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The Discrete Source Classifier (DSC) provides probabilistic classification of sources in Gaia Data Release 3 (GDR3) using a Bayesian framework and a global prior. The DSC Combmod classifier in GDR3 achieved for the extragalactic classes (quasars and galaxies) a high completeness of 92%, but a low purity of 22% (all sky, all magnitudes) due to contamination from the far larger star class. However, these single metrics mask significant variation in performance with magnitude and sky position. Furthermore, a better combination of the individual classifiers that comprise Combmod is possible. Here we compute two-dimensional (2D) representations of the completeness and the purity as a function of Galactic latitude and source brightness, and also exclude the Magellanic Clouds where stellar contamination significantly reduces the purity. Reevaluated on a cleaner validation set and without introducing changes to the published GDR3 DSC probabilities themselves, we here achieve for Combmod average 2D completenesses of 92% and 95% and average 2D purities of 55% and 89% for the quasar and galaxy classes, respectively. Since the relative proportions of extragalactic objects to stars in Gaia is expected to vary significantly with brightness and latitude, we then introduce a new prior that is a continuous function of brightness and latitude, and compute new class probabilities from the GDR3 DSC component classifiers, Specmod and Allosmod. Contrary to expectations, this variable prior only improves the performance by a few percentage points, mostly at the faint end. Significant improvement, however, is obtained by a new additive combination of Specmod and Allosmod. This classifier, Combmod-α, achieves average 2D completenesses of 82% and 93% and average 2D purities of 79% and 93% for the quasar and galaxy classes, respectively, when using the global prior. Thus, we achieve a significant improvement in purity for a small loss of completeness. The improvement is most significant for faint quasars (G≥20) where the purity rises from 20% to 62%. [ABSTRACT FROM AUTHOR]

Context. Galaxy clusters are an essential tool to understand and constrain the cosmological parameters of our universe. Thanks to its multi-band design, J-PAS offers a unique group and cluster detection window using precise photometric redshifts and sufficient depths. Aims. We produced galaxy cluster catalogues from miniJPAS, which is a pathfinder survey for the wider J-PAS survey, using the PZWav algorithm. Methods. Relying only on photometric information, we provide optical mass tracers for the identified clusters, including richness, optical luminosity, and stellar mass. By reanalysing the Chandra mosaic of the AEGIS field, alongside the overlapping XMM-Newton observations, we produced an X-ray catalogue. Results. The analysis revealed the possible presence of structures with masses of 4 × 1013 M⊙ at redshift 0.75, highlighting the depth of the survey. Comparing results with those from two other cluster catalogues provided by AMICO and VT, we found 43 common clusters with cluster centre offsets of 100 ± 60 kpc and redshift differences below 0.001. We provide a comparison of the cluster catalogues with a catalogue of massive galaxies and report on the significance of cluster selection. In general, we were able to recover approximately 75% of the galaxies with M⋆ > 2 × 1011 M⊙. Conclusions. This study emphasises the potential of the J-PAS survey and the employed techniques, including down to group scales. [ABSTRACT FROM AUTHOR]

