44,912 research outputs found
Non-dipolar gauge links for transverse-momentum-dependent pion wave functions
I discuss the factorization-compatible definitions of
transverse-momentum-dependent (TMD) pion wave functions which are fundamental
theory inputs entering QCD factorization formulae for many hard exclusive
processes. I will first demonstrate that the soft subtraction factor introduced
to remove both rapidity and pinch singularities can be greatly reduced by
making the maximal use of the freedom to construct the Wilson-line paths when
defining the TMD wave functions. I will then turn to show that the newly
proposed TMD definition with non-dipolar Wilson lines is equivalent to the one
with dipolar gauge links and with a complicated soft function, to all orders of
the perturbative expansion in the strong coupling, as far as the infrared
behavior is concerned.Comment: 7 pages, 3 figure
Factorization, resummation and sum rules for heavy-to-light form factors
Precision calculations of heavy-to-light form factors are essential to
sharpen our understanding towards the strong interaction dynamics of the
heavy-quark system and to shed light on a coherent solution of flavor
anomalies. We briefly review factorization properties of heavy-to-light form
factors in the framework of QCD factorization in the heavy quark limit and
discuss the recent progress on the QCD calculation of form factors
from the light-cone sum rules with the -meson distribution amplitudes.
Demonstration of QCD factorization for the vacuum-to--meson correlation
function used in the sum-rule construction and resummation of large logarithms
in the short-distance functions entering the factorization theorem are
presented in detail. Phenomenological implications of the newly derived sum
rules for form factors are further addressed with a particular
attention to the extraction of the CKM matrix element .Comment: 6 pages, 3 figures, proceedings prepared for the "QCD@work 2016",
(27-30 June 2016, Martina Franca, Italy
Res2Net: A New Multi-scale Backbone Architecture
Representing features at multiple scales is of great importance for numerous
vision tasks. Recent advances in backbone convolutional neural networks (CNNs)
continually demonstrate stronger multi-scale representation ability, leading to
consistent performance gains on a wide range of applications. However, most
existing methods represent the multi-scale features in a layer-wise manner. In
this paper, we propose a novel building block for CNNs, namely Res2Net, by
constructing hierarchical residual-like connections within one single residual
block. The Res2Net represents multi-scale features at a granular level and
increases the range of receptive fields for each network layer. The proposed
Res2Net block can be plugged into the state-of-the-art backbone CNN models,
e.g., ResNet, ResNeXt, and DLA. We evaluate the Res2Net block on all these
models and demonstrate consistent performance gains over baseline models on
widely-used datasets, e.g., CIFAR-100 and ImageNet. Further ablation studies
and experimental results on representative computer vision tasks, i.e., object
detection, class activation mapping, and salient object detection, further
verify the superiority of the Res2Net over the state-of-the-art baseline
methods. The source code and trained models are available on
https://mmcheng.net/res2net/.Comment: 11 pages, 7 figure
Batalin-Vilkovisky structure over the Hochschild cohomology ring of a group algebra
We realize explicitly the well-known additive decomposition of the Hochschild
cohomology ring of a group algebra in the elements level. As a result, we
describe the cup product, the Batalin-Vilkovisky operator and the Lie bracket
in the Hochschild cohomology ring of a group algebra.Comment: This paper uses a Maple program which is avaible at
http://math.bnu.edu.cn/~liuym
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