Bisous Model Research Articles

Using photometric redshift data to improve the detection of galactic filaments with the Bisous model

Context. Filament finders are limited, among other things, by the abundance of spectroscopic redshift data. This limits the sky areas and depth where we can detect the filamentary network. Aims. As there are proportionally more photometric redshift data than spectroscopic, we aim to use data with photometric redshifts to improve and expand the areas where we can detect the large-scale structure of the Universe. The Bisous model is a filament finder that uses only the galaxy positions. We present a proof of concept, showing that the Bisous filament finder can improve the detected filamentary network with photometric redshift data. Methods. We created mock data from the MULTIDARK-GALAXIES catalogue. Galaxies with spectroscopic redshifts were given exact positions from the simulation. Galaxies with photometric redshifts were given uncertainties along one coordinate. The errors were generated with different Gaussian distributions for different samples. We sample the photometric galaxy positions for each Bisous run based on the uncertainty distribution. In some runs, the sampled positions are closer to the true positions and produce persistent filaments; other runs produce noise, which is suppressed in the post-processing. Results. There are three different types of samples: spectroscopic only, photometric only, and mixed samples of galaxies with photometric and spectroscopic redshifts. In photometric-only samples, the larger the uncertainty for photometric redshifts, the fewer filaments are detected, and the filaments strongly align along the line of sight. Using mixed samples improves the number of filaments detected and decreases the alignment bias of those filaments. The results are compared against the full spectroscopic sample. The recall for photometric-only samples depends heavily on the size of uncertainty and dropped close to 20%; for mixed samples, the recall stayed between 40% and 80%. The false discovery rate stayed below 5% in every sample tested in this work. Mixed samples showed better results than corresponding photometric-only or spectroscopic-only samples for every uncertainty size and number of spectroscopic galaxies in mixed samples. Conclusions. Mixed samples of galaxies with photometric and spectroscopic redshifts help us to improve and extend the large-scale structure further than possible with only spectroscopic samples. Although the uncertainty sizes tested in this work are smaller than those for the available photometric data, upcoming surveys, such as J-PAS, will achieve sufficiently small uncertainties to be useful for large-scale structure detection.

Assessing the reliability of the Bisous filament finder

Context. Recent years have given rise to numerous methods of detecting the cosmic web elements in the large-scale structure of the Universe. All of these methods describe more or less the same features, but each with its nuance. The Bisous filament finder is a stochastic tool for identifying the spines of filaments using galaxy positions. Aims. This work provides an analysis of how the galaxy number density of the input data affects the filaments detected with the Bisous model and gives estimates of the reliability of the method itself to assess the robustness of the results. Methods. We applied the Bisous filament finder to MultiDark-Galaxies data, using various magnitude cuts from the catalogue to study the effects of different galaxy number densities on the results and different parameters of the model. We compared the structures by the fraction of galaxies in filaments and the volume filled by filaments, and we analysed the similarities between the results from different cuts based on the overlap between detected filamentary structures. The filament finder was also applied to the exact same data 200 times with the same parameters to study the stochasticity of the results and the correlation between different runs was calculated. Results. Multiple samples show that galaxies in filaments have preferentially higher luminosity. We found that when a galaxy is in a filament there is a 97% chance that the same galaxy would be in a filament with even more complete input data and about 85% of filaments are persistent when detecting the filamentary network with higher-density input data. Lower galaxy number density inputs mean the Bisous model finds fewer filaments, but the filaments found are persistent even if we use more complete input data for the detection. We calculated the correlation coefficient between 200 Bisous runs on the exact same input, which is 0.98. Conclusions. This study confirms that increased number density of galaxies is important to obtain a more complete picture of the cosmic web. To overcome the limitation of the spectroscopic surveys, we will develop the Bisous model further to apply this tool to combined spectroscopic and narrow-band photometric redshift surveys, such as the J-PAS.

