Modeling Quantum Dot Systems as Random Geometric Graphs with Probability Amplitude-Based Weighted Links.
Lucas CuadraJosé Carlos Nieto-BorgePublished in: Nanomaterials (Basel, Switzerland) (2021)
This paper focuses on modeling a disorder ensemble of quantum dots (QDs) as a special kind of Random Geometric Graphs (RGG) with weighted links. We compute any link weight as the overlap integral (or electron probability amplitude) between the QDs (=nodes) involved. This naturally leads to a weighted adjacency matrix, a Laplacian matrix, and a time evolution operator that have meaning in Quantum Mechanics. The model prohibits the existence of long-range links (shortcuts) between distant nodes because the electron cannot tunnel between two QDs that are too far away in the array. The spatial network generated by the proposed model captures inner properties of the QD system, which cannot be deduced from the simple interactions of their isolated components. It predicts the system quantum state, its time evolution, and the emergence of quantum transport when the network becomes connected.
Keyphrases
- network analysis
- molecular dynamics
- magnetic resonance
- quantum dots
- contrast enhanced
- energy transfer
- sentinel lymph node
- resting state
- neural network
- body mass index
- lymph node
- physical activity
- magnetic resonance imaging
- monte carlo
- high throughput
- computed tomography
- sensitive detection
- weight gain
- early stage
- machine learning
- single cell
- electron transfer