Search

The mysterious nature of the dark sector of the Λ-cold-dark-matter (ΛCDM) model is one of the main motivators behind the study of alternative cosmological models. A central quantity of interest for these models is the matter power spectrum, which quantifies structure formation on various scales and can be cross-validated through theory, simulations, and observations. Here, we present a tool that can be used to create emulators for the non-linear matter power spectrum, and similar global clustering statistics, for models beyond ΛCDM with very little computation effort and without the need for supercomputers. We use fast approximate N-body simulations to emulate the boost, B(k, z) = Pbeyond − ΛCDM(k, z)/PΛCDM(k, z), and then rely on existing high-quality emulators made for ΛCDM to isolate Pbeyond − ΛCDM(k, z). Since both the ΛCDM and beyond-ΛCDM models are simulated in our approach, some of the lack of power on small scales due to the low force-resolution in the simulations is factored out, allowing us to extend the emulator to k ∼ 3 − 5 h Mpc−1 and still maintain good accuracy. In addition, errors from the simulation and emulation process can easily be estimated and factored into the covariance when using the emulator on data. As an example of using the pipeline, we create an emulator for the well-studied f(R) model with massive neutrinos, using approximately 3000 CPU hours of computation time. Provided with the paper is a fully functioning pipeline that generates parameter samples, runs a Boltzmann solver to produce initial conditions, runs the simulations, and then gathers all the data and runs it through a machine learning module to develop the emulator. This tool, named Sesame, can be used by anyone to generate a power spectrum emulator for the cosmological model of their choice. [ABSTRACT FROM AUTHOR]

We investigate the main tensions within the current standard model of cosmology from the perspective of the main statistics of cosmic voids, using the final BOSS DR12 data set. For this purpose, we present the first estimate of the S8 ≡ σ8 Ωm/0.3 and H0 parameters obtained from void number counts and shape distortions. To analyze void counts we relied on an extension of the popular volume-conserving model for the void size function, tailored to the application on data, including geometric and dynamic distortions. We calibrated the two nuisance parameters of this model with the official BOSS Collaboration mock catalogs and propagated their uncertainty through the statistical analysis of the BOSS void number counts. The constraints from void shapes come from the study of the geometric distortions of the stacked void-galaxy cross-correlation function. In this work we focus our analysis on the Ωm − σ8 and Ωm − H0 parameter planes and derive the marginalized constraints S8 = 0.813−0.068+0.093 and H0 = 67.3−9.1+10.0 km s−1 Mpc−1, which are fully compatible with constraints from the literature. These results are expected to notably improve in precision when analyzed jointly with independent probes and will open a new viewing angle on the rising cosmological tensions in the near future. [ABSTRACT FROM AUTHOR]

Super-sample covariance (SSC) is an important effect for cosmological analyses that use the deep structure of the cosmic web; it may, however, be nontrivial to include it practically in a pipeline. We solve this difficulty by presenting a formula for the precision (inverse covariance) matrix and show applications to update likelihood or Fisher forecast pipelines. The formula has several advantages in terms of speed, reliability, stability, and ease of implementation. We present an analytical application to show the formal equivalence between three approaches to SSC: (i) at the usual covariance level, (ii) at the likelihood level, and (iii) with a quadratic estimator. We then present an application of this computationally efficient framework for studying the impact of inaccurate modelling of SSC responses for cosmological constraints from stage IV surveys. We find that a weak-lensing-only analysis is very sensitive to inaccurate modelling of the scale dependence of the response, which needs to be calibrated at the ∼15% level. The sensitivity to this scale dependence is less severe for the joint weak-lensing and galaxy clustering analysis (also known as 3×2pt). Nevertheless, we find that both the amplitude and scale-dependence of the responses have to be calibrated at better than 30%. [ABSTRACT FROM AUTHOR]

With the aim of bringing substantial insight to the fundamental question of how galaxies acquire their material for star formation, we present the first comprehensive characterisation of the galaxy connectivity (i.e. the number of small-scale filamentary streams connected to a galaxy) in relation to the cosmic environment, and a statistical exploration of the impact of connectivity on the star formation rate (SFR) at z = 2. We detected kiloparsec-scale filaments directly connected to galaxies by applying the DisPerSE filament finder to the dark matter density around 2942 central galaxies (M* > 108 M⊙/h) of the TNG50-1 simulation. Our results demonstrate that galaxy connectivity spans a broad range (from 0 to 9), with more than half of the galaxies connected to two or three streams. We examined a variety of factors that might influence the connectivity and found that it increases with mass, decreases with local density for low-mass galaxies, and does not depend on local environment, estimated by the Delaunay tessellation, for high-mass galaxies. Beyond mass and local density, we further classified galaxies according to their location in different cosmic web environments, and we highlight the influence of the large-scale structure on the number of connected streams. Our results reflect the different strengths of the cosmic tides, which can prevent the formation of coherent streams feeding the galaxies or even disconnect the galaxy from its local web. Finally, we show that at fixed local density, the SFR of low-mass galaxies is up to 5.9σ higher as a result of connectivity. This SFR boost is even higher (6.3σ) for galaxies that are embedded in cosmic filaments, where the available matter reservoirs are large. A milder impact is found for high-mass galaxies, which indicates different relative efficiencies of matter inflow via small-scale streams in galaxies of different masses. [ABSTRACT FROM AUTHOR]

Context. As modern-day precision cosmology aims for statistical uncertainties of the percent level or lower, it becomes increasingly important to reconsider estimator assumptions at each step of the process, along with their consequences on the statistical variability of the scientific results. Aims. We compare L1 regression statistics to the weighted mean, the canonical L2 method based on Gaussian assumptions, to infer the weak gravitational shear signal from a catalog of background ellipticity measurements around a sample of clusters, which has been a standard step in the processes of many recent analyses. Methods. We use the shape measurements of background sources around 6925 AMICO clusters detected in the KiDS third data release. We investigate the robustness of our results and the dependence of uncertainties on the signal-to-noise ratios of the background source detections. Using a halo model approach, we derive lensing masses from the estimated excess surface density profiles. Results. The highly significant shear signal allows us to study the scaling relation between the r-band cluster luminosity, L200, and the derived lensing mass, M200. We show the results of the scaling relations derived in 13 bins in L200, with a tightly constrained power-law slope of ∼1.24 ± 0.08. We observe a small, but significant, relative bias of a few percent in the recovered excess surface density profiles between the two regression methods, which translates to a 1σ difference in M200. The efficiency of L1 is at least that of the weighted mean and increases with higher signal-to-noise shape measurements. Concluions. Our results indicate the relevance of optimizing the estimator for inferring the gravitational shear from a distribution of background ellipticities. The interpretation of measured relative biases can be gauged by deeper observations, and the increased computation times remain feasible. [ABSTRACT FROM AUTHOR]

