Hankyu Lee | Searcharxiv

arXiv2026

Imaging asymmetric Coulomb blockade phenomena across metallic nanoislands

Coulomb blockade (CB) arises in nanoscale systems with ultra-small capacitance, where discrete charging effects dictate electron transport, enabling wide-ranging applications based on single-electron transistors. Despite established electrostatic control of charge states in quantum dots and nanoislands, a rigorous quantitative link between junction parameters and the CB spectrum remains elusive. Here, using scanning tunneling spectroscopy, we investigate the spatial variation of CB in indium nanoislands on semiconducting black phosphorus. We observe spatially dispersive charging resonances whose trajectories exhibit a finite shift of the symmetry axis in bias as well as a pronounced asymmetric curvature. By comparing the experimental results with calculations based on orthodox theory, we show that these features originate from work function differences in the junctions, underscoring the importance of junction-specific electrostatics in nanoscale charge transport.

cond-mat.mes-hall↗

arXiv2019

Clear the Fog: Combat Value Assessment in Incomplete Information Games with Convolutional Encoder-Decoders

StarCraft, one of the most popular real-time strategy games, is a compelling environment for artificial intelligence research for both micro-level unit control and macro-level strategic decision making. In this study, we address an eminent problem concerning macro-level decision making, known as the 'fog-of-war', which rises naturally from the fact that information regarding the opponent's state is always provided in the incomplete form. For intelligent agents to play like human players, it is obvious that making accurate predictions of the opponent's status under incomplete information will increase its chance of winning. To reflect this fact, we propose a convolutional encoder-decoder architecture that predicts potential counts and locations of the opponent's units based on only partially visible and noisy information. To evaluate the performance of our proposed method, we train an additional classifier on the encoder-decoder output to predict the game outcome (win or lose). Finally, we designed an agent incorporating the proposed method and conducted simulation games against rule-based agents to demonstrate both effectiveness and practicality. All experiments were conducted on actual game replay data acquired from professional players.

cs.AI↗