Electromagnetic properties of strange baryons in a relativistic quark model

We present some of our results for the electromagnetic properties of excited Σ hyperons, computed within the framework of the Bonn constituent-quark model, which is based on the Bethe-Salpeter approach. The seven parameters entering the model are fitted against the best-known baryon masses. Accordingly, the results for the form factors and helicity amplitudes are genuine predictions. We compare with the scarce experimental data available and discuss the processes in which Σ ^*'s may play an important role.     

Beam-helicity asymmetry in photon and pion electroproduction in the Δ(1232)-resonance region at Q2 = 0.35(GeV/c)2

The beam-helicity asymmetry has been measured simultaneously for the reactions p→epγ and p→epπ ⁰ in the Δ(1232)-resonance region at Q ² = 0.35(GeV/c)². The experiment was performed at MAMI with a longitudinally polarized beam and an out-of-plane detection of the proton. The results are compared with calculations based on dispersion relations for virtual Compton scattering and with the MAID model for pion electroproduction. There is an overall good agreement between experiment and theoretical calculations. The remaining discrepancies may be ascribed to an imperfect parametrization of some γ ^(*) N→πN multipoles, mainly contributing to the non-resonant background. The beam-helicity asymmetry in both channels (γ and π ⁰) shows a good sensitivity to these multipoles and should allow future improvement in their parametrization.     

First-Principles Investigations of Precursor Molecules for Microclusters

Details of the reactive processes by which TiC and TiN microclusters are formed from precursor molecules in the gas phase are not clearly understood. We have performed ab initio calculations based on density functional theory methods in order to get some insight into the chemical reactions of precursor molecules. Using microcanonical molecular-dynamics we have simulated scattering processes between molecules consisting of the elements Ti, Cl, N and H. The simulations show that fluctuations of the kinetic energy can be large enough to break up bonds at moderate temperatures.     

Multi-sensors SAR system for real-time dosimetry assessment

A multi-sensor test-bench for determining the SAR (specific absorption rate) due to wireless devices emitting in equivalent human tissues is presented. Real-time SAR assessment is proposed considering a spatially distributed multiprobe test-bench. In comparison with a multi-axial robot SAR system, the proposed one does not require any displacement, thus reducing drastically acquisition time, once parallel data acquisition and interpolation techniques are employed for accelerating measurements.     

Entanglement of a two-particle Gaussian state interacting with a heat bath

The effect of a thermal reservoir is investigated on a bipartite Gaussian state. We derive a pre-Lindblad master equation in the non-rotating wave approximation for the system. We then solve the master equation for a bipartite harmonic oscillator Hamiltonian with entangled initial state. We show that for strong damping the loss of entanglement is the same as for freely evolving particles. However, if the damping is small, the entanglement is shown to oscillate and eventually tend to a constant non-zero value.     

EAST 装置电子回旋辐射二维成像系统的屏蔽优化

介绍了EAST 装置上的384 道(极向24 道径向16 道)的外差混频式电子回旋辐射成像诊断系统及其在EAST 及其复杂的电磁环境中的运行情况。在低杂波电流驱动期间,高灵敏度的电子回旋辐射成像系统受到严重干扰以至于无法提供正确的实验数据。通过优化系统各模块的接地、外加多层铜网屏蔽等措施,使得ECEI 系统屏蔽效能与改善之前相比提高了40dB,基本保障了EAST 装置上电子回旋辐射成像诊断的正常工作。     

Quantum Bayesian computation

Quantum Bayesian computation is an emerging field that levers the computational gains available from quantum computers. They promise to provide an exponential speed-up in Bayesian computation. Our article adds to the literature in three ways. First, we describe how quantum von Neumann measurement provides quantum versions of popular machine learning algorithms such as Markov chain Monte Carlo and deep learning that are fundamental to Bayesian learning. Second, we describe quantum data encoding methods needed to implement quantum machine learning including the counterparts to traditional feature extraction and kernel embeddings methods. Third, we show how quantum algorithms naturally calculate Bayesian quantities of interest such as posterior distributions and marginal likelihoods. Our goal then is to show how quantum algorithms solve statistical machine learning problems. On the theoretical side, we provide quantum versions of high dimensional regression, Gaussian processes and stochastic gradient descent. On the empirical side, we apply a quantum FFT algorithm to Chicago house price data. Finally, we conclude with directions for future research.     

多色矢量高斯-谢尔模型光束的焦移和焦开关

从交叉谱密度矩阵的传输公式出发,对多色矢量高斯-谢尔模型（GSM）光束的焦移和焦开关作了详细的研究.插入偏振片之前,多色矢量高斯-谢尔模型（GSM）光束通过硬边光阑透镜分离光学系统后,有焦移,但无焦开关;而插入偏振片之后,会出现焦开关.改变偏振片的旋转角度可以控制焦开关的特性.     

Extension of statistical replacement to systems with time-correlated fluctuations

Nonlinear systems with correlated stochastic parameters are approximated by simpler systems. This method is an extension of an earlier version of statistical replacement and statistical linearization. The extended method is applicable to systems with correlated fluctuations. We show how this general method reduces to the earlier methods in special cases.     

克尔效应导致的鬼像位置移动

在近轴条件下,利用矩阵光学的方法研究了高功率高斯光束通过不同光学元件时,克尔效应导致的介质折射率的变化对鬼像位置的影响.计算了单个双凸透镜,单个双凹透镜以及4F系统中反射光线形成的低阶鬼像的位置移动,并将鬼像位置移动的规律表示为入射光束束腰和峰值光强的函数.