DVGAN: Stabilize Wasserstein GAN training for time-domain Gravitational Wave physics. (arXiv:2209.13592v2 [astro-ph.IM] UPDATED)

Simulating time-domain observations of gravitational wave (GW) detector
environments will allow for a better understanding of GW sources, augment
datasets for GW signal detection and help in characterizing the noise of the
detectors, leading to better physics. This paper presents a novel approach to
simulating fixed-length time-domain signals using a three-player Wasserstein
Generative Adversarial Network (WGAN), called DVGAN, that includes an auxiliary
discriminator that discriminates on the derivatives of input signals. An
ablation study is used to compare the effects …

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