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Adaptively compute and evaluate source functions ``S(τ,k)`` with symbolic expressions `Ss` on a grid with fixed conformal times `τs`, but adaptively refined grid of wavenumbers from the problem `prob`.
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The source functions are first evaluated on the (coarse) initial grid `ks`.
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Each subinterval ``(k₁, k₂)`` of `ks` is then adaptively refined until the linear interpolation ``Sᵢ = (S(k₁)+S(k₂))/2`` to the midpoint ``k=(k₁+k₂)/2`` approximates the actual value ``S(k)`` there within some tolerance.
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The comparison ``Sᵢ ≈ S`` is done with `isapprox(Sᵢ, S; kwargs...)`, where `S` and `Sᵢ` are vectors with the (conformal) timeseries of the source function for that wavenumber.
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It receives the keyword arguments `kwargs` passed to this function, so `atol`, `rtol` and/or `norm` can be specified to tune the tolerance.
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Returns the refined wavenumbers sorted in ascending order and a grid with the corresponding source function values.
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If not `sort`, the wavenumbers and source function values are instead left in the order in which they were inserted in the refinement process.
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The options `bgopts` and `ptopts` are passed to the background and perturbation solves.
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