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arXiv 0908.0708quant-ph
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从简单阿贝尔模型设计复杂拓扑存储器

Engineering complex topological memories from simple Abelian models

James R. Wootton, Ville Lahtinen, Benoit Doucot, Jiannis K. Pachos

摘要:

在三维空间中,粒子被限制为玻色子或费米子统计。二维系统,另一方面,可以支持任何准粒子表现出更丰富的统计行为。量子计算的一个令人兴奋的提议是使用任意子统计来操纵信息。由于这种统计演化只依赖于拓扑特征,因此所产生的计算本质上是对错误的弹性。所谓的非阿贝尔任意子是最有希望的量子计算,但他们的物理实现可能会被证明是复杂的。然而,阿贝尔任意子更容易在理论上理解和实验上实现。在这里,我们表明,复杂的拓扑记忆的启发,非阿贝尔任意子可以工程阿贝尔模型。我们明确地展示了控制程序的编码和操作的量子信息在特定的晶格模型,可以在实验室中实现。这弥合了任意子量子计算的需求与最先进技术的潜力之间的差距。

英文摘要:

In three spatial dimensions, particles are limited to either bosonic or fermionic statistics. Two-dimensional systems, on the other hand, can support anyonic quasiparticles exhibiting richer statistical behaviours. An exciting proposal for quantum computation is to employ anyonic statistics to manipulate information. Since such statistical evolutions depend only on topological characteristics, the resulting computation is intrinsically resilient to errors. So-called non-Abelian anyons are most promising for quantum computation, but their physical realization may prove to be complex. Abelian anyons, however, are easier to understand theoretically and realize experimentally. Here we show that complex topological memories inspired by non-Abelian anyons can be engineered in Abelian models. We explicitly demonstrate the control procedures for the encoding and manipulation of quantum information in specific lattice models that can be implemented in the laboratory. This bridges the gap between requirements for anyonic quantum computation and the potential of state-of-the-art technology.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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