Understanding the evolution of galaxies provides crucial insights into a broad range of aspects in astrophysics, including structure formation and growth, the nature of dark energy and dark matter, baryonic physics, and more. It is, however, infeasible to track the evolutionary processes of individual galaxies in real time given their long timescales. As a result, galaxy evolution analyses have been mostly based on ensembles of galaxies that are supposed to be from the same population according to usually basic and crude observational criteria. We propose a new strategy of evaluating the evolution of an individual galaxy by identifying its descendant galaxies as guided by cosmological simulations. As a proof of concept, we examined the evolution of the total mass distribution of a target strong lensing galaxy at z = 0.884 using the proposed strategy. We selected 158 galaxies from the TNG300 simulation that we identified as analogs of the target galaxy. We followed their descendants and found 11 observed strong lensing galaxies that match in stellar mass and size with the descendants at their redshifts. The observed and simulated results are discussed, although no conclusive assessment is made given the low statistical significance due to the small sample size. Nevertheless, the test confirms that our proposed strategy is already feasible with existing data and simulations. We expect it to play an even more important role in studying galaxy evolution as more strong lens systems and larger simulations become available with the advent of next-generation survey programs and cosmological simulations. [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. The morphological classification of galaxies is considered a relevant issue and can be approached from different points of view. The increasing growth in the size and accuracy of astronomical data sets brings with it the need for the use of automatic methods to perform these classifications. Aims. The aim of this work is to propose and evaluate a method for the automatic unsupervised classification of kinematic morphologies of galaxies that yields a meaningful clustering and captures the variations of the fundamental properties of galaxies. Methods.We obtained kinematic maps for a sample of 2064 galaxies from the largest simulation of the EAGLE project that mimics integral field spectroscopy images. These maps are the input of a dimensionality reduction algorithm followed by a clustering algorithm. We analysed the variation of physical and observational parameters among the clusters obtained from the application of this procedure to different inputs. The inputs studied in this paper are (a) line-of-sight velocity maps for the whole sample of galaxies observed at fixed inclinations; (b) line-of-sight velocity, dispersion, and flux maps together for the whole sample of galaxies observed at fixed inclinations; (c) line-of-sight velocity, dispersion, and flux maps together for two separate subsamples of edge-on galaxies with similar amount of rotation; and (d) line-of-sight velocity, dispersion, and flux maps together for galaxies from different observation angles mixed. Results. The application of the method to solely line-of-sight velocity maps achieves a clear division between slow rotators (SRs) and fast rotators (FRs) and can differentiate rotation orientation. By adding the dispersion and flux information at the input, low-rotation edge-on galaxies are separated according to their shapes and, at lower inclinations, the clustering using the three types of maps maintains the overall information obtained using only the line-of-sight velocity maps. This method still produces meaningful groups when applied to SRs and FRs separately, but in the first case the division into clusters is less clear than when the input includes a variety of morphologies. When applying the method to a mixture of galaxies observed from different inclinations, we obtain results that are similar to those in our previous experiments with the advantage that in this case the input is more realistic. In addition, our method has proven to be robust: it consistently classifies the same galaxies viewed from different inclinations. [ABSTRACT FROM AUTHOR]

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across ~15 000deg2 of the sky. Euclid is expected to detect ~12 billion astronomical sources, facilitating new insights into cosmology, galaxy evolution, and various other topics. In order to optimally exploit the expected very large dataset, appropriate methods and software tools need to be developed. Here we present a novel machine-learning-based methodology for the selection of quiescent galaxies using broadband Euclid IE, YE, JE, and HE photometry, in combination with multi-wavelength photometry from other large surveys (e.g. the Rubin LSST). The ARIADNE pipeline uses meta-learning to fuse decision-tree ensembles, nearest-neighbours, and deep-learning methods into a single classifier that yields significantly higher accuracy than any of the individual learning methods separately. The pipeline has been designed to have 'sparsity awareness', such that missing photometry values are informative for the classification. In addition, our pipeline is able to derive photometric redshifts for galaxies selected as quiescent, aided by the 'pseudo-labelling' semi-supervised method, and using an outlier detection algorithm to identify and reject likely catastrophic outliers. After the application of the outlier filter, our pipeline achieves a normalised mean absolute deviation of ≲0.03 and a fraction of catastrophic outliers of ≲0.02 when measured against the COSMOS2015 photometric redshifts. We apply our classification pipeline to mock galaxy photometry catalogues corresponding to three main scenarios: (i) Euclid Deep Survey photometry with ancillary ugriz, WISE, and radio data; (ii) Euclid Wide Survey photometry with ancillary ugriz, WISE, and radio data; and (iii) Euclid Wide Survey photometry only, with no foreknowledge of galaxy redshifts. In a like-for-like comparison, our classification pipeline outperforms UVJ selection, in addition to the Euclid IE – YE, JE – HE and u – IE, IE – JE colour-colour methods, with improvements in completeness and the F1-score (the harmonic mean of precision and recall) of up to a factor of 2. [ABSTRACT FROM AUTHOR]