We present a set of maps classifying regions of the sky according to their information gain potential as quantified by Fisher information. These maps can guide the optimal retrieval of relevant physical information with targeted cosmological searches. Specifically, we calculated the response of observed cosmic structures to perturbative changes in the cosmological model and we charted their respective contributions to Fisher information. Our physical forward-modeling machinery transcends the limitations of contemporary analyses based on statistical summaries to yield detailed characterizations of individual 3D structures. We demonstrate this advantage using galaxy counts data and we showcase the potential of our approach by studying the information gain of the Coma cluster. We find that regions in the vicinity of the filaments and cluster core, where mass accretion ensues from gravitational infall, are the most informative with regard to our physical model of structure formation in the Universe. Hence, collecting data in those regions would be most optimal for testing our model predictions. The results presented in this work are the first of their kind to elucidate the inhomogeneous distribution of cosmological information in the Universe. This study paves a new way forward for the performance of efficient targeted searches for the fundamental physics of the Universe, where search strategies are progressively refined with new cosmological data sets within an active learning framework. [ABSTRACT FROM AUTHOR]

Context. The density split statistics in weak gravitational lensing analyses probes the correlation between regions of different (foreground) galaxy number densities and their weak lensing signal, which is measured by the shape distortion of background galaxies. Aims. In this paper, we reconsider density split statistics, by constructing a new angular filter function that is adapted to the expected relation between the galaxy number density and shear pattern, in a way that the filter weighting the galaxy number density is matched to the filter that is used to quantify the shear signal. Methods. We used the results of numerical ray-tracing simulations, specifically through the Millennium Simulation supplemented by a galaxy distribution based on a semi-analytic model, to construct a matched pair of adapted filter functions for the galaxy density and the tangential shear signal. We compared the performance of our new filter to the previously used top-hat filter, applying both to a different and independent set of numerical simulations (SLICS, cosmo-SLICS). Results. We show that the adapted filter yields a better correlation between the total matter and the galaxy distribution. Furthermore, the adapted filter provides a larger signal-to-noise ratio to constrain the bias between the total matter and the galaxy distribution, and we show that it is, in general, a more sensitive discriminator between different cosmologies, with the exception of cosmologies with very large σ8 values. All analyses lead to the conclusion that our adapted filter should be favoured in future density split statistic works. [ABSTRACT FROM AUTHOR]

We simultaneously present constraints on the stellar-to-halo mass relation for central and satellite galaxies through a weak lensing analysis of spectroscopically classified galaxies. Using overlapping data from the fourth data release of the Kilo-Degree Survey (KiDS), and the Galaxy And Mass Assembly survey (GAMA), we find that satellite galaxies are hosted by halo masses that are 0.53 ± 0.39 dex (68% confidence, 3σ detection) smaller than those of central galaxies of the same stellar mass (for a stellar mass of log(M⋆/M⊙) = 10.6). This is consistent with galaxy formation models, whereby infalling satellite galaxies are preferentially stripped of their dark matter. We find consistent results with similar uncertainties when comparing constraints from a standard azimuthally averaged galaxy-galaxy lensing analysis and a two-dimensional likelihood analysis of the full shear field. As the latter approach is somewhat biased due to the lens incompleteness and as it does not provide any improvement to the precision when applied to actual data, we conclude that stacked tangential shear measurements are best-suited for studies of the galaxy-halo connection. [ABSTRACT FROM AUTHOR]

We address the problem of inferring the three-dimensional matter distribution from a sparse set of one-dimensional quasar absorption spectra of the Lyman-α forest. Using a Bayesian forward modelling approach, we focus on extending the dynamical model to a fully self-consistent hierarchical field-level prediction of redshift-space quasar absorption sightlines. Our field-level approach rests on a recently developed semiclassical analogue to Lagrangian perturbation theory (LPT), which improves over noise problems and interpolation requirements of LPT. It furthermore allows for a manifestly conservative mapping of the optical depth to redshift space. In addition, this new dynamical model naturally introduces a coarse-graining scale, which we exploited to accelerate the Markov chain Monte-Carlo (MCMC) sampler using simulated annealing. By gradually reducing the effective temperature of the forward model, we were able to allow it to first converge on large spatial scales before the sampler became sensitive to the increasingly larger space of smaller scales. We demonstrate the advantages, in terms of speed and noise properties, of this field-level approach over using LPT as a forward model, and, using mock data, we validated its performance to reconstruct three-dimensional primordial perturbations and matter distribution from sparse quasar sightlines. [ABSTRACT FROM AUTHOR]