Detecting cosmic filamentary network with stochastic Bisous model

AbstractThe Bisous model is a tool that uses stochastic methods to detect the network of galactic filaments. This model is explicitly developed to detect the structure from observational data, using only galaxy positions as input. This paper shows that the Bisous model gives reliable results and including photometric data improves the resulting filamentary network. We used MultiDark-Galaxies catalogue to create a mock with photometric redshifts and samples with different galaxy number densities. We found that the filaments detected with the Bisous model are reliable; 85% of the detected filaments are unchanged compared to results with more complete input data. Adding photometric data improves the fraction of galaxies in filaments. Using the confusion matrix technique, we found the false discovery rate to always be below 5% when using photometric data.

From voids to filaments: environmental transformations of galaxies in the SDSS

We investigate the impact of filament and void environments on galaxies, looking for residual effects beyond the known relations with environment density. We quantified the host environment of galaxies as the distance to the spine of the nearest filament, and compared various galaxy properties within 12 bins of this distance. We considered galaxies up to 10 $h^{-1}$Mpc from filaments, i.e. deep inside voids. The filaments were defined by a point process (the Bisous model) from the Sloan Digital Sky Survey data release 10. In order to remove the dependence of galaxy properties on the environment density and redshift, we applied weighting to normalise the corresponding distributions of galaxy populations in each bin. After the normalisation with respect to environment density and redshift, several residual dependencies of galaxy properties still remain. Most notable is the trend of morphology transformations, resulting in a higher elliptical-to-spiral ratio while moving from voids towards filament spines, bringing along a corresponding increase in the $g-i$ colour index and a decrease in star formation rate. After separating elliptical and spiral subsamples, some of the colour index and star formation rate evolution still remains. The mentioned trends are characteristic only for galaxies brighter than about $M_{r} = -20$ mag. Unlike some other recent studies, we do not witness an increase in the galaxy stellar mass while approaching filaments. The detected transformations can be explained by an increase in the galaxy-galaxy merger rate and/or the cut-off of extragalactic gas supplies (starvation) near and inside filaments. Unlike voids, large-scale galaxy filaments are not a mere density enhancement, but have their own specific impact on the constituent galaxies, reducing the star formation rate and raising the chances of elliptical morphology also at a fixed environment density level.

The effect of cosmic web filaments on the properties of groups and their central galaxies

The nature versus nurture scenario in galaxy and group evolution is a long-standing problem not yet fully understood on cosmological scales. We study the properties of groups and their central galaxies in different large-scale environments defined by the luminosity density field and the cosmic web filaments. We use the luminosity density field constructed using 8 Mpc/h smoothing to characterize the large-scale environments and the Bisous model to extract the filamentary structures in different large-scale environments. We find differences in the properties of central galaxies and their groups in and outside of filaments at fixed halo and large-scale environments. In high-density environments, the group mass function has higher number densities in filaments compared to that outside of filaments towards the massive end. The relation is opposite in low-density environments. At fixed group mass and large-scale luminosity density, groups in filaments are slightly more luminous and their central galaxies have redder colors, higher stellar masses, and lower specific star formation rates than those outside of filaments. However, the differences in central galaxy and group properties in and outside of filaments are not clear in some group mass bins. We show that the differences in central galaxy properties are due to the higher abundances of elliptical galaxies in filaments. Filamentary structures in the cosmic web are not simply visual associations of galaxies, but rather play an important role in shaping the properties of groups and their central galaxies. The differences in central galaxy and group properties in and outside of cosmic web filaments are not simple effects related to large-scale environmental density. The results point towards an efficient mechanism in cosmic web filaments which quench star formation and transform central galaxy morphology from late to early types.

Bisous model—Detecting filamentary patterns in point processes

The cosmic web is a highly complex geometrical pattern, with galaxy clusters at the intersection of filaments and filaments at the intersection of walls. Identifying and describing the filamentary network is not a trivial task due to the overwhelming complexity of the structure, its connectivity and the intrinsic hierarchical nature. To detect and quantify galactic filaments we use the Bisous model, which is a marked point process built to model multi-dimensional patterns. The Bisous filament finder works directly with the galaxy distribution data and the model intrinsically takes into account the connectivity of the filamentary network. The Bisous model generates the visit map (the probability to find a filament at a given point) together with the filament orientation field. Using these two fields, we can extract filament spines from the data. Together with this paper we publish the computer code for the Bisous model that is made available in GitHub. The Bisous filament finder has been successfully used in several cosmological applications and further development of the model will allow to detect the filamentary network also in photometric redshift surveys, using the full redshift posterior. We also want to encourage the astro-statistical community to use the model and to connect it with all other existing methods for filamentary pattern detection and characterisation.

