Programmable Hamiltonian engineering with quadratic quantum Fourier transform

Quantum Fourier transform (QFT) is a widely used building block for quantum algorithms, whose scalable implementation is challenging in experiments. Here, we propose a protocol of quadratic quantum Fourier transform (QQFT), considering cold atoms confined in an optical lattice. This QQFT is equivalent to QFT in the single-particle subspace, and produces a different unitary operation in the entire Hilbert space. We show this QQFT protocol can be implemented using programmable laser potential with the digital-micromirror-device techniques recently developed in the experiments. The QQFT protocol enables programmable Hamiltonian engineering, and allows quantum simulations of Hamiltonian models, which are difficult to realize with conventional approaches. The flexibility of our approach is demonstrated by performing quantum simulations of one-dimensional Poincar\'{e} crystal physics and two-dimensional topological flat bands, where the QQFT protocol effectively generates the required long-range tunnelings despite the locality of the cold atom system. We find the discrete Poincar\'{e} symmetry and topological properties in the two examples respectively have robustness against a certain degree of noise that is potentially existent in the experimental realization. We expect this approach would open up wide opportunities for optical lattice based programmable quantum simulations.Comment: 10 pages, 5 figure

RGB-D-based Stair Detection using Deep Learning for Autonomous Stair Climbing

Stairs are common building structures in urban environments, and stair detection is an important part of environment perception for autonomous mobile robots. Most existing algorithms have difficulty combining the visual information from binocular sensors effectively and ensuring reliable detection at night and in the case of extremely fuzzy visual clues. To solve these problems, we propose a neural network architecture with RGB and depth map inputs. Specifically, we design a selective module, which can make the network learn the complementary relationship between the RGB map and the depth map and effectively combine the information from the RGB map and the depth map in different scenes. In addition, we design a line clustering algorithm for the postprocessing of detection results, which can make full use of the detection results to obtain the geometric stair parameters. Experiments on our dataset show that our method can achieve better accuracy and recall compared with existing state-of-the-art deep learning methods, which are 5.64% and 7.97%, respectively, and our method also has extremely fast detection speed. A lightweight version can achieve 300 + frames per second with the same resolution, which can meet the needs of most real-time detection scenes

Inspection of delamination defect in first wall panel of Tokamak device by using laser infrared thermography technique

First wall panels (FWPs), which adjoin the inner wall of the blanket modules in the vacuum vessel (VV) of a Tokamak device, are in structures of multilayer bounded together with a solid welding technique in order to perform its heat exchange, VV protection, and neutron breeding functions. The quality of the welding joint between layers is the key factor for FWP integrity. In order to conduct online inspection of the delamination defect in the FWPs, a nondestructive testing (NDT) method capable to detect delamination defect without accessing into the VV is required. In this paper, the feasibility of the laser infrared thermography (LIRT) testing NDT method was investigated experimentally for this purpose. To clarify its detectability under practical VV environment, inspections of several inspection modes were conducted based on the practical structure of FWP and VV of the EAST Tokamak device, i.e., modes of different distances and angles of FWPs toward the LIRT transducers. In practice, an LIRT testing system was established and several double-layered plate specimens with different artificial delamination defects were inspected under the selected testing conditions. Through thermography signal reconstruction, an image processing algorithm was proposed and adopted to enhance the defect detectability. From the results of different inspection modes, it was found that the angle factor may worsen the inspection precision and reduce the detectability for delamination defects in case of big defect depth-to-width ratio, even though the LIRT method is still applicable for inspection of relative large defects in FWP. Finally, the detectability in different inspection modes was clarified, which proved the feasibility of LIRT for FWP online inspection

Quantitative evaluation of surface crack depth with laser spot thermography

In this study, a numerical method based on finite element method (FEM) is developed to simulate the heat flow generated by laser spot source and investigate the relationship between crack size and temperature distribution. The feasibility of the simulation method is validated by experiments both in time and spatial domains. The simulation and experiment results also show that the crack depth can be described by two characteristic parameters. Furthermore, a quantitative retrieval method based on neural network is developed for the crack depth evaluation by using the parameters. By using the proposed method, crack depth can be determined only by analyzing measured surface temperature values

On Input-to-State Stability of Impulsive Stochastic Systems with Time Delays

This paper is concerned with pth moment input-to-state stability (p-ISS) and stochastic input-to-state stability (SISS) of impulsive stochastic systems with time delays. Razumikhin-type theorems ensuring p-ISS/SISS are established for the mentioned systems with external input affecting both the continuous and the discrete dynamics. It is shown that when the impulse-free delayed stochastic dynamics are p-ISS/SISS but the impulses are destabilizing, the p-ISS/SISS property of the impulsive stochastic systems can be preserved if the length of the impulsive interval is large enough. In particular, if the impulse-free delayed stochastic dynamics are p-ISS/SISS and the discrete dynamics are marginally stable for the zero input, the impulsive stochastic system is p-ISS/SISS regardless of how often or how seldom the impulses occur. To overcome the difficulties caused by the coexistence of time delays, impulses, and stochastic effects, Razumikhin techniques and piecewise continuous Lyapunov functions as well as stochastic analysis techniques are involved together. An example is provided to illustrate the effectiveness and advantages of our results