Galaxy clusters are connected at their peripheries to the large-scale structures by cosmic filaments that funnel accreting material. These filamentary structures are studied to investigate both environment-driven galaxy evolution and structure formation and evolution. In the present work, we probe in a statistical manner the azimuthal distribution of galaxies around clusters as a function of the cluster-centric distance, cluster richness, and star-forming or passive galaxy activity. We performed a harmonic decomposition in large photometric galaxy catalogue around 6400 SDSS clusters with masses M > 1014 solar masses in the redshift range of 0:1 < z < 0:3. The same analysis was performed on the mock galaxy catalogue from the light cone of a Magneticum hydrodynamical simulation. We used the multipole analysis to quantify asymmetries in the 2D galaxy distribution. In the inner cluster regions at R < 2R500, we confirm that the galaxy distribution traces an ellipsoidal shape, which is more pronounced for richest clusters. In the outskirts of the clusters (R = [2-8]R500), filamentary patterns are detected in harmonic space with a mean angular scale mmean = 4:2 ± 0:1. Massive clusters seem to have a larger number of connected filaments than lower-mass clusters. We also find that passive galaxies appear to trace the filamentary structures around clusters better. This is the case even if the contribution of star-forming galaxies tends to increase with the cluster-centric distance, suggesting a gradient of galaxy activity in filaments around clusters. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We revisit the performance and biases of the two-dimensional approach to galaxy–galaxy lensing. This method exploits the information for the actual positions and ellipticities of source galaxies, rather than using only the ensemble properties of statistically equivalent samples. We compare the performance of this method with the traditionally used one-dimensional tangential shear signal on a set of mock data that resemble the current state-of-the-art weak lensing surveys. We find that under idealised circumstances the confidence regions of joint constraints for the amplitude and scale parameters of the NFW model in the two-dimensional analysis can be more than three times tighter than the one-dimensional results. Moreover, this improvement depends on the lens number density and it is larger for higher densities. We compare the method against the results from the hydrodynamical EAGLE simulation in order to test for possible biases that might arise due to lens galaxies being missed, and find that the method is able to return unbiased estimates of halo masses when compared to the true properties of the EAGLE galaxies. Because of its advantage in high galaxy density areas, the method is especially suitable for studying the properties of satellite galaxies in clusters of galaxies. [ABSTRACT FROM AUTHOR]

Context. Galaxy filaments are the dominant feature in the overall structure of the cosmic web. The study of the filamentary web is an important aspect in understanding galaxy evolution and the evolution of matter in the Universe. A map of the filamentary structure is an adequate probe of the web. Aims. We propose that photometric redshift galaxies are significantly positively associated with the filamentary structure detected from the spatial distribution of spectroscopic redshift galaxies. The long-term aim is to use the photometric galaxies in addition to spectroscopic galaxies to create a more detailed and far-reaching map of the filamentary structure. Methods. The catalogues of spectroscopic and photometric galaxies are seen as point-process realisations in a sphere, and the catalogue of filamentary spines is proposed to be a realisation of a random set in a sphere. The positive association between these sets was studied using a bivariate J-function, which is a summary statistics studying clustering. A quotient D was built to estimate the distance distribution of the filamentary spine to galaxies in comparison to the distance distribution of the filamentary spine to random points in 3-dimensional Euclidean space. This measure also gives a physical distance scale to the distances between filamentary spines and the studied sets of galaxies. In the 3-dimensional case, galaxies and random points are described as line of sights following through their positions on the sphere. Results. The bivariate J-function shows a statistically significant clustering effect in between filamentary spines and photometric redshift galaxies. The quotient D confirms the previous result that smaller distances exist with higher probability between the photometric galaxies and filaments. The trend of smaller distances between the objects grows stronger at higher redshift. Additionally, the quotient D for photometric galaxies gives a rough estimate for the filamentary spine width of about 1 Mpc. Conclusions. Photometric redshift galaxies are positively associated with filamentary spines detected from the spatial distribution of spectroscopic galaxies. In addition to the spatial distribution of spectroscopic galaxies, the information embedded in the photometric galaxies could contribute greatly to the detection of cosmic web structures. [ABSTRACT FROM AUTHOR]

The treatment of unknown foreground contaminations will be one of the major challenges for galaxy clustering analyses of coming decadal surveys. These data contaminations introduce erroneous large-scale effects in recovered power spectra and inferred dark matter density fields. In this work, we present an effective solution to this problem in the form of a robust likelihood designed to account for effects due to unknown foreground and target contaminations. Conceptually, this robust likelihood marginalizes over the unknown large-scale contamination amplitudes. We showcase the effectiveness of this novel likelihood via an application to a mock SDSS-III data set subject to dust extinction contamination. In order to illustrate the performance of our proposed likelihood, we infer the underlying dark-matter density field and reconstruct the matter power spectrum, being maximally agnostic about the foregrounds. The results are compared to those of an analysis with a standard Poissonian likelihood, as typically used in modern large-scale structure analyses. While the standard Poissonian analysis yields excessive power for large-scale modes and introduces an overall bias in the power spectrum, our likelihood provides unbiased estimates of the matter power spectrum over the entire range of Fourier modes considered in this work. Further, we demonstrate that our approach accurately accounts for and corrects the effects of unknown foreground contaminations when inferring three-dimensional density fields. Robust likelihood approaches, as presented in this work, will be crucial to control unknown systematic error and maximize the outcome of the decadal surveys. [ABSTRACT FROM AUTHOR]

We present a large-scale Bayesian inference framework to constrain cosmological parameters using galaxy redshift surveys, via an application of the Alcock-Paczyński (AP) test. Our physical model of the non-linearly evolved density field, as probed by galaxy surveys, employs Lagrangian perturbation theory (LPT) to connect Gaussian initial conditions to the final density field, followed by a coordinate transformation to obtain the redshift space representation for comparison with data. We have implemented a Hamiltonian Monte Carlo sampler to generate realisations of three-dimensional (3D) primordial and present-day matter fluctuations from a non-Gaussian LPT-Poissonian density posterior given a set of observations. This hierarchical approach encodes a novel AP test, extracting several orders of magnitude more information from the cosmic expansion compared to classical approaches, to infer cosmological parameters and jointly reconstruct the underlying 3D dark matter density field. The novelty of this AP test lies in constraining the comoving-redshift transformation to infer the appropriate cosmology which yields isotropic correlations of the galaxy density field, with the underlying assumption relying purely on the geometrical symmetries of the cosmological principle. Such an AP test does not rely explicitly on modelling the full statistics of the field. We verified in depth via simulations that this renders our test robust to model misspecification. This leads to another crucial advantage, namely that the cosmological parameters exhibit extremely weak dependence on the currently unresolved phenomenon of galaxy bias, thereby circumventing a potentially key limitation. This is consequently among the first methods to extract a large fraction of information from statistics other than that of direct density contrast correlations, without being sensitive to the amplitude of density fluctuations. We perform several statistical efficiency and consistency tests on a mock galaxy catalogue, using the SDSS-III survey as template, taking into account the survey geometry and selection effects, to validate the Bayesian inference machinery implemented. [ABSTRACT FROM AUTHOR]

