Background and overview information for the use of Boulder Opal in quantum research.


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


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