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We propose an approach based on function evaluations and Bayesian inference to extract higher-order differential information of objective functions {from a given ensemble of particles}. Pointwise evaluation $\{V(x^i)\}_i$ of some potential…

Machine Learning · Statistics 2023-03-02 Claudia Schillings , Claudia Totzeck , Philipp Wacker

Extreme-mass-ratio inspirals (EMRIs) carry valuable information about their surrounding astrophysical environments. Over the course of their long-term evolution, interactions between the secondary object and the accretion disk can produce…

General Relativity and Quantum Cosmology · Physics 2026-04-14 Jian-Dong Liu , Wen-Biao Han , Hiromichi Tagawa

We examine extreme mass-ratio inspirals (EMRIs) as probes of beyond-vacuum general relativistic effects, accounting for both astrophysical environments and scalar Gauss-Bonnet (sGB) gravity. In beyond-vacuum scenarios, the evolution of an…

General Relativity and Quantum Cosmology · Physics 2026-01-08 Tieguang Zi , Mostafizur Rahman , Shailesh Kumar

In this paper, we investigate the impact of loop quantum gravity (LQG) on extreme mass-ratio inspirals (EMRIs), and the results indicate that LQG effects cause the orbital decay to occur faster compared to the Schwarzschild case.…

General Relativity and Quantum Cosmology · Physics 2024-09-20 Guoyang Fu , Yunqi Liu , Bin Wang , Jian-Pin Wu , Chao Zhang

Even if globally neutral, in various scenarios compact objects can have a nonvanishing dipole moment. Examples include neutron stars with magnetic dipoles, black-hole microstates in the string-theory fuzzball scenario, and classical black…

General Relativity and Quantum Cosmology · Physics 2023-10-13 Jacopo Lestingi , Enrico Cannizzaro , Paolo Pani

Using an analytic, static, and spherically symmetric metric for a Schwarzschild black hole immersed in a dark matter (DM) halo with the Hernquist-type profile, we derive analytic expressions for the orbital period and precession of…

General Relativity and Quantum Cosmology · Physics 2024-11-01 Ning Dai , Yungui Gong , Yang Zhao , Tong Jiang

The Gaussian splatting methods are getting popular. However, their loss function only contains the $\ell_1$ norm and the structural similarity between the rendered and input images, without considering the edges in these images. It is…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Yuanhao Gong

Upcoming Large Scale Structure surveys aim to achieve an unprecedented level of precision in measuring galaxy clustering. However, accurately modeling these statistics may require theoretical templates that go beyond second-order…

Cosmology and Nongalactic Astrophysics · Physics 2023-11-21 M. Icaza-Lizaola , Yong-Seon Song , Minji Oh , Yi Zheng

Lagrangian particle tracking is essential for characterizing turbulent flows, but inferring particle acceleration from inherently noisy position data remains a significant challenge. Fluid particles in turbulence experience extreme,…

Data Analysis, Statistics and Probability · Physics 2026-02-27 Griffin M Kearney , Kasey M Laurent , Makan Fardad

We describe a new class of resonances for extreme mass-ratio inspirals (EMRIs): tidal resonances, induced by the tidal field of nearby stars or stellar-mass black holes. A tidal resonance can be viewed as a general relativistic extension of…

General Relativity and Quantum Cosmology · Physics 2019-09-24 Béatrice Bonga , Huan Yang , Scott A. Hughes

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

The future space-based gravitational wave observatory, the Laser Interferometer Space Antenna, is expected to observe between 1-1000s extreme mass-ratio inspirals (EMRIs) per year. Due to the simultaneous presence of other gravitational…

General Relativity and Quantum Cosmology · Physics 2025-12-30 Sviatoslav Khukhlaev , Stanislav Babak

Extreme-mass-ratio inspirals (EMRIs), consisting of a massive black hole and a stellar compact object, are one of the most important sources for space-borne gravitational wave detectors like TianQin. Their population study can be used to…

High Energy Astrophysical Phenomena · Physics 2025-05-08 Hui-Min Fan , Xiang-Yu Lyu , Jian-dong Zhang , Yi-Ming Hu , Rong-Jia Yang , Tai-Fu Feng

This paper presents a probabilistic surrogate model for the accelerated design of electric vehicle battery enclosures with a focus on crash performance. The study integrates high-throughput finite element simulations and Gaussian Process…

Machine Learning · Computer Science 2024-08-08 Shadab Anwar Shaikh , Harish Cherukuri , Kranthi Balusu , Ram Devanathan , Ayoub Soulami

Magnetic Resonance Imaging (MRI) is one of the fields that the compressed sensing theory is well utilized to reduce the scan time significantly leading to faster imaging or higher resolution images. It has been shown that a small fraction…

Information Theory · Computer Science 2014-06-03 Cagdas Bilen , Yao Wang , Ivan Selesnick

We propose a novel exponentially-modified Gaussian (EMG) mixture residual model. The EMG mixture is well suited to model residuals that are contaminated by a distribution with positive support. This is in contrast to commonly used robust…

Machine Learning · Statistics 2019-02-18 Sebastian Ament , John Gregoire , Carla Gomes

We propose to use gravitational waves from extreme mass ratio inspirals (EMRI), composed of a boson star and a supermassive black hole in the center of galaxies, as a new method to search for boson stars. Gravitational waves from EMRI have…

High Energy Physics - Phenomenology · Physics 2019-09-25 Huai-Ke Guo , Kuver Sinha , Chen Sun

Studies regarding extra-dimensions have been of great interest in modern theoretical physics, including their observational consequences from future gravitational wave (GW) observatories. In this direction, extreme-mass-ratio inspirals…

General Relativity and Quantum Cosmology · Physics 2025-07-17 Shailesh Kumar , Tieguang Zi , Arpan Bhattacharyya

Accurate assessment of systematic uncertainties is an increasingly vital task in physics studies, where large, high-dimensional datasets, like those collected at the Large Hadron Collider, hold the key to new discoveries. Common approaches…

Methodology · Statistics 2025-10-02 Alexis Romero , Kyle Cranmer , Daniel Whiteson

Latent Gaussian models have a rich history in statistics and machine learning, with applications ranging from factor analysis to compressed sensing to time series analysis. The classical method for maximizing the likelihood of these models…

Machine Learning · Computer Science 2023-06-07 Alexander Lin , Bahareh Tolooshams , Yves Atchadé , Demba Ba
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