We tested whether refracted gravity, a theory of modified gravity that describes the dynamics of galaxies without the aid of dark matter, can model the dynamics of the three massive elliptical galaxies, NGC 1407, NGC 4486, and NGC 5846, out to ∼10Re, where the baryonic mass component fades out and dark matter is required in Newtonian gravity. We probed these outer regions with the kinematics of the globular clusters provided by the SLUGGS survey. Refracted gravity mimics dark matter with the gravitational permittivity, a monotonic function of the local mass density depending on three parameters, ϵ0, ρc, and Q, which are expected to be universal. Refracted gravity satisfactorily reproduces the velocity dispersion profiles of the stars and red and blue globular clusters, with stellar mass-to-light ratios in agreement with stellar population synthesis models, and orbital anisotropy parameters consistent with previous results obtained in Newtonian gravity with dark matter. The sets of the three parameters of the gravitational permittivity found for each galaxy are consistent with each other within ∼2σ. We compare the mean {ϵ0,Q,log10(ρc[g cm−3])} = {0.089−0.035+0.038, 0.47−0.21+0.29, −24.25−0.20+0.28} { ϵ 0 , Q , log 10 ρ c g cm − 3 } = { 0. 089 − 0.035 + 0.038 , 0. 47 − 0.21 + 0.29 , − 24. 25 − 0.20 + 0.28 } $ \{\epsilon_0,Q,\log_{10}\left(\rho_{\mathrm{c}}\left[\mathrm{g}\,\mathrm{cm}^{-3}\right]\right)\} = \{0.089^{+0.038}_{-0.035}, 0.47^{+0.29}_{-0.21}, -24.25^{+0.28}_{-0.20}\} $ found here with the means of the parameters required to model the rotation curves and vertical velocity dispersion profiles of 30 disk galaxies from the DiskMass Survey (DMS): ρc and Q agree within 1σ with the DMS values, whereas ϵ0 agrees within 3σ. This agreement suggests that ellipticals and disk galaxies allow for common values of the parameters of the permittivity and supports the universality of the permittivity function. [ABSTRACT FROM AUTHOR]

Context. Computational techniques are essential for mining large databases produced in modern surveys with value-added products. Aims. This paper presents a machine learning procedure to carry out a galaxy morphological classification and photometric redshift estimates simultaneously. Currently, only a spectral energy distribution (SED) fitting has been used to obtain these results all at once. Methods. We used the ancillary data gathered in the OTELO catalog and designed a nonsequential neural network that accepts optical and near-infrared photometry as input. The network transfers the results of the morphological classification task to the redshift fitting process to ensure consistency between both procedures. Results. The results successfully recover the morphological classification and the redshifts of the test sample, reducing catastrophic redshift outliers produced by an SED fitting and avoiding possible discrepancies between independent classification and redshift estimates. Our technique may be adapted to include galaxy images to improve the classification. [ABSTRACT FROM AUTHOR]

We performed an internal-consistency test of the KiDS+VIKING-450 (KV450) cosmic shear analysis with a colour-based split of source galaxies. Utilising the same measurements and calibrations for both sub-samples, we inspected the characteristics of the shear measurements and the performance of the calibration pipelines. On the modelling side, we examined the observational nuisance parameters, specifically those for the redshift calibration and intrinsic alignments, using a Bayesian analysis with dedicated test parameters. We verified that the current nuisance parameters are sufficient for the KV450 data to capture residual systematics, with slight deviations seen in the second and the third redshift tomographic bins. Our test also showcases the degeneracy between the inferred amplitude of intrinsic alignments and the redshift uncertainties in low redshift tomographic bins. The test is rather insensitive to the background cosmology and, therefore, can be implemented before any cosmological inference is made. [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]

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]

