Large-scale Structure Data Research Articles

Cosmological discordances. II. Hubble constant, Planck and large-scale-structure data sets

We examine systematically the (in)consistency between cosmological constraints as obtained from various current data sets of the expansion history, Large Scale Structure (LSS), and Cosmic Microwave Background (CMB) from Planck. We run (dis)concordance tests within each set and across the sets using a recently introduced index of inconsistency (IOI) capable of dissecting inconsistencies between two or more data sets. First, we compare the constraints on $H_0$ from five different methods and find that the IOI drops from 2.85 to 0.88 (on Jeffreys' scales) when the local $H_0$ measurements is removed. This seems to indicate that the local measurement is an outlier, thus favoring a systematics-based explanation. We find a moderate inconsistency (IOI=2.61) between Planck temperature and polarization. We find that current LSS data sets including WiggleZ, SDSS RSD, CFHTLenS, CMB lensing and SZ cluster count, are consistent one with another and when all combined. However, we find a persistent moderate inconsistency between Planck and individual or combined LSS probes. For Planck TT+lowTEB versus individual LSS probes, the IOI spans the range 2.92--3.72 and increases to 3.44--4.20 when the polarization data is added in. The joint LSS versus the combined Planck temperature and polarization has an IOI of 2.83 in the most conservative case. But if Planck lowTEB is added to the joint LSS to constrain $\tau$ and break degeneracies, the inconsistency between Planck and joint LSS data increases to the high-end of the moderate range with IOI=4.81. Whether due to systematic effects in the data or to the underlying model, these inconsistencies need to be resolved. Finally, we perform forecast calculations using LSST and find that the discordance between Planck and future LSS data, if it persists as present, can rise up to a high IOI of 17, thus falling in the strong range of inconsistency. (Abridged).

Wandering in the Lyman-alpha forest: a study of dark matter-dark radiation interactions

The amplitude of large-scale matter fluctuations inferred from the observed Sunyaev-Zeldovich (SZ) cluster mass function and from weak gravitational lensing studies, when taken at face value, is in tension with measurements of the cosmic microwave background (CMB) and baryon acoustic oscillation (BAO). In this work, we revisit whether this possible discrepancy can be attributed to new interactions in the dark matter sector. Focusing on a cosmological model where dark matter interacts with a dark radiation species until the epoch of matter-radiation equality, we find that measurements of the Lyman-alpha flux power spectrum from the Sloan Digital Sky Survey provide no support to the hypothesis that new dark matter interactions can resolve the possible tension between CMB and large-scale structure (LSS). Indeed, while the addition of dark matter-dark radiation interactions leads to an improvement of 2Δ ln ℒ=12 with respect to the standard Λ cold dark matter (ΛCDM) model when only CMB, BAO, and LSS data are considered, the inclusion of Lyman-alpha data reduces the improvement of the fit to 2Δ ln ℒ=6 relative to ΛCDM . We thus conclude that the statistical evidence for new dark matter interactions (largely driven by the Planck SZ dataset) is marginal at best, and likely caused by systematics in the data. We also perform a Fisher forecast analysis for the reach of a future dataset composed of a CMB-S4 experiment combined with the Large Synoptic Survey Telescope galaxy survey. We find that the constraint on the effective number of fluid-like dark radiation species, Δ Nfluid, will be improved by an order of magnitude compared to current bounds.

The cosmological principle is not in the sky

The homogeneity of matter distribution at large scales, known as the cosmological principle, is a central assumption in the standard cosmological model. The case is testable though, thus no longer needs to be a principle. Here we perform a test for spatial homogeneity using the Sloan Digital Sky Survey Luminous Red Galaxies (LRG) sample by counting galaxies within a specified volume with the radius scale varying up to 300 Mpc/h. We directly confront the large-scale structure data with the definition of spatial homogeneity by comparing the averages and dispersions of galaxy number counts with allowed ranges of the random distribution with homogeneity. The LRG sample shows significantly larger dispersions of number counts than the random catalogues up to 300 Mpc/h scale, and even the average is located far outside the range allowed in the random distribution; the deviations are statistically impossible to be realized in the random distribution. This implies that the cosmological principle does not hold even at such large scales. The same analysis of mock galaxies derived from the N-body simulation, however, suggests that the LRG sample is consistent with the current paradigm of cosmology, thus the simulation is also not homogeneous in that scale. We conclude that the cosmological principle is not in the observed sky and nor is demanded to be there by the standard cosmological world model. This reveals the nature of the cosmological principle adopted in the modern cosmology paradigm, and opens new field of research in theoretical cosmology.

