Topics
Background and overview information for the use of Boulder Opal in quantum research.
Basics
- Boulder Opal overview
- Functionality and application of Boulder Opal in theoretical and experimental quantum research
- Boulder Opal for quantum computing
- An introduction to the application of Boulder Opal for key tasks in quantum computing
- Boulder Opal for quantum sensing
- An introduction to the application of Boulder Opal for augmenting the performance of quantum sensors in real environments
- Boulder Opal workflows for research
- Understand how and when to integrate Boulder Opal into your research: for theorists or experimentalists, new hardware, or established systems
- AI automation for quantum experiments
- An overview of how Boulder Opal's AI tools can be used to automate the tune-up and optimization of quantum hardware systems
- Visualizing your data using the Q-CTRL Visualizer
- An introduction to the purpose and functionality of the Q-CTRL Visualizer
Hardware characterization
- Characterizing your hardware using system identification in Boulder Opal
- Build a system model using probe measurements and data fusion routines
Control optimization
- Choosing a control-design (optimization) strategy in Boulder Opal
- An overview of choices and tradeoffs in control design for your quantum system
Graphs
- Understanding graphs in Boulder Opal
- An overview of how Boulder Opal uses computational graphs to represent systems and perform operations
- Working with time-dependent functions in Boulder Opal
- An overview of how time-dependent functions are represented in Boulder Opal graphs
- Improving calculation performance in graphs
- Tips and tricks to speed up your calculations in Boulder Opal
- Batching and broadcasting in Boulder Opal
- Approaches to handle multidimensional data efficiently in graphs