Filaments from the galaxy distribution and from the velocity field in the local universe

Abstract The cosmic web that characterizes the large-scale structure of the Universe can be quantified by a variety of methods. For example, large redshift surveys can be used in combination with point process algorithms to extract long curvilinear filaments in the galaxy distribution. Alternatively, given a full 3D reconstruction of the velocity field, kinematic techniques can be used to decompose the web into voids, sheets, filaments and knots. In this Letter, we look at how two such algorithms – the Bisous model and the velocity shear web – compare with each other in the local Universe (within 100 Mpc), finding good agreement. This is both remarkable and comforting, given that the two methods are radically different in ideology and applied to completely independent and different data sets. Unsurprisingly, the methods are in better agreement when applied to unbiased and complete data sets, like cosmological simulations, than when applied to observational samples. We conclude that more observational data is needed to improve on these methods, but that both methods are most likely properly tracing the underlying distribution of matter in the Universe.

Galaxy pairs align with Galactic filaments

Context. Gravitational collapse theory and numerical simulations suggest that the velocity field within large-scale galaxy filaments is dominated by motions along the filaments. Aims. Our aim is to check whether observational data reveal any preferred orientation of galaxy pairs with respect to the underlying filaments as a result of the expectedly anisotropic velocity field. Methods. We use galaxy pairs and galaxy filaments identified from the Sloan Digital Sky Survey data. For filament extraction, we use the Bisous model that is based the marked point process technique. During the filament detection, we use the centre point of each pair instead of the positions of galaxies to avoid a built-in influence of pair orientation on the filament construction. For pairs lying within filaments (3012 cases), we calculate the angle between the line connecting galaxies of each pair and their host filament. To avoid redshift-space distortions, the angle is measured in the plain of the sky. Results. The alignment analysis shows that the orientation of galaxy pairs correlates strongly with their host filaments. The alignment signal is stronger for loose pairs, with at least 25% excess of aligned pairs compared to a random distribution. The alignment of galaxy pairs and filaments measured from the observational data is in good concordance with the alignment in the Millennium simulation and thus provides support to the {\Lambda}CDM formalism.

Galaxy filaments as pearl necklaces

Context. Galaxies in the Universe form chains (filaments) that connect groups and clusters of galaxies. The filamentary network includes nearly half of the galaxies and is visually the most striking feature in cosmological maps. Aims. We study the distribution of galaxies along the filamentary network, trying to find specific patterns and regularities. Methods. Galaxy filaments are defined by the Bisous model, a marked point process with interactions. We use the two-point correlation function and the Rayleigh Z-squared statistic to study how galaxies and galaxy groups are distributed along the filaments. Results. We show that galaxies and groups are not uniformly distributed along filaments, but tend to form a regular pattern. The characteristic length of the pattern is around 7 Mpc/h. A slightly smaller characteristic length 4 Mpc/h can also be found, using the Z-squared statistic. Conclusions. We find that galaxy filaments in the Universe are like pearl necklaces, where the pearls are galaxy groups distributed more or less regularly along the filaments. We propose that this well defined characteristic scale could be used to test various cosmological models and to probe environmental effects on the formation and evolution of galaxies.

Detecting multi-scale filaments in galaxy distribution

AbstractThe main feature of the spatial large-scale galaxy distribution is its intricate network of galaxy filaments. This network is spanned by the galaxy locations that can be interpreted as a three-dimensional point distribution. The global properties of the point process can be measured by different statistical methods, which, however, do not describe directly the structure elements. The morphology of the large-scale structure, on the other hand, is an important property of the galaxy distribution. Here, we apply an object point process with interactions (the Bisous model) to trace and extract the filamentary network in the presently largest galaxy redshift survey, the Sloan Digital Sky Survey (SDSS data release 10). We search for multi-scale filaments in the galaxy distribution that have a radius of about 0.5, 1.0, 2.0, and 4.0h−1Mpc. We extract the spines of the filamentary network and divide the detected network into single filaments.

