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Structural Analysis of the SDSS Cosmic Web I.Nonlinear Density Field Reconstructions
Cosmology and Nongalactic Astrophysics · Submitted 7 Jul 2011
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Quantitatively, however, DTFE performs better, even while computationally far less demanding.
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The abstract, sentence by sentence
We investigate the ability of three reconstruction techniques to analyze and investigate weblike features and geometries in a discrete distribution of objects. The three methods are the linear Delaunay Tessellation Field Estimator (DTFE), its higher order equivalent Natural Neighbour Field Estimator (NNFE) and a version of Kriging interpolation adapted to the specific circumstances encountered in galaxy redshift surveys, the Natural Lognormal Kriging technique. DTFE and NNFE are based on the local geometry defined by the Voronoi and Delaunay tessellations of the galaxy distribution. The three reconstruction methods are analysed and compared using mock magnitude-limited and volume-limited SDSS redshift surveys, obtained on the basis of the Millennium simulation. We investigate error trends, biases and the topological structure of the resulting fields, concentrating on the void population identified by the Watershed Void Finder. Environmental effects are addressed by evaluating the density fields on a range of Gaussian filter scales. Comparison with the void population in the original simulation yields the fraction of false void mergers and false void splits. In most tests DTFE, NNFE and Kriging have largely similar density and topology error behaviour. Cosmetically, higher order NNFE and Kriging methods produce more visually appealing reconstructions. Quantitatively, however, DTFE performs better, even while computationally far less demanding. A successful recovery of the void population on small scales appears to be difficult, while the void recovery rate improves significantly on scales > 3 h-1Mpc. A study of small scale voids and the void galaxy population should therefore be restricted to the local Universe, out to at most 100 h-1Mpc.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | We investigate the ability of three reconstruction techniques to analyze and investigate weblike features and geometries in a discrete distribution of objects. | contribution 1.00 | 0.83 | 0.03 | unclear 0.55 |
| s1 | The three methods are the linear Delaunay Tessellation Field Estimator (DTFE), its higher order equivalent Natural Neighbour Field Estimator (NNFE) and a version of Kriging interpolation adapted to the specific circumstances encountered in galaxy redshift surveys, the Natural Lognormal Kriging technique. | method 0.91 | 0.29 | 0.02 | asserted 0.99 |
| s2 | DTFE and NNFE are based on the local geometry defined by the Voronoi and Delaunay tessellations of the galaxy distribution. | method 0.98 | 0.19 | 0.02 | asserted 1.00 |
| s3 | The three reconstruction methods are analysed and compared using mock magnitude-limited and volume-limited SDSS redshift surveys, obtained on the basis of the Millennium simulation. | method 0.99 | 0.86 | 0.02 | asserted 0.98 |
| s4 | We investigate error trends, biases and the topological structure of the resulting fields, concentrating on the void population identified by the Watershed Void Finder. | method 0.72 | 0.94 | 0.03 | asserted 0.81 |
| s5 | Environmental effects are addressed by evaluating the density fields on a range of Gaussian filter scales. | method 0.99 | 0.90 | 0.02 | asserted 0.92 |
| s6 | Comparison with the void population in the original simulation yields the fraction of false void mergers and false void splits. | method 0.89 | 0.93 | 0.04 | asserted 0.96 |
| s7 | In most tests DTFE, NNFE and Kriging have largely similar density and topology error behaviour. | result 1.00 | 0.92 | 0.23 | asserted 0.97 |
| s8 | Cosmetically, higher order NNFE and Kriging methods produce more visually appealing reconstructions. | result 0.98 | 0.86 | 0.04 | asserted 1.00 |
| s9 | Quantitatively, however, DTFE performs better, even while computationally far less demanding. | result 0.97 | 0.92 | 0.55 | asserted 1.00 |
| s10 | A successful recovery of the void population on small scales appears to be difficult, while the void recovery rate improves significantly on scales > 3 h-1Mpc. | result 0.94 | 0.93 | 0.23 | asserted 0.93 |
| s11 | A study of small scale voids and the void galaxy population should therefore be restricted to the local Universe, out to at most 100 h-1Mpc. | future work 0.58 | 0.64 | 0.32 | asserted 0.83 |
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Original abstract
We investigate the ability of three reconstruction techniques to analyze and investigate weblike features and geometries in a discrete distribution of objects. The three methods are the linear Delaunay Tessellation Field Estimator (DTFE), its higher order equivalent Natural Neighbour Field Estimator (NNFE) and a version of Kriging interpolation adapted to the specific circumstances encountered in galaxy redshift surveys, the Natural Lognormal Kriging technique. DTFE and NNFE are based on the local geometry defined by the Voronoi and Delaunay tessellations of the galaxy distribution. The three reconstruction methods are analysed and compared using mock magnitude-limited and volume-limited SDSS redshift surveys, obtained on the basis of the Millennium simulation. We investigate error trends, biases and the topological structure of the resulting fields, concentrating on the void population identified by the Watershed Void Finder. Environmental effects are addressed by evaluating the density fields on a range of Gaussian filter scales. Comparison with the void population in the original simulation yields the fraction of false void mergers and false void splits. In most tests DTFE, NNFE and Kriging have largely similar density and topology error behaviour. Cosmetically, higher order NNFE and Kriging methods produce more visually appealing reconstructions. Quantitatively, however, DTFE performs better, even while computationally far less demanding. A successful recovery of the void population on small scales appears to be difficult, while the void recovery rate improves significantly on scales > 3 h-1Mpc. A study of small scale voids and the void galaxy population should therefore be restricted to the local Universe, out to at most 100 h-1Mpc.
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4 arXiv papers cite this in 6 sentences
Papers citing it · 4 sentences without a confident label
Compares with it 1 paper
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It has the advantage over other structure finders [ref] in that it provides a self-consistent method for classifying structures.
A New Multi-Scale Structure Finding Algorithm to Identify Cosmological Structure · Discussion · 0.86
Cites it as background 1 paper
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The classification of voids based on galaxy surveys has turned into a common practice, (see, e.g., the CfA [ref] , the IRAS [ref] , Las Campanas [ref] , the PSCz [ref] , the 2dFRGS [ref] , the DEEP2 [ref] , the 2MRS [ref] , the SDSS survey [ref] , and the VIMOS survey [ref] ).
Signatures of the Primordial Universe from Its Emptiness: Measurement of Baryon Acoustic Oscillations from Minima of the Density Field · Introduction · 0.84
What it cites
Cites as background 1 paper
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However, various interesting new approaches and methods have been forwarded in the past few years, often based on ideas stemming from image processing, mathematical morphology, and medical imaging [ref] .
The Geometry of Nonparametric Filament Estimation · Introduction · 0.85
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