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Quantum Machine Learning
Qudi: a modular python suite for experiment control and data processing
arXiv
Authors: Jan M Binder, Alexander Stark, Nikolas Tomek, Jochen Scheuer, Florian Frank, Kay D Jahnke, Christoph Müller, Simon Schmitt, Mathias H Metsch, Thomas Unden, Tobias Gehring, Alexander Huck, Ulrik L Andersen, Lachlan J Rogers, Fedor Jelezko
Year
2016
Paper ID
42177
Status
Preprint
Abstract Read
~2 min
Abstract Words
102
Citations
N/A
Abstract
Qudi is a general, modular, multi-operating system suite written in Python 3 for controlling laboratory experiments. It provides a structured environment by separating functionality into hardware abstraction, experiment logic and user interface layers. The core feature set comprises a graphical user interface, live data visualization, distributed execution over networks, rapid prototyping via Jupyter notebooks, configuration management, and data recording. Currently, the included modules are focused on confocal microscopy, quantum optics and quantum information experiments, but an expansion into other fields is possible and encouraged. Qudi is available from https://github.com/Ulm-IQO/qudi and is freely useable under the GNU General Public Licence.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2016 reference point for readers tracking recent quantum research.
- Qudi is a general, modular, multi-operating system suite written in Python 3 for controlling laboratory experiments.
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