We present DisPerSE, a novel approach to the coherent multiscale identification of all types of astrophysical structures, in particular the filaments, in the large-scale distribution of the matter in ...the Universe. This method and the corresponding piece of software allows for a genuinely scale-free and parameter-free identification of the voids, walls, filaments, clusters and their configuration within the cosmic web, directly from the discrete distribution of particles in N-body simulations or galaxies in sparse observational catalogues. To achieve that goal, the method works directly over the Delaunay tessellation of the discrete sample and uses the Delaunay tessellation field estimator density computed at each tracer particle; no further sampling, smoothing or processing of the density field is required.
The idea is based on recent advances in distinct subdomains of the computational topology, namely the discrete Morse theory which allows for a rigorous application of topological principles to astrophysical data sets, and the theory of persistence, which allows us to consistently account for the intrinsic uncertainty and Poisson noise within data sets. Practically, the user can define a given persistence level in terms of robustness with respect to noise (defined as a 'number of σ') and the algorithm returns the structures with the corresponding significance as sets of critical points, lines, surfaces and volumes corresponding to the clusters, filaments, walls and voids - filaments, connected at cluster nodes, crawling along the edges of walls bounding the voids. From a geometrical point of view, the method is also interesting as it allows for a robust quantification of the topological properties of a discrete distribution in terms of Betti numbers or Euler characteristics, without having to resort to smoothing or having to define a particular scale.
In this paper, we introduce the necessary mathematical background and describe the method and implementation, while we address the application to 3D simulated and observed data sets in the companion paper (Sousbie, Pichon & Kawahara, Paper II).
Abstract
We present measurements of the Baryon Acoustic Oscillation (BAO) scale in redshift-space using the clustering of quasars. We consider a sample of 147 000 quasars from the extended Baryon ...Oscillation Spectroscopic Survey (eBOSS) distributed over 2044 square degrees with redshifts 0.8 < z < 2.2 and measure their spherically averaged clustering in both configuration and Fourier space. Our observational data set and the 1400 simulated realizations of the data set
allow us to detect a preference for BAO that is greater than 2.8σ. We determine the spherically averaged BAO distance to z = 1.52 to 3.8 per cent precision: DV(z = 1.52) = 3843 ± 147(rd/rd, fid)Mpc. This is the first time the location of the BAO feature has been measured between redshifts 1 and 2. Our result is fully consistent with the prediction obtained by extrapolating the Planck flat ΛCDM best-fitting cosmology. All of our results are consistent with basic large-scale structure (LSS) theory, confirming quasars to be a reliable tracer of LSS, and provide a starting point for numerous cosmological tests to be performed with eBOSS quasar samples. We combine our result with previous, independent, BAO distance measurements to construct an updated BAO distance-ladder. Using these BAO data alone and marginalizing over the length of the standard ruler, we find ΩΛ > 0 at 6.6σ significance when testing a ΛCDM model with free curvature.
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