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Related papers: The Multi-parameter Test of Gravitational Wave Dis…

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In the near future, space-borne gravitational wave (GW) detector LISA can open the window of low-frequency band of GW and provide new tools to test gravity theories. In this work, we consider multi-parameter tests of GW generation and…

General Relativity and Quantum Cosmology · Physics 2024-03-05 Rui Niu , Zhi-Chu Ma , Ji-Ming Chen , Chang Feng , Wen Zhao

Principal Component Analysis (PCA) is an efficient tool to optimize the multiparameter tests of general relativity (GR) where one tests for simultaneous deviations in multiple post-Newtonian (PN) phasing coefficients by introducing…

General Relativity and Quantum Cosmology · Physics 2022-08-17 Sayantani Datta , M. Saleem , K. G. Arun , B. S. Sathyaprakash

Searching for departures from general relativity (GR) in more than one post-Newtonian (PN) phasing coefficients, called a \emph{multi-parameter test}, is known to be ineffective given the sensitivity of the present generation of…

General Relativity and Quantum Cosmology · Physics 2022-05-11 Muhammed Saleem , Sayantani Datta , K. G. Arun , B. S. Sathyaprakash

We present a comprehensive assessment of multiparameter tests of general relativity (GR) in the inspiral regime of compact binary coalescences using principal component analysis (PCA). Our analysis is based on an extensive set of simulated…

We present a new multivariate regression model for analysis and parameter estimation of gravitational waves observed from well but not perfectly modeled sources such as core-collapse supernovae. Our approach is based on a principal…

General Relativity and Quantum Cosmology · Physics 2014-12-17 William J. Engels , Raymond Frey , Christian D. Ott

The Laser Interferometer Space Antenna (LISA) will provide us with a unique opportunity to observe the early inspiral phase of supermassive binary black holes (SMBBHs) in the mass range of $10^5-10^6\,M_{\odot}$, that lasts for several…

General Relativity and Quantum Cosmology · Physics 2023-03-09 Sayantani Datta

The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like compression, event detection, and event recognition. This technique is…

Networking and Internet Architecture · Computer Science 2010-03-13 Yann-Aël Le Borgne , Sylvain Raybaud , Gianluca Bontempi

The growing catalog of gravitational wave (GW) detections by the LIGO-Virgo-KAGRA Collaboration enables increasingly stringent tests of general relativity, particularly regarding possible parity and Lorentz violations. While most current…

General Relativity and Quantum Cosmology · Physics 2025-07-15 Wei-Hua Guo , Yuan-Zhu Wang , Tao Zhu

Searching for a modified dispersion relation is one of the general relativity tests performed by the LIGO-Virgo-KAGRA collaboration with each new cumulative Gravitational Wave Transient Catalog (GWTC). It considers classes of theories that…

General Relativity and Quantum Cosmology · Physics 2026-04-02 Tomasz Baka , Balázs Cirok , K. Haris , Johannes Noller , N. V. Krishnendu

We present a new straightforward principal component analysis (PCA) method based on the diagonalization of the weighted variance-covariance matrix through two spectral decomposition methods: power iteration and Rayleigh quotient iteration.…

Instrumentation and Methods for Astrophysics · Physics 2014-12-16 Ludovic Delchambre

Gravitational wave observations offer unique opportunities to probe gravity in the strong and dynamical regime, which was difficult to access previously. We here review two theory-agnostic ways to carry out tests of general relativity with…

General Relativity and Quantum Cosmology · Physics 2020-05-19 Zack Carson , Kent Yagi

Amplitude and phase of the gravitational waveform from compact binary systems can be decomposed in terms of their mass- and current-type multipole moments. In a modified theory of gravity, one or more of these multipole moments could…

General Relativity and Quantum Cosmology · Physics 2024-10-14 Parthapratim Mahapatra , Shilpa Kastha , Anuradha Gupta , B. S. Sathyaprakash , K. G. Arun

Any modification on gravity would affect not only gravitational wave (GW) generation but also GW propagation. Therefore, tests of general relativity (GR) with only GW generation or GW propagation will lead to an overestimate for deviations.…

General Relativity and Quantum Cosmology · Physics 2020-09-22 Ke Wang

Successful detection of gravitational waves has presented a new avenue to explore the nature of gravity. With the cumulative catalog of detected events, we can perform tests on General Relativity from various aspects with increasing…

General Relativity and Quantum Cosmology · Physics 2023-03-07 Rui Niu , Tao Zhu , Wen Zhao

Probabilistic principal component analysis (PPCA) seeks a low dimensional representation of a data set in the presence of independent spherical Gaussian noise. The maximum likelihood solution for the model is an eigenvalue problem on the…

Machine Learning · Computer Science 2012-06-22 Alfredo Kalaitzis , Neil Lawrence

A general linear gauge-invariant equation for dispersive gravitational waves (GWs) propagating in matter is derived. This equation describes, on the same footing, both the usual tensor modes and the gravitational modes strongly coupled with…

General Relativity and Quantum Cosmology · Physics 2022-08-12 Deepen Garg , I. Y. Dodin

We present an improved subdominant-mode amplitude (SMA) test of general relativity (GR), which probes amplitude-level deviations in the higher-order modes of gravitational-wave (GW) signals from binary black hole mergers while keeping the…

General Relativity and Quantum Cosmology · Physics 2025-11-18 Ish Gupta , Purnima Narayan , Lionel London , Shubhanshu Tiwari , Bangalore Sathyaprakash

The direct detection of gravitational waves by the LIGO-Virgo collaboration has opened a new window with which to measure cosmological parameters such as the Hubble constant $H_0$, and also probe general relativity on large scales. In this…

General Relativity and Quantum Cosmology · Physics 2020-08-14 S. Mastrogiovanni , D. Steer , M. Barsuglia

Principal component analysis (PCA) is arguably the most widely used approach for large-dimensional factor analysis. While it is effective when the factors are sufficiently strong, it can be inconsistent when the factors are weak and/or the…

Methodology · Statistics 2025-08-22 Zhongyuan Lyu , Ming Yuan

Principal Component Analysis (PCA) is a cornerstone of dimensionality reduction, yet its classical formulation relies critically on second-order moments and is therefore fragile in the presence of heavy-tailed data and impulsive noise.…

Machine Learning · Computer Science 2026-05-05 Mario Sayde , Christopher Khater , Jihad Fahs , Ibrahim Abou-Faycal
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