Sparse Matrix Gate
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- Dominant language
- C++
- Stars
- 1.1k
- Forks
- 456
- Avg merge
- 1d 22h
- Merged PRs (30d)
- 165
Description
Required prerequisites
- Search the issue tracker to check if your feature has already been mentioned or rejected in other issues.
Describe the feature
The ability to apply a sparse matrix is needed for quantum algorithm research. A synthesis for real quantum computers would be ideal, but I think the algorithm there is non-trivial. At the very least
I would prefer it to work on a simulator first.
Qulacs has the feature:
https://docs.qulacs.org/en/latest/guide/2.0_python_advanced.html#Sparse-matrix-gate
I think the natural workflow for CUDA-Q is that a sparse matrix can be registered with cudaq.register_operation for python and CUDAQ_REGISTER_OPERATION for C++.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the existing cudaq.register_operation Python API and CUDAQ_REGISTER_OPERATION C++ macro, then compare the sparse-matrix gate behavior documented by Qulacs. Define the simulator-first scope and determine what registration and execution support would be required; done means a sparse matrix can be registered and applied in the simulator from Python and C++.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- quantum-computing
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100