AI feature - Best backend and backend options for haiqu.run
As an application scientist, I want to run my algorithm on the most relevant backends. I want AI to suggest a backend based on my algorithm and help me build the correct backend_option dictionary to pass to haiqu.run()
Subtlety spotter
If I am recreating something from a paper it can be helpful if I can state this at the beginning and have the AI point out parts that may functionally (obv the code will differ semantically) subtly differ from what is stated elsewhere. Not as a ‘you must change this‘ but more as a hint/warning. It’s perfectly possible some subtle alteration is intended, but it’s also possible that it’s not. I’m thinking niche qubit grouping choices, specific optimiser choices in specific param regimes, all the nasty things that can get pushed into a corner of an appendix
Feature Request - AI for plots
As a user, I want to quickly generate beautiful plots with the context of the experiment and execution results
As a Haiqu SDK user, I want
to have the ability to access external resources about Haiqu SDK with examples/notebooks to help me write my own code without looking much into documentation.
Feature Request - Use AI to explore use cases
As an application scientist, I want to explore use cases quickly. I want to define a problem statement, have an AI agent ask guiding questions, and build for me a script that uses an optimized quantum algorithm to find the solution to my problem.
Feature request - sharable experiments
As an application developer, I want to be able to share my experiments with all the circuits and results with other users
Drawer: support matplotlib-compatible marker symbols (e.g., 'o')
The Drawer.plot method currently requires custom marker names such as "circle", "square", etc., and does not accept the standard matplotlib marker symbols like 'o', '^', 's'. This makes it harder to reuse code or switch between matplotlib and Drawer plots.