Convolutional and graph neural networks outperform the Wiener filter by factors of 15-80 in predicting Newtonian noise from single seismic events on synthetic seismometer array data.
Site-selection criteria for the Einstein Telescope
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Optimized seismic arrays with multiple sensors per borehole plus tunnel extensions achieve broadband Newtonian noise mitigation above 3-4 Hz with high robustness to position variations for the Einstein Telescope.
The paper evaluates how triangular versus two-L-shaped geometries, arm lengths, and presence of low-frequency instruments affect the science reach of the Einstein Telescope for compact binaries, multi-messenger events, and stochastic backgrounds.
citing papers explorer
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NNNN: Neural Networks for Newtonian Noise Mitigation at the Einstein Telescope
Convolutional and graph neural networks outperform the Wiener filter by factors of 15-80 in predicting Newtonian noise from single seismic events on synthetic seismometer array data.
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Optimization and robustness of cost-efficient seismic arrays for Newtonian noise cancellation at the Einstein Telescope
Optimized seismic arrays with multiple sensors per borehole plus tunnel extensions achieve broadband Newtonian noise mitigation above 3-4 Hz with high robustness to position variations for the Einstein Telescope.