Scratches from the Past: Inflationary Archaeology through Features in the Power Spectrum of Primordial Fluctuations

Abstract

Inflation may provide unique insight into the physics at the highest available energy scales that cannot be replicated in any realistic terrestrial experiment. Features in the primordial power spectrum are generically predicted in a wide class of models of inflation and its alternatives, and are observationally one of the most overlooked channels for finding evidence for non-minimal inflationary models. Constraints from observations of the cosmic microwave background cover the widest range of feature frequencies, but the most sensitive constraints will come from future large-scale structure surveys that can measure the largest number of linear and quasi-linear modes.

5 pages + references, 1 figure; science white paper submitted to the Astro2020 decadal survey

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• Comparing multi-field primordial feature models with the Planck data
• Detecting primordial features with LISA
• Back to the features: assessing the discriminating power of future CMB missions on inflationary models
• The effect of multiple features on the power spectrum in two-field inflation
• Density reconstruction from biased tracers and its application to primordial non-Gaussianity
• Packed Ultra-wideband Mapping Array (PUMA): Astro2020 RFI Response
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• Searching for local features in primordial power spectrum using genetic algorithms
• On the primordial origin of the smoothing excess in the $Planck$ temperature power spectrum in light of LSS data
• Optimising Inflationary Features the Bayesian Way
• Scalar induced gravitational waves review
• Cosmology at high redshift -- a probe of fundamental physics
• Refining the nonlinear modelling of primordial oscillatory features
• Investigating the Origin of CMB Large-Scale Features Using LiteBIRD and CMB-S4
• Potential Surge Preheating: enhanced resonance from potential features
• Rapid-turn inflation in supergravity is rare and tachyonic
• Non-Gaussianity from explicit $U(1)$-breaking interactions