Single transverse-spin asymmetry in Drell-Yan lepton angular distribution

We calculate a single transverse-spin asymmetry for the Drell-Yan lepton-pair's angular distribution in perturbative QCD. At leading order in the strong coupling constant, the asymmetry is expressed in terms of a twist-3 quark-gluon correlation function T_F^{(V)}(x_1,x_2). In our calculation, the same result was obtained in both light-cone and covariant gauge in QCD, while keeping explicit electromagnetic current conservation for the virtual photon that decays into the lepton pair. We also present a numerical estimate of the asymmetry and compare the result to an existing other prediction.Comment: 15 pages, Revtex, 5 Postscript figures, uses aps.sty, epsfig.st

Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research

Aerodynamic performance of a free-flying dragonfly—A span-resolved investigation

We present a quantitative characterization of the unsteady aerodynamic features of a live, free-flying dragonfly under a well-established flight condition. In particular, our investigations cover the span-wise features of vortex interactions between the fore- and hind-pairs of wings that could be a distinctive feature of a high aspect ratio tandem flapping wing pair. Flapping kinematics and dynamic wing-shape deformation of a dragonfly were measured by tracking painted landmarks on the wings. Using it as the input, computational fluid dynamics analyses were conducted, complemented with time-resolved particle image velocimetry flow measurements to better understand the aerodynamics associated with a dragonfly. The results show that the flow structures around hindwing’s inner region are influenced by forewing’s leading edge vortex, while those around hindwing’s outer region are more influenced by forewing’s shed trailing edge vortex. Using a span-resolved approach, we found that the forewing–hindwing interactions affect the horizontal force (thrust) generation of the hindwing most prominently and the modulation of the force generation is distributed evenly around the midspan. Compared to operating in isolation, the thrust of the hindwing is largely increased during upstroke, albeit the drag is also slightly increased during the downstroke. The vertical force generation is moderately affected by the forewing–hindwing interactions and the modulation takes place in the outer 40% of the hindwing span during the downstroke and in the inner 60% of the span during the upstroke

Using Stacked Sparse Auto-Encoder and Superpixel CRF for Long-Term Visual Scene Understanding of UGVs

Multiple images have been widely used for scene understanding and navigation of unmanned ground vehicles in long term operations. However, as the amount of visual data in multiple images is huge, the cumulative error in many cases becomes untenable. This paper proposes a novel method that can extract features from a large dataset of multiple images efficiently. Then the membership K-means clustering is used for high dimensional features, and the large dataset is divided into N subdatasets to train N conditional random field (CRF) models based on superpixel. A Softmax subdataset selector is used to decide which one of the N CRF models is chosen as the prediction model for labeling images. Furthermore, some experiments are conducted to evaluate the feasibility and performance of the proposed approach

An increase in TcT_c under hydrostatic pressure in the superconducting doped topological insulator Nb0.25_{0.25}Bi2_2Se3_3

We report an unexpected positive hydrostatic pressure derivative of the superconducting transition temperature in the doped topological insulator \NBS via $dc$ SQUID magnetometry in pressures up to 0.6 GPa. This result is contrary to reports on the homologues \CBS and \SBS where smooth suppression of $T_c$ is observed. Our results are consistent with recent Ginzburg-Landau theory predictions of a pressure-induced enhancement of $T_c$ in the nematic multicomponent $E_u$ state proposed to explain observations of rotational symmetry breaking in doped Bi$_2$Se$_3$ superconductors.Comment: 5 pages, 5 figure

On the contribution of twist-3 multi-gluon correlation functions to single transverse-spin asymmetry in SIDIS

We study the single spin asymmetry (SSA) induced by purely gluonic correlation inside a nucleon, in particular, by the three-gluon correlation functions in the transversely polarized nucleon, $p^\uparrow$. This contribution is embodied as a twist-3 mechanism in the collinear factorization framework and controls the SSA to be observed in the $D$-meson production with large transverse-momentum in semi-inclusive DIS (SIDIS), $ep^\uparrow \rightarrow eDX$. We define the relevant three-gluon correlation functions in the nucleon, and determine their complete set at the twsit-3 level taking into account symmetry constraints in QCD. We derive the single-spin-dependent cross section for the $D$-meson production in SIDIS, taking into account all the relevant contributions at the twist-3 level. The result is obtained in a manifestly gauge-invariant form as the factorization formula in terms of the three-gluon correlation functions and reveals the five independent structures with respect to the dependence on the azimuthal angle for the produced $D$ meson. We also demonstrate the remarkable relation between the twist-3 single-spin-dependent cross section and twist-2 cross sections for the $D$-meson production, as a manifestation of universal structure behind the SSA in a variety of hard processes.Comment: 8 pages, 2 figures. To appear in the proceedings of the 19th International Spin Physics Symposium (SPIN2010), Juelich, Germany, Sept.27 - Oct.2, 201

The structures of Hausdorff metric in non-Archimedean spaces

For non-Archimedean spaces $X$ and $Y,$ let $\mathcal{M}_{\flat } (X), \mathfrak{M}(V \rightarrow W)$ and $\mathfrak{D}_{\flat }(X, Y)$ be the ballean of $X$ (the family of the balls in $X$), the space of mappings from $X$ to $Y,$ and the space of mappings from the ballen of $X$ to $Y,$ respectively. By studying explicitly the Hausdorff metric structures related to these spaces, we construct several families of new metric structures (e.g., $\widehat{\rho } _{u}, \widehat{\beta }_{X, Y}^{\lambda }, \widehat{\beta }_{X, Y}^{\ast \lambda }$) on the corresponding spaces, and study their convergence, structural relation, law of variation in the variable $\lambda,$ including some normed algebra structure. To some extent, the class $\widehat{\beta }_{X, Y}^{\lambda }$ is a counterpart of the usual Levy-Prohorov metric in the probability measure spaces, but it behaves very differently, and is interesting in itself. Moreover, when $X$ is compact and $Y = K$ is a complete non-Archimedean field, we construct and study a Dudly type metric of the space of $K-$valued measures on $X.$Comment: 43 pages; this is the final version. Thanks to the anonymous referee's helpful comments, the original Theorem 2.10 is removed, Proposition 2.10 is stated now in a stronger form, the abstact is rewritten, the Monna-Springer is used in Section 5, and Theorem 5.2 is written in a more general for

Minimum-error discrimination between mixed quantum states

We derive a general lower bound on the minimum-error probability for {\it ambiguous discrimination} between arbitrary $m$ mixed quantum states with given prior probabilities. When $m=2$, this bound is precisely the well-known Helstrom limit. Also, we give a general lower bound on the minimum-error probability for discriminating quantum operations. Then we further analyze how this lower bound is attainable for ambiguous discrimination of mixed quantum states by presenting necessary and sufficient conditions related to it. Furthermore, with a restricted condition, we work out a upper bound on the minimum-error probability for ambiguous discrimination of mixed quantum states. Therefore, some sufficient conditions are obtained for the minimum-error probability attaining this bound. Finally, under the condition of the minimum-error probability attaining this bound, we compare the minimum-error probability for {\it ambiguously} discriminating arbitrary $m$ mixed quantum states with the optimal failure probability for {\it unambiguously} discriminating the same states.Comment: A further revised version, and some results have been adde