We explore the use of the cosmic infrared background (CIB) as a tracer of the large scale structures for cross-correlating with the cosmic microwave background (CMB) and exploit the integrated Sachs–Wolfe (ISW) effect. We used an improved linear CIB model from our previous work and derived the theoretical CIB×ISW cross-correlation for different Planck HFI frequencies (217, 353, 545 and 857 GHz) and IRAS (3000 GHz). As expected, we predict a positive cross-correlation between the CIB and the CMB whose amplitude decreases rapidly at small scales. We perform a signal-to-noise ratio (S/N) analysis of the predicted cross-correlation. In the ideal case when the cross-correlation is obtained over 70% (40%) of the sky without residual contaminants (e.g. galactic dust) in maps, the S/N ranges from 4.2 to 5.6 (3.2 to 4.3); the highest S/N comes from 857 GHz. A Fisher matrix analysis shows that an ISW signal detected with a S/N this high on the 40% sky can considerably improve the constraints on the cosmological parameters; constraints on the equation of state of the dark energy especially are improved by 80%. We then performed a more realistic analysis considering the effect of residual galactic dust contamination in CIB maps. We calculated the dust power spectra for different frequencies and sky fractions that dominate the CIB power spectra at the lower multipoles we are interested in. Considering a conservative 10% residual level of galactic dust in the CIB power spectra, we observe that the S/N drops drastically, which makes it very challenging to detect the ISW. To determine the capability of current maps to detect the ISW effect through this method, we measured the cross-correlation of the CIB and the CMB Planck maps on the so-called GASS field, which covers an area of ∼11% in the southern hemisphere. We find that with such a small sky fraction and the dust residuals in the CIB maps, we do not detect any ISW signal, and the measured cross-correlation is consistent with zero. To avoid degrading the S/N for the ISW measurement by more than 10% on the 40% sky, we find that the dust needs to be cleaned up to the 0.01% level on the power spectrum. [ABSTRACT FROM AUTHOR]

We have examined dust emission in galaxy clusters at millimeter wavelengths using the Planck 857 GHz map to constrain the model based on Herschel observations that was used in studies for the Cosmic ORigins Explorer (CORE) mission concept. By stacking the emission from Planck-detected clusters, we estimated the normalization of the infrared luminosity versus mass relation and constrained the spatial profile of the dust emission. We used this newly constrained model to simulate clusters that we inject into Planck frequency maps. The comparison between clusters extracted using these gas+dust simulations and the basic gas-only simulations allows us to assess the impact of cluster dust emission on Planck results. In particular, we determined the impact on cluster parameter recovery (size, flux) and on Planck cluster cosmology results (survey completeness, determination of cosmological parameters). We show that dust emission has a negligible effect on the recovery of individual cluster parameters for the Planck mission, but that it impacts the cluster catalog completeness, reducing the number of detections in the redshift range [0.3–0.8] by up to ∼9%. Correcting for this incompleteness in the cosmological analysis has a negligible effect on cosmological parameter measurements: in particular, it does not ease the tension between Planck cluster and primary cosmic microwave background cosmologies. [ABSTRACT FROM AUTHOR]

We present a machine-learning photometric redshift (ML photo-z) analysis of the Kilo-Degree Survey Data Release 3 (KiDS DR3), using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes provide photo-zs of quality comparable to, if not better than, those from the Bayesian Photometric Redshift (BPZ) code, at least up to zphot ≲ 0.9 and r ≲ 23.5. At the bright end of r ≲ 20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared (IR) bands are added. While the fiducial four-band ugri setup gives a photo-z bias 〈δz/(1 + z)〉 = -2 × 10-4 and scatter σδz/(1+z) < 0.022 at mean 〈z〉 = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by ~7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 μm, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives 〈δz/(1 + z)〉 < 4 × 10-5 and σδz/(1+z) < 0.019. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimised for low-redshift studies such as galaxy-galaxy lensing, is limited to r ≲ 20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation. [ABSTRACT FROM AUTHOR]

Context. Upcoming weak lensing surveys such as Euclid will provide an unprecedented opportunity to quantify the geometry and topology of the cosmic web, in particular in the vicinity of lensing clusters. Aims. Understanding the connectivity of the cosmic web with unbiased mass tracers, such as weak lensing, is of prime importance to probe the underlying cosmology, seek dynamical signatures of dark matter, and quantify environmental effects on galaxy formation. Methods. Mock catalogues of galaxy clusters are extracted from the N-body PLUS simulation. For each cluster, the aperture multipolar moments of the convergence are calculated in two annuli (inside and outside the virial radius). By stacking their modulus, a statistical estimator is built to characterise the angular mass distribution around clusters. The moments are compared to predictions from perturbation theory and spherical collapse. Results. The main weakly chromatic excess of multipolar power on large scales is understood as arising from the contraction of the primordial cosmic web driven by the growing potential well of the cluster. Besides this boost, the quadrupole prevails in the cluster (ellipsoidal) core, while at the outskirts, harmonic distortions are spread on small angular modes, and trace the non-linear sharpening of the filamentary structures. Predictions for the signal amplitude as a function of the cluster-centric distance, mass, and redshift are presented. The prospects of measuring this signal are estimated for current and future lensing data sets. Conclusions. The Euclid mission should provide all the necessary information for studying the cosmic evolution of the connectivity of the cosmic web around lensing clusters using multipolar moments and probing unique signatures of, for example, baryons and warm dark matter. [ABSTRACT FROM AUTHOR]

