Moderately mitigated glitch streams induce negligible to minor biases (0.04–0.6σ) in EMRI parameters while weakly mitigated streams with higher-SNR events can reach ~1σ biases, making EMRI inference more robust than for MBHBs.
Baghi, The lisa data challenges (2022), arXiv:2204.12142 [gr-qc]
2 Pith papers cite this work. Polarity classification is still indexing.
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Inpainting allows recovery of pre-merger massive black hole binary signals in LISA data despite gaps and overlaps.
citing papers explorer
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First-time assessment of glitch-induced bias and uncertainty in inference of extreme mass ratio inspirals
Moderately mitigated glitch streams induce negligible to minor biases (0.04–0.6σ) in EMRI parameters while weakly mitigated streams with higher-SNR events can reach ~1σ biases, making EMRI inference more robust than for MBHBs.
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Inpainting over the cracks: challenges of applying pre-merger searches for massive black hole binaries to realistic LISA datasets
Inpainting allows recovery of pre-merger massive black hole binary signals in LISA data despite gaps and overlaps.