--- jupytext: text_representation: extension: .md format_name: myst format_version: 0.13 jupytext_version: 1.11.1 kernelspec: display_name: Python 3 (ipykernel) language: python name: python3 --- # What happens when I use QSE? A figure for the typical workflow for QSE is shown below: ```{figure} ../img/qse-data-flow-diagram.png --- width: 700px name: qse_workflow_overview --- Workflow of the QSE technique in Mitiq, detailed in the [What happens when I use QSE?](qse-4-low-level.md) section. ``` The QSE workflow in Mitiq is divided into two steps 1. Generate the code and overlap Hamiltonian 2. Perform a classical minimization problem in order to retrieve the error-mitigated expectation value. Similar to the workflow of other mitigation techniques on Mitiq, a user will have to provide an input circuit, an executor and an observable for which to compute the error-mitigated expectation value. Furthermore, this technique relies on choosing a basis of expansion operators (the check operators), and a Hamiltonian which defines the state with least amount of errors. This method will perform the necessary computation in order to project to a state that minimizes the energy of the state with respect to the Hamiltonian. It will then return the error-mitigated expected value by solving the [generalized eigenvalue problem](https://en.wikipedia.org/wiki/Eigendecomposition_of_a_matrix#Generalized_eigenvalue_problem).