Aims. Gravitational lensing allows us to quantify the angular distribution of the convergence field around clusters of galaxies to constrain their connectivity to the cosmic web. We describe the corresponding theory in Lagrangian space in which analytical results can be obtained by identifying clusters to peaks in the initial field. Methods. We derived the three-point Gaussian statistics of a two-dimensional (2D) field and its first and second derivatives. The formalism allowed us to study the statistics of the field in a shell around a central peak, in particular its multipolar decomposition. Results. The peak condition is shown to significantly remove power from the dipolar contribution and to modify the monopole and quadrupole. As expected, higher order multipoles are not significantly modified by the constraint. Analytical predictions are successfully checked against measurements in Gaussian random fields. The effect of substructures and radial weighting is shown to be small and does not change the qualitative picture. The non-linear evolution is shown to induce a non-linear bias of all multipoles proportional to the cluster mass. Conclusions. We predict the Gaussian and weakly non-Gaussian statistics of multipolar moments of a 2D field around a peak as a proxy for the azimuthal distribution of the convergence field around a cluster of galaxies. A quantitative estimate of this multipolar decomposition of the convergence field around clusters in numerical simulations of structure formation and in observations will be presented in two forthcoming papers. [ABSTRACT FROM AUTHOR]

Context: The Sloan Digital Sky Survey (SDSS) is the first dense redshift survey encompassing a volume large enough to find the best analytic probability density function that fits the galaxy counts-in-cells distribution fV (N), the frequency distribution of galaxy counts in a volume V. Aims: Different analytic functions have been proposed that can account for some of the observed features of the observed frequency counts, but fail to provide an overall good fit to this important statistical descriptor of the galaxy large-scale distribution. Our goal is to find the probability density function that best fits the observed counts-in-cells distribution fV (N). Methods: We have made a systematic study of this function applied to several samples drawn from the SDSS. We show the effective ways to deal with incompleteness of the sample (masked data) in the calculation of fV (N). We used LasDamas simulations to estimate the errors in the calculation. We tested four different distribution functions to find the best fit: the gravitational quasi-equilibrium distribution, the negative binomial distribution, the log normal distribution, and the log normal distribution including a bias parameter. In the two latter cases, we apply a shot-noise correction to the distributions assuming the local Poisson model. Results: We show that the best fit for the counts-in-cells distribution function is provided by the negative binomial distribution. In addition, at large scales the log normal distribution modified with the inclusion of the bias term also performs a satisfactory fit of the empirical values of fV (N). Our results demonstrate that the inclusion of a bias term in the log normal distribution is necessary to fit the observed galaxy count-in-cells distribution function. [ABSTRACT FROM AUTHOR]

Context. The next generation of galaxy surveys will provide cluster catalogues probing an unprecedented range of scales, redshifts, and masses with large statistics. Their analysis should therefore enable us to probe the spatial distribution of clusters with high accuracy and derive tighter constraints on the cosmological parameters and the dark energy equation of state. However, for the majority of these surveys, redshifts of individual galaxies will be mostly estimated by multiband photometry which implies nonnegligible errors in redshift resulting in potential difficulties in recovering the real-space clustering. Aims. We investigate to which accuracy it is possible to recover the real-space two-point correlation function of galaxy clusters from cluster catalogues based on photometric redshifts, and test our ability to detect and measure the redshift and mass evolution of the correlation length r0 and of the bias parameter b(M, z) as a function of the uncertainty on the cluster redshift estimate. Methods. We calculate the correlation function for cluster sub-samples covering various mass and redshift bins selected from a 500 deg² light-cone limited to H < 24. In order to simulate the distribution of clusters in photometric redshift space, we assign to each cluster a redshift randomly extracted from a Gaussian distribution having a mean equal to the cluster cosmological redshift and a dispersion equal to σz. The dispersion is varied in the range σ(z=0) = ... = 0.005,0.010,0.030 and 0.050, in order to cover the typical values expected in forthcoming surveys. The correlation function in real-space is then computed through estimation and deprojection of wp(rp). Four mass ranges (from Mhalo > 2 × 1013 h-1 M∡ to Mhalo > 2 × 1014 h-1 M∡) and six redshift slices covering the redshift range [0, 2] are investigated, first using cosmological redshifts and then for the four photometric redshift configurations. Results. From the analysis of the light-cone in cosmological redshifts we find a clear increase of the correlation amplitude as a function of redshift and mass. The evolution of the derived bias parameter b(M, z) is in fair agreement with theoretical expectations. We calculate the r0 - d relation up to our highest mass, highest redshift sample tested (z = 2, Mhalo > 2 × 1014 h-1 M∡). From our pilot sample limited to Mhalo > 5 × 1013 h1 M∡ (0.4 < z < 0.7), we find that the real-space correlation function can be recovered by deprojection of wp(rp) within an accuracy of 5% for σz = 0.001 × (1 + zc) and within 10% for σz = 0.03 × (1 + zc). For higher dispersions (besides σz > 0.05 × (1 + zc)), the recovery becomes noisy and difficult. The evolution of the correlation in redshift and mass is clearly detected for all σz tested, but requires a large binning in redshift to be detected significantly between individual redshift slices when increasing σz. The best-fit parameters (r0 and) as well as the bias obtained from the deprojection method for all σz are within the 1σ uncertainty of the zc sample. [ABSTRACT FROM AUTHOR]

Determining magnetic field properties in different environments of the cosmic large-scale structure as well as their evolution over redshift is a fundamental step toward uncovering the origin of cosmic magnetic fields. Radio observations permit the study of extragalactic magnetic fields via measurements of the Faraday depth of extragalactic radio sources. Our aim is to investigate how much different extragalactic environments contribute to the Faraday depth variance of these sources. We develop a Bayesian algorithm to distinguish statistically Faraday depth variance contributions intrinsic to the source from those due to the medium between the source and the observer. In our algorithm the Galactic foreground and measurement noise are taken into account as the uncertainty correlations of the Galactic model. Additionally, our algorithm allows for the investigation of possible redshift evolution of the extragalactic contribution. This work presents the derivation of the algorithm and tests performed on mock observations. Because cosmic magnetism is one of the key science projects of the new generation of radio interferometers, we have predicted the performance of our algorithm on mock data collected with these instruments. According to our tests, high-quality catalogs of a few thousands of sources should already enable us to investigate magnetic fields in the cosmic structure. [ABSTRACT FROM AUTHOR]

