Flowchart of the targeted search approach. The core idea is to use the existing knowledge as quantified by the posterior p(θ, ϕ|d) in order to calculate the Fisher map marginalized over this posterior, ⟨ℐ(θ|d₀)⟩_{(ϕ|θ, d0)}, while keeping the observables of interest. This allows this Fisher map to provide us with regions of the sky with highest information gain potential for acquiring new data that are optimal for testing our model predictions, ⟨ℐ(θ|d₀)⟩_{(ϕ|θ, d0)}: d₀ → d. This data will in turn be used to update our knowledge about the model through updating the posterior and the procedure would repeat until the information content is fully depleted.