297,724 research outputs found
Possible and Molecular states in a chiral quark model
We perform a systematic study of the bound state problem of and
systems by using effective interaction in our chiral quark model.
Our results show that both the interactions of and states
are attractive, which consequently result in
and bound states.Comment: arXiv admin note: substantial text overlap with arXiv:1204.395
Orthogonal learning particle swarm optimization
Particle swarm optimization (PSO) relies on its
learning strategy to guide its search direction. Traditionally,
each particle utilizes its historical best experience and its neighborhood’s
best experience through linear summation. Such a
learning strategy is easy to use, but is inefficient when searching
in complex problem spaces. Hence, designing learning strategies
that can utilize previous search information (experience) more
efficiently has become one of the most salient and active PSO
research topics. In this paper, we proposes an orthogonal learning
(OL) strategy for PSO to discover more useful information that
lies in the above two experiences via orthogonal experimental
design. We name this PSO as orthogonal learning particle swarm
optimization (OLPSO). The OL strategy can guide particles to
fly in better directions by constructing a much promising and
efficient exemplar. The OL strategy can be applied to PSO with
any topological structure. In this paper, it is applied to both global
and local versions of PSO, yielding the OLPSO-G and OLPSOL
algorithms, respectively. This new learning strategy and the
new algorithms are tested on a set of 16 benchmark functions, and
are compared with other PSO algorithms and some state of the
art evolutionary algorithms. The experimental results illustrate
the effectiveness and efficiency of the proposed learning strategy
and algorithms. The comparisons show that OLPSO significantly
improves the performance of PSO, offering faster global convergence,
higher solution quality, and stronger robustness
Tuning electronic structure of graphene via tailoring structure: theoretical study
Electronic structures of graphene sheet with different defective patterns are
investigated, based on the first principles calculations. We find that
defective patterns can tune the electronic structures of the graphene
significantly. Triangle patterns give rise to strongly localized states near
the Fermi level, and hexagonal patterns open up band gaps in the systems. In
addition, rectangular patterns, which feature networks of graphene nanoribbons
with either zigzag or armchair edges, exhibit semiconducting behaviors, where
the band gap has an evident dependence on the width of the nanoribbons. For the
networks of the graphene nanoribbons, some special channels for electronic
transport are predicted.Comment: 5 figures, 6 page
Yang-Mills condensate dark energy coupled with matter and radiation
The coincidence problem is studied for the dark energy model of effective
Yang-Mills condensate in a flat expanding universe during the matter-dominated
stage. The YMC energy is taken to represent the dark energy, which
is coupled either with the matter, or with both the matter and the radiation
components. The effective YM Lagrangian is completely determined by quantum
field theory up to 1-loop order. It is found that under very generic initial
conditions and for a variety of forms of coupling, the existence of the scaling
solution during the early stages and the subsequent exit from the scaling
regime are inevitable. The transition to the accelerating stage always occurs
around a redshift . Moreover, when the Yang-Mills
condensate transfers energy into matter or into both matter and radiation, the
equation of state of the Yang-Mills condensate can cross over -1 around
, and takes on a current value . This is consistent with
the recent preliminary observations on supernovae Ia. Therefore, the
coincidence problem can be naturally solved in the effective YMC dark energy
models.Comment: 24 pages, 18 figure
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