Defines peak-integrated sensitivity curves (PISCs) that fold in the expected spectral shape of gravitational waves from cosmological phase transitions and supplies semianalytical fits plus public data for major detectors.
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A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.
citing papers explorer
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New Sensitivity Curves for Gravitational-Wave Signals from Cosmological Phase Transitions
Defines peak-integrated sensitivity curves (PISCs) that fold in the expected spectral shape of gravitational waves from cosmological phase transitions and supplies semianalytical fits plus public data for major detectors.
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Machine Learning for Multi-messenger Probes of New Physics and Cosmology: A Review and Perspective
A review summarizing machine learning methods for multi-messenger probes of dark matter and new physics, with a proposed plan for future integrated analyses.