7,037 research outputs found
Chiral anomaly and anomalous finite-size conductivity in graphene
Graphene is a monolayer of carbon atoms packed into a hexagon lattice to host
two pairs of massless two-dimensional Dirac fermions in the absence of or with
negligible spin-orbit coupling. It is known that the existence of non-zero
electric polarization in reduced momentum space which is associated with a
hidden chiral symmetry will lead to the zero-energy flat band of zigzag
nanoribbon. The Adler-Bell-Jackiw chiral anomaly or non-conservation of chiral
charges at different valleys can be realized in a confined ribbon of finite
width. In the laterally diffusive regime, the finite-size correction to
conductivity is always positive and goes inversely with the square of the
lateral dimension W, which is different from the finite-size correction
inversely with W from boundary modes. This anomalous finite-size conductivity
reveals the signature of the chiral anomaly in graphene, and is measurable
experimentally.Comment: 5 pages, 2 figure
Improving Variational Encoder-Decoders in Dialogue Generation
Variational encoder-decoders (VEDs) have shown promising results in dialogue
generation. However, the latent variable distributions are usually approximated
by a much simpler model than the powerful RNN structure used for encoding and
decoding, yielding the KL-vanishing problem and inconsistent training
objective. In this paper, we separate the training step into two phases: The
first phase learns to autoencode discrete texts into continuous embeddings,
from which the second phase learns to generalize latent representations by
reconstructing the encoded embedding. In this case, latent variables are
sampled by transforming Gaussian noise through multi-layer perceptrons and are
trained with a separate VED model, which has the potential of realizing a much
more flexible distribution. We compare our model with current popular models
and the experiment demonstrates substantial improvement in both metric-based
and human evaluations.Comment: Accepted by AAAI201
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