks have δ13Corg values in the range of −26.0 to −29.7‰ VPDB, consistent with photoautotrophic carbon fixation with the Rubisco enzyme. Close association of phosphorites with the Marinoan tillites in stratigraphic level supports a genetic link between deglaciation and phosphogenesis, at least for the Doushantuo occurrence. Our new data suggest that major cyanobacterial blooms probably took place in the terminal Proterozoic, which might have resulted in rapid scavenging of bioavailable phosphorus and massive accumulations of organic matter (OM). Within a redox-stratified intra-shelf basin, the OM-bound phosphorus could have liberated by microbial sulfate reduction and other anaerobic metabolisms and subsequently concentrated by Fe-redox pumping below the chemocline. Upwelling of the bottom waters or upward fluctuation of the chemocline might have brought P-enriched waters to the photic zone, where it was again scavenged by cyanobacteria through their EPS to be subsequently precipitated as francolite. The feedbacks between enhanced continental weathering, cyanobacterial blooms, carbon burial, and accelerated phosphorus cycle thus controlled the marine biogeochemical changes, which led to further oxygenation of the atmosphere and oceans, ultimately paving the way for the rise of metazoans

A Model-Free Sampling Method for Estimating Basins of Attraction Using Hybrid Active Learning (HAL)

Understanding the basins of attraction (BoA) is often a paramount consideration for nonlinear systems. Most existing approaches to determining a high-resolution BoA require prior knowledge of the system's dynamical model (e.g., differential equation or point mapping for continuous systems, cell mapping for discrete systems, etc.), which allows derivation of approximate analytical solutions or parallel computing on a multi-core computer to find the BoA efficiently. However, these methods are typically impractical when the BoA must be determined experimentally or when the system's model is unknown. This paper introduces a model-free sampling method for BoA. The proposed method is based upon hybrid active learning (HAL) and is designed to find and label the "informative" samples, which efficiently determine the boundary of BoA. It consists of three primary parts: 1) additional sampling on trajectories (AST) to maximize the number of samples obtained from each simulation or experiment; 2) an active learning (AL) algorithm to exploit the local boundary of BoA; and 3) a density-based sampling (DBS) method to explore the global boundary of BoA. An example of estimating the BoA for a bistable nonlinear system is presented to show the high efficiency of our HAL sampling method.Comment: Update: 1) add the schematic of the magnet-induced bistable system, 2) emphasize that the proposed method can be implemented when the system's model is unknown. 6 pages, 5 figures, 2 table

On the dynamics of a self-gravitating medium with random and non-random initial conditions

The dynamics of a one-dimensional self-gravitating medium, with initial density almost uniform is studied. Numerical experiments are performed with ordered and with Gaussian random initial conditions. The phase space portraits are shown to be qualitatively similar to shock waves, in particular with initial conditions of Brownian type. The PDF of the mass distribution is investigated.Comment: Latex, figures in eps, 23 pages, 11 figures. Revised versio

Handling dropout probability estimation in convolution neural networks using meta-heuristics

Deep learning-based approaches have been paramount in recent years, mainly due to their outstanding results in several application domains, ranging from face and object recognition to handwritten digit identification. Convolutional Neural Networks (CNN) have attracted a considerable attention since they model the intrinsic and complex brain working mechanisms. However, one main shortcoming of such models concerns their overfitting problem, which prevents the network from predicting unseen data effectively. In this paper, we address this problem by means of properly selecting a regularization parameter known as Dropout in the context of CNNs using meta-heuristic-driven techniques. As far as we know, this is the first attempt to tackle this issue using this methodology. Additionally, we also take into account a default dropout parameter and a dropout-less CNN for comparison purposes. The results revealed that optimizing Dropout-based CNNs is worthwhile, mainly due to the easiness in finding suitable dropout probability values, without needing to set new parameters empirically

Coincident extremely large sporadic sodium and sporadic E layers observed in the lower thermosphere over Colorado and Utah

International audienceOn the night of 2 June 2002, the sodium lidar in Fort Collins, CO (40.6 N, 105 W) measured an extremely strong sporadic sodium layer lasting from 03:30 to 05:00 UT with several weaker layers later in the night at 06:00 and 09:00 UT. There is a double layer structure with peaks at 101 and 104 km. The peak sodium density was 21 000 atoms/cm3 with a column abundance of up to twice that of the normal sodium layer. The peak density was 500 times greater than the typical density at that altitude. The sporadic layer abundance and strength factor were higher than any reported in the literature. The two lidar beams, separated by 70 km at this altitude, both measured 0.6 h periodicities in the abundance, but out of phase with each other by 0.3 h. There is also evidence for strong wave activity in the lidar temperatures and winds. The NOAA ionosonde in Boulder, CO (40.0 N, 105 W) measured a critical frequency (foEs) of 14.3 MHz at 03:00 UT on this night, the highest value anytime during 2002. The high values of total ion density inferred means that Na+ fraction must have been only a few percent to explain the neutral Na layer abundances. The Bear Lake, Utah (41.9 N, 111.4 W) dynasonde also measured intense Es between 02:00 and 05:00 UT and again from 06:00 to 08:00 UT about 700 km west of the lidar, with most of the ionograms during these intervals measuring Es up to 12 MHz, the limit of the ionosonde sweep. Other ionosondes around North America on the NGDC database measured normal foEs values that night, so it was a localized event within North America. The peak of Es activity observed in Europe during the summer of 2002 occurred on 4 June. The observations are consistent with the current theories where a combination of wind shears and long period waves form and push downward a concentrated layer of ions, which then chemically react and form a narrow layer of sodium atoms