Consistency of the growth rate in different environments with the 6-degree Field Galaxy Survey: Measurement of the void-galaxy and galaxy-galaxy correlation functions

We present a new test of gravitational physics by comparing the growth rate of cosmic structure measured around voids with that measured around galaxies in the same large-scale structure data set: the low-redshift 6-degree Field Galaxy Survey. By fitting a redshift space distortion model to the two-dimensional galaxy-galaxy and void-galaxy correlation functions, we recover the growth rate values $f{\ensuremath{\sigma}}_{8}=0.42\ifmmode\pm\else\textpm\fi{}0.06$ and $0.39\ifmmode\pm\else\textpm\fi{}0.11$, respectively. The environmental dependence of cosmological statistics can potentially discriminate between modified-gravity scenarios which modulate the growth rate as a function of scale or environment and test the underlying assumptions of homogeneity and isotropy.

Hiding neutrino mass in modified gravity cosmologies

Cosmological observables show a dependence with the neutrino mass, which is partially degenerate with parameters of extended models of gravity. We study and explore this degeneracy in Horndeski generalized scalar-tensor theories of gravity. Using forecasted cosmic microwave background and galaxy power spectrum datasets, we find that a single parameter in the linear regime of the effective theory dominates the correlation with the total neutrino mass. For any given mass, a particular value of this parameter approximately cancels the power suppression due to the neutrino mass at a given redshift. The extent of the cancellation of this degeneracy depends on the cosmological large-scale structure data used at different redshifts. We constrain the parameters and functions of the effective gravity theory and determine the influence of gravity on the determination of the neutrino mass from present and future surveys.

Needlet estimation of cross-correlation between CMB lensing maps and LSS

In this paper we develop a novel needlet-based estimator to investigate the cross-correlation between cosmic microwave background (CMB) lensing maps and large-scale structure (LSS) data. We compare this estimator with its harmonic counterpart and, in particular, we analyze the bias effects of different forms of masking. In order to address this bias, we also implement a MASTER-like technique in the needlet case. The resulting estimator turns out to have an extremely good signal-to-noise performance. Our analysis aims at expanding and optimizing the operating domains in CMB-LSS cross-correlation studies, similarly to CMB needlet data analysis. It is motivated especially by next generation experiments (such as Euclid) which will allow us to derive much tighter constraints on cosmological and astrophysical parameters through cross-correlation measurements between CMB and LSS.

Future constraints on angle-dependent non-Gaussianity from large radio surveys

Abstract We investigate how well future large-scale radio surveys could measure different shapes of primordial non-Gaussianity; in particular we focus on angle-dependent non-Gaussianity arising from primordial anisotropic sources, whose bispectrum has an angle dependence between the three wavevectors that is characterized by Legendre polynomials P L and expansion coefficients c L . We provide forecasts for measurements of galaxy power spectrum, finding that Large-Scale Structure (LSS) data could allow measurements of primordial non-Gaussianity that would be competitive with, or improve upon, current constraints set by CMB experiments, for all the shapes considered. We argue that the best constraints will come from the possibility to assign redshift information to radio galaxy surveys, and investigate a few possible scenarios for the EMU and SKA surveys. A realistic (futuristic) modeling could provide constraints of f NL loc ≈ 1 ( 0 . 5 ) for the local shape, f NL of O ( 10 ) ( O ( 1 ) ) for the orthogonal, equilateral and folded shapes, and c L = 1 ≈ 80 ( 2 ) , c L = 2 ≈ 400 ( 10 ) for angle-dependent non-Gaussianity showing that only futuristic galaxy surveys will be able to set strong constraints on these models. Nevertheless, the more futuristic forecasts show the potential of LSS analyses to considerably improve current constraints on non-Gaussianity, and so on models of the primordial Universe. Finally, we find the minimum requirements that would be needed to reach σ ( c L = 1 ) = 10 , which can be considered as a typical (lower) value predicted by some (inflationary) models.