We provide predictions of the yield of 7 <  z <  9 quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisions to the Euclid near-infrared filter wavelengths; we adopt steeper rates of decline of the quasar luminosity function (QLF; Φ) with redshift, Φ ∝ 10k(z − 6), k = −0.72, and a further steeper rate of decline, k = −0.92; we use better models of the contaminating populations (MLT dwarfs and compact early-type galaxies); and we make use of an improved Bayesian selection method, compared to the colour cuts used for the Red Book calculation, allowing the identification of fainter quasars, down to JAB ∼ 23. Quasars at z >  8 may be selected from EuclidOYJH photometry alone, but selection over the redshift interval 7 <  z <  8 is greatly improved by the addition of z-band data from, e.g., Pan-STARRS and LSST. We calculate predicted quasar yields for the assumed values of the rate of decline of the QLF beyond z = 6. If the decline of the QLF accelerates beyond z = 6, with k = −0.92, Euclid should nevertheless find over 100 quasars with 7.0 <  z <  7.5, and ∼25 quasars beyond the current record of z = 7.5, including ∼8 beyond z = 8.0. The first Euclid quasars at z >  7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 <  z <  8, M1450 <  −25, using 8 m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at JAB ∼ 23. The precision with which k can be determined over 7 <  z <  8 depends on the value of k, but assuming k = −0.72 it can be measured to a 1σ uncertainty of 0.07. [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]

Using the same lens galaxies, the ratios of tangential shears for different source galaxy redshifts is equal to the ratios of their corresponding angular-diameter distances. This is the so-called shear-ratio test (SRT) and it is valid when effects induced by the intervening large-scale structure (LSS) can be neglected. The dominant LSS effect is magnification bias which, on the one hand, induces an additional shear, and on the other hand, causes a magnification of the lens population. Our objective is to quantify the magnification bias for the SRT and show an easy-to-apply mitigation strategy that does not rely on additional observations. We use ray-tracing data through the Millennium simulation to measure the influence of magnification on the SRT and test our mitigation strategy. Using the SRT as a null-test we find deviations from zero up to 10% for a flux-limited sample of lens galaxies, which is a strong function of lens redshift and the lens-source line-of-sight separation. Using our mitigation strategy we can improve the null-test by a factor of ∼100. [ABSTRACT FROM AUTHOR]

Context. Large spectroscopic surveys open the way to explore our Galaxy. In order to use the data from these surveys to understand the Galactic stellar population, we need to be sure that stars contained in a survey are a representative sub-set of the underlying population. Without the selection function taken into account, the results might reflect the properties of the selection function rather than those of the underlying stellar population. Aims. In this work, we introduce a method to estimate the selection function for a given spectroscopic survey. We aim to apply this method to a large sample of public spectroscopic surveys. Methods. We have applied a median division binning algorithm to bin observed stars in the colour–magnitude space. This approach produces lower uncertainties and lower biases of the selection function estimate as compared to traditionally used 2D-histograms. We ran a set of simulations to verify the method and calibrate the one free parameter it contains. These simulations allow us to test the precision and accuracy of the method. Results. We produce and publish estimated values and uncertainties of selection functions for a large sample of public spectroscopic surveys. We publicly release the code used to produce the selection function estimates. Conclusions. The effect of the selection function on distance modulus and metallicity distributions of stars in surveys is important for surveys with small and largely inhomogeneous spatial coverage. For surveys with contiguous spatial coverage the effect of the selection function is almost negligible. [ABSTRACT FROM AUTHOR]

Star-forming regions on different scales, such as giant molecular clouds in our Galaxy and star-forming galaxies, emit GeV gamma-rays. These are thought to originate from hadronic interactions of cosmic-ray (CR) nuclei with the interstellar medium. It has recently been shown that the gamma-ray luminosity (Lγ) of star-forming galaxies is well correlated with their star formation rates (SFR). We investigated Fermi data of eight Galactic molecular clouds in the Gould belt and found that molecular clouds do not follow the Lγ −SFR correlation of star-forming galaxies. We also compared the scaling relations of gamma-ray luminosity, SFR, and the gas mass for molecular clouds and star-forming galaxies. Using a multiple-variable regression analysis, we found different dependences of gamma-ray emission on SFR or mass for molecular clouds and star-forming galaxies. This suggests that different mechanisms may govern the production of gamma-rays in these two types of sources. Specifically, the strong dependence on mass supports that gamma-ray emission of molecular clouds primarily comes from passive interaction by diffuse Galactic CRs, whereas the strong dependence on SFR supports that gamma-ray emission of star-forming galaxies originates from CRs that are accelerated by local active sources. [ABSTRACT FROM AUTHOR]

