Prediction of 4f7-4f65d1 transition energy of Eu2+ in oxides based on first-principles calculations and machine learning

In order to establish a method to predict the 4f7-4f65d1 transition energy of Eu2+ in oxides, linear regression models were created based on first-principles calculations and machine learning. The model clusters consisting of the central Eu2+ and O2- ions closer than the nearest cation were constructed and the 4f7-4f65d1 absorption energy of Eu2+ in these clusters were calculated by first-principles many-electron calculation using the relativistic discrete variational multi-electron (DVME) method. However, the 4f7-4f65d1 absorption energies of Eu2+ in oxides calculated by relatively simple first-principles calculations tend to be overestimated by ca. 1.6 eV. In order to improve the accuracy of the prediction, we performed machine learning considering the calculated absorption energy as well as the other electronic and structural parameters as the attributes. As a result, the regression formula to predict the 4f7-4f65d1 absorption energy of Eu2+ in oxides has been created by machine learning. The 4f7-4f65d1 absorption energy predicted by this model are in good agreement with the experimental ones. Therefore, accuracy of the prediction was significantly improved compared to the simple first-principles calculations. In a similar way, a predictive model of the 4f65d1-4f7 emission energy of Eu2+ in oxides has been also create

Entangled N-photon states for fair and optimal social decision making

Situations involving competition for resources among entities can be modeled by the competitive multi-armed bandit (CMAB) problem, which relates to social issues such as maximizing the total outcome and achieving the fairest resource repartition among individuals. In these respects, the intrinsic randomness and global properties of quantum states provide ideal tools for obtaining optimal solutions to this problem. Based on the previous study of the CMAB problem in the two-arm, two-player case, this paper presents the theoretical principles necessary to find polarization-entangled N-photon states that can optimize the total resource output while ensuring equality among players. These principles were applied to two-, three-, four-, and five-player cases by using numerical simulations to reproduce realistic configurations and find the best strategies to overcome potential misalignment between the polarization measurement systems of the players. Although a general formula for the N-player case is not presented here, general derivation rules and a verification algorithm are proposed. This report demonstrates the potential usability of quantum states in collective decision making with limited, probabilistic resources, which could serve as a first step toward quantum-based resource allocation systems.Comment: 22 pages and 7 figures, version 1.1 of July 27th 202

Entangled-photon decision maker

The competitive multi-armed bandit (CMAB) problem is related to social issues such as maximizing total social benefits while preserving equality among individuals by overcoming conflicts between individual decisions, which could seriously decrease social benefits. The study described herein provides experimental evidence that entangled photons physically resolve the CMAB in the 2-arms 2-players case, maximizing the social rewards while ensuring equality. Moreover, we demonstrated that deception, or outperforming the other player by receiving a greater reward, cannot be accomplished in a polarization-entangled-photon-based system, while deception is achievable in systems based on classical polarization-correlated photons with fixed polarizations. Besides, random polarization-correlated photons have been studied numerically and shown to ensure equality between players and deception prevention as well, although the CMAB maximum performance is reduced as compared with entangled photon experiments. Autonomous alignment schemes for polarization bases were also experimentally demonstrated based only on decision conflict information observed by an individual without communications between players. This study paves a way for collective decision making in uncertain dynamically changing environments based on entangled quantum states, a crucial step toward utilizing quantum systems for intelligent functionalities

Mutant analyses reveal different functions of fgfr1 in medaka and zebrafish despite conserved ligand–receptor relationships

AbstractMedaka (Oryzias latipes) is a small freshwater teleost that provides an excellent developmental genetic model complementary to zebrafish. Our recent mutagenesis screening using medaka identified headfish (hdf) which is characterized by the absence of trunk and tail structures with nearly normal head including the midbrain–hindbrain boundary (MHB). Positional-candidate cloning revealed that the hdf mutation causes a functionally null form of Fgfr1. The fgfr1hdf is thus the first fgf receptor mutant in fish. Although FGF signaling has been implicated in mesoderm induction, mesoderm is induced normally in the fgfr1hdf mutant, but subsequently, mutant embryos fail to maintain the mesoderm, leading to defects in mesoderm derivatives, especially in trunk and tail. Furthermore, we found that morpholino knockdown of medaka fgf8 resulted in a phenotype identical to the fgfr1hdf mutant, suggesting that like its mouse counterpart, Fgf8 is a major ligand for Fgfr1 in medaka early embryogenesis. Intriguingly, Fgf8 and Fgfr1 in zebrafish are also suggested to form a major ligand–receptor pair, but their function is much diverged, as the zebrafish fgfr1 morphant and zebrafish fgf8 mutant acerebellar (ace) only fail to develop the MHB, but develop nearly unaffected trunk and tail. These results provide evidence that teleost fish have evolved divergent functions of Fgf8–Fgfr1 while maintaining the ligand–receptor relationships. Comparative analysis using different fish is thus invaluable for shedding light on evolutionary diversification of gene function

Appling Fuzzy Measure and lntegral to Diagnose Faults in Rotating Machinery

This paper proposes a system for diagnosing faults in rotating machinery utilizing fuzzy measure and integral. The membership functions and fuzzy measure are composed based on the syndrome matrix made by skilled engineers. The possibility of faults are determined by the fuzzy integral using the membership degree and fuzzy measure for spectra. The paper also evaluates the method using an example of fault diagnosis of backlash fault