Neutrino Physics from the Cosmic Microwave Background and Large-Scale Structure

Cosmology and neutrino physics have converged into a recent discovery era. The success of the standard model of cosmology in explaining the cosmic microwave background and cosmological large-scale structure data allows for the possibility of measuring the absolute neutrino mass and providing exquisite constraints on the number of light degrees of freedom, including neutrinos. This sensitivity to neutrino physics requires the validity of some of the assumptions, including general relativity, inflationary cosmology, and standard thermal history, many of which can be tested with cosmological data. This sensitivity is also predicated on the robust handling of systematic uncertainties associated with different cosmological observables. We review several past, current, and future measurements of the cosmic microwave background and cosmological large-scale structure that allow us to do fundamental neutrino physics with cosmology.

Rock-avalanche dynamics revealed by large-scale field mapping and seismic signals at a highly mobile avalanche in the West Salt Creek valley, western Colorado

On 25 May 2014, a rain-on-snow–induced rock avalanche occurred in the West Salt Creek valley on the northern flank of Grand Mesa in western Colorado (United States). The avalanche mobilized from a preexisting rock slide in the Green River Formation and traveled 4.6 km down the confined valley, killing three people. The avalanche was rare for the contiguous United States because of its large size (54.5 Mm 3 ) and high mobility (height/length = 0.14). To understand the avalanche failure sequence, mechanisms, and mobility, we conducted a forensic analysis using large-scale (1:1000) structural mapping and seismic data. We used high-resolution, unmanned aircraft system imagery as a base for field mapping, and analyzed seismic data from 22 broadband stations (distances

Searching for scalar gravitational interactions in current and future cosmological data

Modified gravity theories often contain a scalar field of gravitational strength which interacts with matter. We examine constraints on the range and the coupling strength of a scalar gravitational degree of freedom using a subset of current data that can be safely analyzed within the linear perturbation theory. Using a model-independent implementation of scalar-tensor theories in MGCAMB in terms of two functions of the scale factor describing the mass and the coupling of the scalar degree of freedom, we derive constraints on the $f(R)$, generalized chameleon, Symmetron and Dilaton models. Since most of the large scale structure data available today is from relatively low redshifts, only a limited range of observed scales is in the linear regime, leading to relatively weak constraints. We then perform a forecast for a future large scale structure survey, such as Large Synoptic Survey Telescope (LSST), which will map a significant volume at higher redshifts, and show that it will produce much stronger constraints on scalar interactions in specific models. We also perform a principal component analysis and find that future surveys should be able to provide tight constraints on several eigenmodes of the scalar mass evolution.

Systematic Prioritization of Druggable Mutations in ∼5000 Genomes Across 16 Cancer Types Using a Structural Genomics-based Approach

A massive amount of somatic mutations has been cataloged in large-scale projects such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium projects. The majority of the somatic mutations found in tumor genomes are neutral 'passenger' rather than damaging "driver" mutations. Now, understanding their biological consequences and prioritizing them for druggable targets are urgently needed. Thanks to the rapid advances in structural genomics technologies (e.g. X-ray), large-scale protein structural data has now been made available, providing critical information for deciphering functional roles of mutations in cancer and prioritizing those alterations that may mediate drug binding at the atom resolution and, as such, be druggable targets. We hypothesized that mutations at protein-ligand binding-site residues are likely to be druggable targets. Thus, to prioritize druggable mutations, we developed SGDriver, a structural genomics-based method incorporating the somatic missense mutations into protein-ligand binding-site residues using a Bayes inference statistical framework. We applied SGDriver to 746,631 missense mutations observed in 4997 tumor-normal pairs across 16 cancer types from The Cancer Genome Atlas. SGDriver detected 14,471 potential druggable mutations in 2091 proteins (including 1,516 recurrently mutated proteins) across 3558 cancer genomes (71.2%), and further identified 298 proteins harboring mutations that were significantly enriched at protein-ligand binding-site residues (adjusted p value < 0.05). The identified proteins are significantly enriched in both oncoproteins and tumor suppressors. The follow-up drug-target network analysis suggested 98 known and 126 repurposed druggable anticancer targets (e.g. SPOP and NR3C1). Furthermore, our integrative analysis indicated that 13% of patients might benefit from current targeted therapy, and this -proportion would increase to 31% when considering drug repositioning. This study provides a testable strategy for prioritizing druggable mutations in precision cancer medicine.

