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With present and future observations becoming of higher and higher quality, it is timely and necessary to investigate the most significant theoretical uncertainties in the predictions of inflation. We show that our ignorance of the entire history of the Universe, including the physics of reheating after inflation, translates to considerable errors in observationally relevant parameters. Using the inflationary flow formalism, we estimate that for a spectral index $n$ and tensor/scalar ratio $r$ in the region favored by current observational constraints, the theoretical errors are of order $Delta n / | n - 1| sim 0.1 - 1$ and $Delta r /r sim 0.1 - 1$. These errors represent the dominant theoretical uncertainties in the predictions of inflation, and are generically of the order of or larger than the projected uncertainties in future precision measurements of the Cosmic Microwave Background. We also show that the lowest-order classification of models into small field, large field, and hybrid breaks down when higher order corrections to the dynamics are included. Models can flow from one region to another.
We show how to account for correlations between theoretical uncertainties incorporated in parton distribution function (PDF) fits, and the theoretical uncertainties in the predictions made using these PDFs. We demonstrate by explicit calculations, bo
The scalar-tensor Dirac-Born-Infeld (DBI) inflation scenario provides a simple mechanism to reduce the large values of the boost factor associated with single field models with DBI action, whilst still being able to drive 60 efolds of inflation. Usin
Inflation is an early period of accelerated cosmic expansion, thought to be sourced by high energy physics. A key task today is to use the influx of increasingly precise observational data to constrain the plethora of inflationary models suggested by
We explore whether multifield inflationary models make unambiguous predictions for fundamental cosmological observables. Focusing on $N$-quadratic inflation, we numerically evaluate the full perturbation equations for models with 2, 3, and $mathcal{O
Combining measurements which have theoretical uncertainties is a delicate matter, due to an unclear statistical basis. We present an algorithm based on the notion that a theoretical uncertainty represents an estimate of bias.