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arxiv: 1111.2426 · v1 · pith:KKO4YJFYnew · submitted 2011-11-10 · 🪐 quant-ph

Error tolerance of the BosonSampling model for linear optics quantum computing

classification 🪐 quant-ph
keywords quantumsystemsclassicallyhardlikelymodelapproachcomputing
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Linear optics quantum computing (LOQC) is a promising approach to implementing scalable quantum computation (QC). However, this approach has very demanding physical resource requirements. Recently, Aaronson & Arkhipov showed that a simplified model, which avoids the requirement for fast feed-forward and post-selection, while likely not capable of solving BQP-complete problems efficiently, can solve an interesting sampling problem, believed to be classically hard. Loss and mode-mismatch are the dominant sources of error in such systems. We provide evidence that even lossy systems, or systems with mode-mismatch, are likely to be classically hard to simulate. This is of practical interest to experimentalists wishing to demonstrate such systems, since it suggests that even with errors in their implementation, they are likely implementing an algorithm which is classically hard to simulate. Our results also equivalently apply to the multi-walker quantum walk model.

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