Charge-state lifetimes of single molecules on ultrathin insulating films

In scanning tunneling microscopy (STM) experiments of molecules on insulating films, tunneling through molecular resonances implies transiently charging the molecule. The transition back to the charge ground state by tunneling through the insulating film is crucial, for example, for understanding STM-induced electroluminescence. Here, using STM, we report on the charge-state lifetimes of individual molecules adsorbed on NaCl films of different thicknesses on Cu(111) and Au(111). To that end, we approached the tip to the molecule at resonant tunnel conditions up to a regime where charge transport was limited by tunneling through the NaCl film. The resulting saturation of tunnel current is a direct measure of the molecule's charge-state lifetime, thus providing a means to study charge and, thereby, exciton dynamics. A comparison of anion and cation lifetimes on different substrates reveals the critical role of the level alignment with the insulator's conduction and valence band, and the metal-insulator interface state

Efficient Multi-Task Scene Analysis with RGB-D Transformers

Scene analysis is essential for enabling autonomous systems, such as mobile robots, to operate in real-world environments. However, obtaining a comprehensive understanding of the scene requires solving multiple tasks, such as panoptic segmentation, instance orientation estimation, and scene classification. Solving these tasks given limited computing and battery capabilities on mobile platforms is challenging. To address this challenge, we introduce an efficient multi-task scene analysis approach, called EMSAFormer, that uses an RGB-D Transformer-based encoder to simultaneously perform the aforementioned tasks. Our approach builds upon the previously published EMSANet. However, we show that the dual CNN-based encoder of EMSANet can be replaced with a single Transformer-based encoder. To achieve this, we investigate how information from both RGB and depth data can be effectively incorporated in a single encoder. To accelerate inference on robotic hardware, we provide a custom NVIDIA TensorRT extension enabling highly optimization for our EMSAFormer approach. Through extensive experiments on the commonly used indoor datasets NYUv2, SUNRGB-D, and ScanNet, we show that our approach achieves state-of-the-art performance while still enabling inference with up to 39.1 FPS on an NVIDIA Jetson AGX Orin 32 GB.Comment: To be published in IEEE International Joint Conference on Neural Networks (IJCNN) 202

String Physics and Black Holes

In these lectures we review the quantum physics of large Schwarzschild black holes. Hawking's information paradox, the theory of the stretched horizon and the principle of black hole complementarity are covered. We then discuss how the ideas of black hole complementarity may be realized in string theory. Finally, arguments are given that the world may be a hologram. Lectures delivered at ICTP Spring School on String Theory, Gauge Theory, and Quantum Gravity, 1995.Comment: 20 pages, Latex (needs espcrc2.sty), 6 figure