<i>López–Ruiz–Mancini–Calbet</i>–Rényi Complexity of Hydrogenic Impurity States in the InP Semiconductor Quantum Dot
The López–Ruiz–Mancini–Calbet (LMC)–Rényi complexity is a significant metric for quantifying the informational characteristics of quantum states, playing a crucial role in quantum information science and quantum technology applications. This study investigates the LMC‐Rényi complexity of hydrogenic impurity states in the InP semiconductor quantum dot (QD). Through calculating the LMC‐Rényi complexity for two specific cases of Rényi entropy orders, an optical balance between localization and entropy uncertainty for given impurity states is demonstrated. Furthermore, we examine the temperature dependence of the LMC‐Rényi complexity for hydrogenic impurity states in the InP QD. It is intriguing to discover that the LMC‐Rényi complexity demonstrates the characteristic of translation invariance under temperature variations. The investigation of temperature effects on the LMC‐Rényi complexity of hydrogenic impurity states provides valuable insights into how thermal fluctuations influence quantum states, thereby contributing to the optimization of quantum dot performance in various technological applications. This study reveals that the LMC‐Rényi complexity of hydrogenic impurity states in the QD can be effectively tuned by adjusting entropy orders and external factors, including temperature and quantum size effects. This research provides valuable guidance for experimental studies in quantum information measurement and the development of advanced optoelectronic devices.
Authors
- Wen Xu (ORCID: https://orcid.org/0000-0003-4698-5899)
- Tian‐tian Tang
- Dehua Wang
Institutions
- Ludong University (CN)
- Yantai Nanshan University (CN)
Publication Details
- Journal
- physica status solidi (b)
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1002/pssb.202500010
- Primary Topic
- Semiconductor Quantum Structures and Devices
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province