arXiv subjects

Shunsuke Watanabe

Publications and source records attributed to Shunsuke Watanabe.

5 recordsLinked to original sources

arXiv2021

Hyperparameter tuning of optical neural network classifiers for high-order gaussian beams

High-order Gaussian beams with multiple propagation modes have been studied for free-space optical communications. Fast classification of beams using a diffractive deep neural network, D2NN, has been proposed. D2NN optimization is important because it has numerous hyperparameters, such as interlayer distances and mode combinations. In this study, we classify Hermite-Gaussian beams, which are high-order Gaussian beams, using a D2NN, and automatically tune one of its hyperparameters known as the interlayer distance. We used the tree-structured Parzen estimator, a hyperparameter auto-tuning algorithm, to search for the best model. Results indicated that classification accuracy obtained by auto-tuning hyperparameters was higher than that obtained by manually setting interlayer distances at equal intervals. In addition, we confirmed that accuracy by auto-tuning improves as the number of classification modes increases.

physics.optics↗

arXiv2020

Robustness of football passing networks against continuous node and link removals

We can construct passing networks when we regard a player as a node and a pass as a link in football games. Thus, we can analyze the networks by using tools developed in network science. Among various metrics characterizing a network, centrality metrics have often been used to identify key players in a passing network. However, a tolerance to players being marked or passes being blocked in a passing network, namely the robustness of the network, has been poorly understood so far. Because the robustness of a passing network can be connected to the increase of ball possession, it would be deeply related to the outcome of a game. Here, we developed position-dependent passing networks of 45 matches by 18 teams belonging to the Japan Professional Football League. Then, nodes or links were continuously removed from the passing networks by two removal methods so that we could evaluate the robustness of these networks against the removals. The results show that these passing networks commonly contain hubs (key players making passes). Then, we analyzed the most robust networks in detail and found that their full backs increase the robustness by often invoking a heavier emphasis on attack. Moreover, we showed that the robustness of the passing networks and the team performance have a positive correlation.

physics.soc-ph↗

arXiv2016

Resilience of antagonistic networks with regard to the effects of initial failures and degree-degree correlations

In this study, we investigate the resilience of duplex networked layers ($α$ and $β$) coupled with antagonistic interlinks, each layer of which inhibits its counterpart at the microscopic level, changing the following factors: whether the influence of the initial failures in $α$ remains (quenched (Case Q)) or not (free (Case F)); the effect of intralayer degree-degree correlations in each layer and interlayer degree-degree correlations; and the type of the initial failures, such as random failures (RFs) or targeted attacks (TAs). We illustrate that the percolation processes repeat in both Cases Q and F, although only in Case F are nodes that initially failed reactivated. To analytically evaluate the resilience of each layer, we develop a methodology based on the cavity method for deriving the size of a giant component (GC). Strong hysteresis, which is ignored in the standard cavity analysis, is observed in the repetition of the percolation processes particularly in Case F. To handle this, we heuristically modify interlayer messages for macroscopic analysis, the utility of which is verified by numerical experiments. The percolation transition in each layer is continuous in both Cases Q and F. We also analyze the influences of degree-degree correlations on the robustness of layer $α$, in particular for the case of TAs. The analysis indicates that the critical fraction of initial failures that makes the GC size in layer $α$ vanish depends only on its intralayer degree-degree correlations. Although our model is defined in a somewhat abstract manner, it may have relevance to ecological systems that are composed of endangered species (layer $α$) and invaders (layer $β$), the former of which are damaged by the latter whereas the latter are exterminated in the areas where the former are active.

cond-mat.dis-nn↗

arXiv2015

Feshbach-Resonance-Enhanced Coherent Atom-Molecule Conversion with Ultra-Narrow Photoassociation Resonance

We reveal the existence of high-density Feshbach resonances in the collision between the ground and metastable states of $^{171}$Yb and coherently produce the associated Feshbach molecules by photoassociation. The extremely small transition rate is overcome by the enhanced Franck-Condon factor of the weakly bound Feshbach molecule, allowing us to observe Rabi oscillations with long decay time between an atom pair and a molecule in an optical lattice. We also perform the precision measurement of the binding energies, which characterizes the observed resonances. The ultra-narrow photoassociation will be a basis for practical implementation of optical Feshbach resonances.

physics.atom-ph↗

arXiv2014

Cavity-based robustness analysis of interdependent networks: Influences of intranetwork and internetwork degree-degree correlations

We develop a methodology for analyzing the percolation phenomena of two mutually coupled (interdependent) networks based on the cavity method of statistical mechanics. In particular, we take into account the influence of degree-degree correlations inside and between the networks on the network robustness against targeted attacks and random failures. We show that the developed methodology is reduced to the well-known generating function formalism in the absence of degree-degree correlations. The validity of the developed methodology is confirmed by a comparison with the results of numerical experiments. Our analytical results imply that the robustness of the interdependent networks depends considerably on both the intra- and internetwork degree-degree correlations in the case of targeted attacks, whereas the significance of the degree-degree correlations is relatively low for random failures.

cond-mat.dis-nn↗