A normalising flow trained on real Blip glitches provides a data-informed prior that, used jointly with the signal model in Bilby, removes glitches and reduces bias in gravitational-wave parameter estimates.
11 show the signal pos- teriors as inferred from data with or without the glitch being removed, respectively
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
gr-qc 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Joint inference for gravitational wave signals and glitches using a data-informed glitch model
A normalising flow trained on real Blip glitches provides a data-informed prior that, used jointly with the signal model in Bilby, removes glitches and reduces bias in gravitational-wave parameter estimates.