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quant-ph2024
Noiseless Loss Suppression for Entanglement Distribution
Cory M. Nunn, Daniel E. Jones, Todd B. Pittman +1
Recent work by Mičuda et al. (arXiv:1206.2852v1) suggests that pairing noiseless amplification with noiseless attenuation can conditionally suppress loss terms in the direct transm…
quant-ph2023
An Exponential Reduction in Training Data Sizes for Machine Learning Derived Entanglement Witnesses
Aiden R. Rosebush, Alexander C. B. Greenwood, Brian T. Kirby +1
We propose a support vector machine (SVM) based approach for generating an entanglement witness that requires exponentially less training data than previously proposed methods. SVM…
quant-ph2020
Nonlocal Dispersion Cancellation for Three or More Photons
I. C. Nodurft, S. U. Shringarpure, B. T. Kirby +2
The entanglement of quantum systems can produce a variety of nonclassical effects that have practical applications in quantum information science. One example of this is nonlocal d…