Erratum to: Operational earthquake loss forecasting: a retrospective analysis of some recent Italian seismic sequences

Operational earthquake forecasting (OEF) relies on real-time monitoring of seismic activity in an area of interest to provide constant (e.g., daily) updates of the expected number of events exceeding a certain magnitude threshold in a given time window (e.g., 1 week). It has been demonstrated that the rates from OEF can be used to estimate expected values of the seismic losses in the same time interval OEF refers to. This is a procedure recently defined as operational earthquake loss forecasting (OELF), which may be the basis for rational short-term seismic risk assessment and management. In Italy, an experimental OELF system, named MANTIS-K, is currently under testing. It is based on weekly rates of earthquakes exceeding magnitude (M) 4, which are updated once a day or right after the occurrence in the country of an M 3.5+ earthquake. It also relies on large-scale structural vulnerability and exposure data, which serve to the system to provide continuously the weekly expected number of: (1) collapsed buildings, (2) displaced residents, and (3) casualties. While the probabilistic basis of MANTIS-K was described in previous work, in this study OELF is critically discussed with respect to three recent Italian seismic sequences. The aim is threefold: (1) illustrating all the features of the OELF system in place; (2) providing insights to evaluate whether if it would have been a useful additional tool for short-term management; (3) recognizing common features, if any, among the losses computed for different sequences.

Accounting for baryonic effects in cosmic shear tomography: determining a minimal set of nuisance parameters using PCA

Systematic uncertainties that have been subdominant in past large-scale structure (LSS) surveys are likely to exceed statistical uncertainties of current and future LSS data sets, potentially limiting the extraction of cosmological information. Here we present a general framework (PCA marginalization) to consistently incorporate systematic effects into a likelihood analysis. This technique naturally accounts for degeneracies between nuisance parameters and can substantially reduce the dimension of the parameter space that needs to be sampled. As a practical application, we apply PCA marginalization to account for baryonic physics as an uncertainty in cosmic shear tomography. Specifically, we use CosmoLike to run simulated likelihood analyses on three independent sets of numerical simulations, each covering a wide range of baryonic scenarios differing in cooling, star formation, and feedback mechanisms. We simulate a Stage III (Dark Energy Survey) and Stage IV (Large Synoptic Survey Telescope/Euclid) survey and find a substantial bias in cosmological constraints if baryonic physics is not accounted for. We then show that PCA marginalization (employing at most 3 to 4 nuisance parameters) removes this bias. Our study demonstrates that it is possible to obtain robust, precise constraints on the dark energy equation of state even in the presence of large levels of systematic uncertainty in astrophysical processes. We conclude that the PCA marginalization technique is a powerful, general tool for addressing many of the challenges facing the precision cosmology program.

Sterile neutrinos with secret interactions—lasting friendship with cosmology

Sterile neutrinos with mass ≃ 1 eV and order 10% mixing with active neutrinos have been proposed as a solution to anomalies in neutrino oscillation data, but are tightly constrained by cosmological limits. It was recently shown that these constraints are avoided if sterile neutrinos couple to a new MeV-scale gauge boson A′. However, even this scenario is restricted by structure formation constraints when A′-mediated collisional processes lead to efficient active-to-sterile neutrino conversion after neutrinos have decoupled. In view of this, we reevaluate in this paper the viability of sterile neutrinos with such ``secret'' interactions. We carefully dissect their evolution in the early Universe, including the various production channels and the expected modifications to large scale structure formation. We argue that there are two regions in parameter space—one at very small A′ coupling, one at relatively large A′ coupling—where all constraints from big bang nucleosynthesis (BBN), cosmic microwave background (CMB), and large scale structure (LSS) data are satisfied. Interestingly, the large A′ coupling region is precisely the region that was previously shown to have potentially important consequences for the small scale structure of dark matter halos if the A′ boson couples also to the dark matter in the Universe.

