Using Time Series to Identify Strongly-Lensed Gravitational Waves with Deep Learning

Learn about innovative machine learning approaches for detecting gravitational wave lensing effects in a 30-minute research presentation from the Workshop on "Lensing and Wave Optics in Strong Gravity." Explore how time series data and neural networks can improve the identification of strongly-lensed gravitational waves compared to traditional time-frequency methods. Discover a novel neural network architecture that processes raw time series data to preserve phase information while reducing preprocessing requirements. Examine the model's superior performance, achieving up to 5 times better efficiency at low false-alarm rates compared to baseline approaches. Understand how this method maintains robustness across different waveform models, handles lensing-induced phase shifts, and accommodates timing misalignments - critical features for next-generation gravitational wave detectors.