papers
Publications (3)
astro-ph.HE2026
Mitigating Systematic Errors in Parameter Estimation of Binary Black Hole Mergers in O1-O3 LIGO-Virgo Data
Sumit Kumar, Max Melching, Frank Ohme +3
Systematic errors in the parameter estimation (PE) of gravitational wave (GW) mergers can arise from various sources, including waveform systematics, noise mischaracterization, dat…
astro-ph.IM2026
SGN: A python framework for stream-processing pipelines
Yun-Jing Huang, Olivia Godwin, Chad Hanna +11
We present the Stream Graph Navigator (SGN), a lightweight Python framework for building streaming data applications. In SGN, stream-processing pipelines are built by connecting co…
gr-qc2025
Accounting for the Known Unknowns: A Parametric Framework to Incorporate Systematic Waveform Errors in Gravitational-Wave Parameter Estimation
Sumit Kumar, Max Melching, Frank Ohme
The PE for GW merger events relies on a waveform model calibrated using numerical simulations. Within the Bayesian framework, this waveform model represents the GW signal produced…