  Taking advantage of the unprecedented statistical power of upcoming cosmic
shear surveys will require exquisite knowledge of the matter power spectrum
over a wide range of scales. Analytical methods can achieve such precision only
up to quasi-linear scales. For smaller non-linear scales we must resort to
$N$-body and hydrodynamical simulations, which despite recent technological
advances and improved algorithms remain computationally expensive. Over the
past decade machine learning and the advent of emulators have propelled our
ability to hit the target accuracy with impressive computing efficiency. Yet,
realistically these techniques will be able to produce high-precision
non-linear matter power spectra only for a restricted sub-set of extensions to
the "vanilla" ${\Lambda}$CDM cosmology. I will present a promising alternative
to alleviate these shortcomings that draws strength from the combination of
halo model, perturbation theory and emulators--the reaction framework. I will
show how a power spectrum evolved in the standard cosmology can be readily
adjusted to account for physics beyond ${\Lambda}$CDM, and discuss the accuracy
of the reaction for well-known modifications to gravity, dark energy
parametrizations and massive neutrino cosmologies.
