The bull's-eye effect is a distortion in redshift-space that enhances large scale structures lying transverse to the line of sight, producing maps in which the observer seems to be ringed by concentric walls of galaxies [1]. A bull's-eye pattern shows up in many large scale surveys, like the one at left.
A demo from Adrian Melott's website shows how the effect arises. This animation shows a 2-D numerical simulation morphing back and forth between real-space (when running counter is 0.0) and redshift-space (when counter is 1.0).
As you watch, note that the bull's-eye pattern arises from two distortions: (1) finger of god artifacts, which thicken up filaments which happen to lie transverse to the line of sight; and (2) filament infall, which draws transverse pairs of filaments closer together, forming characteristic double walls.
Three-dimensional simulations show another feature of the bull's-eye effect: it gets stronger with increasing slice thickness [2]. This is because filaments in 3D tend to snake in and out of a thin slice. Only when the volume increases enough to capture complete filamentary networks do the walls appear. Thus, in constant angle slices like those in surveys, walls begin to appear at a distance corresponding to some critical slice thickness.We do not yet have a statistical test which can reliably distinguish between strong and weak patterns and permit quantitative comparison between simulation and survey data. This is unfortunate, since simulations show that the strength of the pattern depends on cosmological parameters such as flatness parameter Omega. For example, high omega simulations produce a strong bull's-eye; low omega simulations do not [3].
A method based on density contours and path length statistics, although initially promising when applied to thin slices of 3D simulation [4], does not work well when applied to thick slices [5, 6, 7]. Our group is currently looking at other approaches.
References
- Praton, E.A., Melott, A., & McKee, M. 1997, "The bull's-eye effect: Are galaxy walls observationally enhanced?" Ap.J., 479, L1. [ADS abstract]
- Praton, E.A., Melott, A.M., & Peterson, S.A. 1997, "Further Investigations of the Bull's-Eye Effect," 191st AAS Meet., #86.05. [ADS abstract] [some figures (ppt)].
- Melott, A.L., Coles, P., Feldman, H.A., & Wilhite, B. 1998, "The bull's-eye effect as a probe of Omega," ApJ, 496, L85. [ADS abstract]
- Thomas, B.C., Melott, A.L., Feldman, H.A., & Shandarin, S.F. 2004, "Quantifying the bull's-eye effect", ApJ, 601, 28. [ADS abstract]
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Praton, E.A., Bilikova, J., Melott, A., & Thomas, B. 2004, "Quantifying the bull's-eye effect: Thick slices," 205th AAS meet., #148.05. [ADS abstract] [poster thumbnail (pdf)]
This poster sums up results from Reports 1, 2, 3 below. - Praton, E. 2004a, "Characterizing path lengths," Report, F&M College. [full paper (pdf)]
[Report 1]
Praton, E. 2004b, "Four slices: Mean path length vs. weighted mean path length." Report, F&M College. [full paper (pdf)]
[Report 2]
Praton, E. 2004c, "Filling factor and slice thickness in measuring the bull's-eye effect." Report, F&M College. [full paper (pdf)]
[Report 3] - Edgington-Giordano, F. & Praton, E. 2005, "Quantifying the bull's-eye effect: Investigating a large sample of thick slices." Report, F&M College. [full paper (pdf)]
[Report 4]