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

Characterizing your hardware using system identification in Boulder Opal: Build a system model using probe measurements and data fusion routines

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