In this paper, we develop a full statistical method for the pairwise velocity estimator previously proposed, and apply Cosmicflows-2 catalogue to this method to constrain cosmology. We first calculate the covariance matrix for line-of-sight velocities for a given catalogue, and then simulate the mock full-sky surveys from it, and then calculate the variance for the pairwise velocity field. By applying the 8315 independent galaxy samples and compressed 5224 group samples from Cosmicflows-2 catalogue to this statistical method, we find that the joint constraint on Ωm0.6h and s8 is completely consistent with the WMAP 9-year and Planck 2015 best-fitting cosmology. Currently, there is no evidence for the modified gravity models or any dynamic dark energy models from this practice, and the error-bars need to be reduced in order to provide any concrete evidence against/to support ΛCDM cosmology. [ABSTRACT FROM AUTHOR]

We present a method for measuring the masses of galaxy clusters using the imprint of their gravitational lensing signal on the cosmic microwave background (CMB) temperature anisotropies. The method first reconstructs the projected gravitational potential with a quadratic estimator and then applies a matched filter to extract cluster mass. The approach is well-suited for statistical analyses that bin clusters according to other mass proxies. We find that current experiments, such as Planck, the South Pole Telescope and the Atacama Cosmology Telescope, can practically implement such a statistical methodology, and that future experiments will reach sensitivities sucient for individual measurements of massive systems. As illustration, we use simulations of Planck observations to demonstrate that it is possible to constrain the mass scale of a set of 62 massive clusters with prior information from X-ray observations, similar to the published Planck ESZ-XMM sample. We examine the eect of the thermal (tSZ) and kinetic (kSZ) Sunyaev-Zeldovich (SZ) signals, finding that the impact of the kSZ remains small in this context. The stronger tSZ signal, however, must be actively removed from the CMB maps by component separation techniques prior to reconstruction of the gravitational potential. Our study of two such methods highlights the importance of broad frequency coverage for this purpose. A companion paper presents application to the Planck data on the ESZ-XMM sample. [ABSTRACT FROM AUTHOR]

Context. Upcoming spectroscopic galaxy surveys are extremely promising to help in addressing the major challenges of cosmology, in particular in understanding the nature of the dark universe. The strength of these surveys, naturally described in spherical geometry, comes from their unprecedented depth and width, but an optimal extraction of their three-dimensional information is of utmost importance to best constrain the properties of the dark universe. Aims. Although there is theoretical motivation and novel tools to explore these surveys using the 3D spherical Fourier-Bessel (SFB) power spectrum of galaxy number counts Cl(k, k'), most survey optimisations and forecasts are based on the tomographic spherical harmonics power spectrum Cl(i j). The goal of this paper is to perform a new investigation of the information that can be extracted from these two analyses in the context of planned stage IV wide-field galaxy surveys. Methods. We compared tomographic and 3D SFB techniques by comparing the forecast cosmological parameter constraints obtained from a Fisher analysis. The comparison was made possible by careful and coherent treatment of non-linear scales in the two analyses, which makes this study the first to compare 3D SFB and tomographic constraints on an equal footing. Nuisance parameters related to a scale- and redshift-dependent galaxy bias were also included in the computation of the 3D SFB and tomographic power spectra for the first time. Results. Tomographic and 3D SFB methods can recover similar constraints in the absence of systematics. This requires choosing an optimal number of redshift bins for the tomographic analysis, which we computed to be N = 26 forzmed ≃ 0.4, N = 30 for zmed ≃ 1.0, and N = 42 for zmed ≃ 1.7. When marginalising over nuisance parameters related to the galaxy bias, the forecast 3D SFB constraints are less affected by this source of systematics than the tomographic constraints. In addition, the rate of increase of the figure of merit as a function of median redshift is higher for the 3D SFB method than for the 2D tomographic method. Conclusions. Constraints from the 3D SFB analysis are less sensitive to unavoidable systematics stemming from a redshift- and scale-dependent galaxy bias. Even for surveys that are optimised with tomography in mind, a 3D SFB analysis is more powerful. In addition, for survey optimisation, the figure of merit for the 3D SFB method increases more rapidly with redshift, especially at higher redshifts, suggesting that the 3D SFB method should be preferred for designing and analysing future wide-field spectroscopic surveys. CosmicPy, the Python package developed for this paper, is freely available at https://cosmicpy.github.io. [ABSTRACT FROM AUTHOR]

Do current observational data confirm the assumptions of the cosmological principle, or is there statistical evidence for deviations from spatial homogeneity on large scales? To address these questions, we developed a flexible framework based on spherically symmetric, but radially inhomogeneous Lemaître-Tolman-Bondi (LTB) models with synchronous Big Bang. We expanded the (local) matter density profile in terms of flexible interpolation schemes and orthonormal polynomials. A Monte Carlo technique in combination with recent observational data was used to systematically vary the shape of these profiles. In the first part of this article, we reconsider giant LTB voids without dark energy to investigate whether extremely fine-tuned mass profiles can reconcile these models with current data. While the local Hubble rate and supernovae can easily be fitted without dark energy, however, model-independent constraints from the Planck 2013 data require an unrealistically low local Hubble rate, which is strongly inconsistent with the observed value; this result agrees well with previous studies. In the second part, we explain why it seems natural to extend our framework by a non-zero cosmological constant, which then allows us to perform general tests of the cosmological principle. Moreover, these extended models facilitate explorating whether fluctuations in the local matter density profile might potentially alleviate the tension between local and global measurements of the Hubble rate, as derived from Cepheid-calibrated type Ia supernovae and CMB experiments, respectively. We show that current data provide no evidence for deviations from spatial homogeneity on large scales. More accurate constraints are required to ultimately confirm the validity of the cosmological principle, however. [ABSTRACT FROM AUTHOR]