Tension between the power spectrum of density perturbations measured on large and small scales

There is a tension between measurements of the amplitude of the power spectrum of density perturbations inferred using the Cosmic Microwave Background (CMB) and directly measured by Large-Scale Structure (LSS) on smaller scales. We show that this tension exists, and is robust, for a range of LSS indicators including clusters, lensing and redshift space distortions and using CMB data from either $Planck$ or WMAP+SPT/ACT. One obvious way to try to reconcile this is the inclusion of a massive neutrino which could be either active or sterile. Using $Planck$ and a combination of all the LSS data we find that (i) for an active neutrino $\sum m_{\nu}= (0.357\pm0.099)\,{\rm eV}$ and (ii) for a sterile neutrino $m_{\rm sterile}^{\rm eff}= (0.67\pm0.18)\,{\rm eV}$ and $\Delta N_{\rm eff}= 0.32\pm0.20$. This is, however, at the expense of a degraded fit to $Planck$ temperature data, and we quantify the residual tension at $2.5\sigma$ and $1.6 \sigma$ for massive and sterile neutrinos respectively. We also consider alternative explanations including a lower redshift for reionization that would be in conflict with polarisation measurements made by WMAP and $ad$-$hoc$ modifications to primordial power spectrum.

Sloan Digital Sky Survey III photometric quasar clustering: probing the initial conditions of the Universe

The Sloan Digital Sky Survey has surveyed 14,555 square degrees of the sky, and delivered over a trillion pixels of imaging data. We present the large-scale clustering of 1.6 million quasars between z=0.5 and z=2.5 that have been classified from this imaging, representing the highest density of quasars ever studied for clustering measurements. This data set spans 0∼ 11,00 square degrees and probes a volume of 80 h−3 Gpc3. In principle, such a large volume and medium density of tracers should facilitate high-precision cosmological constraints. We measure the angular clustering of photometrically classified quasars using an optimal quadratic estimator in four redshift slices with an accuracy of ∼ 25% over a bin width of δl ∼ 10−15 on scales corresponding to matter-radiation equality and larger (0ℓ ∼ 2−3).Observational systematics can strongly bias clustering measurements on large scales, which can mimic cosmologically relevant signals such as deviations from Gaussianity in the spectrum of primordial perturbations. We account for systematics by employing a new method recently proposed by Agarwal et al. (2014) to the clustering of photometrically classified quasars. We carefully apply our methodology to mitigate known observational systematics and further remove angular bins that are contaminated by unknown systematics. Combining quasar data with the photometric luminous red galaxy (LRG) sample of Ross et al. (2011) and Ho et al. (2012), and marginalizing over all bias and shot noise-like parameters, we obtain a constraint on local primordial non-Gaussianity of fNL = −113+154−154 (1σ error). We next assume that the bias of quasar and galaxy distributions can be obtained independently from quasar/galaxy-CMB lensing cross-correlation measurements (such as those in Sherwin et al. (2013)). This can be facilitated by spectroscopic observations of the sources, enabling the redshift distribution to be completely determined, and allowing precise estimates of the bias parameters. In this paper, if the bias and shot noise parameters are fixed to their known values (which we model by fixing them to their best-fit Gaussian values), we find that the error bar reduces to 1σ ≃ 65. We expect this error bar to reduce further by at least another factor of five if the data is free of any observational systematics. We therefore emphasize that in order to make best use of large scale structure data we need an accurate modeling of known systematics, a method to mitigate unknown systematics, and additionally independent theoretical models or observations to probe the bias of dark matter halos.

