Research on the Current Situation, Prospects and Countermeasures of Digital RMB

In the economic environment of global economic recession, weak consumption and weakened momentum of economic recovery, due to the impact of the prolonged epidemic, the global economy has become more polarized, and the development of China’s digital RMB has also fallen into difficulties, and the complex international environment has led to China’s economic development is relatively unstable; however, because the world is entering the era of informationization, the development of the digital RMB is imminent. Combined with the background of economic recovery in the post epidemic era, this paper analyzes and summarizes the current situation of digital RMB at this stage, studies the existing deficiencies of digital RMB, and ultimately puts forward four relevant countermeasures and targeted recommendations to promote the development of digital RMB, which mainly include strengthening the internationalization of RMB, continuing to make efforts to reduce the difficulties in payment, improving the relevant technology, and strengthening the measures of market supervision

Quantifying immediate price impact of trades based on the kk-shell decomposition of stock trading networks

Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into $k$ classes using the $k$-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.Comment: 6 pages including 3 figures and 1 tabl

Boosted Dark Matter From Centaurus A and Its Detection

Dark matter can be boosted by high energy particles in astrophysical environments through elastic scattering. We study the production of boosted dark matter via scattering with electrons in the relativistic jet of the closest active galactic nucleus, Centaurus A, and its detection in the Super-Kamiokande experiment. Since there are a huge number of electrons in the jet and dark matter is extremely dense around the supermassive black hole that powers the jet, the number of boosted dark matter is tremendously large. Compared to boosted dark matter from blazars, the dark matter flux from Centaurus A is enhanced due to the proximity of Centaurus A. The constraint on dark matter-electron scattering cross section set by Super-Kamiokande is more stringent, down to $\sim 10^{-36} \, \mathrm{cm}^2$ for $\mathrm{MeV}$ dark matter.Comment: 18 pages, 5 figures, version appeared in JHE

Characterization of conductivity fields through iterative ensemble smoother and improved correlation-based adaptive localization

Localization is critical to the effective use of an (iterative) ensemble Kalman filter or ensemble smoother to estimate uncertain quantities of interest. Here, we propose a novel, fully adaptive, correlation-based localization method (termed FBadap). We embed our FBadap approach within an iterative ensemble smoother to estimate three-dimensional spatially heterogeneous log-conductivity (Y) fields. The latter are characterized through a Generalized sub-Gaussian model, which includes the Gaussian distribution as a particular case. They constitute random fields within which head and concentration observations are collected at monitoring wells screened at multiple depths. To ensure transparent comparisons, we study and analyze the performance of our approach through a wide range of synthetic test cases. These comprise diverse configurations, including (a) various ensemble sizes, (b) various degrees of departure of the description of the spatial heterogeneity from a Gaussian model, as well as (c) different values of the mean and variance of the initial ensemble of Y. Our results show that (i) FBadap is robust adaptive approach enabling one to tackle a variety of settings; (ii) FBadap exhibits stronger adaptivity to cope with diverse ensemble sizes than FBconst, and can provide improved accuracy of conductivity estimates in comparison with traditional methods; and (iii) the quality of conductivity estimates is jointly impacted by the degree of departures of the reference Y field and of the initial ensemble of Y from a description based on a Gaussian model.Characterization of conductivity fields through iterative ensemble smoother and improved correlation-based adaptive localizationpublishedVersio