We present a new method to estimate shear measurement bias in image simulations that significantly improves the precision with respect to current techniques. Our method is based on measuring the shear response for individual images. We generated sheared versions of the same image to measure how the galaxy shape changes with the small applied shear. This shear response is the multiplicative shear bias for each image. In addition, we also measured the individual additive bias. Using the same noise realizations for each sheared version allows us to compute the shear response at very high precision. The estimated shear bias of a sample of galaxies is then the average of the individual measurements. The precision of this method leads to an improvement with respect to previous methods concerned with the precision of estimates of multiplicative bias since our method is not affected by noise from shape measurements, which until now has been the dominant uncertainty. As a consequence, the method does not require shape-noise suppression for a precise estimation of shear multiplicative bias. Our method can be readily used for numerous applications such as shear measurement validation and calibration, reducing the number of necessary simulated images by a few orders of magnitude to achieve the same precision. [ABSTRACT FROM AUTHOR]

We present an analysis of the deepest Herschel images in four major extragalactic fields GOODS-North, GOODS-South, UDS, and COSMOS obtained within the GOODS-Herschel and CANDELS-Herschel key programs. The star formation picture provided by a total of 10 497 individual far-infrared detections is supplemented by the stacking analysis of a mass complete sample of 62 361 star-forming galaxies from the Hubble Space Telescope (HST) H band-selected catalogs of the CANDELS survey and from two deep ground-based Ks band-selected catalogs in the GOODS-North and the COSMOS-wide field to obtain one of the most accurate and unbiased understanding to date of the stellar mass growth over the cosmic history. We show, for the first time, that stacking also provides a powerful tool to determine the dispersion of a physical correlation and describe our method called "scatter stacking", which may be easily generalized to other experiments. The combination of direct UV and far-infrared UV-reprocessed light provides a complete census on the star formation rates (SFRs), allowing us to demonstrate that galaxies at z = 4 to 0 of all stellar masses (M∗) follow a universal scaling law, the so-called main sequence of star-forming galaxies. We find a universal close-to-linear slope of the log?10(SFR)-log?10(M∗) relation, with evidence for a flattening of the main sequence at high masses (log?10(M∗/M⊙) > 10.5) that becomesless prominent with increasing redshift and almost vanishes by z ≃ 2. This flattening may be due to the parallel stellar growth of quiescent bulges in star-forming galaxies, which mostly happens over the same redshift range. Within the main sequence, we measure a nonvarying SFR dispersion of 0.3 dex: at a fixed redshift and stellar mass, about 68% of star-forming galaxies form stars at a universal rate within a factor 2. The specific SFR (sSFR = SFR/M∗) of star-forming galaxies is found to continuously increase from z = 0 to 4. Finally we discuss the implications of our findings on the cosmic SFR history and on the origin of present-day stars: more than two-thirds of present-day stars must have formed in a regime dominated by the "main sequence" mode. As a consequence we conclude that, although omnipresent in the distant Universe, galaxy mergers had little impact in shaping the global star formation history over the last 12.5 billion years. [ABSTRACT FROM AUTHOR]

We present a new hybrid photometry and extraction routine called Hyper. It is designed to do compact source photometry, allowing for varying spatial resolution and sensitivity in multi-wavelength surveys. Hyper combines multi-Gaussian fitting with aperture photometry to provide reliable photometry in regions with variable backgrounds and in crowded fields. The background is evaluated and removed locally for each source using polynomial fits of various orders. Source deblending is done through simultaneous multi-Gaussian fitting of the main source and its companion(s), followed by the subtraction of the companion(s). Hyper also allows simultaneous multi-wavelength photometry by setting a fixed aperture size independent of the map resolution and by evaluating the source flux within the same region of the sky at multiple wavelengths at the same time. This new code has been initially designed for precise aperture photometry in complex fields such as the Galactic plane observed in the far infrared (FIR) by the Herschel infrared survey of the Galactic plane (Hi-GAL). Hyper has been tested on both simulated and real Herschel fields to quantify the quality of the source identification and photometry. The code is highly modular and fully parameterisable, therefore it can be easily adapted to different experiments. Comparison of the Hyper photometry with the catalogued sources in the Bolocam Galactic Plane Survey (BGPS), the 1.1 mm survey of the Galactic plane carried out with the Caltech Submillimeter Observatory, demonstrates the versatility of Hyper on different datasets. It is fast and light in its memory, and it is freely available to the scientific community. [ABSTRACT FROM AUTHOR]

