Dissipation of small-scale primordial perturbations after neutrino decoupling cools relic neutrinos and reduces their abundance, enabling PTOLEMY to constrain the primordial curvature power spectrum to O(0.1) on scales k ≲ 3×10^5 Mpc^{-1}.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 3roles
background 2representative citing papers
SWIM solves Warm Inflation stochastic perturbations fully numerically, speeds MCMC with machine learning, and integrates with Cobaya to constrain any Warm Inflation model against CMB data.
DSWIM adds a Hubble-scaled deterministic correlation matrix evolution to SWIM that preserves the primordial curvature power spectrum exactly while improving numerical conditioning and resolving stochastic-deterministic discrepancies.
citing papers explorer
-
Probing the small-scale primordial power spectrum via relic neutrinos and acoustic reheating
Dissipation of small-scale primordial perturbations after neutrino decoupling cools relic neutrinos and reduces their abundance, enabling PTOLEMY to constrain the primordial curvature power spectrum to O(0.1) on scales k ≲ 3×10^5 Mpc^{-1}.
-
SWIM: Stochastic Warm Inflation Module to generate and analyse Warm Inflationary power spectrum
SWIM solves Warm Inflation stochastic perturbations fully numerically, speeds MCMC with machine learning, and integrates with Cobaya to constrain any Warm Inflation model against CMB data.
-
DSWIM:Efficient and Stable Deterministic Computation of Warm Inflation Perturbations
DSWIM adds a Hubble-scaled deterministic correlation matrix evolution to SWIM that preserves the primordial curvature power spectrum exactly while improving numerical conditioning and resolving stochastic-deterministic discrepancies.