The data for "Simulation-based Inference in Searches for the Inflationary Stochastic Gravitational-Wave Backgrounds using Multi-band Conditional Normalizing Flows"

This record contains the training data, the trained models, the noise inputs, the posterior summaries and a frozen copy of the code used in the article "Simulation-based Inference in Searches for the Inflationary Stochastic Gravitational-Wave Backgrounds using Multi-band Conditional Normalizing Flows" (Luo, Li, Zhang, Zhou, Meyers & Shapiro; ApJS, manuscript AAS76432). The models are conditional normalizing flows that infer nine cosmological parameters from the energy density spectrum Omega_GW(f) of the stochastic gravitational-wave background in the PTA, LISA and ground-based (LIGO) bands.