From the 1 of 5 linked papers with an AI index.
5 papers
Global Structure in Learned Latent Representations of Confusion-Limited LISA Data
Jericho Cain
The paper studies how machine‑learning latent representations of simulated, confusion‑limited LISA data capture source resolvability, finding that global latent density models outp…
Manifold Learning for Source Separation in Confusion-Limited Gravitational-Wave Data
Jericho Cain
The Laser Interferometer Space Antenna (LISA) will observe gravitational waves in a regime that differs sharply from what ground-based detectors such as LIGO handle. Instead of sea…
Detectability Scaling Laws for Environmental Phase Modulation in Gravitational-Wave Signals
Jericho Cain
Environmental effects such as hierarchical triple motion can introduce cumulative phase modulation in gravitational-wave signals through time-dependent line-of-sight acceleration.…
Gauge Freedom and Metric Dependence in Neural Representation Spaces
Jericho Cain
Neural network representations are often analyzed as vectors in a fixed Euclidean space. However, their coordinates are not uniquely defined. If a hidden representation is transfor…
Template-Free Gravitational Wave Detection with CWT-LSTM Autoencoders: A Case Study of Run-Dependent Calibration Effects in LIGO Data
Jericho Cain
Gravitational wave detection requires sophisticated signal processing to identify weak astrophysical signals buried in instrumental noise. Traditional matched filtering approaches…