Potential high-TcT_{c} superconductivity in YCeH20_{20} and LaCeH20_{20} under pressure

Lanthanum, yttrium, and cerium hydrides are the three most well-known superconducting binary hydrides, which have gained great attention in both theoretical and experimental studies. Recent studies have shown that ternary hydrides composed of lanthanum and yttrium can achieve high superconductivity around 253 K. In this study, we employ the evolutionary-algorithm-based crystal structure prediction (CSP) method and first-principles calculations to investigate the stability and superconductivity of ternary hydrides composed of (Y, Ce) and (La, Ce) under high pressure. Our calculations show that there are multiple stable phases in Y-Ce-H and La-Ce-H hydrides, among which $P4/mmm$-YCeH$_{8}$, $P4/mmm$-LaCeH$_{8}$, $R\bar{3}m$-YCeH$_{20}$, and $R\bar{3}m$-LaCeH$_{20}$ possessing H$_{18}$ or H$_{32}$ clathrate structures can maintain both of the thermodynamic and dynamic stabilities. In addition, we also find that these phases also maintain a strong resistance to decomposition at high temperature. Electron-phonon coupling calculations show that all of these four phases can exhibit high-temperature superconductivity. $R\bar{3}m$-YCeH$_{20}$ is predicted to have a superconducting transition temperature ($T_{c}$) as high as 246 K at 350 GPa. The $T_{c}$ value of $R\bar{3}m$-LaCeH$_{20}$ at 250 GPa is about 233 K, which is slightly smaller than that of $R\bar{3}m$-YCeH$_{20}$. However, it is found that $R\bar{3}m$-LaCeH$_{20}$ can be stabilized at 200 GPa, making the high-pressure synthesis of LaCeH$_{20}$ easier.Comment: 5 figure

A General Class of Transfer Learning Regression without Implementation Cost

We propose a novel framework that unifies and extends existing methods of transfer learning (TL) for regression. To bridge a pretrained source model to the model on a target task, we introduce a density-ratio reweighting function, which is estimated through the Bayesian framework with a specific prior distribution. By changing two intrinsic hyperparameters and the choice of the density-ratio model, the proposed method can integrate three popular methods of TL: TL based on cross-domain similarity regularization, a probabilistic TL using the density-ratio estimation, and fine-tuning of pretrained neural networks. Moreover, the proposed method can benefit from its simple implementation without any additional cost; the regression model can be fully trained using off-the-shelf libraries for supervised learning in which the original output variable is simply transformed to a new output variable. We demonstrate its simplicity, generality, and applicability using various real data applications.Comment: 31 pages, 6 figure

The brightest UV-selected galaxies in protoclusters at z∼4z\sim4: Ancestors of Brightest Cluster Galaxies?

We present the results of a survey of the brightest UV-selected galaxies in protoclusters. These proto-brightest cluster galaxy (proto-BCG) candidates are drawn from 179 overdense regions of $g$-dropout galaxies at $z\sim4$ from the Hyper Suprime-Cam Subaru Strategic Program identified previously as good protocluster candidates. This study is the first to extend the systematic study of the progenitors of BCGs from $z\sim2$ to $z\sim4$. We carefully remove possible contaminants from foreground galaxies and, for each structure, we select the brightest galaxy that is at least 1 mag brighter than the fifth brightest galaxy. We select 63 proto-BCG candidates and compare their properties with those of galaxies in the field and those of other galaxies in overdense structures. The proto-BCG candidates and their surrounding galaxies have different rest-UV color $(i - z)$ distributions to field galaxies and other galaxies in protoclusters that do not host proto-BCGs. In addition, galaxies surrounding proto-BCGs are brighter than those in protoclusters without proto-BCGs. The image stacking analysis reveals that the average effective radius of proto-BCGs is $\sim28\%$ larger than that of field galaxies. The $i-z$ color differences suggest that proto-BCGs and their surrounding galaxies are dustier than other galaxies at $z\sim4$. These results suggest that specific environmental effects or assembly biasses have already emerged in some protoclusters as early as $z \sim 4$, and we suggest that proto-BCGs have different star formation histories than other galaxies in the same epoch.Comment: 18 pages, 11 figures, Accepted for publication in Ap

Cross-Speaker Emotion Transfer for Low-Resource Text-to-Speech Using Non-Parallel Voice Conversion with Pitch-Shift Data Augmentation

Data augmentation via voice conversion (VC) has been successfully applied to low-resource expressive text-to-speech (TTS) when only neutral data for the target speaker are available. Although the quality of VC is crucial for this approach, it is challenging to learn a stable VC model because the amount of data is limited in low-resource scenarios, and highly expressive speech has large acoustic variety. To address this issue, we propose a novel data augmentation method that combines pitch-shifting and VC techniques. Because pitch-shift data augmentation enables the coverage of a variety of pitch dynamics, it greatly stabilizes training for both VC and TTS models, even when only 1,000 utterances of the target speaker's neutral data are available. Subjective test results showed that a FastSpeech 2-based emotional TTS system with the proposed method improved naturalness and emotional similarity compared with conventional methods.Comment: Submitted to Interspeech 202