3 papers
physics.flu-dyn2019
Unsupervised Machine Learning to Teach Fluid Dynamicists to Think in 15 Dimensions
S. M. de Bruyn Kops, D. J. Saunders, E. A. Rietman +1
An autoencoder is used to compress and then reconstruct three-dimensional stratified turbulence data in order to better understand fluid dynamics by studying the errors in the reco…
quant-ph2019
Raman Quantum Memory with Built-In Suppression of Four-wave Mixing Noise
Sarah E. Thomas, Thomas M. Hird, Joseph H. D. Munns +5
Quantum memories are essential for large-scale quantum information networks. Along with high efficiency, storage lifetime and optical bandwidth, it is critical that the memory add…
quant-ph2019
Optimal Coherent Filtering for Single Noisy Photons
S. Gao, O. Lazo-Arjona, B. Brecht +6
We introduce a filter using a noise-free quantum buffer with large optical bandwidth that can both filter temporal-spectral modes, as well as inter-convert them and change their fr…