Vol 40, No 2 (2019)

We develop an approach where the quantum system states and quantum observables are described as in classical statistical mechanics – the states are identified with probability distributions and observables, with random variables. An example of the spin-1/2 state is considered. We show that the triada of Malevich’s squares can be used to illustrate the qubit state. We formulate the superposition principle of quantum states in terms of probabilities determining the quantum states. New formulas for nonlinear addition rules of probabilities providing the probabilities associated with the interference of quantum states are obtained. The evolution equation for quantum states is given in the form of a kinetic equation for the probability distribution identified with the state.

We map the 2+1 Dirac–Moshinsky oscillator (2+1 DMO) coupled to an external isospin field onto the Jaynes–Cummings model (JCM), which describes the interaction between two two-level systems and a quantum single-mode field. We obtain the time-dependent wave function and the density matrix in two cases. As an initial state, we consider the quantum number state in the first case and the coherent state in the second case. We study the effect of the detuning parameter and the coherence angle on the entanglement and the population inversion. The obtained results show that the coherent state provides a better description than the number state for both the entanglement and the population inversion.

We describe theoretically a possible application of advanced noise-filtering technique to X-ray imaging of low contrast objects, using the example of X-ray studies of laser fusion capsules. Based on the concept of the nonlinear anisotropic diffusion equation, we develop a computer code which uses noise-driven parameterization to optimize the image denoising process. The computation results demonstrate an effective noise filtering while preserving the edge pattern of noisy images obtained with the original contrast as low as ~1%.

To enhance the model integrity in the fast three-dimensional (3D) reconstruction of complex indoor scenes, we propose an automatic acquisition method of point cloud data and RGB images at different heights, using height-adjustable mobile LIDAR (a system for light identification detection and ranging) for indoor scenes and design a complete reconstruction workflow. In the data acquisition and processing phases, some strategies and algorithms are used to eliminate the redundant data of a point cloud, which can effectively reduce the computation burden of subsequent processes such as the point cloud registration. Our experimental results further demonstrate that this method not only enhances the integrity of indoor scene models and visual effects of model roaming at different heights but also improves the speed and accuracy of 3D reconstruction.

We report on a passively mode-locked YVO₄/Nd:YVO₄ composite crystal laser using a semiconductor saturable absorber mirror. At a pump power of 21.39 W, we achieve a 3.51 W average output power from a continuous wave mode-locked laser with a repetition rate of passively mode-locked pulse of 89 MHz and a pulse width of 38.3 ps. The pulse energy and peak power are 39.4 nJ and 1.03 kW, respectively. Our experiment results show that a composite crystal is an excellent laser crystal for mode locking.

We design high-power AlGaInP laser diodes emitting at ~640 nm. AlN and SiC submounts are used as heat sinks for the laser chips. The laser diode with SiC submount showed a higher thermal rollover power of 3.9 W and higher maximum conversion efficiency of 39% at 25°C. In the range of 15 – 35°C, the two types of lasers have similar characteristic temperature T₀. At higher temperatures beyond 40°C, the laser chip mounted on SiC revealed an improved T₀, compared to that on AlN. By measuring the wavelength drift of the two types of lasers, we estimate the thermal resistance to be 9.1 K/W for the laser diode on AlN and 5.6 K/W for the laser diode on SiC.