Context. The nature of dark energy is imprinted in the large-scale structure of the Universe and thus in the mass and redshift distribution of galaxy clusters. The upcoming eROSITA instrument will exploit this method of probing dark energy by detecting ~100 000 clusters of galaxies in X-rays. Aims. For a precise cosmological analysis the various galaxy cluster properties need to be measured with high precision and accuracy. To predict these characteristics of eROSITA galaxy clusters and to optimise optical follow-up observations, we estimate the precision and the accuracy with which eROSITA will be able to determine galaxy cluster temperatures and redshifts from X-ray spectra. Additionally, we present the total number of clusters for which these two properties will be available from the eROSITA survey directly. Methods. We simulate the spectra of galaxy clusters for a variety of different cluster masses and redshifts while taking into account the X-ray background as well as the instrumental response. An emission model is then fit to these spectra to recover the cluster temperature and redshift. The number of clusters with precise properties is then based on the convolution of the above fit results with the galaxy cluster mass function and an assumed eROSITA selection function. Results. During its four years of all-sky surveys, eROSITA will determine cluster temperatures with relative uncertainties of ΔT=T ≲ 10% at the 68%-confidence level for clusters up to redshifts of z ~ 0:16 which corresponds to ~1670 new clusters with precise properties. Redshift information itself will become available with a precision of Δz=(1 + z) ≲ 10% for clusters up to z ~ 0:45. Additionally, we estimate how the number of clusters with precise properties increases with a deepening of the exposure. For the above clusters, the fraction of catastrophic failures in the fit is below 20% and in most cases it is even much smaller. Furthermore, the biases in the best-fit temperatures as well as in the estimated uncertainties are quantified and shown to be negligible in the relevant parameter range in general. For the remaining parameter sets, we provide correction functions and factors. In particular, the standard way of estimating parameter uncertainties significantly underestimates the true uncertainty, if the redshift information is not available. Conclusions. The eROSITA survey will increase the number of galaxy clusters with precise temperature measurements by a factor of 5-10. Thus the instrument presents itself as a powerful tool for the determination of tight constraints on the cosmological parameters. At the same time, this sample of clusters will extend our understanding of cluster physics, e.g. through precise LX - T scaling relations. [ABSTRACT FROM AUTHOR]

Context. Research over the past three decades has revolutionized cosmology while supporting the standard cosmological model. However, the cosmological principle of Universal homogeneity and isotropy has always been in question, since structures as large as the survey size have always been found each time the survey size has increased. Until 2013, the largest known structure in our Universe was the Sloan Great Wall, which is more than 400 Mpc long located approximately one billion light years away. Aims. Gamma-ray bursts (GRBs) are the most energetic explosions in the Universe. As they are associated with the stellar endpoints of massive stars and are found in and near distant galaxies, they are viable indicators of the dense part of the Universe containing normal matter. The spatial distribution of GRBs can thus help expose the large scale structure of the Universe. Methods. As of July 2012, 283 GRB redshifts have been measured. Subdividing this sample into nine radial parts, each containing 31 GRBs, indicates that the GRB sample having 1.6 < z < 2.1 differs significantly from the others in that 14 of the 31 GRBs are concentrated in roughly 1/8 of the sky. A two-dimensional Kolmogorov-Smirnov test, a nearest-neighbour test, and a Bootstrap Point-Radius Method explore the significance of this clustering. Results. All tests used indicate that there is a statistically significant clustering of the GRB sample at 1.6 < z < 2.1. Furthermore, this angular excess cannot be entirely attributed to known selection biases, making its existence due to chance unlikely. Conclusions. This huge structure lies ten times farther away than the Sloan Great Wall, at a distance of approximately ten billion light years. The size of the structure defined by these GRBs is about 2000-3000 Mpc, or more than six times the size of the largest known object in the Universe, the Sloan Great Wall. [ABSTRACT FROM AUTHOR]

With third-order statistics of gravitational shear it will be possible to extract valuable cosmological information from ongoing and future weak lensing surveys that is not contained in standard second-order statistics because of the non-Gaussianity of the shear field. Aperture mass statistics are an appropriate choice for third-order statistics because of their simple form and their ability to separate E- and B-modes of the shear. However, it has been demonstrated that second-order aperture mass statistics suffer from E-/B-mode mixing because it is impossible to reliably estimate the shapes of close pairs of galaxies. This finding has triggered developments of several new second-order statistical measures for cosmic shear. Whether the same developments are needed for third-order shear statistics is largely determined by how severe this E-/B-mixing is for third-order statistics. We tested third-order aperture mass statistics against E-/B-mode mixing and found that the level of contamination is well described by a function of θ / θmin, where θmin is the cutoff scale. At angular scales of θ > 10 θmin, the decrease in the E-mode signal due to E-/B-mode mixing is lower than 1 percent, and the leakage into B-modes is even less. For typical small-scale cutoffs this E-/B-mixing is negligible on scales larger than a few arcminutes. Therefore, third-order aperture mass statistics can safely be used to separate E- and B-modes and infer cosmological information, for ground-based surveys as well as forthcoming space-based surveys such as Euclid. [ABSTRACT FROM AUTHOR]

Context. Although there is currently a debate over the significance of the claimed large-scale anomalies in the cosmic microwave background (CMB), their existence is not totally dismissed. In parallel to the debate over their statistical significance, recent work has also focussed on masks and secondary anisotropies as potential sources of these anomalies. Aims. In this work we investigate simultaneously the impact of the method used to account for masked regions as well as the impact of the integrated Sachs-Wolfe (ISW) effect, which is the large-scale secondary anisotropy most likely to affect the CMB anomalies. In this sense, our work is an update of previous works. Our aim is to identify trends in CMB data from different years and with different mask treatments. Methods. We reconstruct the ISW signal due to 2 Micron All-Sky Survey (2MASS) and NRAO VLA Sky Survey (NVSS) galaxies, effectively reconstructing the low-redshift ISW signal out to z ~ 1.We account for regions of missing data using the sparse inpainting technique. We test sparse inpainting of the CMB, large scale structure and ISW and find that it constitutes a bias-free reconstruction method suitable to study large-scale statistical isotropy and the ISW effect. Results. We focus on three large-scale CMB anomalies: the low quadrupole, the quadrupole/octopole alignment, and the octopole planarity. After sparse inpainting, the low quadrupole becomes more anomalous, whilst the quadrupole/octopole alignment becomes less anomalous. The significance of the low quadrupole is unchanged after subtraction of the ISW effect, while the trend amongst the CMB maps is that both the low quadrupole and the quadrupole/octopole alignment have reduced significance, yet other hypotheses remain possible as well (e.g. exotic physics). Our results also suggest that both of these anomalies may be due to the quadrupole alone. While the octopole planarity significance is reduced after inpainting and after ISW subtraction, however, we do not find that it was very anomalous to start with. [ABSTRACT FROM AUTHOR]

