Error tolerance of the BosonSampling model for linear optics quantum computing

Physics – Quantum Physics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

6 pages, 3 figures

Scientific paper

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.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Error tolerance of the BosonSampling model for linear optics quantum computing does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Error tolerance of the BosonSampling model for linear optics quantum computing, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Error tolerance of the BosonSampling model for linear optics quantum computing will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-727798

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.