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Stellar surface rotation carries information about stellarparameters---particularly ages---and thus the large rotational datasetsextracted from Kepler timeseries represent powerful probes of stellarpopulations. In this article, we address the challenge of interpreting suchdatasets with a forward-modeling exercise. We combine theoretical models ofstellar rotation, a stellar population model for the galaxy, and prescriptionsfor observational bias and confusion to predict the rotation distribution inthe Kepler field under standard "vanilla" assumptions. We arrive at two centralconclusions: first, that standard braking models fail to reproduce the observeddistribution at long periods, and second, that the interpretation of the perioddistribution is complicated by mixtures of unevolved and evolved stars andobservational uncertainties. By assuming that the amplitude and thusdetectability of rotational signatures is tied to the Rossby number, we showthat the observed period distribution contains an apparent "Rossby edge" at$\textrm{Ro}_{thresh} = 2.08$, above which long-period, high-Rossby numberstars are either absent or undetected. This $\textrm{Ro}_{thresh}$ iscomparable to the Rossby number at which van Saders et al. (2016) observed theonset of weakened magnetic braking, and suggests either that this modifiedbraking is in operation in the full Kepler population, or that stars undergo atransition in spottedness and activity at a very similar Rossby number. Wediscuss the observations necessary to disentangle these competing scenarios.(abridged)

Forward Modeling of the Kepler Stellar Rotation Period Distribution: Interpreting Periods from Mixed and Biased Stellar Populations