Microanalytical study of some cosmic dust discovered in sea-floor sediments in China

The study of cosmic dust can provide useful data in the investigation of the origin of the Earth and the evolution of celestial bodies. Three types of cosmic dust (ferriginous, siliceous, and glassy) were discovered in the seafloor sediments near China. Their chemical composition and microstructure were examined by X-ray diffraction, fractography, and electron microscopy. The major mineral in an iron-containing cosmic dust is magnetite. The silicate spheres contain sundry metals and metal oxides. Glassy microtektites are similar in composition to tektites, and are found in all the major meteorite areas worldwide

Dr. Yang Zhong: an explorer on the road forever

On the morning of September 25th 2017, grievous news spread from the remote Ordos region of Inner Mongolia to Fudan University campus in Shanghai. Professor Yang Zhong, a famous botanist and the Dean of Fudan University’s graduate school, passed away in a tragic car accident while on a business trip

Retraction of articles by H. Zhong et al.

Retraction of 41 articles by H. Zhong et al.

A New Solution of the Yang-Baxter Equation Related to the Adjoint Representation of UqB2U_{q}B_{2}

A new solution of the Yang-Baxter equation, that is related to the adjoint representation of the quantum enveloping algebra $U_{q}B_{2}$, is obtained by fusion formulas from a non-standard solution.Comment: 16 pages (Latex), Preprint BIHEP-TH-93-3

Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long Short-Term Memory Networks

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.Comment: 31 page

Determination of Dark Matter Halo Mass from Dynamics of Satellite Galaxies

We show that the mass of a dark matter halo can be inferred from the dynamical status of its satellite galaxies. Using 9 dark-matter simulations of halos like the Milky Way (MW), we find that the present-day substructures in each halo follow a characteristic distribution in the phase space of orbital binding energy and angular momentum, and that this distribution is similar from halo to halo but has an intrinsic dependence on the halo formation history. We construct this distribution directly from the simulations for a specific halo and extend the result to halos of similar formation history but different masses by scaling. The mass of an observed halo can then be estimated by maximizing the likelihood in comparing the measured kinematic parameters of its satellite galaxies with these distributions. We test the validity and accuracy of this method with mock samples taken from the simulations. Using the positions, radial velocities, and proper motions of 9 tracers and assuming observational uncertainties comparable to those of MW satellite galaxies, we find that the halo mass can be recovered to within $\sim$40%. The accuracy can be improved to within $\sim$25% if 30 tracers are used. However, the dependence of the phase-space distribution on the halo formation history sets a minimum uncertainty of $\sim$20% that cannot be reduced by using more tracers. We believe that this minimum uncertainty also applies to any mass determination for a halo when the phase space information of other kinematic tracers is used.Comment: Accepted for publication in ApJ, 18 pages, 13 figure

Suppression of dephasing by qubit motion in superconducting circuits

We suggest and demonstrate a protocol which suppresses dephasing due to the low-frequency noise by qubit motion, i.e., transfer of the logical qubit of information in a system of $n \geq 2$ physical qubits. The protocol requires only the nearest-neighbor coupling and is applicable to different qubit structures. We further analyze its effectiveness against noises with arbitrary correlations. Our analysis, together with experiments using up to three superconducting qubits, shows that for the realistic uncorrelated noises, qubit motion increases the dephasing time of the logical qubit as $\sqrt{n}$. In general, the protocol provides a diagnostic tool to measure the noise correlations.Comment: 5 pages with 3 embedded figures, plus supplementary informatio