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Recent advances in medical research have improved survival outcomes for patients with life-threatening diseases. As a result, the existence of long-term survivors from these illnesses is becoming common. However, conventional models in…

Applications · Statistics 2025-07-16 Dionisio Silva Neto , Francisco Louzada Neto , Vera Lucia Tomazella

The growth rate of matter density perturbations has been measured from redshift-space distortion (RSD) in the galaxy power spectrum. We constrain the model parameter space for representative modified gravity models to explain the dark…

Cosmology and Nongalactic Astrophysics · Physics 2013-05-13 Hiroyuki Okada , Tomonori Totani , Shinji Tsujikawa

We investigate the ability of state-of-the-art redshift-space distortions models for the galaxy anisotropic two-point correlation function \xi(r_p, \pi), to recover precise and unbiased estimates of the linear growth rate of structure f,…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-04 Sylvain de la Torre , Luigi Guzzo

Adding to our previous method for dealing with gravitational modifications at redshift $z\gtrsim3$ through a single parameter, we investigate treatment of lower redshift modifications to linear growth observables. We establish subpercent…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-29 Mikhail Denissenya , Eric V. Linder

The observed accelerated expansion of the Universe may be explained by dark energy or the breakdown of general relativity (GR) on cosmological scales. When the latter case, a modified gravity scenario, is considered, it is often assumed…

Cosmology and Nongalactic Astrophysics · Physics 2020-08-04 Jiro Matsumoto , Teppei Okumura , Misao Sasaki

Finding an unconstrained and statistically interpretable reparameterization of a covariance matrix is still an open problem in statistics. Its solution is of central importance in covariance estimation, particularly in the recent…

Methodology · Statistics 2012-02-09 Mohsen Pourahmadi

Constraints on the properties of the cosmological dark matter have previously been obtained in a model-independent fashion using the Generalised Dark Matter (GDM) framework. Here we extend that work in several directions: We consider the…

Cosmology and Nongalactic Astrophysics · Physics 2020-05-05 Daniel B Thomas , Michael Kopp , Katarina Markovič

We propose a new nonlinear factorization model for graphs that are with topological structures, and optionally, node attributes. This model is based on a pseudometric called Gromov-Wasserstein (GW) discrepancy, which compares graphs in a…

Machine Learning · Computer Science 2019-11-21 Hongteng Xu

We constrain the expansion history of the Universe and the cosmological matter density fraction in a model-independent way by exclusively making use of the relationship between background and perturbations under a minimal set of…

Cosmology and Nongalactic Astrophysics · Physics 2022-02-16 Jaime Ruiz-Zapatero , Carlos García-García , David Alonso , Pedro G. Ferreira , Richard D. P. Grumitt

In this paper, a specific family of $f(R)$ models that can produce the $\Lambda$CDM background expansion history is constrained by using the currently available geometric and dynamic probes. The scale dependence of the growth rate $f(z,k)$…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-23 Lixin Xu

Deep Generative Models (DGMs) are versatile tools for learning data representations while adequately incorporating domain knowledge such as the specification of conditional probability distributions. Recently proposed DGMs tackle the…

Machine Learning · Computer Science 2024-01-30 Romain Lopez , Jan-Christian Huetter , Ehsan Hajiramezanali , Jonathan Pritchard , Aviv Regev

In this work we discuss observational aspects of three time-dependent parameterisations of the dark energy equation of state $w(z)$. In order to determine the dynamics associated with these models, we calculate their background evolution…

Cosmology and Nongalactic Astrophysics · Physics 2016-11-09 Celia Escamilla-Rivera , Luciano Casarini , Julio C. Fabris , Jailson S. Alcaniz

ReParameterization (RP) Policy Gradient Methods (PGMs) have been widely adopted for continuous control tasks in robotics and computer graphics. However, recent studies have revealed that, when applied to long-term reinforcement learning…

Machine Learning · Computer Science 2023-11-01 Shenao Zhang , Boyi Liu , Zhaoran Wang , Tuo Zhao

Analytic formulas reproducing the warm dark matter (WDM) primordial spectra are obtained for WDM particles decoupling in and out of thermal equilibrium which provide the initial data for WDM non-linear structure formation. We compute and…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-16 C. Destri , H. J. de Vega , N. G. Sanchez

We have studied the dependence of topology of large scale structure on tracer, gravitational evolution, redshift space distortion, and cosmology. A series of large N-body simulations of the $\Lambda$CDM and SCDM models that have evolved 1.1…

Astrophysics · Physics 2009-11-10 Changbom Park , Juhan Kim , J. Richard Gott

We investigate the exact analytic solutions for the growths of the dark matter and the baryon in sub-horizon scale. The growth of the dark matter $\delta_{\DM}$ is related to that of the halos. Thus, the exact solution for the growth of the…

Cosmology and Nongalactic Astrophysics · Physics 2009-07-03 Seokcheon Lee

The key probes of the growth of large-scale structure are its rate $f$ and amplitude $\sigma_8$. Redshift space distortions in the galaxy power spectrum allow us to measure only the combination $f\sigma_8$, which can be used to constrain…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-14 Louis Perenon , Stéphane Ilić , Roy Maartens , Alvaro de la Cruz-Dombriz

As a test of general relativity on cosmological scales, we measure the \gamma parameter for the growth rate of density perturbations using the redshift-space distortion of the luminous red galaxies in the Sloan Digital Sky Survey (SDSS).…

Astrophysics · Physics 2008-12-18 Kazuhiro Yamamoto , Takahiro Sato , Gert Huetsi

Despite the proliferation of generative models, achieving fast sampling during inference without compromising sample diversity and quality remains challenging. Existing models such as Denoising Diffusion Probabilistic Models (DDPM) deliver…

Machine Learning · Computer Science 2023-10-12 Yanwu Xu , Mingming Gong , Shaoan Xie , Wei Wei , Matthias Grundmann , Kayhan Batmanghelich , Tingbo Hou

Recently, a novel Einstein-Gauss-Bonnet gravity in four dimensions has been introduced [Phys. Rev. Lett. 124 (2020) 081301]. We will investigate cosmological consequences of this model in details. We will consider linear matter density…

General Relativity and Quantum Cosmology · Physics 2020-10-05 Zahra Haghani
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