A neural-network-based simulation inference method improves 3σ detection probability of gravitational-wave background anisotropies by 90-200% over Gaussian frequentist searches by learning non-Gaussian structure in pulsar timing residuals.
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PTA statistical tests cannot distinguish Gaussian and non-Gaussian GWB amplitude distributions in a model-agnostic way after decorrelation.
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Detecting Gravitational-Wave Anisotropies with Simulation-Based Inference
A neural-network-based simulation inference method improves 3σ detection probability of gravitational-wave background anisotropies by 90-200% over Gaussian frequentist searches by learning non-Gaussian structure in pulsar timing residuals.
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Are PTA measurements sensitive to gravitational wave non-Gaussianities?
PTA statistical tests cannot distinguish Gaussian and non-Gaussian GWB amplitude distributions in a model-agnostic way after decorrelation.