Strategies for enhancing quantum entanglement by local photon subtraction
Tim J. Bartley, Philip J. D. Crowley, Animesh Datta, Joshua Nunn,, Lijian Zhang, Ian A. Walmsley

TL;DR
This paper analyzes various local photon subtraction strategies on two-mode squeezed states, considering imperfections and losses, to optimize entanglement gain and success probability for quantum communication applications.
Contribution
It develops a comprehensive framework incorporating losses and imperfections, comparing symmetric and asymmetric subtraction strategies, and identifying optimal parameters for entanglement enhancement.
Findings
Single-photon subtraction from one mode yields maximum entanglement gain in lossless conditions.
Losses significantly influence the optimal subtraction strategy, requiring tailored approaches.
Asymmetric subtraction can outperform symmetric strategies under certain lossy conditions.
Abstract
Subtracting photons from a two-mode squeezed state is a well-known method to increase entanglement. We analyse different strategies of local photon subtraction from a two-mode squeezed state in terms of entanglement gain and success probability. We develop a general framework that incorporates imperfections and losses in all stages of the process: before, during, and after subtraction. By combining all three effects into a single efficiency parameter, we provide analytical and numerical results for subtraction strategies using photon-number-resolving and threshold detectors. We compare the entanglement gain afforded by symmetric and asymmetric subtraction scenarios across the two modes. For a given amount of loss, we identify an optimised set of parameters, such as initial squeezing and subtraction beam splitter transmissivity, that maximise the entanglement gain rate. We identify…
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.
