A proof of concept that autoencoder and CNN classifiers can detect and classify four ultra-light dark matter signal models in simulated pulsar-timing residuals, with sensitivity several times worse than the one-step Bayesian benchmark.
Convolutional neural network for gravitational-wave early alert: Going down in frequency
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Deep Neural Networks Hunting Ultra-Light Dark Matter
A proof of concept that autoencoder and CNN classifiers can detect and classify four ultra-light dark matter signal models in simulated pulsar-timing residuals, with sensitivity several times worse than the one-step Bayesian benchmark.