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Register a new userArtificial Neural Networks for Galaxy Clustering. Learning from the two-point correlation function of BOSS galaxies
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Added by
Niccol\\`o Veronesi
Publication date
2021
fields
Physics
and research's language is
English
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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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We perform theoretical and numerical studies of the full relativistic two-point galaxy correlation function, considering the linear-order scalar and tensor perturbation contributions and the wide-angle effects. Using the gauge-invariant relativistic description of galaxy clustering and accounting for the contributions at the observer position, we demonstrate that the complete theoretical expression is devoid of any long-mode contributions from scalar or tensor perturbations and it lacks the infrared divergences in agreement with the equivalence principle. By showing that the gravitational potential contribution to the correlation function converges in the infrared, our study justifies an IR cut-off $(k_{text{IR}} leq H_0)$ in computing the gravitational potential contribution. Using the full gauge-invariant expression, we numerically compute the galaxy two-point correlation function and study the individual contributions in the conformal Newtonian gauge. We find that the terms at the observer position such as the coordinate lapses and the observer velocity (missing in the standard formalism) dominate over the other relativistic contributions in the conformal Newtonian gauge such as the source velocity, the gravitational potential, the integrated Sachs-Wolf effect, the Shapiro time-delay and the lensing convergence. Compared to the standard Newtonian theoretical predictions that consider only the density fluctuation and redshift-space distortions, the relativistic effects in galaxy clustering result in a few percent-level systematic errors beyond the scale of the baryonic acoustic oscillation. Our theoretical and numerical study provides a comprehensive understanding of the relativistic effects in the galaxy two-point correlation function, as it proves the validity of the theoretical prediction and accounts for effects that are often neglected in its numerical evaluation.
We present an $8.1sigma$ detection of the non-Gaussian 4-Point Correlation Function (4PCF) using a sample of $N_{rm g} approx 8times 10^5$ galaxies from the BOSS CMASS dataset. Our measurement uses the $mathcal{O}(N_{rm g}^2)$ NPCF estimator of Philcox et al. (2021), including a new modification to subtract the disconnected 4PCF contribution (arising from the product of two 2PCFs) at the estimator level. This approach is unlike previous work and ensures that our signal is a robust detection of gravitationally-induced non-Gaussianity. The estimator is validated with a suite of lognormal simulations, and the analytic form of the disconnected contribution is discussed. Due to the high dimensionality of the 4PCF, data compression is required; we use a signal-to-noise-based scheme calibrated from theoretical covariance matrices to restrict to $sim$ $100$ basis vectors. The compression has minimal impact on the detection significance and facilitates traditional $chi^2$-like analyses using a suite of mock catalogs. The significance is stable with respect to different treatments of noise in the sample covariance (arising from the limited number of mocks), but decreases to $4.7sigma$ when a minimum galaxy separation of $14 h^{-1}mathrm{Mpc}$ is enforced on the 4PCF tetrahedra (such that the statistic can be modelled more easily). The detectability of the 4PCF in the quasi-linear regime implies that it will become a useful tool in constraining cosmological and galaxy formation parameters from upcoming spectroscopic surveys.
The two-point correlation function of the galaxy distribution is a key cosmological observable that allows us to constrain the dynamical and geometrical state of our Universe. To measure the correlation function we need to know both the galaxy positions and the expected galaxy density field. The expected field is commonly specified using a Monte-Carlo sampling of the volume covered by the survey and, to minimize additional sampling errors, this random catalog has to be much larger than the data catalog. Correlation function estimators compare data-data pair counts to data-random and random-random pair counts, where random-random pairs usually dominate the computational cost. Future redshift surveys will deliver spectroscopic catalogs of tens of millions of galaxies. Given the large number of random objects required to guarantee sub-percent accuracy, it is of paramount importance to improve the efficiency of the algorithm without degrading its precision. We show both analytically and numerically that splitting the random catalog into a number of subcatalogs of the same size as the data catalog when calculating random-random pairs, and excluding pairs across different subcatalogs provides the optimal error at fixed computational cost. For a random catalog fifty times larger than the data catalog, this reduces the computation time by a factor of more than ten without affecting estimator variance or bias.
We obtain constraints on cosmological parameters from the spherically averaged redshift-space correlation function of the CMASS Data Release 9 (DR9) sample of the Baryonic Oscillation Spectroscopic Survey (BOSS). We combine this information with additional data from recent CMB, SN and BAO measurements. Our results show no significant evidence of deviations from the standard flat-Lambda CDM model, whose basic parameters can be specified by Omega_m = 0.285 +- 0.009, 100 Omega_b = 4.59 +- 0.09, n_s = 0.96 +- 0.009, H_0 = 69.4 +- 0.8 km/s/Mpc and sigma_8 = 0.80 +- 0.02. The CMB+CMASS combination sets tight constraints on the curvature of the Universe, with Omega_k = -0.0043 +- 0.0049, and the tensor-to-scalar amplitude ratio, for which we find r < 0.16 at the 95 per cent confidence level (CL). These data show a clear signature of a deviation from scale-invariance also in the presence of tensor modes, with n_s <1 at the 99.7 per cent CL. We derive constraints on the fraction of massive neutrinos of f_nu < 0.049 (95 per cent CL), implying a limit of sum m_nu < 0.51 eV. We find no signature of a deviation from a cosmological constant from the combination of all datasets, with a constraint of w_DE = -1.033 +- 0.073 when this parameter is assumed time-independent, and no evidence of a departure from this value when it is allowed to evolve as w_DE(a) = w_0 + w_a (1 - a). The achieved accuracy on our cosmological constraints is a clear demonstration of the constraining power of current cosmological observations.
We obtain constraints on the variation of the fundamental constants from the full shape of the redshift-space correlation function of a sample of luminous galaxies drawn from the Data Release 9 of the Baryonic Oscillations Spectroscopic Survey. We combine this information with data from recent CMB, BAO and H_0 measurements. We focus on possible variations of the fine structure constant alpha and the electron mass m_e in the early universe, and study the degeneracies between these constants and other cosmological parameters, such as the dark energy equation of state parameter w_DE, the massive neutrinos fraction f_ u, the effective number of relativistic species N_eff, and the primordial helium abundance Y_He. When only one of the fundamental constants is varied, our final bounds are alpha / alpha_0 = 0.9957_{-0.0042}^{+0.0041} and m_e /(m_e)_0 = 1.006_{-0.013}^{+0.014}. For their joint variation, our results are alpha / alpha_0 = 0.9901_{-0.0054}^{+0.0055} and m_e /(m_e)_0 = 1.028 +/- 0.019. Although when m_e is allowed to vary our constraints on w_DE are consistent with a cosmological constant, when alpha is treated as a free parameter we find w_DE = -1.20 +/- 0.13; more than 1 sigma away from its standard value. When f_ u and alpha are allowed to vary simultaneously, we find f_ u < 0.043 (95% CL), implying a limit of sum m_ u < 0.46 eV (95% CL), while for m_e variation, we obtain f_nu < 0.086 (95% CL), which implies sum m_ u < 1.1 eV (95% CL). When N_eff or Y_He are considered as free parameters, their simultaneous variation with alpha provides constraints close to their standard values (when the H_0 prior is not included in the analysis), while when m_e is allowed to vary, their preferred values are significantly higher. In all cases, our results are consistent with no variations of alpha or m_e at the 1 or 2 sigma level.
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