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Scalable quantum computing architecture with mixed species ion chains

机译:具有混合物种离子链的可扩展量子计算架构

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We describe our work on trapping, cooling and detecting mixed ion species for a scalable ion trap quantum information processing architecture. These mixed species chains in linear RF traps may help solve several problems with scaling ion trap quantum computation to large numbers of qubits. Initial temperature measurements of linear Coulomb crystals containing barium and ytterbium ions indicate that the mass difference does not significantly impede sympathetic cooling of normal modes that couple well to the coolant ions (Ba in our case). Average motional occupation numbers are estimated to be 10 to 20 quanta per mode for these well cooled modes for chains with small numbers of ions, consistent with the Doppler limit temperature. For normal modes that do not couple significantly to the coolant atoms, the occupation numbers are significantly higher, of order several thousand. Strategies for better cooling of these modes are discussed. Further, we are working to implement these techniques in microfabricated surface traps in order to exercise greater control over ion chain ordering and positioning.
机译:我们描述了在可伸缩离子阱量子信息处理体系结构中捕获,冷却和检测混合离子物种的工作。线性RF阱中的这些混合物种链可以帮助解决将离子阱量子计算缩放到大量qubit的几个问题。包含钡和离子的线性库仑晶体的初始温度测量结果表明,质量差不会显着阻碍与冷却剂离子(在本例中为Ba)耦合的正常模式的同情冷却。对于具有少量离子的链,这些良好冷却的模式的平均运动职业数估计为每个模式10至20量子,与多普勒极限温度一致。对于没有明显耦合到冷却剂原子的普通模式,占有数要高得多,约为几千。讨论了更好地冷却这些模式的策略。此外,我们正在努力在微细加工的表面陷阱中实施这些技术,以便对离子链的排列和定位进行更大的控制。

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