Yong Zeng 1 Peng Xu 1 Xiaodong He 1 Yangyang Liu 1 Min Liu 1 Jin Wang 1 D. j. Papoular 2 G. v. Shlyapnikov 3 Mingsheng Zhan 1
Physical Review Letters, American Physical Society, 2017, 119 (16), 〈10.1103/PhysRevLett.119.160502〉
Quantum entanglement is crucial for simulating and understanding exotic physics of strongly correlated many-body systems, such as high–temperature superconductors, or fractional quantum Hall states. The entanglement of non-identical particles exhibits richer physics of strong many-body correlations and offers more opportunities for quantum computation, especially with neutral atoms where in contrast to ions the interparticle interaction is widely tunable by Feshbach resonances. Moreover, the inter-species entanglement forms a basis for the properties of various compound systems, ranging from Bose-Bose mixtures to photosynthetic light-harvesting complexes. So far, the inter-species entanglement has only been obtained for trapped ions. Here we report on the experimental realization of entanglement of two neutral atoms of different isotopes. A ${}^{87}\mathrm{Rb}$ atom and a ${}^{85}\mathrm{Rb}$ atom are confined in two single–atom optical traps separated by 3.8 $\mu$m. Creating a strong Rydberg blockade, we demonstrate a heteronuclear controlled–NOT (C–NOT) quantum gate and generate a heteronuclear entangled state, with raw fidelities $0.73 \pm 0.01$ and $0.59 \pm 0.03$, respectively. Our work, together with the technologies of single–qubit gate and C–NOT gate developed for identical atoms, can be used for simulating any many–body system with multi-species interactions. It also has applications in quantum computing and quantum metrology, since heteronuclear systems exhibit advantages in low crosstalk and in memory protection.
- 1. State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, 430071 China
- 2. LPTM – Laboratoire de Physique Théorique et Modélisation
- 3. LPTMS – Laboratoire de Physique Théorique et Modèles Statistiques