2025/06/10 by Naoto Yokoi, Yokoi, Naoto, Yuki Tanaka +8 · 1 citation
Engineering · Physics and Astronomy · #Advancements in Semiconductor Devices and Circuit Design #FOS: Physical sciences #Mesoscale and Nanoscale Physics (cond-mat.mes-hall) #Quantum Physics (quant-ph) #Quantum and electron transport phenomena #Quantum many-body systems
paper · pdf · doi:10.48550/arxiv.2506.08617
openalex publication_date 2025/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A conditional diffusion model has been developed to analyze intricate conductance fluctuations called universal conductance fluctuations or quantum fingerprints appearing in quantum transport phenomena. The model reconstructs impurity arrangements and quantum interference patterns in nanometals by using magnetoconductance data, providing a novel approach to analyze complex data based on machine learning. In addition, we visualize the attention weights in the model, which efficiently extract information on the non-local correlation of the electron wave functions, and the score functions, which represent the force fields in the wave-function space.