아파치 스쿱을 사용한 하둡의 데이터 적재 성능 영향 요인 분석

ABSTRACT Big Data technology has been attracted much attention in aspect of fast data processing. Research of practicing Big Data technology is also ongoing to process large-scale structured data much faster in Relatioinal Database(RDB). Although there are lots of studies about measuring analyzing performance, studies about structured data loading performance, prior step of analyzing, is very rare. Thus, in this study, structured data in RDB is tested the performance that loads distributed processing platform Hadoop using Apache sqoop. Also in order to analyze the influence factors of data loading, it is tested repeatedly with different options of data loading and compared with data loading performance among RDB based servers. Although data loading performance of Apache Sqoop in test environment was low, but in large-scale Hadoop cluster environment we can expect much better performance because of getting more hardware resources. It is expected to be based on study improving data loading performance and whole steps of performance analyzing structured data in Hadoop Platform.Keywords:Apache Sqoop, Hadoop, Relational Database, Data Loading Performance

Models of the Primordial Standard Clock

Oscillating massive fields in the primordial universe can be used as Standard Clocks. The ticks of these oscillations induce features in the density perturbations, which directly record the time evolution of the scale factor of the primordial universe, thus if detected, provide a direct evidence for the inflation scenario or the alternatives. In this paper, we construct a full inflationary model of primordial Standard Clock and study its predictions on the density perturbations. This model provides a full realization of several key features proposed previously. We compare the theoretical predictions from inflation and alternative scenarios with the Planck 2013 temperature data on Cosmic Microwave Background (CMB), and identify a statistically marginal but interesting candidate. We discuss how future CMB temperature and polarization data, non-Gaussianity analysis and Large Scale Structure data may be used to further test or constrain the Standard Clock signals.

Constraints on the Nambu-Goto cosmic string contribution to the CMB power spectrum in light of new temperature and polarisation data

Cosmic strings generate vector and tensor modes in the B-channel of polarisation, as well as the usual temperature power spectrum and E-mode polarisation spectrum. We use the power spectrum obtained from high-resolution Nambu-Goto cosmic string simulations together with the Planck and BICEP2 likelihoods to explore the degeneracies appearing between cosmic strings and other cosmological parameters in different inflationary scenarios, as well as the constraints that can be imposed on cosmic strings in each of these situations. In standard ΛCDM, the Planck likelihood yields an upper limit Gμ<1.49 × 10−7 (95% confidence). We also analyse the possibility of explaining the BB power spectrum signal recently detected by the BICEP2 probe. We find that cosmic strings alone are able to explain only part of the B-mode polarisation signal. Apart from the standard ΛCDM model, we look at the following non-minimal parameters: the running of the spectral index, non-zero tensor-to-scalar ratio, additional degrees of freedom (Neff) and sterile neutrinos. We find that in both Planck and BICEP2 scenarios adding Neff induces degeneracies between cosmic strings and Neff and other ΛCDM parameters. With Neff a larger contribution from cosmic strings is allowed, even favoured, but after combining with large-scale structure data, such as BAOs, strings remain strongly constrained.

Matrix-free large-scale Bayesian inference in cosmology

In this work we propose a new matrix-free implementation of the Wiener sampler which is traditionally applied to high dimensional analysis when signal covariances are unknown. Specifically, the proposed method addresses the problem of jointly inferring a high dimensional signal and its corresponding covariance matrix from a set of observations. Our method implements a Gibbs sampling adaptation of the previously presented messenger approach, permitting to cast the complex multivariate inference problem into a sequence of uni-variate random processes. In this fashion, the traditional requirement of inverting high dimensional matrices is completely eliminated from the inference process, resulting in an efficient algorithm that is trivial to implement. Using cosmic large scale structure data as a showcase, we demonstrate the capabilities of our Gibbs sampling approach by performing a joint analysis of three dimensional density fields and corresponding power-spectra from Gaussian mock catalogues. These tests clearly demonstrate the ability of the algorithm to accurately provide measurements of the three dimensional density field and its power-spectrum and corresponding uncertainty quantification. Moreover, these tests reveal excellent numerical and statistical efficiency which will generally render the proposed algorithm a valuable addition to the toolbox of large scale Bayesian inference in cosmology and astrophysics.