We study the relationship between the K-band and the sub-millimetre (submm) emissions of nearby galaxies by computing the bivariate K-band-submm luminosity function (BLF) of the Herschel Reference Survey (HRS), a volume-limited sample observed in submm with Herschel/SPIRE. We derive the BLF from the K-band and submm cumulative distributions using a copula method. Using the BLF allows us to derive the relationship between the luminosities on more solid statistical ground. The analysis shows that over the whole HRS sample, no statistically meaningful conclusion can be derived for any relationship between the K-band and the submm luminosity. However, a very tight relationship between these luminosities is highlighted, by restricting our analysis to late-type galaxies. The luminosity function of late-type galaxies computed in the K-band and in the submm are dependent and the dependence is caused by the link, between the stellar mass and the cold dust mass, which has been already observed. [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]

Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky surveys and to apply the techniques to the VIMOS Public Extragalactic Redshift Survey (VIPERS). Using the optical (u", g', r', i') and near-infrared (NIR) data (z', Ks), we develop a classifier, based on broad-band photometry, for identifying stars, active galactic nuclei (AGNs), and galaxies, thereby improving the purity of the VIPERS sample. Methods. Support vector machine (SVM) supervised learning algorithms allow the automatic classification of objects into two or more classes based on a multidimensional parameter space. In this work, we tailored the SVM to classifying stars, AGNs, and galaxies and applied this classification to the VIPERS data. We trained the SVM using spectroscopically confirmed sources from the VIPERS and VVDS surveys. Results. We tested two SVM classifiers and concluded that including NIR data can significantly improve the efficiency of the classifier. The self-check of the best optical + NIR classifier has shown 97% accuracy in the classification of galaxies, 97% for stars, and 95% for AGNs in the 5-dimensional colour space. In the test of VIPERS sources with 99% redshift confidence, the classifier gives an accuracy equal to 94% for galaxies, 93% for stars, and 82% for AGNs. The method was applied to sources with low-quality spectra to verify their classification, hence increasing the security of measurements for almost 4900 objects. Conclusions. We conclude that the SVM algorithm trained on a carefully selected sample of galaxies, AGNs, and stars outperforms simple colour-colour selection methods and can be regarded as a very efficient classification method particularly suitable for modern large surveys. [ABSTRACT FROM AUTHOR]

Context. Data mining techniques must be developed and applied to analyse the large public data bases containing hundreds to thousands of millions entries. Aims. We develop methods for locating previously unknown stellar clusters from the UKIDSS Galactic Plane Survey (GPS) catalogue data. Methods. The cluster candidates are computationally searched from pre-filtered catalogue data using a method that fits a mixture mo Jel of Gaussian densities and background noise using the expectation maximization algorithm. The catalogue data contains a significant number of false sources clustered around bright stars. A large fraction of these artefacts were automatically filtered out before or during the cluster search. The UKIDSS data reduction pipeline tends to classify marginally resolved stellar pairs and objects seen against variable surface brightness as extended objects (or "galaxies" in the archive parlance). 10% or 66 x 106 of the aources in the IJKIDSS GPS catalogue brighter than 17m in the K band are classified as "galaxies". Young embedded clusters create variable NTR surface brightness because the gas/dust clouds in which they were formed scatters the light from the cluster members. Such clusters appear therefore an clusters of "galaxies" in the catalogue and can be found using only a subset of the catalogue data. The detected "galaxy clusters" were finally screened visually to eliminate the remaining false detections due to dala artefacts. Besides the embedded clusters the search also located locations of non clustered embedded star formation. Results. The search covered an area of 1302 deg2 and 137 previously unknown cluster candidates and 30 previously unknown sites of star formation were found. [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. The recent results of the HARPS and Kepler surveys provided us with a bounty of extrasolar systems. While the two teams extensively analyzed each of their data-sets, little work has been done comparing the two. Aims. We study a subset of the planetary population whose characterization is simultaneously within reach of both instruments. We compare the statistical properties of planets in systems with m sin i > 5-10 M☉ and R > 2 R☉, as inferred from the HARPS and Kepler surveys, respectively. If we assume that the underlying population has the same characteristics, the different detection sensitivity to the orbital inclination relative to the line of sight allows us to probe the planets' mutual inclination. Methods. We considered the frequency of systems with one, two, and three planets as dictated by HARPS data. We used Kepler's planetary period and host mass and radius distributions (corrected from detection bias) to model planetary systems in a simple, yet physically plausible way. We then varied the mutual inclination between planets in a system according to different prescriptions (completely aligned, Rayleigh distributions, and isotropic) and compared the transit frequencies with one, two, or three planets with those measured by Kepler. Results. The results show that the two datasets are compatible, a remarkable result especially because there are no tunable knobs other than the assumed inclination distribution. For msin i cutoffs of 7-10 M☉, which are those expected to correspond to the radius cutoff of 2 R☉, we conclude that the results are better described by a Rayleigh distribution with a mode of 1° or smaller.We show that the best-fit scenario only becomes a Rayleigh distribution with a mode of 5° if we assume a quite extreme mass-radius relationship for the planetary population. Conclusions. These results have important consequences for our understanding of the role of several proposed formation and evolution mechanisms. They confirm that planets are likely to have been formed in a disk and show that most planetary systems evolve quietly without strong angular momentum exchanges such as those produced by Kozai mechanism or planet scattering. [ABSTRACT FROM AUTHOR]

