Ringklein2928

The maximum enhancement factor of the chiral molecular solutions could reach up to 3500 times in the THz region. These results can help to design dynamically adjustable THz chiral sensors and promote their application in biological monitoring and asymmetric catalysis.We propose an algorithm to track the rotation of state of polarization (RSOP) for short-distance coherent subcarrier-multiplexing systems. 3 pilot tones are used to estimate RSOP matrices on a block-by-block basis and recover phase noise as well. An ultra-fast RSOP tracking ability using the proposed algorithm is demonstrated by experiment. Specifically, the bit error rate increases from 2.3×10-3 to 5.6×10-3 when the RSOP speed increases from 0 rad/s to 50 Mrad/s. We also demonstrate the robustness of the algorithm against polarization mode dispersion and polarization dependent loss.Fast and noise-suppressed incoherent coded aperture correlation holographic imaging is proposed, which is utilized by employing an annular sparse coded phase mask together with adaptive phase-filter cross-correlation reconstruction method. Thus the proposed technique here is coined as adaptive interferenceless coded aperture correlation holography (AI-COACH). In AI-COACH, an annular sparse coded phase mask is first designed and generated by the Gerchberg-Saxton algorithm for suppressing background noise during reconstruction. In order to demonstrate the three-dimensional and sectional imaging capabilities of the AI-COACH system, the imaging experiments of 3D objects are designed and implemented by dual-channel optical configuration. One resolution target is placed in the focal plane of the system as input plane and ensured Fourier transform configuration, which is employed as reference imaging plane, and moved the other resolution target to simulate different planes of a three-dimensional object. One point spread hologram (PSH) and multiple object-holograms without phase-shift at different axial positions are captured by single-exposure sequentially with the annular sparse CPMs. A complex-reconstruction method is developed to obtain adaptively high-quality reconstructed images by employing the cross-correlation of PSH and OH with optimized phase filter. The imaging performance of AI-COACH is investigated by imaging various type of objects. The research results show that AI-COACH is adaptive to different experimental conditions in the sense of autonomously finding optimal parameters during reconstruction procedure and possesses the advantages of fast and adaptive imaging with high-quality reconstructions.High-precision optical components with complex shapes or microstructures have been extensively used in numerous fields such as biomedicine, energy and aerospace. In order to accurately achieve the specific functions of the components, the form accuracy and uniform surface quality need to reach an ever-high level. To achieve this, ultra-precision normal grinding is used for machining various types of complex optical surfaces. However, the intricate variation of the workpiece curvature and grinding wheel vibration gives rise to great challenges to obtain higher precision and uniform surface conditions. In this study, the influence of curvature on surface topography generation has been investigated and a novel model of scallop height has been developed for surface topography generation in the normal grinding of the curved surface. In addition, the relative influence of the curvature is analyzed experimentally, in which the micro-waviness generation as a consequence of the unbalanced vibration of the grinding wheel is modeled and validated by experiments. Finally, the micro sinusoidal array with the setting value for scallop height is achieved by controlling the feed speed, which is determined by the local curvature of surface profile. The results indicated that the curvature variation posed a significant effect on surface uniformity and the model is valid to achieve surface scallop height control in the normal grinding effectively.Multiple works have applied deep learning to fringe projection profilometry (FPP) in recent years. However, to obtain a large amount of data from actual systems for training is still a tricky problem, and moreover, the network design and optimization is still worth exploring. In this paper, we introduce graphic software to build virtual FPP systems in order to generate the desired datasets conveniently and simply. The way of constructing a virtual FPP system is described in detail firstly, and then some key factors to set the virtual FPP system much closer to reality are analyzed. With the aim of accurately estimating the depth image from only one fringe image, we also design a new loss function to enhance the overall quality and detailed information is restored. And two representative networks, U-Net and pix2pix, are compared in multiple aspects. The real experiments prove the good accuracy and generalization of the network trained by the diverse data from our virtual systems and the designed loss, providing a good guidance for real applications of deep learning methods.We investigate scalar and vector multi-hump spatial solitons resulting from competing Kerr-like nonlinear responses excited in a nonlocal medium by either one or two (mutually incoherent) light beams. Two-color vector supermode solitons are more amenable to control but exhibit an intriguing form of spontaneous symmetry breaking in propagation.The stimulated Raman adiabatic passage shows an efficient technique that accurately transfers population between two discrete quantum states with the same parity in three-level quantum systems based on adiabatic evolution. This technique has widely theoretical and experimental applications in many fields of physics, chemistry, and beyond. Here, we present a general approach to robust stimulated Raman shortcut-to-adiabatic passage with invariant-based optimal control. By controlling the dynamical process, we inversely design a family of Hamiltonians with non-divergent Rabi frequencies that can realize fast and accurate population transfer from the first to the third level, while the systematic errors are largely suppressed in general. Furthermore, a detailed trade-off relation between the population of the intermediate state and the amplitudes of Rabi frequencies in the transfer process is illustrated. Cu-CPT22 These results provide an optimal route toward manipulating the evolution of three-level quantum systems in future quantum information processing.