Dynamic synthesis of Heisenberg-limited spin squeezing

Spin squeezing is a key resource in quantum metrology, allowing improvements of measurement signal-to-noise ratio. Its generation is a challenging task because the experimental realization of the required squeezing interaction remains difficult. Here, we propose a generic scheme to synthesize spin squeezing in non-squeezing systems. By using periodical rotation pulses, the original non-squeezing interaction can be transformed into squeezing interaction, with significantly enhanced interaction strength. The sign of the interaction coefficient is also flippable, facilitating time-reversal readout protocol for nonlinear interferometers. The generated spin squeezing is capable of achieving the Heisenberg limit with measurement precision ∝ 1/N for N particles and its robustness to noises of pulse areas and separations has been verified as well. This work offers a path to extending the scope of Heisenberg-limited quantum precision measurements in non-squeezing systems.

Contemporary Approach to the Porosity of Dental Materials and Methods of Its Measurement

Porosity is an important parameter for characterizing the microstructure of solids that corresponds to the volume of the void space, which may contain fluid or air, over the total volume of the material. Many materials of natural and technically manufactured origin have a large number of voids in their internal structure, relatively small in size, compared to the characteristic dimensions of the body itself. Thus, porosity is an important feature of industrial materials, but also of biological ones. The porous structure affects a number of material properties, such as sorption capacity, as well as mechanical, thermal, and electrical properties. Porosity of materials is an important factor in research on biomaterials. The most popular materials used to rebuild damaged tooth tissues are composites and ceramics, whilst titanium alloys are used in the production of implants that replace the tooth root. Research indicates that the most comprehensive approach to examining such materials should involve an analysis using several complementary methods covering the widest possible range of pore sizes. In addition to the constantly observed increase in the resolution capabilities of devices, the development of computational models and algorithms improving the quality of the measurement signal remains a big challenge.

Research on the Cooperative Detection of Stochastic Resonance and Chaos for Weak SNR Signals in Measurement While Drilling

In the process of drilling, severe downhole vibration causes attitude measurement sensors to be erroneous; the errors will accumulate gradually during the inclination calculation. As a result, the ultimate well path could deviate away from the planned trajectory. In order to solve this problem, this paper utilized the stochastic resonance (SR) and chaos phase transition (CPT) produced by the second-order Duffing system to identify the frequency and estimate the parameters of the signal during measurement while drilling. Firstly, the idea of a variable-scale is introduced in order to reconstruct the frequency of the attitude measurement signal, and an SR frequency detection model based on a scale transformation Duffing system is established in order to meet the frequency limit condition of the SR. Then, an attitude measurement signal with a known frequency value is input into the Duffing chaos system, and the scale transformation is used again to make the frequency value meet the parameter requirement of chaos detection. Finally, two Duffing oscillators with different initial phases of their driving signal are combined in order to estimate the amplitude and phase parameters of the measurement signal by using their CPT characteristics. The results of the laboratory test and the field-drilling data demonstrated that the proposed algorithm has good immunity to the interference noise in the attitude measurement sensor, improving the solution accuracy of the inclination in a severe noise environment and thus ensuring the dynamic stability of the well trajectory.

Ground semi-physical simulation experiment study of one-dimensional drag-free control

Drag-free control is one of the key technologies for the verification of Taiji-1 satellite. In the direction of sensitive axis, the drag-free controller receives the measurement signal from the high-precision gravitational reference sensor on the satellite, and instructs the micro-thruster system to counteract the disturbance force acting on the sensitive axis, so that the microgravity level in the sensing axis direction of the satellite can reach the order of 10[Formula: see text] m/s2 in the measurement band. In order to fully verify the drag-free control system, a ground one-dimensional drag-free semi-physical simulation system is built to simulate the performance of various payloads in the drag-free control loop, and to verify the performance and technical targets that the drag-free control system can achieve in the ground control loop. Through the small angle approximation, the equivalent relationship between the rotation of the experimental model and the translational motion of the experimental satellite in the direction of drag-free is demonstrated. In the condition of neglecting the stiffness and damping of the suspended pendulum, the parameters of the suspended pendulum are designed according to the principle of equal acceleration, and their effectiveness is verified by numerical simulation. According to the operation mode of on orbit drag-free control, the ground drag-free experimental scheme and drag-free controller are designed, and the experimental research and verification are carried out. The results show that the controller can effectively control the displacement and acceleration of the experimental model, and also can effectively suppress the disturbance of certain amplitude and frequency.

An IoT-Based Platform for Rehabilitation Monitoring and Biosignal Identification

This article describes how as a result of technological advances of the embedded system, the Internet-of-Things (IoT) has created a wealth of new applications and tailored solutions, even in the area of health and medical technology. The integration of state-of-the-art IoT-systems in an existing prototype platform for biosignal acquisition, identification, and prosthesis control provides new applications for prevention and rehabilitation monitoring. This article concentrates on an IoT-based platform for rehabilitation monitoring and biosignal identification. The IoT-characteristics for the application in the area of medical technology are discussed and the integration of such IoT-modules in the given architecture is introduced. Based on this extended architecture, new applications in the field of biosignal measurement, signal processing and biosignal monitoring are presented. Some results of a rehabilitation monitoring system, based on a self-designed IoT-module, integrated in the whole platform, are shown.