相关论文: Deep Learning for estimating parameters of Gravita…
Deep learning (DL), a branch of artificial intelligence (AI) techniques, has shown great promise in various disciplines such as image classification and segmentation, speech recognition, language translation, among others. This remarkable…
Recent observations of gravitational waves from binary black holes and neutron stars allow us to probe the strong and dynamical field regime of gravity. On the other hand, a collective signal from many individual, unresolved sources results…
With the anticipated launch of space-based gravitational wave detectors, including LISA, TaiJi, TianQin, and DECIGO, expected around 2030, the detection of gravitational waves generated by intermediate-mass black hole binaries (IMBBHs)…
The increasing focus on predicting renewable energy production aligns with advancements in deep learning (DL). The inherent variability of renewable sources and the complexity of prediction methods require robust approaches, such as DL…
Gravitational waves provide a unique opportunity to test general relativity in the strong-field regime, enabling the extraction of key physical parameters from observational data. Traditional likelihood-based inference methods, while…
The physics governing the boundary between the most massive neutron stars (NSs) and the least massive black holes (BHs) is currently uncertain, but could potentially be constrained with new observations. While NSs have been observed with…
The speed-up of parameter estimation is an active field of research in gravitational-wave data analysis. In this paper we present GP15, a deep-learning method that merges residual networks and normalizing flows into a general-purpose,…
The computational cost of searching for gravitational wave (GW) signals in low latency has always been a matter of concern. We present a self-supervised learning model applicable to the GW detection. Based on simulated massive black hole…
As two neutron stars merge, they emit gravitational waves that can potentially be detected by earth bound detectors. Matched-filtering based algorithms have traditionally been used to extract quiet signals embedded in noise. We introduce a…
While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for problems involving discrete variables remain challenging. This is primarily due to the zero-gradient…
On September 14, 2015, the newly upgraded Laser Interferometer Gravitational-wave Observatory (LIGO) recorded a loud gravitational-wave (GW) signal, emitted a billion light-years away by a coalescing binary of two stellar-mass black holes.…
We propose a lightweight deep convolutional neural network (lCNN) to estimate cosmological parameters from simulated three-dimensional dark matter (DM) halo distributions and associated statistics. The training dataset comprises 2000…
In this study, we investigate the role of the non-linear memory effect in gravitational wave (GW) parameter estimation, particularly we explore its capability to break the degeneracy between luminosity distance and inclination angle in…
Gravitational waves (GWs) from distant sources such as inspiralling and merging stellar-mass compact binaries, intermediate-mass and supermassive-binary-black-hole can be gravitationally lensed by intervening objects, ranging from stars and…
The number of astrophysical sources detected by Advanced LIGO and Virgo is expected to increase as the detectors approach their design sensitivity. Gravitational wave detectors are also sensitive to transient noise sources created by the…
Precision pulsar timing at the level of tens to hundreds of nanoseconds allows detection of nanohertz gravitational waves (GWs) from supermassive binary black holes (SMBBHs) at the cores of merging galaxies and, potentially, from exotic…
The simultaneous observation of gravitational waves (GW) and prompt electromagnetic counterparts from the merger of two neutron stars can help reveal the properties of extreme matter and gravity during and immediately after the final…
We present the astrophysical science case for a space-based, decihertz gravitational-wave (GW) detector. We particularly highlight an ability to infer a source's sky location, both when combined with a network of ground-based detectors to…
We investigate the synergy of upcoming galaxy surveys and gravitational wave (GW) experiments in constraining late-time cosmology, examining the cross-correlations between the weak lensing of gravitational waves (GW-WL) and the galaxy…
Gravitational wave (GW) astronomy truly began with the detection of merging compact binaries. The next breakthrough lies in detecting GWs from core-collapse supernovae (CCSNe), particularly the GW linear memory -- a phenomenon arising from…