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Found 4 papers, 1 papers with code
Dark solitons in Bose-Einstein condensates: a dataset for many-body physics research
We establish a dataset of over $1. 6\times10^4$ experimental images of Bose--Einstein condensates containing solitonic excitations to enable machine learning (ML) for many-body physics research.
Combining machine learning with physics: A framework for tracking and sorting multiple dark solitons
In ultracold-atom experiments, data often comes in the form of images which suffer information loss inherent in the techniques used to prepare and measure the system.
Multiple-camera defocus imaging of ultracold atomic gases
In cold atom experiments, each image of light refracted and absorbed by an atomic ensemble carries a remarkable amount of information.
Quantum Gases Atomic Physics Optics
Machine-learning enhanced dark soliton detection in Bose-Einstein condensates
Most data in cold-atom experiments comes from images, the analysis of which is limited by our preconceptions of the patterns that could be present in the data.