Context. Results from gravitational microlensing suggested the existence of a large population of free-floating planetary mass objects. The main conclusion from this work was partly based on constraints from a direct imaging survey. This survey determined upper limits for the frequency of stars that harbor giant exoplanets at large orbital separations. Aims. We want to verify to what extent upper limits from direct imaging do indeed constrain the microlensing results. Methods. We examine the current derivation of the upper limits used in the microlensing study and re-analyze the data from the corresponding imaging survey. We focus on the mass and semi-major axis ranges that are most relevant in context of the microlensing results. We also consider new results from a recent M-dwarf imaging survey as these objects are typically the host stars for planets detected by microlensing. Results. We find that the upper limits currently applied in context of the microlensing results are probably underestimated. This means that a larger fraction of stars than assumed may harbor gas giant planets at larger orbital separations. Also, the way the upper limit is currently used to estimate the fraction of free-floating objects is not strictly correct. If the planetary surface density of giant planets around M-dwarfs is described as d fPlanet ∝ aβda, we find that β ≲ 0.5-0.6 is consistent with results from different observational studies probing semi-major axes between ∼0.03-30 AU. Conclusions. Having a higher upper limit on the fraction of stars that may have gas giant planets at orbital separations probed by the microlensing data implies that more of the planets detected in the microlensing study are potentially bound to stars rather than freefloating. The current observational data are consistent with a rising planetary surface density for giant exoplanets around M-dwarfs out to ∼30 AU. Future direct imaging surveys will show out to what semi-major axis the above mentioned range of β is valid and what fraction of the planetary mass objects detected by microlensing are indeed bound. [ABSTRACT FROM AUTHOR]

Aims. We present an optimized library of synthetic galaxy spectra that are to be used for the Gaia satellite observations of unresolved galaxies. These galaxy spectral templates are useful for the optimal performance of the unresolved galaxy classifier (UGC) software. The UGC will assign spectral classes to the observed unresolved galaxies by Gaia (classification) and estimate some of their intrinsic astrophysical parameters, which were used to create the synthetic library (parametrization). We present the new optimized synthetic library of galaxy spectra and the classification and parametrization results using the Gaia-simulated version of this library. Methods. To optimize our synthetic library, we applied the principal component analysis (PCA) method to our synthetic spectra and studied the influence of the star-formation rate parameters on the spectra, and how these agree with some typical characteristics of the galaxy spectral types. We used support vector machines (SVM) to classify and parametrize the optimal simulated spectra. Results. The library of synthetic galaxy spectra was optimized. In this new set of synthetic spectra, overlaps in spectral energy distributions and colors are highly suppressed, while the results of UGC classification are improved. [ABSTRACT FROM AUTHOR]