Experimental Determination of the Landé g-Factors for 5s^2 ^1S and 5s5p ^3P States of the ^87Sr Atom

We present an experimental determination on the Lande g-factors for the 5 s^2 ^1 S0 and 5 s5 p ^3P0 states in ultra-cold atomic systems, which is important for evaluating the Zeeman shift of the clock transition in the ^87Sr optical lattice clock. The Zeeman shift of the 5 s5 p ^3 P0-5 s^2 ^1 S0 forbidden transition is measured with the π-polarized and σ^±-polarized interrogations at different magnetic field strengths. Moreover, in the g-factor measurement with the σ^±-transition spectra, it is unnecessary to calibrate the external magnetic field. By this means, the ground state 5 s^2 ^1 S0 g-factor for the ^87Sr atom is-1.306（52） ×10^-4, which is the first experimental determination to the best of our knowledge, and the result matches very well with the theoretical estimation. The differential g-factorδg between the 5 s5 p^3 P0 state and the 5 s^2 ^1 S0 state of the ^87Sr atoms is measured in the experiment as well,which are-7.67（36） ×10^-5 with π-transition spectra and-7.72（43） X 10^-5 with σ^±-transition spectra, in good agreement with the previous report [Phys. Rev. A 76（2007） 022510]. This work can also be used for determining the differential g-factor of the clock states for the optical clocks based on other atoms.

Research on the Models of Automotive Suspension Springs Stress

This paper introduced two methods of automotive suspension springs stress analysis, the FEA （finite element analysis） and the experimental measurement, through which the maximum stress is found located where the cylinder number is the integer multiple of the first half cycle from the spring end. By scattering or removing the maximum stress points, optimum design, which is based on the cosmosworks method, will promote the fatigue reliability and the employ life of the springs.

Numerical Experiment of Combined Infrared and Ultraviolet Radiation Remote Sensing to Determine the Profile and Total Content of Atmospheric Ozone

A new remote sensing method is described to determine the vertical distribution and total content of atmospheric ozone. The method combines surface infrared, satellite infrared and ultraviolet channels. The width of the infrared channels is 0.01 cm-1, less than Lorentz half-width at the earth's surface, rather than the present width, because these channels can obtain information about variations in the ozone profile below the profile main-peak. The numerical experiments show that the method has a satisfactory precision in determining total ozone content, just about I percent error, and vertical distribution from the earth to 65 km space. In addition, some semi-analysis functions lor calculating backscattered ultraviolet and a relaxation equation are described in this paper.

An Improved Experiment to Determine the‘Past of a Particle’in the Nested Mach-Zehnder Interferometer

We argue that the modification proposed by Li et al. [Chin. Phys. Lett. 32 （2015）050303] to the experiment of Danan et al. [Phys. Rev. Lett. 111 （2013） 240402] does not test the past of the photon as characterized by local weak traces. Instead of answering the questions： （i） were the photons in A？ （ii） were the photons in B？ and （iii） were the photons in C？ the proposed experiment measures a degenerate operator answering the questions： （i） were the photons in A？ and （ii） were the photons in B and C together？ A negative answer to the last question does not tell us if photons were present in B or C. On the other hand, a simple variation of the proposal by Li et al. does provide conceptually better evidence for the past of the pre- and post-selected photon, but this evidence will be in agreement with the results of Danan et al.

An Ideal Experiment to Determine the ’Past of a Particle’ in the Nested Mach-Zehnder Interferometer

An ideal experiment is designed to determine the past of a particle in the nested Mach-Zehnder interferometer （MZI） by using standard quantum mechanics with quantum non-demolition measurements. We find that when the photon reaches the detector, it only follows one arm of the outer interferometer and leaves no trace in the inner MZI. When it goes through the inner MZI, it cannot reach the detector. Our result obtained from the standard quantum mechanics contradicts the statement based on two-state vector formulism, ＇the photon did not enter the （inner） interferometer, the photon never left the interferometer, but it was there＇. Therefore, the statement and also the overlapping claim are incorrect.

An experimental methodology for the concurrent characterization of multiple parameters influencing nanoscale friction

A structured transdisciplinary method for the experimental determination of friction in the nanometric domain is proposed in this paper.The dependence of nanoscale friction on multiple process parameters on these scales,which comprise normal forces,sliding velocities,and temperature,was studied via the lateral force microscopy approach.The procedure used to characterize the stiffness of the probes used,and especially the influence of adhesion on the obtained results,is thoroughly described.The analyzed thin films were obtained by using either atomic layer or pulsed laser deposition.The developed methodology,based on elaborated design of experiments algorithms,was successfully implemented to concurrently characterize the dependence of nanoscale friction in the multidimensional space defined by the considered process parameters.This enables the establishment of a novel methodology that extends the current state-of-the-art of nanotribological studies,as it allows not only the gathering of experimental data,but also the ability to do so systematically and concurrently for several influencing variables at once.This,in turn,creates the basis for determining generalizing correlations of the value of nanoscale friction in any multidimensional experimental space.These developments create the preconditions to eventually extend the available macro-and mesoscale friction models to a true multiscale model that will considerably improve the design,modelling and production of MEMS devices,as well as all precision positioning systems aimed at micro-and nanometric accuracy and precision.

Dynamical analysis of high-pressure supercritical carbon dioxide jet in well drilling

This paper presents the design of an experimental setup and mathematical and physical models to determine the dynamical characteristics of the high-pressure supercritical carbon dioxide （SC-CO2） jet with a highly potential applications in the well drilling. The effects of three major factors on the wellbore dynamical characteristics of the high-pressure SC-CO2 jet, i.e., the nozzle diameter, the standoff distance and the jet pressure are determined. It is indicated that the pressure of CO2 reduces severely in the SC-CO2 jet impact process. It is also found that the bottom-hole pressure and the temperature increase as the nozzle diameter increases but de- crease with the increase of the standoff distance. The higher the jet pressure at the welIbore inlet is, the higher the pressure and the lower the temperature at the bottom-hole will be.

Comparative evaluation of data mining methods in predicting the water vapor permeability of cement-based materials

Water vapor permeability of building materials is a crucial parameter for analysing and optimizing the hygrothermal performance of building envelopes and built environments.Its measurement is accurate but time-consuming,while data mining methods have the potential to predict water vapor permeability efficiently.In this study,six data mining methods—support vector regression(SVR),decision tree regression(DT),random forest regression(RF),K-nearest neighbor(KNN),multi-layer perceptron(MLP),and adaptive boosting regression(AdaBoost)—were compared to predict the water vapor permeability of cement-based materials.A total of 143 datasets of material properties were collected to build prediction models,and five materials were experimentally determined for model validation.The results show that RF has excellent generalization,stability,and precision.AdaBoost has great generalization and precision,only slightly inferior to the former,and its stability is excellent.DT has good precision and acceptable generalization,but its stability is poor.SVR and KNN have superior stability,but their generalization and precision are inadequate.MLP lacks generalization,and its stability and precision are unacceptable.In short,RF has the best comprehensive performance,demonstrated by a limited prediction deviation of 26.3%from the experimental results,better than AdaBoost(38.0%)and DT(38.3%)and far better than other remaining methods.It is also found that data mining methods provide better predictions when cement-based materials’water vapor permeability is high.