Hanle detection for optical clocks

Considering the strong inhomogeneous spatial polarization and intensity distribution of spontaneous decay fluorescence due to the Hanle effect, we propose and demonstrate a universe Hanle detection configuration of electron-shelving method for optical clocks. Experimental results from Ca atomic beam optical frequency standard with 423 nm electron-shelving method show that a designed Hanle detection geometry with optimized magnetic field direction, detection laser beam propagation and polarization direction, and detector position can improve the fluorescence collection rate by more than one order of magnitude comparing with that of inefficient geometry. With the fixed 423 nm fluorescence, the improved 657 nm optical frequency standard signal intensity is presented. And the potential application of the Hanle detection geometry designed for facilitating the fluorescence collection for optical lattice clock with a limited solid angle of the fluorescence collection has been discussed. This Hanle detection configuration is also effective for ion detection in ion optical clock and quantum information experiments. Besides, a cylinder fluorescence collection structure is designed to increase the solid angle of the fluorescence collection in Ca atomic beam optical frequency standard.Comment: 5 pages, 6 figure

Hydraulic fracturing-induced seismicity characterization through coupled modeling of stress and fracture-fault systems

This work summarizes our recent findings on hydraulic fracturing-induced seismicity nucleated in the Duvernay shale reservoirs within the Western Canada Sedimentary Basin. A coupled model of in-situ stress and fracture-fault systems was built to quantify four-dimensional stress and pressure changes and spatiotemporal seismicity nucleation during hydraulic fracturing. Five triggering mechanisms were successfully recognized in seismicity-frequent areas, including a direct hydraulic connection between impermeable faults and hydraulic fractures, fault slip owing to downward pressure diffusion, fault reactivation due to upward poroelastic stress perturbation, aftershocks of mainshock events, and reactivation of natural fractures surrounding the faults. This work shed light on how fracturing operations triggered the induced seismicity, providing a solid foundation for the investigation of controlling factors and mitigation strategies for hydraulic fracturing-induced seismicity.Cited as: Hui, G., Chen, Z., Chen, S., Gu, F. Hydraulic fracturing-induced seismicity characterization through coupled modeling of stress and fracture-fault systems. Advances in Geo-Energy Research, 2022, 6(3): 269-270. https://doi.org/10.46690/ager.2022.03.1

An evaluation of different RANS turbulence models for simulating breaking waves past a vertical cylinder

The purpose of the present study is to evaluate the performance of different turbulence models for predicting the interaction between breaking waves and a vertical cylinder based on the volume of fluid (VOF) method. Six different models are investigated in the present study, i.e., no turbulence model, the k − ω SST turbulence model, the buoyancymodified k − ω SST turbulence model, the stabilized k − ω SST turbulence model, the modified stabilized k − ωSST turbulence model and the realizable k − ε turbulence model. The vertical cylinder is installed at the edge of a 1:10 slope on the bottom of the numerical wave tank. The numerical simulations are conducted by solving the unsteady ReynoldsAveraged Navier-Stokes (RANS) equations using waves2Foam (a solver based on the open-source Computational Fluid Dynamic (CFD) software OpenFOAM). The present numerical results of the surface elevations and the breaking wave forces are compared with published experimental data. The kinetic characteristics beneath the free surface including averaged velocity, turbulent kinetic energy and turbulent kinematic viscosity are also investigated. It is observed that the stabilized k − ω SST turbulence (λ2 = 0.05, αβs = 1.36) and the buoyancy-modified k − ωSST turbulence model (αβs = 1.176) effectively reduce the turbulent kinetic energy before wave breaking, but the predicted breaking wave forces on the cylinder are smaller than that of the experimental data. The k − ω SST turbulence model shows good agreement with the experimental data in terms of the free surface elevation and the breaking wave force, but it overpredicts the turbulent kinetic energy. The realizable k − ε turbulence model does not give good predictions of both the free surface elevation and the breaking wave force as compared to the published experimental data.publishedVersio

Poisson regression with Laplace measurement error

Doctor of PhilosophyDepartment of StatisticsWeixing SongIn this dissertation, novel estimation procedures are proposed for a class of Poisson linear regression when the covariate is contaminated with Laplace measurement error. This dissertation contains two research projects. In the first project, we propose a weighted least squares estimation procedure that incorporates the first two conditional moments of the response variable given the observed surrogate, and the weight function is intentionally chosen to avoid the complexity caused by the random denominator and to increase the estimation efficiency. To solve for the conditional moments, a Tweedie-type formula for the conditional expectation of the likelihood function given the observed surrogate has been adopted. Instead of assuming the distribution of the unobserved covariate is known, we assume that the distribution of that latent variable is unknown. Large sample properties of the proposed estimator, including the consistency and the asymptotic normality, are discussed. The finite sample performance of the proposed estimation procedure is evaluated by simulation studies, showing that the proposed estimator is more efficient than the existing ones. In the second project, we propose a corrected maximum likelihood estimation procedure based upon the Tweedie-type formula. Two situations, the distribution of the latent variable is known as well as unknown, are considered. Large sample properties of the proposed estimator are discussed, and simulation study shows that the estimator is more efficient than the existing estimation procedures. Besides, further simulation studies are also conducted to compare our proposed two estimation procedures. And sensitivity analysis has been done to examine the robustness of our methods in real data. Although the discussion is conducted for univariate cases, the proposed estimation procedure can be readily extended to the multivariate cases by using multivariate Tweedie-type formulae

Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization

Consider a network of $N$ decentralized computing agents collaboratively solving a nonconvex stochastic composite problem. In this work, we propose a single-loop algorithm, called DEEPSTORM, that achieves optimal sample complexity for this setting. Unlike double-loop algorithms that require a large batch size to compute the (stochastic) gradient once in a while, DEEPSTORM uses a small batch size, creating advantages in occasions such as streaming data and online learning. This is the first method achieving optimal sample complexity for decentralized nonconvex stochastic composite problems, requiring $\mathcal{O}(1)$ batch size. We conduct convergence analysis for DEEPSTORM with both constant and diminishing step sizes. Additionally, under proper initialization and a small enough desired solution error, we show that DEEPSTORM with a constant step size achieves a network-independent sample complexity, with an additional linear speed-up with respect to $N$ over centralized methods. All codes are made available at~\url{https://github.com/gmancino/DEEPSTORM}.Comment: AAAI 202

Unsteady RANS Simulations of Flow around a Twin-Box Bridge Girder Cross Section

The aerodynamic performance of bridge deck girders requires a thorough assessment and optimization in the design of long-span bridges. The present paper describes a numerical investigation of the aerodynamic characteristics of a twin-box bridge girder cross section in the range of angles of attack between −10.0° and +10.2°. The simulations are performed by solving 2D unsteady Reynolds-averaged Navier–Stokes (URANS) equations together with the k–ω shear stress transport (SST) turbulence model. The investigated Reynolds number (Re) based on the free stream velocity (U∞) and the height of the deck (D) is 31,000. The predicted aerodynamic characteristics such as the mean drag, lift and moment coefficients, are generally in good agreement with the results from the wind tunnel tests. Changes of flow patterns and aerodynamic forces with different angles of attack are investigated. Flow characteristics during one vortex shedding period are highlighted. Relative contributions of each of the two bridge decks to the overall drag and lift coefficients, with respect to the angle of attack, are also discussed.publishedVersio

Extremely large magnetoresistance in topologically trivial semimetal α\alpha-WP2_2

Extremely large magnetoresistance (XMR) was recently discovered in many non-magnetic materials, while its underlying mechanism remains poorly understood due to the complex electronic structure of these materials. Here, we report an investigation of the $\alpha$-phase WP$_2$, a topologically trivial semimetal with monoclinic crystal structure (C2/m), which contrasts to the recently discovered robust type-II Weyl semimetal phase in $\beta$-WP$_2$. We found that $\alpha$-WP$_2$ exhibits almost all the characteristics of XMR materials: the near-quadratic field dependence of MR, a field-induced up-turn in resistivity following by a plateau at low temperature, which can be understood by the compensation effect, and high mobility of carriers confirmed by our Hall effect measurements. It was also found that the normalized MRs under different magnetic fields has the same temperature dependence in $\alpha$-WP$_2$, the Kohler scaling law can describe the MR data in a wide temperature range, and there is no obvious change in the anisotropic parameter $\gamma$ value with temperature. The resistance polar diagram has a peanut shape when field is rotated in $\textit{ac}$ plane, which can be understood by the anisotropy of Fermi surface. These results indicate that both field-induced-gap and temperature-induced Lifshitz transition are not the origin of up-turn in resistivity in the $\alpha$-WP$_2$ semimetal. Our findings establish $\alpha$-WP$_2$ as a new reference material for exploring the XMR phenomena.Comment: 18 pages, 12 figure

Convolutional Neural Networks and Feature Fusion for Flow Pattern Identification of the Subsea Jumper

The gas–liquid two-phase flow patterns of subsea jumpers are identified in this work using a multi-sensor information fusion technique, simultaneously collecting vibration signals and electrical capacitance tomography of stratified flow, slug flow, annular flow, and bubbly flow. The samples are then processed to obtain the data set. Additionally, the samples are trained and learned using the convolutional neural network (CNN) and feature fusion model, which are built based on experimental data. Finally, the four kinds of flow pattern samples are identified. The overall identification accuracy of the model is 95.3% for four patterns of gas–liquid two-phase flow in the jumper. Through the research of flow profile identification, the disadvantages of single sensor testing angle and incomplete information are dramatically improved, which has a great significance on the subsea jumper’s operation safety.publishedVersio