248,206 research outputs found
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
Structure propagation for zero-shot learning
The key of zero-shot learning (ZSL) is how to find the information transfer
model for bridging the gap between images and semantic information (texts or
attributes). Existing ZSL methods usually construct the compatibility function
between images and class labels with the consideration of the relevance on the
semantic classes (the manifold structure of semantic classes). However, the
relationship of image classes (the manifold structure of image classes) is also
very important for the compatibility model construction. It is difficult to
capture the relationship among image classes due to unseen classes, so that the
manifold structure of image classes often is ignored in ZSL. To complement each
other between the manifold structure of image classes and that of semantic
classes information, we propose structure propagation (SP) for improving the
performance of ZSL for classification. SP can jointly consider the manifold
structure of image classes and that of semantic classes for approximating to
the intrinsic structure of object classes. Moreover, the SP can describe the
constrain condition between the compatibility function and these manifold
structures for balancing the influence of the structure propagation iteration.
The SP solution provides not only unseen class labels but also the relationship
of two manifold structures that encode the positive transfer in structure
propagation. Experimental results demonstrate that SP can attain the promising
results on the AwA, CUB, Dogs and SUN databases
A derivative formula for the free energy function
We consider bond percolation on the lattice. Let be the
number of open clusters in . It is well known that converges to the free energy function at the zero field.
In this paper, we show that converges to
.Comment: 8 pages 1 figur
Interacting Individuals Leading to Zipf's Law
We present a general approach to explain the Zipf's law of city distribution.
If the simplest interaction (pairwise) is assumed, individuals tend to form
cities in agreement with the well-known statisticsComment: 4 pages 2 figure
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