Neutrinos propagating in a dense neutrino gas, such as those expected in core-collapse
supernovae (CCSNe) and neutron star mergers (NSMs), can experience fast flavor …

The use of the Audio Spectrogram Transformer (AST) model for gravitational-wave data
analysis is investigated. The AST machine-learning model is a convolution-free classifier …

Convolutional neural networks (CNNs) have demonstrated potential for the real-time
analysis of data from gravitational wave detector networks for the specific case of signals …

Massive objects located between Earth and a compact binary merger can act as
gravitational lenses magnifying signals and improving the sensitivity of gravitational wave …

Abstract Low-surface-brightness (LSB) galaxies play a crucial role in our understanding of
galaxy evolution and dark matter cosmology. However, efficiently detecting them in large …

In our previous work [Physical Review D, 2024, 109 (4): 043009], we introduced MSNRnet, a
framework integrating deep learning and matched filtering methods for gravitational wave …

Gravitational wave astronomy has emerged as a new branch of observational astronomy,
since the first detection of gravitational waves in 2015. The current number of O (100) …

Future GW observatories, such as the Einstein Telescope (ET), are expected to detect
gravitational wave signals, some of which are likely to overlap with each other. This overlap …

Gravitational waves are now routinely detected from compact binary mergers, with binary
neutron star mergers being of note for multi-messenger astronomy as they have been …

In the future, the third generation (3G) gravitational wave (GW) detectors, exemplified by the
Einstein Telescope (ET), will be operational. The detection rate of GW from binary neutron …