experimentalsimulationoftheunruheffectonannmrquantumsimulator
文献类型:期刊论文
作者 | Jin Fangzhou1; Chen Hongwei2; Rong Xing1; Zhou Hui1; Shi Mingjun1; Zhang Qi1; Ju Chenyong1; Cai Yifu1; Luo Shunlong3![]() |
刊名 | sciencechinaphysicsmechanicsastronomy
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出版日期 | 2016 |
卷号 | 59期号:3页码:8 |
ISSN号 | 1674-7348 |
英文摘要 | The Unruh effect is one of the most fundamental manifestations of the fact that the particle content of a field theory is observer dependent. However, there has been so far no experimental verification of this effect, as the associated temperatures lie far below any observable threshold. Recently, physical phenomena, which are of great experimental challenge, have been investigated by quantum simulations in various fields. Here we perform a proof-of-principle simulation of the evolution of fermionic modes under the Unruh effect with a nuclear magnetic resonance (NMR) quantum simulator. By the quantum simulator, we experimentally demonstrate the behavior of Unruh temperature with acceleration, and we further investigate the quantum correlations quantified by quantum discord between two fermionic modes as seen by two relatively accelerated observers. It is shown that the quantum correlations can be created by the Unruh effect from the classically correlated states. Our work may provide a promising way to explore the quantum physics of accelerated systems. |
语种 | 英语 |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/46445] ![]() |
专题 | 应用数学研究所 |
作者单位 | 1.中国科学技术大学 2.中国科学院强磁场科学中心 3.中国科学院数学与系统科学研究院 |
推荐引用方式 GB/T 7714 | Jin Fangzhou,Chen Hongwei,Rong Xing,et al. experimentalsimulationoftheunruheffectonannmrquantumsimulator[J]. sciencechinaphysicsmechanicsastronomy,2016,59(3):8. |
APA | Jin Fangzhou.,Chen Hongwei.,Rong Xing.,Zhou Hui.,Shi Mingjun.,...&Du Jiangfeng.(2016).experimentalsimulationoftheunruheffectonannmrquantumsimulator.sciencechinaphysicsmechanicsastronomy,59(3),8. |
MLA | Jin Fangzhou,et al."experimentalsimulationoftheunruheffectonannmrquantumsimulator".sciencechinaphysicsmechanicsastronomy 59.3(2016):8. |
入库方式: OAI收割
来源:数学与系统科学研究院
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