Accelerating parameter estimation of gravitational waves from compact binary coalescence using adaptive frequency resolutions

Bayesian parameter estimation of gravitational waves from compact binary coalescence (CBC) typically requires more than millions evaluations computationally expensive template waveforms. We propose a technique to reduce the cost waveform generation by exploiting chirping behavior CBC signal. Our does not require waveforms at all frequencies in frequency range used analysis, and suffer fixed due upsampling speeds up typical neutron star signal factor $\mathcal{O}(10)$ for low-frequency cutoff $20\,\mathrm{Hz}$, $\mathcal{O}(10^2)$ $5\,\mathrm{Hz}$. It any offline preparations or accurate estimates source parameters provided detection pipelines.