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Interferometric gravitational-wave detectors like LIGO, GEO600 and Virgo record a surplus of information above and beyond possible gravitational-wave events. These auxiliary channels capture information about the state of the detector and…

Instrumentation and Methods for Astrophysics · Physics 2014-07-29 Reed Essick , Lindy Blackburn , Erik Katsavounidis

We propose a new sequential classification model for astronomical objects based on a recurrent convolutional neural network (RCNN) which uses sequences of images as inputs. This approach avoids the computation of light curves or difference…

Electromagnetic follow-up observations of gravitational wave events offer critical insights and provide significant scientific gain from this new class of astrophysical transients. Accurate identification of gravitational wave candidates…

Relic gravitational waves (RGWs) from early universe carry fundamental information, so it's extraordinarily important to search RGW signals from data of observatories like LIGO-Virgo network. Here, focusing on typical RGWs from inflation…

General Relativity and Quantum Cosmology · Physics 2025-04-15 Minghui Zhang , Hao Wen

The detection of an electromagnetic transient which may originate from a binary neutron star merger can increase the probability that a given segment of data from the LIGO-Virgo ground-based gravitational-wave detector network contains a…

Instrumentation and Methods for Astrophysics · Physics 2013-06-27 Luke Zoltan Kelley , Ilya Mandel , Enrico Ramirez-Ruiz

The detection and reconstruction of gravitational waves from core-collapse supernovae (CCSN) present significant challenges due to the highly stochastic nature of the signals and the complexity of detector noise. In this work, we introduce…

High Energy Astrophysical Phenomena · Physics 2026-01-06 Ao-Bo Wang , Yong Yuan , Hao Cai , Xi-Long Fan

Gravitational lensing is the relativistic effect generated by massive bodies, which bend the space-time surrounding them. It is a deeply investigated topic in astrophysics and allows validating theoretical relativistic results and studying…

Instrumentation and Methods for Astrophysics · Physics 2023-06-26 Nicolò Oreste Pinciroli Vago , Piero Fraternali

Denoising of time domain data is a crucial task for many applications such as communication, translation, virtual assistants etc. For this task, a combination of a recurrent neural net (RNNs) with a Denoising Auto-Encoder (DAEs) has shown…

Cosmology and Nongalactic Astrophysics · Physics 2019-05-27 Hongyu Shen , Daniel George , E. A. Huerta , Zhizhen Zhao

We introduce a transformer-based neural network for the accurate classification of real and bogus transient detections in astronomical images. This network advances beyond the conventional convolutional neural network (CNN) methods, widely…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Adi Inada , Masao Sako , Tatiana Acero-Cuellar , Federica Bianco

Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and…

Instrumentation and Methods for Astrophysics · Physics 2018-02-27 Ashish Mahabal , Kshiteej Sheth , Fabian Gieseke , Akshay Pai , S. George Djorgovski , Andrew Drake , Matthew Graham , the CSS/CRTS/PTF Collaboration

As the sensitivity and observing time of gravitational-wave detectors increase, a more diverse range of signals is expected to be observed from a variety of sources. Especially, long-lived gravitational-wave transients have received…

Instrumentation and Methods for Astrophysics · Physics 2021-11-24 Adrian Macquet , Marie-Anne Bizouard , Nelson Christensen , Michael Coughlin

In this paper, we study an application of deep learning to the advanced LIGO and advanced Virgo coincident detection of gravitational waves (GWs) from compact binary star mergers. This deep learning method is an extension of the Deep…

Instrumentation and Methods for Astrophysics · Physics 2019-02-20 Xilong Fan , Jin Li , Xin Li , Yuanhong Zhong , Junwei Cao

We seek to achieve the Holy Grail of Bayesian inference for gravitational-wave astronomy: using deep-learning techniques to instantly produce the posterior $p(\theta|D)$ for the source parameters $\theta$, given the detector data $D$. To do…

General Relativity and Quantum Cosmology · Physics 2020-01-31 Alvin J. K. Chua , Michele Vallisneri

Classical convolutional neural networks (cCNNs) are very good at categorizing objects in images. But, unlike human vision which is relatively robust to noise in images, the performance of cCNNs declines quickly as image quality worsens.…

Computer Vision and Pattern Recognition · Computer Science 2018-11-22 Till S. Hartmann

This paper investigates the problem of classification of unmanned aerial vehicles (UAVs) from radio frequency (RF) fingerprints at the low signal-to-noise ratio (SNR) regime. We use convolutional neural networks (CNNs) trained with both RF…

Signal Processing · Electrical Eng. & Systems 2020-09-22 Ender Ozturk , Fatih Erden , Ismail Guvenc

This study evaluates the use of Quantum Convolutional Neural Networks (QCNNs) for identifying signals resembling Gamma-Ray Bursts (GRBs) within simulated astrophysical datasets in the form of light curves. The task addressed here focuses on…

This paper provides a comprehensive guide to gravitational wave data processing, with a particular focus on signal generation, noise modeling, and optimization techniques. Beginning with an introduction to gravitational waves and the…

Instrumentation and Methods for Astrophysics · Physics 2024-10-17 Jingxu Wu , YuWei Yin , Chenjia Li , Yan Wang

The Gravitational waves have opened a new window on the Universe and paved the way to a new era of multimessenger observations of cosmic sources. Second-generation ground-based detectors such as Advanced LIGO and Advanced Virgo have been…

General Relativity and Quantum Cosmology · Physics 2023-01-13 M. Razzano , F. Di Renzo , F. Fidecaro , G. Hemming , S. Katsanevas

We present a methodology for automated real-time analysis of a radio image data stream with the goal to find transient sources. Contrary to previous works, the transients we are interested in occur on a time-scale where dispersion starts to…

Instrumentation and Methods for Astrophysics · Physics 2021-08-09 David Ruhe , Mark Kuiack , Antonia Rowlinson , Ralph Wijers , Patrick Forré

Astronomical transients are stellar objects that become temporarily brighter on various timescales and have led to some of the most significant discoveries in cosmology and astronomy. Some of these transients are the explosive deaths of…

Machine Learning · Computer Science 2021-12-20 Daniel Muthukrishna , Kaisey S. Mandel , Michelle Lochner , Sara Webb , Gautham Narayan
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