21 citations · 59 across the 12 of their papers we have counts for
6 papers · 1 filter
Glitch noise classification in KAGRA O3GK observing data using unsupervised machine learning
Shoichi Oshino, Yusuke Sakai, Marco Meyer-Conde +5
Gravitational wave interferometers are disrupted by various types of nonstationary noise, referred to as glitch noise, that affect data analysis and interferometer sensitivity. The…
Regression of Suspension Violin Modes in KAGRA O3GK Data with Kalman Filters
Lucas Moisset, Marco Meyer-Conde, Christopher Allene +4
Suspension thermal modes in interferometric gravitational-wave detectors produce narrow, high-Q spectral lines that can contaminate gravitational searches and bias parameter estima…
Parameter estimation of protoneutron stars from gravitational wave signals using the Hilbert-Huang transform
Seiya Sasaoka, Yusuke Sakai, Diego Dominguez +5
Core-collapse supernovae (CCSNe) are potential multimessenger events detectable by current and future gravitational wave (GW) detectors. The GW signals emitted during these events…
Comparative study of 1D and 2D convolutional neural network models with attribution analysis for gravitational wave detection from compact binary coalescences
Seiya Sasaoka, Naoki Koyama, Diego Dominguez +4
Recent advancements in gravitational wave astronomy have seen the application of convolutional neural networks (CNNs) in signal detection from compact binary coalescences. This stu…
Training Process of Unsupervised Learning Architecture for Gravity Spy Dataset
Yusuke Sakai, Yousuke Itoh, Piljong Jung +11
Transient noise appearing in the data from gravitational-wave detectors frequently causes problems, such as instability of the detectors and overlapping or mimicking gravitational-…
Unsupervised Learning Architecture for Classifying the Transient Noise of Interferometric Gravitational-wave Detectors
Yusuke Sakai, Yousuke Itoh, Piljong Jung +11
In the data obtained by laser interferometric gravitational wave detectors, transient noise with non-stationary and non-Gaussian features occurs at a high rate. This often results…