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docs/src/users_guide/cluster.md

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@@ -227,4 +227,4 @@ tlist = range(0, 20 / γ, 1000)
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sol = mesolve_map(H, ψ_list, tlist, c_ops; e_ops = e_ops, params = (ωq_list, ωd_list, F_list), ensemblealg = EnsembleSplitThreads())
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```
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Notice that we are using the [`mesolve_map`](@ref) function, which internally uses the `SciMLBase.EnsembleProblem` function to parallelize the computation of [`mesolveProblem`](@ref). The result is an array of `TimeEvolutionSol` objects, where each element corresponds to a specific combination of initial states and parameters. One can access the solution for a specific combination of initial states and parameters using indexing. For example, `sol[i,j,k,l].expect` will give the expectation values for the case of `ψ_list[i]`, `ωq_list[j]`, `ωd_list[k]`, and `F_list[l]`.
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Notice that we are using the [`mesolve_map`](@ref) function, which internally uses the `SciMLBase.EnsembleProblem` function to parallelize the computation of [`mesolveProblem`](@ref). The result is an array of [`TimeEvolutionSol`](@ref), where each element corresponds to a specific combination of initial states and parameters. One can access the solution for a specific combination of initial states and parameters using indexing. For example, `sol[i,j,k,l].expect` will give the expectation values for the case of `ψ_list[i]`, `ωq_list[j]`, `ωd_list[k]`, and `F_list[l]`.

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