arXiv · 2407.01713
Precision Inflationary Predictions: Impact of Accurate End-of-Inflation Dynamics
Abstract
The precision era of cosmology demands accurate theoretical predictions from inflationary models. In quantitative reheating analyses, inflationary observables depend sensitively on the number of e-folds between horizon exit and the end of inflation, $N_k$, whose determination relies on slow-roll approximations near the end of inflation. Since inflation ends when the first slow-roll parameter reaches unity, even modest inaccuracies in this approximation can shift the end of inflation and thereby alter $N_k$, leading to modifications in predicted observables -- including those evaluated at leading-order. While such effects are implicit in standard treatments, their quantitative impact on observable constraints has not been systematically assessed. In this work, we first re-evaluate leading-order slow-roll predictions using an improved determination of $N_k$ within a simple quantitative reheating framework, and then incorporate higher-order slow-roll corrections consistently with the revised background evolution. Applying this framework to the Starobinsky model, we find that improved end-of-inflation dynamics alone can induce shifts of order $\Delta n_s \sim 10^{-3}$, while higher-order slow-roll corrections provide additional refinements at the $\sim 4 \times 10^{-4}$ level. The cumulative effect yields a maximum shift of $\Delta n_s \sim 1.2 \times 10^{-3}$ within the allowed reheating range. To our knowledge, this is the first systematic decomposition of end-of-inflation corrections and their individual contributions to $n_s$ in the Starobinsky model, with implications for model discrimination in next-generation CMB surveys. These results demonstrate that an accurate determination of the end of inflation is essential for precision tests of inflationary models.
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Debottam Nandi, Simran Yadav, Manjeet Kaur. 2024-07-01. Precision Inflationary Predictions: Impact of Accurate End-of-Inflation Dynamics. https://doi.org/10.1016/j.dark.2026.102325
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