Conflict-free joint decision by lag and zero-lag synchronization in laser network

With the end of Moore's Law and the increasing demand for computing, photonic accelerators are garnering considerable attention. This is due to the physical characteristics of light, such as high bandwidth and multiplicity, and the various synchronization phenomena that emerge in the realm of laser physics. These factors come into play as computer performance approaches its limits. In this study, we explore the application of a laser network, acting as a photonic accelerator, to the competitive multi-armed bandit problem. In this context, conflict avoidance is key to maximizing environmental rewards. We experimentally demonstrate cooperative decision-making using zero-lag and lag synchronization within a network of four semiconductor lasers. Lag synchronization of chaos realizes effective decision-making and zero-delay synchronization is responsible for the realization of the collision avoidance function. We experimentally verified a low collision rate and high reward in a fundamental 2-player, 2-slot scenario, and showed the scalability of this system. This system architecture opens up new possibilities for intelligent functionalities in laser dynamics

Information-theoretical analysis of statistical measures for multiscale dynamics

Multiscale entropy (MSE) has been widely used to examine nonlinear systems involving multiple time scales, such as biological and economic systems. Conversely, Allan variance has been used to evaluate the stability of oscillators, such as clocks and lasers, ranging from short to long time scales. Although these two statistical measures were developed independently for different purposes in different fields in the literature, their interest is to examine multiscale temporal structures of physical phenomena under study. We show that, from an information-theoretical perspective, they share some foundations and exhibit similar tendencies. We experimentally confirmed that similar properties of the MSE and Allan variance can be observed in low-frequency fluctuations (LFF) in chaotic lasers and physiological heartbeat data. Furthermore, we calculated the condition under which this consistency between the MSE and Allan variance exists, which is related to certain conditional probabilities. Heuristically, physical systems in nature including the aforementioned LFF and heartbeat data mostly satisfy this condition, and hence the MSE and Allan variance demonstrate similar properties. As a counterexample, an artificially constructed random sequence is demonstrated, for which the MSE and Allan variance exhibit different trends

STUDI KELAYAKAN INVESTASI TI PADA PT. INTRAPOLA LOGISTICS INTERNATIONAL

STUDI KELAYAKAN INVESTASI TI PADA PT. INTRAPOLA LOGISTICS INTERNATIONAL - Investasi teknologi informasi, Cost Benefit Analysis

Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk

Quantum walks (QWs) have a property that classical random walks (RWs) do not possess—the coexistence of linear spreading and localization—and this property is utilized to implement various kinds of applications. This paper proposes RW- and QW-based algorithms for multi-armed-bandit (MAB) problems. We show that, under some settings, the QW-based model realizes higher performance than the corresponding RW-based one by associating the two operations that make MAB problems difficult—exploration and exploitation—with these two behaviors of QWs

Memory Effect on Adaptive Decision Making with a Chaotic Semiconductor Laser

We investigate the effect of a memory parameter on the performance of adaptive decision making using a tug-of-war method with the chaotic oscillatory dynamics of a semiconductor laser. We experimentally generate chaotic temporal waveforms of the semiconductor laser with optical feedback and apply them for adaptive decision making in solving a multiarmed bandit problem that aims at maximizing the total reward from slot machines whose hit probabilities are dynamically switched. We examine the dependence of making correct decisions on different values of the memory parameter. The degree of adaptivity is found to be enhanced with a smaller memory parameter, whereas the degree of convergence to the correct decision is higher for a larger memory parameter. The relations among the adaptivity, environmental changes, and the difficulties of the problem are also discussed considering the requirement of past decisions. This examination of ultrafast adaptive decision making highlights the importance of memorizing past events and paves the way for future photonic intelligence

The influence of mg and mn content on abnormal grain growth in aa5182 type alloys

The occurrence of abnormal grain growth (AGG) in AA5182 alloy during annealing imposes severe restrictions on processing parameters and deteriorates mechanical properties. In this work, we investigated the effect of chemical composition on the appearance of abnormal grain growth by varying Mg and Mn content in the range of composition limits for standard AA5182 alloy, 4.0-5.0% Mg, and 0.2-0.5% Mn, respectively. Thermo-mechanical processing of alloys included cold rolling with reductions ranging from 40 to 85%, followed by annealing in the temperature range from 350 to 520 degrees C. The results showed that the rise in alloying elements content drives the onset of abnormal grain growth toward higher temperatures. The increase in the cold rolling reduction degree promotes abnormal grain growth and lowers its onset temperature. Abnormal grain growth and grain boundary mobility showed strong anisotropy related to rod-like shape and alignment of Al6Mn(Fe) dispersoids through Zener pinning