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The current accelerated expansion of the Universe remains ones of the most intriguing topics in modern cosmology, driving the search for innovative statistical techniques. Recent advancements in machine learning have significantly enhanced…

Cosmology and Nongalactic Astrophysics · Physics 2025-01-03 José de Jesús Velázquez , Luis A. Escamilla , Purba Mukherjee , J. Alberto Vázquez

Cosmological models and their parameters are widely debated, especially about whether the current discrepancy between the values of the Hubble constant, $H_{0}$, obtained by type Ia supernovae (SNe Ia), and the Planck data from the Cosmic…

In this work, using the Gaussian Process, we explore the potentiality of future gravitational wave (GW) measurement to probe cosmic opacity through comparing its opacity-free luminosity distance (LD) with the opacity-dependent one from type…

General Relativity and Quantum Cosmology · Physics 2020-01-22 Lu Zhou , Xiangyun Fu , Zhaohui Peng , Jun Chen

The cosmic distance ladder is the succession of techniques by which it is possible to determine distances to astronomical objects. Here, we present a new method to build the cosmic distance ladder, going from local astrophysical…

Cosmology and Nongalactic Astrophysics · Physics 2020-06-09 David Camarena , Valerio Marra

The cosmic distance relation (DDR) associates the angular diameters distance ($D_A$) and luminosity distance ($D_L$) by a simple formula, i.e., $D_L=(1+z)^2D_A$. The strongly lensed gravitational waves (GWs) provide a unique way to measure…

General Relativity and Quantum Cosmology · Physics 2021-01-19 Hai-Nan Lin , Xin Li , Li Tang

A plethora of observational data obtained over the last couple of decades has allowed cosmology to enter into a precision era and has led to the foundation of the standard cosmological constant and cold dark matter paradigm, known as the…

Cosmology and Nongalactic Astrophysics · Physics 2021-05-31 Rubén Arjona , Savvas Nesseris

Providing accurate uncertainty estimations is essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold…

We present a novel non-parametric method for inferring smooth models of the mean velocity field and velocity dispersion tensor of the Milky Way from astrometric data. Our approach is based on Stochastic Variational Gaussian Process…

Astrophysics of Galaxies · Physics 2025-07-15 Timothy Hapitas , Lawrence M. Widrow , Thavisha E. Dharmawardena , Daniel Foreman-Mackey

The galaxy distributions along the line-of-sight are significantly contaminated by the uncertainty on redshift measurements obtained through multiband photometry, which makes it difficult to get cosmic distance information measured from…

Cosmology and Nongalactic Astrophysics · Physics 2019-07-15 Srivatsan Sridhar , Yong-Seon Song

We test the possible deviation of the cosmic distance duality relation $D_A(z)(1+z)^2/D_L(z)\equiv 1$ using the standard candles/rulers in a fully model-independent manner. Type-Ia supernovae are used as the standard candles to derive the…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-14 Xin Li , Hai-Nan Lin

In this letter, the distance-duality (DD) relation is reconstructed by Gaussian process (GP) which is cosmological model-independent. Generally, the GP plays two important roles. One is to shape the $\eta$ tendency which denotes the…

Cosmology and Nongalactic Astrophysics · Physics 2015-01-07 Yi Zhang

The redshifted 21\,cm line is an emerging tool in observational cosmology that can serve as a direct probe of the intergalactic medium throughout the cosmic timeline. However, the observation of the cosmological 21\,cm signal from early…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-12 Samit Kumar Pal , Abhirup Datta , Aishrila Mazumder , Anshuman Tripathi

Gaussian Process (GP) regression is a powerful nonparametric Bayesian framework, but its performance depends critically on the choice of covariance kernel. Selecting an appropriate kernel is therefore central to model quality, yet remains…

Machine Learning · Computer Science 2026-01-14 Md Shafiqul Islam , Shakti Prasad Padhy , Douglas Allaire , Raymundo Arróyave

Semantic distance measurement is a fundamental problem in computational linguistics, providing a quantitative characterization of similarity or relatedness between text segments, and underpinning tasks such as text retrieval and text…

Computation and Language · Computer Science 2025-12-16 Yinzhu Cheng , Haihua Xie , Yaqing Wang , Miao He , Mingming Sun

Crosscorrelation of the outputs of two Gravitational Wave (GW) detectors has recently been proposed [1] as a method for detecting statistical association between GWs and Gamma Ray Bursts (GRBs). Unfortunately, the method can be effectively…

Astrophysics · Physics 2009-11-07 G. Modestino , A. Moleti

The cosmic distance duality relates the angular-diameter and luminosity distances and its possible violation may puzzle the standard cosmological model. This appears particularly interesting in view of the recent results found by the DESI…

Cosmology and Nongalactic Astrophysics · Physics 2025-01-28 Anna Chiara Alfano , Orlando Luongo

In this work, using the Gaussian process, we explore the potentiality of future gravitational wave (GW) measurements to probe cosmic opacity at high redshifts through comparing its opacity-free luminosity distance (LD) with the…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-28 Xiangyun Fu , Jianfei Yang , Zhaoxia Chen , Lu Zhou , Jun Chen

We use the two-point correlation function of the extrema points (peaks and valleys) in the COBE Differential Microwave Radiometers (DMR) 2-year sky maps as a test for non-Gaussian temperature distribution in the cosmic microwave background…

Astrophysics · Physics 2011-05-10 A. Kogut , A. J. Banday , C. L. Bennett , G. Hinshaw , P. M. Lubin , G. F. Smoot

The distribution closeness testing (DCT) assesses whether the distance between a distribution pair is at least $\epsilon$-far. Existing DCT methods mainly measure discrepancies between a distribution pair defined on discrete one-dimensional…

Machine Learning · Computer Science 2025-10-10 Zhijian Zhou , Liuhua Peng , Xunye Tian , Feng Liu

This study aims to test the validity of general relativity (GR) on kiloparsec scales by employing a newly compiled galaxy-scale strong gravitational lensing (SGL) sample. We utilize the distance sum rule within the…

Cosmology and Nongalactic Astrophysics · Physics 2024-01-10 Jing-Yu Ran , Jun-Jie Wei
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