prototype-qrao
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qiskit-community
Quantum random access optimization prototype
### What is the expected enhancement? We've talked about renaming the following members of `RoundingContext`: https://github.com/qiskit-community/prototype-qrao/blob/38527fd1bcce038a6e407592831e5f2023307461/qrao/rounding_common.py#L65-L66 - `trace_values` isn't really a standard term (they are really Pauli expectation values) -...
### What is the expected enhancement? Currently, we use the the Qiskit `r` gate to return the basis rotation corresponding to the (3,1,p) QRAC: https://github.com/qiskit-community/prototype-qrao/blob/38527fd1bcce038a6e407592831e5f2023307461/qrao/encoding.py#L83-L90 However, this obscures the connection...
### What is the expected enhancement? Currently, we have https://github.com/qiskit-community/prototype-qrao/blob/38527fd1bcce038a6e407592831e5f2023307461/qrao/quantum_random_access_optimizer.py#L80-L82 but the parallel class in qiskit-optimization [calls it `min_eigen_solver_result`](https://github.com/Qiskit/qiskit-optimization/blob/1f74e426a532ae4ab09a80c213b97a8e3d38f3d4/qiskit_optimization/algorithms/minimum_eigen_optimizer.py#L70-L73). We've decided against renaming it in QRAO in this way because...
### What is the expected enhancement? A while back, @BryceFuller drafted a how-to guide on preparing and visualizing logical QRAC states. I'd like to refresh it and add it to...
### What is the expected enhancement? Currently, there is a build of the API reference at https://qiskit-community.github.io/prototype-qrao/apidocs/. However, the use of Sphinx could be improved. Most notably, some classes and...
### What is the expected enhancement? In Qiskit Optimization, it is customary for an `OptimizationAlgorithm` to attempt to convert a problem to a QUBO if necessary, by invoking [`QuadraticProgramToQubo`](https://qiskit.org/documentation/optimization/stubs/qiskit_optimization.converters.QuadraticProgramToQubo.html#qiskit_optimization.converters.QuadraticProgramToQubo) (see...
### What is the expected enhancement? The typical interface in Qiskit Optimzation for performing a quantum optimization is the `OptimizationAlgorithm.solve(problem: QuadraticProgram)` method. However, a lot happens "underneath the hood" when...
### What is the expected enhancement? Currently, `QuantumRandomAccessOptimizer.solve()` performs some post-processing on the rounding results. However, if one calls `solve_relaxed()` and then performs rounding manually, there is no convenient way...
We have improved the bug report issue template, and I would like to get it in QRAO before release. Let me know what you think of this
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Quantum random access optimization prototype