Detection of gravitational waves using topological data analysis and convolutional neural network: An improved approach

Understand

The gravitational wave detection problem is challenging because the noise is typically overwhelming.

• Convolutional neural networks (CNNs) have been successfully applied, but require a large training set and the accuracy suffers significantly in the case of low SNR.
• We propose an improved method that employs a feature extraction step using persistent homology.
• The resulting method is more resilient to noise, more capable of detecting signals with varied signatures and requires less training.