Observation of hybrid higher-order skin-topological effect in non-Hermitian topolectrical circuits

Robust boundary states epitomize how deep physics can give rise to concrete experimental signatures with technological promise. Of late, much attention has focused on two distinct mechanisms for boundary robustness—topological protection, as well as the non-Hermitian skin effect. In this work, we report the experimental realizations of hybrid higher-order skin-topological effect, in which the skin effect selectively acts only on the topological boundary modes, not the bulk modes. Our experiments, which are performed on specially designed non-reciprocal 2D and 3D topolectrical circuit lattices, showcases how non-reciprocal pumping and topological localization dynamically interplays to form various states like 2D skin-topological, 3D skin-topological-topological hybrid states, as well as 2D and 3D higher-order non-Hermitian skin states. Realized through our highly versatile and scalable circuit platform, theses states have no Hermitian nor lower-dimensional analog, and pave the way for applications in topological switching and sensing through the simultaneous non-trivial interplay of skin and topological boundary localizations.

Observation of hybrid higher-order skin-topological effect in non-Hermitian topolectrical circuits

Robust boundary states epitomize how deep physics can give rise to concrete experimental signatures with technological promise. Of late, much attention has focused on two distinct mechanisms for boundary robustness - topological protection, as well as the non-Hermitian skin effect. In this work, we report the first experimental realizations of hybrid higher-order skin-topological effect, in which the skin effect selectively acts only on the topological boundary modes, not the bulk modes. Our experiments, which are performed on specially designed non-reciprocal 2D and 3D topolectrical circuit lattices, showcases how non-reciprocal pumping and topological localization dynamically interplays to form various novel states like 2D skin-topological, 3D skin-topological-topological hybrid states, as well as 2D and 3D higher-order non-Hermitian skin states. Realized through our highly versatile and scalable circuit platform, theses states have no Hermitian nor lower-dimensional analog, and pave the way for new applications in topological switching and sensing through the simultaneous non-trivial interplay of skin and topological boundary localizations.

ERF-IMCS: An Efficient and Robust Framework with Image-Based Monte Carlo Scheme for Indoor Topological Navigation

Conventional approaches to global localization and navigation mainly rely on metric maps to provide precise geometric coordinates, which may cause the problem of large-scale structural ambiguity and lack semantic information of the environment. This paper presents a scalable vision-based topological mapping and navigation method for a mobile robot to work robustly and flexibly in large-scale environment. In the vision-based topological navigation, an image-based Monte Carlo localization method is presented to realize global topological localization based on image retrieval, in which fine-tuned local region features from an object detection convolutional neural network (CNN) are adopted to perform image matching. The combination of image retrieval and Monte Carlo provide the robot with the ability to effectively avoid perceptual aliasing. Additionally, we propose an effective visual localization method, simultaneously employing the global and local CNN features of images to construct discriminative representation for environment, which makes the navigation system more robust to the interference of occlusion, translation, and illumination. Extensive experimental results demonstrate that ERF-IMCS exhibits great performance in the robustness and efficiency of navigation.

Vision and Wi-Fi fusion in probabilistic appearance-based localization

This article introduces an indoor topological localization algorithm that uses vision and Wi-Fi signals. Its main contribution is a novel way of merging data from these sensors. The designed system does not require knowledge of the building plan or the positions of the Wi-Fi access points. By making the Wi-Fi signature suited to the FABMAP algorithm, this work develops an early fusion framework that solves global localization and kidnapped robot problems. The resulting algorithm has been tested and compared with FABMAP visual localization, over data acquired by a Pepper robot in three different environments: an office building, a middle school, and a private apartment. Numerous runs of different robots have been realized over several months for a total covered distance of 6.4 km. Constraints were applied during acquisitions to make the experiments fitted to real use cases of Pepper robots. Without any tuning, our early fusion framework outperforms visual localization in all testing situations and with a significant margin in environments where vision faces problems such as moving objects or perceptual aliasing. In such conditions, 90.6% of estimated localizations are less than 5 m away from ground truth with our early fusion framework compared with 77.6% with visual localization. Furthermore, compared with other classical fusion strategies, the early fusion framework produces the best localization results because in all tested situations, it improves visual localization results without damaging them where Wi-Fi signals carry little information.

Bulk, Surface and Interface Promotion of Co3O4 for the Low-Temperature N2O Decomposition Catalysis

Nanocrystalline cobalt spinel has been recognized as a very active catalytic material for N2O decomposition. Its catalytic performance can be substantially modified by proper doping with alien cations with precise control of their loading and location (spinel surface, bulk, and spinel-dopant interface). Various doping scenarios for a rational design of the optimal catalyst for low-temperature N2O decomposition are analyzed in detail and the key reactivity descriptors are identified (content and topological localization of dopants, their redox vs. non-redox nature and catalyst work function). The obtained results are discussed in the broader context of the available literature data to establish general guidelines for the rational design of the N2O decomposition catalyst based on a cobalt spinel platform.