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Register a new userC$^3$-Cluster Clustering Cosmology II. First detection of the BAO peak in the three-point correlation function of galaxy clusters
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Third-order statistics of the cosmic density field provides a powerful cosmological probe containing synergistic information to the more commonly explored second-order statistics. Here, we exploit a spectroscopic catalog of 72,563 clusters of galaxies extracted from the Sloan Digital Sky Survey, providing the first detection of the baryon acoustic oscillations (BAO) peak in the three-point correlation function (3PCF) of galaxy clusters. We measure and analyze both the connected and the reduced 3PCF of SDSS clusters from intermediate ($rsim10$ Mpc/h) up to large ($rsim140$ Mpc/h) scales, exploring a variety of different configurations. From the analysis of reduced 3PCF at intermediate scales, in combination with the analysis of the two-point correlation function, we constrain both the cluster linear and non-linear bias parameters, $b_1=2.75pm0.03$ and $b_2=1.2pm0.5$. We analyze the measurements of the 3PCF at larger scales, comparing them with theoretical models. The data show clear evidence of the BAO peak in different configurations, which appears more visible in the reduced 3PCF rather than in the connected one. From the comparison between theoretical models considering or not the BAO peak, we obtain a quantitative estimate of this evidence, with a $Delta chi^2$ between 2 and 75, depending on the considered configuration. Finally, we set up a generic framework to estimate the expected signal-to-noise ratio of the BAO peak in the 3PCF exploring different possible definitions, that can be used to forecast the most favorable configurations to be explored also in different future surveys, and applied it to the case of the Euclid mission.
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We present the 3-point function xi_3 and Q_3=xi_3/xi_2^2 for a spectroscopic sample of luminous red galaxies (LRG) from SDSS DR6 & DR7. We find a strong (S/N$>$6) detection of $Q_3$ on scales of 55-125 Mpc/h, with a well defined peak around 105 Mpc/h in all xi_2, xi_3 and Q_3, in excellent agreement with the predicted shape and location of the imprint of the baryon acoustic oscillations (BAO). We use very large simulations to asses and test the significance of our measurement. Models without the BAO peak are ruled out by the $Q_3$ data with 99% confidence. Our measurements show the expected shape for Q_3 as a function of the triangular configuration. This provides a first direct measurement of the non-linear mode coupling coefficients of density and velocity fluctuations which, on these large scales, are independent of cosmic time, the amplitude of fluctuations or cosmological parameters. The location of the BAO peak in the data indicates Omega_m =0.28 pm 0.05 and Omega_B=0.079 pm 0.025 (h=0.70) after marginalization over spectral index (n_s=0.8-1.2) linear b_1 and quadratic c_2 bias,which are found to be in the range: b_1=1.7-2.2 and c_2=0.75-3.55. The data allows a hierarchical contribution from primordial non-Gaussianities in the range Q_3=0.55-3.35. These constraints are independent and complementary to the ones that can be obtained using the 2-point function, which are presented in a separate paper. This is the first detection of the shape of $Q_3$ on BAO scales, but our errors are shot-noise dominated and the SDSS volume is still relatively small, so there is ample room for future improvement in this type of measurements.
We present the integrated 3-point shear correlation function $izeta_{pm}$ -- a higher-order statistic of the cosmic shear field -- which can be directly estimated in wide-area weak lensing surveys without measuring the full 3-point shear correlation function, making this a practical and complementary tool to 2-point statistics for weak lensing cosmology. We define it as the 1-point aperture mass statistic $M_{mathrm{ap}}$ measured at different locations on the shear field correlated with the corresponding local 2-point shear correlation function $xi_{pm}$. Building upon existing work on the integrated bispectrum of the weak lensing convergence field, we present a theoretical framework for computing the integrated 3-point function in real space for any projected field within the flat-sky approximation and apply it to cosmic shear. Using analytical formulae for the non-linear matter power spectrum and bispectrum, we model $izeta_{pm}$ and validate it on N-body simulations within the uncertainties expected from the sixth year cosmic shear data of the Dark Energy Survey. We also explore the Fisher information content of $izeta_{pm}$ and perform a joint analysis with $xi_{pm}$ for two tomographic source redshift bins with realistic shape-noise to analyse its power in constraining cosmological parameters. We find that the joint analysis of $xi_{pm}$ and $izeta_{pm}$ has the potential to considerably improve parameter constraints from $xi_{pm}$ alone, and can be particularly useful in improving the figure of merit of the dynamical dark energy equation of state parameters from cosmic shear data.
We present new results for the 3-point correlation function, zeta, measured as a function of scale, luminosity and colour from the final version of the two-degree field galaxy redshift survey (2dFGRS). The reduced three point correlation function, Q_3 is estimated for different triangle shapes and sizes, employing a full covariance analysis. The form of Q_3 is consistent with the expectations for the Lambda-cold dark matter model, confirming that the primary influence shaping the distribution of galaxies is gravitational instability acting on Gaussian primordial fluctuations. However, we find a clear offset in amplitude between Q_3 for galaxies and the predictions for the dark matter. We are able to rule out the scenario in which galaxies are unbiased tracers of the mass at the 9-sigma level. On weakly non-linear scales, we can interpret our results in terms of galaxy bias parameters. We find a linear bias term that is consistent with unity, b_1 = 0.93^{+0.10}_{-0.08} and a quadratic bias c_2 = b_2 /b_1 = -0.34^{+0.11}_{-0.08}. This is the first significant detection of a non-zero quadratic bias, indicating a small but important non-gravitational contribution to the three point function. Our estimate of the linear bias from the three point function is independent of the normalisation of underlying density fluctuations, so we can combine this with the measurement of the power spectrum of 2dFGRS galaxies to constrain the amplitude of matter fluctuations. We find that the rms linear theory variance in spheres of radius 8Mpc/h is sigma_8 = 0.88^{+0.12}_{-0.10}, providing an independent confirmation of values derived from other techniques. On non-linear scales, where xi>1, we find that Q_3 has a strong dependence on scale, colour and luminosity.
In a series of papers we have recently studied the clustering of LRG galaxies in the latest spectroscopic SDSS data release, which has 75000 LRG galaxies sampling 1.1 Gpc^3/h^3 to z=0.47. Here we focus on detecting a local maxima shaped as a circular ring in the bidimensional galaxy correlation function xi(pi,sigma), separated in perpendicular sigma and line-of-sight pi distances. We find a significant detection of such a peak at r ~110 Mpc/h. The overall shape and location of the ring is consistent with it originating from the recombination-epoch baryon acoustic oscillations (BAO). This agreement provides support for the current understanding of how large scale structure forms in the universe. We study the significance of such feature using large mock galaxy simulations to provide accurate errorbars.
The increasingly large amount of cosmological data coming from ground-based and space-borne telescopes requires highly efficient and fast enough data analysis techniques to maximise the scientific exploitation. In this work, we explore the capabilities of supervised machine learning algorithms to learn the properties of the large-scale structure of the Universe, aiming at constraining the matter density parameter, Omega m. We implement a new Artificial Neural Network for a regression data analysis, and train it on a large set of galaxy two-point correlation functions in standard cosmologies with different values of Omega m. The training set is constructed from log-normal mock catalogues which reproduce the clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) galaxies. The presented statistical method requires no specific analytical model to construct the likelihood function, and runs with negligible computational cost, after training. We test this new Artificial Neural Network on real BOSS data, finding Omega m=0.309p/m0.008, which is remarkably consistent with standard analysis results.
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