Driven Boson Sampling
Sonja Barkhofen, Tim J. Bartley, Linda Sansoni, Regina Kruse, Craig S., Hamilton, Igor Jex, Christine Silberhorn

TL;DR
Driven boson sampling introduces photons within the network to significantly enhance input state generation rates and signal quality, advancing the feasibility of quantum advantage in boson sampling tasks.
Contribution
It proposes a novel driven boson sampling method that boosts input photon rates and reduces noise, surpassing scattershot boson sampling with heralded sources.
Findings
Approximate e-fold increase in input rate over scattershot boson sampling.
Significant improvement in signal-to-noise ratio for larger systems.
Reduces need for photon number resolution in heralding process.
Abstract
Sampling the distribution of bosons that have undergone a random unitary evolution is strongly believed to be a computationally hard problem. Key to outperforming classical simulations of this task is to increase both the number of input photons and the size of the network. We propose driven boson sampling, in which photons are input within the network itself, as a means to approach this goal. When using heralded single-photon sources based on parametric down-conversion, this approach offers an -fold enhancement in the input state generation rate over scattershot boson sampling, reaching the scaling limit for such sources. More significantly, this approach offers a dramatic increase in the signal-to-noise ratio with respect to higher-order photon generation from such probabilistic sources, which removes the need for photon number resolution during the heralding process as the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