Detecting filamentary pattern in the cosmic web: a catalogue of filaments for the SDSS

The main feature of the spatial large-scale galaxy distribution is its intricate network of galaxy filaments. This network is spanned by the galaxy locations that can be interpreted as a three-dimensional point distribution. The global properties of the point process can be measured by different statistical methods, which, however, do not describe directly the structure elements. The morphology of the large scale structure, on the other hand, is an important property of the galaxy distribution. Here we apply an object point process with interactions (the Bisous model) to trace and extract the filamentary network in the presently largest galaxy redshift survey, the Sloan Digital Sky Survey (SDSS). We search for filaments in the galaxy distribution that have a radius of about 0.5 Mpc/h. We divide the detected network into single filaments and present a public catalogue of filaments. We study the filament length distribution and show that the longest filaments reach the length of 60 Mpc/h. The filaments contain 35-40% of the total galaxy luminosity and they cover roughly 5-8% of the total volume, in good agreement with N-body simulations and previous observational results.

Orientation of cosmic web filaments with respect to the underlying velocity field

Abstract The large-scale structure of the Universe is characterized by a web-like structure made of voids, sheets, filaments and knots. The structure of this so-called cosmic web is dictated by the local velocity shear tensor. In particular, the local direction of a filament should be strongly aligned with $\hat{e}_3$, the eigenvector associated with the smallest eigenvalue of the tensor. That conjecture is tested here on the basis of a cosmological simulation. The cosmic web delineated by the halo distribution is probed by a marked point process with interactions (the Bisous model), detecting filaments directly from the halo distribution (P-web). The detected P-web filaments are found to be strongly aligned with the local $\hat{e}_3$: the alignment is within 30° for ∼80 per cent of the elements. This indicates that large-scale filaments defined purely from the distribution of haloes carry more than just morphological information, although the Bisous model does not make any prior assumption on the underlying shear tensor. The P-web filaments are also compared to the structure revealed from the velocity shear tensor itself (V-web). In the densest regions, the P- and V-web filaments overlap well (90 per cent), whereas in lower density regions, the P-web filaments preferentially mark sheets in the V-web.

GALAXY SPIN ALIGNMENT IN FILAMENTS AND SHEETS: OBSERVATIONAL EVIDENCE

Galaxies properties are known to be affected by their environment. One important question is how their angular momentum reflects the surrounding cosmic web. We use the SDSS to investigate the spin axes of spiral and elliptical galaxies relative to their surrounding filament/sheet orientations. To detect filaments a marked point process with interactions (the "Bisous model") is used. Sheets are found by detecting "flattened" filaments. The minor axes of ellipticals are found to be preferentially perpendicular to hosting filaments. A weak correlation is found with sheets. These findings are consistent with the notion that elliptical galaxies formed via mergers which predominantly occurred along the filaments. The spin axis of spiral galaxies is found to align with the host filament, with no correlation between spiral spin and sheet normal. When examined as a function of distance from the filament axis, a much stronger correlation is found in outer parts, suggesting that the alignment is driven by the laminar infall of gas from sheets to filaments. When compared with numerical simulations our results suggest that the connection between DM halo and galaxy spin is not straightforward. Our results provide an important input to the understanding of how galaxies acquire their angular momentum.

Simulated annealing and object point processes: Tools for analysis of spatial patterns

This paper introduces a three-dimensional object point process—the Bisous model—that can be used as a prior for three-dimensional spatial pattern analysis. Maximization of likelihood or penalized-likelihood functions based on this model requires global optimization techniques, such as the simulated annealing algorithm. Theoretical properties of the model are discussed and the convergence of the proposed optimization method is proved. Finally, a simulation study is presented.