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Extreme Mass Ratio Inspirals (EMRIs) are important sources for space-borne gravitational wave detectors, such as LISA (Laser Interferometer Space Antenna) and TianQin. Previous EMRI rate studies have focused on the "loss cone" scenario,…

High Energy Astrophysical Phenomena · Physics 2021-06-16 Zhen Pan , Huan Yang

The future space-borne Laser Interferometer Space Antenna (LISA) is expected to detect gravitational waves (GW) from Extreme Mass Ratio Inspiral (EMRI) binaries which may live in nontrivial environments such as accretion disks. In this…

General Relativity and Quantum Cosmology · Physics 2024-06-25 Marco Immanuel B. Rivera , Reinabelle C. Reyes

The enhanced Gaussian noise (EGN) model, which accounts for inter-channel stimulated Raman scattering (ISRS), has been extensively utilized for evaluating nonlinear interference (NLI) within the C+L band. Compared to closed-form expressions…

Signal Processing · Electrical Eng. & Systems 2025-09-03 Ruiyang Xia , Guanjun Gao , Zanshan Zhao , Haoyu Wang , Kun Wen , Daobin Wang

This paper re-examines the problem of parameter estimation in Bayesian networks with missing values and hidden variables from the perspective of recent work in on-line learning [Kivinen & Warmuth, 1994]. We provide a unified framework for…

Machine Learning · Computer Science 2013-02-08 Eric Bauer , Daphne Koller , Yoram Singer

Extremely large mass-ratio inspirals (XMRIs), formed by brown dwarfs inspiraling into a massive black hole, emit gravitational waves (GWs) that fall within the detection band of future space-borne detectors such as LISA, TianQin, and Taiji.…

General Relativity and Quantum Cosmology · Physics 2025-11-12 Hui-Min Fan , Alejandro Torres-Orjuela , Verónica Vázquez-Aceves , Tian-Xiao Wang , Tai-Fu Feng

Systems of two black holes with unbound orbits can produce a diverse array of gravitational wave signals with rich morphology. This parameter space encompasses both hyperbolic orbit scattering events and dynamical captures, including…

General Relativity and Quantum Cosmology · Physics 2025-07-03 Chad Henshaw , Jacob Lange , Peter Lott , Richard O'Shaughnessy , Laura Cadonati

We consider the inverse problem of estimating the spatially varying pulse wave velocity in blood vessels in the brain from dynamic MRI data, as it appears in the recently proposed imaging technique of Magnetic Resonance Advection Imaging…

Numerical Analysis · Mathematics 2020-01-13 Simon Hubmer , Andreas Neubauer , Ronny Ramlau , Henning U. Voss

Estimating the probability of rare channel conditions is a central challenge in ultra-reliable wireless communication, where random events, such as deep fades, can cause sudden variations in the channel quality. This paper proposes a…

Signal Processing · Electrical Eng. & Systems 2024-07-08 Tobias Kallehauge , Anders E. Kalør , Pablo Ramírez-Espinosa , Christophe Biscio , Petar Popovski

Detecting the coalescences of massive black hole binaries (MBHBs) is one of the primary targets for space-based gravitational wave observatories such as LISA, Taiji, and Tianqin. The fast and accurate parameter estimation of merging MBHBs…

General Relativity and Quantum Cosmology · Physics 2024-12-06 Bo Liang , Minghui Du , He Wang , Yuxiang Xu , Chang Liu , Xiaotong Wei , Peng Xu , Li-e Qiang , Ziren Luo

We show that the loudest extreme mass-ratio inspirals (EMRIs) detected by the future space-based gravitational wave detector LISA can be used as dark standard sirens, statistically matching their sky localisation region with mock galaxy…

Cosmology and Nongalactic Astrophysics · Physics 2021-09-30 Danny Laghi

Extreme Mass Ratio Inspirals (EMRIs) are among the key targe sources for the space-based gravitational wave (GW) detectors. The waveforms of the EMRIs are highly sensitive to the types of the central supermassive black hole (SBH) and can…

General Relativity and Quantum Cosmology · Physics 2026-04-28 Kun Meng , Shao-Jun Zhang , Nan Yang

Inferring parameters of macro-kinetic growth models, typically represented by Ordinary Differential Equations (ODE), from the experimental data is a crucial step in bioprocess engineering. Conventionally, estimates of the parameters are…

Machine Learning · Computer Science 2023-12-07 Maxim Borisyak , Stefan Born , Peter Neubauer , Mariano Nicolas Cruz-Bournazou

The exact properties of dark matter remain largely unknown despite the accumulating evidence. If dark matter is composed of weakly interacting massive particles, it would be accreted by the black hole in the galactic center and form a…

Cosmology and Nongalactic Astrophysics · Physics 2022-09-07 Gen-Liang Li , Yong Tang , Yue-Liang Wu

Mutual Information (MI) is a crucial measure for capturing dependencies between variables, but exact computation is challenging in high dimensions with intractable likelihoods, impacting accuracy and robustness. One idea is to use an…

Machine Learning · Statistics 2025-03-13 Forough Fazeliasl , Michael Minyi Zhang , Bei Jiang , Linglong Kong

Learning energy-based models (EBMs) is known to be difficult especially on discrete data where gradient-based learning strategies cannot be applied directly. Although ratio matching is a sound method to learn discrete EBMs, it suffers from…

Machine Learning · Computer Science 2023-02-28 Meng Liu , Haoran Liu , Shuiwang Ji

This paper addresses the problem of estimating the modes of an observed non-stationary mixture signal in the presence of an arbitrary distributed noise. A novel Bayesian model is introduced to estimate the model parameters from the…

Signal Processing · Electrical Eng. & Systems 2022-03-31 Quentin Legros , Dominique Fourer , Sylvain Meignen , Marcelo A. Colominas

Using very long baseline interferometry, the Event Horizon Telescope (EHT) collaboration has resolved the shadows of two supermassive black holes. Model comparison is traditionally performed in image space, where imaging algorithms…

The low-energy effective action of String Theory introduces corrections to the dilaton-graviton sector, resulting in deformed black holes beyond general relativity. We analyze extreme mass-ratio inspiral systems (EMRIs), where a…

General Relativity and Quantum Cosmology · Physics 2024-08-29 Chao Zhang , Guoyang Fu , Yungui Gong

Purpose: We address the challenge of inaccurate parameter estimation in diffusion MRI when the signal-to-noise ratio (SNR) is very low, as in the spinal cord. The accuracy of conventional maximum-likelihood estimation (MLE) depends highly…

Reconstruction of magnetic resonance imaging (MRI) data has been positively affected by deep learning. A key challenge remains: to improve generalisation to distribution shifts between the training and testing data. Most approaches aim to…

Image and Video Processing · Electrical Eng. & Systems 2024-02-15 Yuyang Xue , Chen Qin , Sotirios A. Tsaftaris
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