qiskit-community / qiskit-experiments

Qiskit Experiments
https://qiskit-community.github.io/qiskit-experiments/
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Implementing an adaptive Trotter decomposition that dynamically adjusts the number of Trotter steps based on the complexity of the quantum circuit. #1402

Open AbdullahKazi500 opened 7 months ago

AbdullahKazi500 commented 7 months ago

Suggested feature

Implementing an adaptive Trotter decomposition that dynamically adjusts the number of Trotter steps based on the complexity of the quantum circuit. This would allow for more accurate error mitigation in a scalable manner.

Developing a feature for Qiskit experiments to intelligently select qubits for error mitigation based on their susceptibility to Trotter errors. This could involve analyzing historical data or using heuristics to identify qubits that are more prone to errors and prioritizing their mitigation. Introducing a mechanism functionality for dynamically adjusting the error threshold used in error mitigation. This could involve monitoring the performance of previous error mitigation attempts and adapting the threshold to achieve optimal reduction without sacrificing computational efficiency.

Proposed Solution We can Create a simulation configuration where the Trotter error arising from non-commuting Hamiltonians in a multi-qubit system offset, to some extent, the Trotter error between the unitary component and the noise component of the simulated dynamics. Alternatively, we can also explore methodologies that eliminate time discretization as an intermediary step and focus on continuous-in-time mappings to transition from one dissipative dynamics to another.

AbdullahKazi500 commented 7 months ago

@nkanazawa1989 @yaelbh Please do let me know if this sounds good

nkanazawa1989 commented 7 months ago

Sounds like this is another independent software built on top of Qiskit Experiments. Since the ExperimentData class provides APIs to the experiment service where we can have a data storage, we can leverage that resource for statistical or historical trend analysis. However, the built-in library of Qiskit Experiments focuses on providing fundamental (and the minimum set of) experiment assets.

But it would be great some community contributor like you can develop intelligent transpiler software with Qiskit Experiments :)