Context. Whenever correlation functions are used for inference about cosmological parameters in the context of a Bayesian analysis, the likelihood function of correlation functions needs to be known. Usually, it is approximated as a multivariate Gaussian, though this is not necessarily a good approximation. Aims. We show how to calculate a better approximation for the probability distribution of correlation functions of one-dimensional random fields, which we call "quasi-Gaussian". Methods. Using the exact univariate probability distribution function (PDF) as well as constraints on correlation functions previously derived, we transform the correlation functions to an unconstrained variable for which the Gaussian approximation is well justified. From this Gaussian in the transformed space, we obtain the quasi-Gaussian PDF. The two approximations for the probability distributions are compared to the "true" distribution as obtained from simulations. Additionally, we test how the new approximation performs when used as likelihood in a toy-model Bayesian analysis. Results. The quasi-Gaussian PDF agrees very well with the PDF obtained from simulations; in particular, it provides a significantly better description than a straightforward copula approach. In a simple toy-model likelihood analysis, it yields noticeably different results than the Gaussian likelihood, indicating its possible impact on cosmological parameter estimation. [ABSTRACT FROM AUTHOR]

We statistically analyse a recent sample of data points measuring the fine-structure constant a (relative to the terrestrial value) in quasar absorption systems, where a spatial gradient in a was recently reported. We find agreement with previous authors that the dipole model is a robust, well-justified fit to the data. Using a simple analysis we find that the monopole term (the constant offset in Δα/α) may be caused by non-terrestrial magnesium isotope abundances in the absorbers. Finally we test the domain-wall model against the data. [ABSTRACT FROM AUTHOR]

Context. Baryon acoustic oscillations (BAO) are imprinted in the density field by acoustic waves travelling in the plasma of the early universe. Their fixed scale can be used as a standard ruler to study the geometry of the universe. Aims. The BAO have been previously detected using correlation functions and power spectra of the galaxy distribution. We present a new method to detect the real-space structures associated with BAO. These baryon acoustic structures are spherical shells of relatively small density contrast, surrounding high density central regions. Methods. We design a specific wavelet adapted to search for shells, and exploit the physics of the process by making use of two different mass tracers, introducing a specific statistic to detect the BAO features. We show the effect of the BAO signal in this new statistic when applied to the Λ - cold dark matter (ΛCDM) model, using an analytical approximation to the transfer function. We confirm the reliability and stability of our method by using cosmological N-body simulations from the MareNostrum Institut de Ciències de l'Espai (MICE). Results. We apply our method to the detection of BAO in a galaxy sample drawn from the Sloan Digital Sky Survey (SDSS). We use the "main" catalogue to trace the shells, and the luminous red galaxies (LRG) as tracers of the high density central regions. Using this new method, we detect, with a high significance, that the LRG in our sample are preferentially located close to the centres of shell-like structures in the density field, with characteristics similar to those expected from BAO. We show that stacking selected shells, we can find their characteristic density profile. Conclusions. We delineate a new feature of the cosmic web, the BAO shells. As these are real spatial structures, the BAO phenomenon can be studied in detail by examining those shells. [ABSTRACT FROM AUTHOR]

We report the detection, with a high level of confidence, of coherent outflows around voids found in the seventh data release of the Sloan Digital Sky Survey (SDSS DR7). In particular, we developed a robust ≺∣cos θ∣≻ statistical test to quantify the strength of redshiftspace distortions (RSD) associated with extended coherent velocity fields. We consistently find that the vector that joins void centers with galaxies that lie in shells around them is more likely to be perpendicular to the line-of-sight than parallel to it. This effect is clear evidence for the existence of outflows in the vicinity of voids. We show that the RSD exist for a wide range of void radius and shell thickness, but they are more evident in the largest voids in our sample. For instance, we find that the ≺∣cos θ∣≻ for galaxies located in shells within 2 h-1Mpc from the edge of voids larger than 15 h-1Mpc deviates 3.81σ from uniformity. The measurements presented in this work provide useful information to constrain cosmological parameters, in particular Ωm and σ8. [ABSTRACT FROM AUTHOR]

Context. Weak gravitational lensing is an ideal probe of the dark universe. In recent years, several linear methods have been developed to reconstruct the density distribution in the Universe in three dimensions, making use of photometric redshift information to determine the radial distribution of lensed sources. Aims. We aim to address three key problems seen in these methods; namely, the bias in the redshifts of detected objects, the line-ofsight smearing seen in reconstructions, and the damping of the amplitude of the reconstruction relative to the underlying density. We also aim to detect structures at higher redshifts than have previously been achieved, and to improve the line-of-sight resolution of our reconstructions. Methods. We considered the problem under the framework of compressed sensing (CS). Under the assumption that the data are sparse or compressible in an appropriate dictionary, we constructed a robust estimator and employ state-of-the-art convex optimisation methods to reconstruct the density contrast. For simplicity in implementation, and as a proof of concept of our method, we reduced the problem to one dimension, considering the reconstruction along each line of sight independently. We also assumed an idealised survey in which the redshifts of sources are known. Results. Despite the loss of information inherent in our one-dimensional implementation, we demonstrate that our method is able to accurately reproduce cluster haloes up to a redshift of zd = 1.0, deeper than state-of-the-art linear methods. We directly compare our method with these linear methods, and demonstrate minimal radial smearing and redshift bias in our reconstructions, as well as a reduced damping of the reconstruction amplitude as compared to the linear methods. In addition, the CS framework allows us to consider an underdetermined inverse problem, thereby allowing us to reconstruct the density contrast at finer resolution than the input data. Conclusions. The CS approach allows us to recover the density distribution more accurately than current state-of-the-art linear methods. Specifically, it addresses three key problem areas inherent in linear methods. Moreover, we are able to achieve superresolution and increased high-redshift sensitivity in our reconstructions. [ABSTRACT FROM AUTHOR]