7,542 research outputs found
Di-neutron correlation and soft dipole excitation in medium mass neutron-rich nuclei near drip-line
The neutron pairing correlation and the soft dipole excitation in medium-mass
nuclei near drip-line are investigated from a viewpoint of the di-neutron
correlation. Numerical analyses by means of the coordinate-space HFB and the
continuum QRPA methods are performed for even-even O, Ca
and Ni. A clear signature of the di-neutron correlation is found in
the HFB ground state; two neutrons are correlated at short relative distances
\lesim 2 fm with large probability . The soft dipole excitation is
influenced strongly by the neutron pairing correlation, and it accompanies a
large transition density for pair motion of neutrons. This behavior originates
from a coherent superposition of two-quasiparticle configurations consisting of continuum states with high orbital angular momenta
reaching an order of . It raises a picture that the soft dipole
excitation under the influence of neutron pairing is characterized by motion of
di-neutron in the nuclear exterior against the remaining subsystem.
Sensitivity to the density dependence of effective pair force is discussed.Comment: 35 pages, 22 figure
Quantum Nernst effect in a bismuth single crystal
We report a theoretical calculation explaining the quantum Nernst effect
observed experimentally in a bismuth single crystal. Generalizing the
edge-current picture in two dimensions, we show that the peaks of the Nernst
coefficient survive in three dimensions due to a van Hove singularity. We also
evaluate the phonon-drag effect on the Nernst coefficient numerically. Our
result agrees with the experimental result for a bismuth single crystal.Comment: 4 pages, 4 figures, to be published in Proceedings of ISQM-Tokyo '0
A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews
Despite the recent advances in opinion mining for written reviews, few works
have tackled the problem on other sources of reviews. In light of this issue,
we propose a multi-modal approach for mining fine-grained opinions from video
reviews that is able to determine the aspects of the item under review that are
being discussed and the sentiment orientation towards them. Our approach works
at the sentence level without the need for time annotations and uses features
derived from the audio, video and language transcriptions of its contents. We
evaluate our approach on two datasets and show that leveraging the video and
audio modalities consistently provides increased performance over text-only
baselines, providing evidence these extra modalities are key in better
understanding video reviews.Comment: Second Grand Challenge and Workshop on Multimodal Language ACL 202
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