17,196 research outputs found
Associated production of the top-pions and single top at hadron colliders
In the context of topcolor assisted technicolor(TC2) models, we study the
production of the top-pions with single top quark via the
processes and ,
and discuss the possibility of detecting these new particles at Tevatron and
LHC. We find that it is very difficult to observe the signals of these
particles via these processes at Tevatron, while the neutral and charged
top-pions and can be detecting via considering
the same sign top pair event and the (or )
event at LHC, respectively.Comment: latex files,14 pages, 7 figures. Accepted for publication in Phys.
Rev.
Weiqi games as a tree: Zipf's law of openings and beyond
Weiqi is one of the most complex board games played by two persons. The
placement strategies adopted by Weiqi players are often used to analog the
philosophy of human wars. Contrary to the western chess, Weiqi games are less
studied by academics partially because Weiqi is popular only in East Asia,
especially in China, Japan and Korea. Here, we propose to construct a directed
tree using a database of extensive Weiqi games and perform a quantitative
analysis of the Weiqi tree. We find that the popularity distribution of Weiqi
openings with a same number of moves is distributed according to a power law
and the tail exponent increases with the number of moves. Intriguingly, the
superposition of the popularity distributions of Weiqi openings with the number
of moves no more than a given number also has a power-law tail in which the
tail exponent increases with the number of moves, and the superposed
distribution approaches to the Zipf law. These findings are the same as for
chess and support the conjecture that the popularity distribution of board game
openings follows the Zipf law with a universal exponent. We also find that the
distribution of out-degrees has a power-law form, the distribution of branching
ratios has a very complicated pattern, and the distribution of uniqueness
scores defined by the path lengths from the root vertex to the leaf vertices
exhibits a unimodal shape. Our work provides a promising direction for the
study of the decision making process of Weiqi playing from the angle of
directed branching tree.Comment: 6 Latex pages including 6 figure
The next-to-next-to-leading order soft function for top quark pair production
We present the first calculation of the next-to-next-to-leading order
threshold soft function for top quark pair production at hadron colliders, with
full velocity dependence of the massive top quarks. Our results are fully
analytic, and can be entirely written in terms of generalized polylogarithms.
The scale-dependence of our result coincides with the well-known two-loop
anomalous dimension matrix including the three-parton correlations, which at
the two-loop order only appear when more than one massive partons are involved
in the scattering process. In the boosted limit, our result exhibits the
expected factorization property of mass logarithms, which leads to a consistent
extraction of the soft fragmentation function. The next-to-next-to-leading
order soft function obtained in this paper is an important ingredient for
threshold resummation at the next-to-next-to-next-to-leading logarithmic
accuracy.Comment: 34 pages, 9 figures; v2: added references, matches the published
versio
ADMM Training Algorithms for Residual Networks: Convergence, Complexity and Parallel Training
We design a series of serial and parallel proximal point (gradient) ADMMs for
the fully connected residual networks (FCResNets) training problem by
introducing auxiliary variables. Convergence of the proximal point version is
proven based on a Kurdyka-Lojasiewicz (KL) property analysis framework, and we
can ensure a locally R-linear or sublinear convergence rate depending on the
different ranges of the Kurdyka-Lojasiewicz (KL) exponent, in which a necessary
auxiliary function is constructed to realize our goal. Moreover, the advantages
of the parallel implementation in terms of lower time complexity and less
(per-node) memory consumption are analyzed theoretically. To the best of our
knowledge, this is the first work analyzing the convergence, convergence rate,
time complexity and (per-node) runtime memory requirement of the ADMM applied
in the FCResNets training problem theoretically. Experiments are reported to
show the high speed, better performance, robustness and potential in the deep
network training tasks. Finally, we present the advantage and potential of our
parallel training in large-scale problems
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