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复杂的氧化物异构结构中高度稳定的两级电流波动
Doyeop Kim1, Jung-Woo Lee2, Jihyun Lim3
1Department of Energy Systems Research, Ajou University, Suwon, Republic of Korea.
Nature communications
|July 2, 2025
概括
来自氧化物异构的稳定随机电报噪声 (RTN) 为安全的随机数生成提供了可靠的源. 这一突破使得强大的随机位链能够用于先进的计算和密码学.
科学领域:
- 材料科学 材料科学 材料科学
- 凝聚物质物理学 凝聚物质物理学
- 量子计算是一种量子计算.
背景情况:
- 介电氧化物中的双层系统是随机数发生器有前途的源.
- 这些系统的随机电报噪声 (RTN) 对于生成用于计算和加密的随机比特字符串至关重要.
- 经典的氧化物系统面临着由于缺陷迁移和超稳定状态的不稳定性问题,阻碍了可靠的RTN生成.
研究的目的:
- 为可靠的随机数生成提供一个稳定的两级量子系统.
- 为了提高系统稳定性,研究使用互补的阴离子和离子点缺陷.
- 展示在随机机器学习算法中生成的随机位链的应用.
主要方法:
- 制造一个SrRuO3/LaAlO3/Nb合的SrTiO3异构结构.
- 利用氧气空缺和反位点Ti缺陷作为补充点缺陷.
- 分析两级电流波动的时间电子定位和库伦相互作用.
- 为图像超分辨率任务生成和测试随机位链.
主要成果:
- 证明了基于室温异构的稳定双层量子系统.
- 观察到高度稳定的RTN类电流信号,归因于缺陷相互作用.
- 从稳定的波动中成功生成随机位链.
- 证实了这些随机位串在图像超分辨率的随机机器学习中的适用性.
结论:
- 配有SrRuO3/LaAlO3/Nb的SrTiO3异构结构提供了一个稳定可靠的源.
- 阴离子和离子点缺陷之间的互补相互作用是设计稳定的基于氧化物的电子系统的关键.
- 这种方法为开发强大的基于硬件的先进技术随机数生成器提供了一条途径.
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