3,240 research outputs found
Quasi-Eigenstate Evolution in Open Chaotic Billiards
We experimentally studied evolution of quasi-eigenmodes as classical dynamics
undergoing a transition from being regular to chaotic in open quantum
billiards. In a deformation-variable microcavity we traced all high-Q cavity
modes in a wide range of frequency as the cavity deformation increased. By
employing an internal parameter we were able to obtain a mode-dynamics diagram
at a given deformation, showing avoided crossings between different mode
groups, and could directly observe the coupling strengths induced by ray chaos
among encountering modes. We also show that the observed mode-dynamics diagrams
reflect the underlying classical ray dynamics in the phase space.Comment: 4 pages, 4 figure
Development of deformation-tunable quadrupolar microcavity
We have developed a technique for realizing a two-dimensional quadrupolar
microcavity with its deformation variable from 0% to 20% continuously. We
employed a microjet ejected from a noncircular orifice in order to generate a
stationary column with modulated quadrupolar deformation in its cross section.
Wavelength red shifts of low-order cavity modes due to shape deformation were
measured and were found to be in good agreement with the wave calculation for
the same deformation, indicating the observed deformation is quadrupolar in
nature.Comment: 7 pages, 6 figures, intended for Rev. Sci. Instu
Chaos-assisted nonresonant optical pumping of quadrupole-deformed microlasers
Efficient nonresonant optical pumping of a high-Q scar mode in a
two-dimensional quadrupole-deformed microlaser has been demonstrated based on
ray and wave chaos. Three-fold enhancement in the lasing power was achieved at
a properly chosen pumping angle. The experimental result is consistent with ray
tracing and wave overlap integral calculations.Comment: 3 pages, 5 figure
An Ensemble Approach for Multiple Emotion Descriptors Estimation Using Multi-task Learning
This paper illustrates our submission method to the fourth Affective Behavior
Analysis in-the-Wild (ABAW) Competition. The method is used for the Multi-Task
Learning Challenge. Instead of using only face information, we employ full
information from a provided dataset containing face and the context around the
face. We utilized the InceptionNet V3 model to extract deep features then we
applied the attention mechanism to refine the features. After that, we put
those features into the transformer block and multi-layer perceptron networks
to get the final multiple kinds of emotion. Our model predicts arousal and
valence, classifies the emotional expression and estimates the action units
simultaneously. The proposed system achieves the performance of 0.917 on the
MTL Challenge validation dataset
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