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Surveys of the cosmic large-scale structure carry opportunities for building and testing cosmological theories about the origin and evolution of the Universe. This endeavor requires appropriate data assimilation tools, for establishing the…

宇宙学与河外天体物理 · 物理学 2015-12-17 Florent Leclercq

We present a chrono-cosmography project, aiming at the inference of the four dimensional formation history of the observed large scale structure from its origin to the present epoch. To do so, we perform a full-scale Bayesian analysis of…

宇宙学与河外天体物理 · 物理学 2016-08-22 Jens Jasche , Florent Leclercq , Benjamin D. Wandelt

We describe an innovative statistical approach for the ab initio simultaneous analysis of the formation history and morphology of the large-scale structure of the inhomogeneous Universe. Our algorithm explores the joint posterior…

宇宙学与河外天体物理 · 物理学 2016-07-29 Florent Leclercq , Benjamin Wandelt

In this work we present the first non-linear, non-Gaussian full Bayesian large scale structure analysis of the cosmic density field conducted so far. The density inference is based on the Sloan Digital Sky Survey data release 7, which…

宇宙学与河外天体物理 · 物理学 2015-05-14 J. Jasche , F. S. Kitaura , C. Li , T. A. Ensslin

Analysis of three-dimensional cosmological surveys has the potential to answer outstanding questions on the initial conditions from which structure appeared, and therefore on the very high energy physics at play in the early Universe. We…

宇宙学与河外天体物理 · 物理学 2016-11-28 Florent Leclercq

What do we know about voids in the dark matter distribution given the Sloan Digital Sky Survey (SDSS) and assuming the $\Lambda\mathrm{CDM}$ model? Recent application of the Bayesian inference algorithm BORG to the SDSS Data Release 7 main…

宇宙学与河外天体物理 · 物理学 2015-06-23 Florent Leclercq , Jens Jasche , P. M. Sutter , Nico Hamaus , Benjamin Wandelt

We perform an analysis of the three-dimensional cosmic matter density field traced by galaxies of the SDSS-III/BOSS galaxy sample. The systematic-free nature of this analysis is confirmed by two elements: the successful cross-correlation…

宇宙学与河外天体物理 · 物理学 2019-09-17 Guilhem Lavaux , Jens Jasche , Florent Leclercq

The cosmic web is a complex spatial pattern of walls, filaments, cluster nodes and underdense void regions. It emerged through gravitational amplification from the Gaussian primordial density field. Here we infer analytical expressions for…

宇宙学与河外天体物理 · 物理学 2014-12-17 Job Feldbrugge , Johan Hidding , Rien van de Weygaert

We apply the BORG algorithm to the Sloan Digital Sky Survey Data Release 7 main sample galaxies. The method results in the physical inference of the initial density field at a scale factor $a~=~10^{-3}$, evolving gravitationally to the…

宇宙学与河外天体物理 · 物理学 2014-10-06 Florent Leclercq

Wide-angle, moderately deep redshift surveys such as that conducted as part of the Sloan Digital Sky Survey (SDSS) allow study of the relationship between the structural elements of the large-scale distribution of galaxies -- including…

天体物理学 · 物理学 2009-11-10 Michael S. Vogeley , Fiona Hoyle , Randall R. Rojas , David M. Goldberg

The BORG algorithm is an inference engine that derives the initial conditions given a cosmological model and galaxy survey data, and produces physical reconstructions of the underlying large-scale structure by assimilating the data into the…

宇宙学与河外天体物理 · 物理学 2015-12-09 Florent Leclercq , Jens Jasche , Guilhem Lavaux , Benjamin Wandelt

Detecting the large-scale structure of the Universe based on the galaxy distribution and characterising its components is of fundamental importance in astrophysics but is also a difficult task to achieve. Wide-area spectroscopic redshift…

宇宙学与河外天体物理 · 物理学 2020-09-30 Nicola Malavasi , Nabila Aghanim , Marian Douspis , Hideki Tanimura , Victor Bonjean

We propose a decision criterion for segmenting the cosmic web into different structure types (voids, sheets, filaments, and clusters) on the basis of their respective probabilities and the strength of data constraints. Our approach is…

宇宙学与河外天体物理 · 物理学 2015-06-23 Florent Leclercq , Jens Jasche , Benjamin Wandelt

We measure the three-dimensional topology of large-scale structure in the Sloan Digital Sky Survey (SDSS). This allows the genus statistic to be measured with unprecedented statistical accuracy. The sample size is now sufficiently large to…

A dynamical classification of the cosmic web is proposed. The large scale environment is classified into four web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor, i.e. the…

天体物理学 · 物理学 2010-11-02 J. E. Forero-Romero , Y. Hoffman , S. Gottloeber , A. Klypin , G. Yepes

We describe the Bayesian BARCODE formalism that has been designed towards the reconstruction of the Cosmic Web in a given volume on the basis of the sampled galaxy cluster distribution. Based on the realization that the massive compact…

宇宙学与河外天体物理 · 物理学 2017-03-15 E. G. Patrick Bos , Rien van de Weygaert , Francisco Kitaura , Marius Cautun

The cosmic web consists of a complex configuration of voids, walls, filaments, and clusters, which formed under the gravitational collapse of Gaussian fluctuations. Understanding under what conditions these different structures emerge from…

宇宙学与河外天体物理 · 物理学 2023-03-08 Job Feldbrugge , Rien van de Weygaert

The cosmic large scale structure encodes the formation and evolution of a weblike network of dark matter and galaxies within the Universe. The cosmological information is wrapped up in non-Gaussian statistics requiring characterisation…

宇宙学与河外天体物理 · 物理学 2024-11-26 Alex Gough

We present COSMIC BIRTH: COSMological Initial Conditions from Bayesian Inference Reconstructions with THeoretical models: an algorithm to reconstruct the primordial and evolved cosmic density fields from galaxy surveys on the light-cone.…

Morphological features in galaxies, like spiral arms, bars, rings, tidal tails etc. carry information about their structure, origin and evolution. It is therefore important to catalog and study such features and to correlate them with other…

星系天体物理 · 物理学 2025-03-06 Linn Abraham , Sheelu Abraham , Ajit K. Kembhavi , N. S. Philip , A. K. Aniyan , Sudhanshu Barway , Harish Kumar
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