In this report, we demonstrate a new principle to improve the resolution of the acoustic microscopy, which is based on the sub-wavelength focusing of acoustic wave passing through an acoustically transparent mesoscale particle. In the principle, the width of the acoustic focal area can be less than one wavelength. The sub-wavelength focusing effect is verified by the FEM simulation.
As an extension of the ideas of Hanbury-Brown and Twiss, a method is proposed to eliminate the phase noise of white chaotic light in the regime where it is dominant, and to measure the much smaller Poisson fluctuations from which the incoming flux can be reconstructed (via the equality between variance and mean). The best effect is achieved when the timing resolution is finer than the inverse bandwidth of the spectral filter. There may be applications to radio astronomy at the phase noise dominated frequencies of $1 - 10$GHz, in terms of potentially increasing the sensitivity of telescopes by an order of magnitude.
The analysis of the secondary Bjerknes force between two bubbles suggests that this force is analogous to the electrostatic forces. The same analogy is suggested by the existence of a scattering cross section of an acoustic wave on a bubble. Our paper brings new arguments in support of this analogy. The study which we perform is dedicated to the acoustic force and to the scattering cross section at resonance in order to highlight their angular frequency independence of the inductor wave. Also, our study reveals that the angular frequency and the amplitude of the induction pressure wave are not related. Highlighting this analogy will allow us a better understanding of the electrostatic interaction if the electron is modeled as an oscillating bubble in the vacuum.
Acoustic systems that are without limitations imposed by the Fermi level have been demonstrated as significant platform for the exploration of fruitful topological phases. By surrounding the nontrivial domain with trivial environment, the domain-wall topological states have been theoretically and experimentally demonstrated. In this work, based on the topological crystalline insulator with a kagome lattice, we rigorously derive the corresponding Hamiltonian from the traditional acoustics perspective, and exactly reveal the correspondences of the hopping and onsite terms within acoustic systems. Crucially, these results directly indicate that instead of applying the trivial domain, the soft boundary condition precisely corresponds to the theoretical models which always require generalized chiral symmetry. These results provide a general platform to construct desired acoustic topological devices hosting desired topological phenomena for versatile applications.
Acoustic-to-word (A2W) models that allow direct mapping from acoustic signals to word sequences are an appealing approach to end-to-end automatic speech recognition due to their simplicity. However, prior works have shown that modelling A2W typically encounters issues of data sparsity that prevent training such a model directly. So far, pre-training initialization is the only approach proposed to deal with this issue. In this work, we propose to build a shared neural network and optimize A2W and conventional hybrid models in a multi-task manner. Our results show that training an A2W model is much more stable with our multi-task model without pre-training initialization, and results in a significant improvement compared to a baseline model. Experiments also reveal that the performance of a hybrid acoustic model can be further improved when jointly training with a sequence-level optimization criterion such as acoustic-to-word.
We introduce a novel mechanism, called timid/bold coding, by which feedback can be used to improve coding performance. For a certain class of DMCs, called compound-dispersion channels, we show that timid/bold coding allows for an improved second-order coding rate compared with coding without feedback. For DMCs that are not compound dispersion, we show that feedback does not improve the second-order coding rate. Thus we completely determine the class of DMCs for which feedback improves the second-order coding rate. An upper bound on the second-order coding rate is provided for compound-dispersion DMCs. We also show that feedback does not improve the second-order coding rate for very noisy DMCs. The main results are obtained by relating feedback codes to certain controlled diffusions.