Parameter Estimation

Finally, to quantify the precision of measurements on parameters, we will make use of the the linear signal approx- imation (LSA) (Finn 1992). By considering a small pertur- bation θ “ θtr ` ∆θ, one can expand the waveform model in the vicinity of the best-fit parameters as —— 2104.01897

  • Finn L. S., 1992, Phys. Rev. D, 46, 5236

(Flanagan & Hughes 1998), (Miller 2005) and (Cutler & Vallisneri 2007), in which expressions are provided for the error on parameters due to the presence of noise and due to waveform errors. —— 2104.01897

  • Flanagan E. E., Hughes S. A., 1998, Phys. Rev. D, 57, 4566
  • Miller M., 2005, Phys. Rev. D, 71, 104016
  • Cutler C., Vallisneri M., 2007, Phys. Rev. D, 76, 104018

GEOMETRICAL INTERPRETATION OF PARAMETER ERRORS —— 2104.01897

Overlaping paper: We qualitatively confirm one of the main results of (Samajdar et al. 2021; Pizzati et al. 2021; Himemoto, Nishizawa & Taruya 2021; Relton & Raymond 2021) in Sec. (5.2), showing that biases arise when the difference between the coalescence times of two overlap- ping signals is smaller than a fraction of a second. —— 2104.01897

  • Samajdar A., Janquart J., Van Den Broeck C., Dietrich T., 2021
  • Pizzati E., Sachdev S., Gupta A., Sathyaprakash B., 2021
  • Himemoto Y., Nishizawa A., Taruya A., 2021
  • Relton P., Raymond V., 2021