Speaker
Description
Third-generation gravitational-wave detectors such as the Einstein Telescope
(ET) will observe compact binary coalescences at event rates orders of magnitude
above those of current detectors. This high event rate introduces a
qualitatively new challenge for matched-filter search pipelines: at realistic
ET-era merger rates, signal-signal coincidences accumulate in the time-slide
background, inflating background trigger rates at high signal-to-noise ratio and
miscalibrating the false alarm rate (FAR) used to assign detection significance.
The severity of this contamination is expected to grow with merger rate and with
in-band signal duration — making ET's low-frequency sensitivity advantage
inseparable from the background validity problem.
We present a systematic numerical study of FAR miscalibration under ET-era
signal rates. Using synthetic Gaussian noise colored by the ET power spectral
density and compact binary populations injected at a range of astrophysically
motivated merger rates, we run a standard matched-filter search and characterize
the contamination of the time-slide background as a function of merger rate.
Signal-signal coincidences are identified by cross-matching background triggers
against the injected truth table, quantifying the contamination fraction and the
resulting FAR inflation as a function of rate. A contamination-free reference
background, produced from noise-only data with the true power spectral density,
provides a strict lower bound on FAR miscalibration and detection efficiency
loss that is free from PSD estimation bias.
The study is carried out for both the triangular and 2L ET configurations under
identical search conditions, providing a direct comparison of how background
contamination affects each geometry at 5 Hz. This enables assessment of whether
the two configurations respond differently to increasing signal rates,
contributing quantitative input to ongoing discussions of ET detector design.
This work characterizes a systematic effect that must be addressed in the design
of third-generation search pipelines, and provides a foundation for developing
background estimation strategies robust to signal confusion at ET-era rates.