Awesome
Auspex, the automated system for python-based experiments, is a framework for performing laboratory measurements. Auspex was developed by a group that primarily performs measurements on superconducting qubits and magnetic memory elements, but its underpinnings are sufficiently general to allow for extension to arbitrary equipment and experiments. Using several layers of abstraction, we attempt to meet the following goals:
- Instrument drivers should be easy to write.
- Measurement code should be flexible and reusable.
- Data acquisition and processing should be pipelined, asynchronous, and reconfigurable.
- Experiments should be adaptive, not always pre-defined.
Features
- Easy driver specification using metaprogramming.
- Fast multiprocessing pipeline for digitizer (or other) data.
- Tight integration with QGL for quantum experiment definition.
- Qubit calibration routines.
- Run within Jupyter notebooks.
- Easy pipeline specification and graphical display of pipelines.
- Separate zmq/matplotlib plotting clients for local or remote use.
- Custom high-performance file format (numpy mmaps) with full data axis descriptors and metadata.
Regrettably in-notebook plotting is difficult to implement for more than simple 1D sweeps. Notebook caching and javascript interface limitations make returning large amounts of data impractical. Final plots may be displayed
Documentation
Full documentation can be found at readthedocs.
Funding
This software is based in part upon work supported by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via contract W911NF-14-C0089 and Army Research Office contract No. W911NF-14-1-0114. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the ODNI, IARPA, or the U.S. Government.