Context. To understand the evolution of galaxies, it is necessary to have a reference sample where the effect of the environment is minimized and quantified. In the framework of the AMIGA project (Analysis of the interstellar Medium of Isolated GAlaxies), we present a revision of the environment for galaxies in the Catalogue of Isolated Galaxies (CIG, Karachentseva 1973, Astrof. Issledovaniia Byu. Spec. Ast. Obs., 8, 3) using the ninth data release of the Sloan Digital Sky Survey (SDSS-DR9). Aims. The aims of this study are to refine the photometric-based AMIGA sample of isolated galaxies and to provide an improvement of the quantification of the isolation degree with respect to previous works, using both photometry and spectroscopy. Methods. We developed an automatic method to search for neighbours within a projected area of 1 Mpc radius centred on each primary galaxy to revise the CIG isolation criteria introduced by Karachentseva (1973). The local number density at the fifth nearest neighbour and the tidal strength affecting the CIG galaxy were estimated to quantify the isolation degree. Results. Of the 636 CIG galaxies considered in the photometric study, 426 galaxies fulfil the CIG isolation criteria within 1 Mpc, taking into account projected neighbours. Of the 411 CIG galaxies considered in the spectroscopic study, 347 galaxies fulfil the CIG isolation criteria when a criterion about redshift difference is added. The available redshifts allow us to reject background neighbours and thus improve the photometric assessment. On average, galaxies in the AMIGA sample show lower values in the local number density and the tidal strength parameters than galaxies in denser environments such as pairs, triplets, compact groups, and clusters. Conclusions. For the first time, the environment and the isolation degree of AMIGA galaxies are quantified using digital data. The use of the SDSS database permits one to identify fainter and smaller-size satellites than in previous AMIGA works. The AMIGA sample is improved by this study, because we reduced the sample of isolated galaxies used in previous AMIGA works by about 20%. The availability of the spectroscopic data allows us to check the validity of the CIG isolation criteria, which is not fully efficient. About 50% of the neighbours considered as potential companions in the photometric study are in fact background objects. We also find that about 92% of the neighbour galaxies that show recession velocities similar to the corresponding CIG galaxy are not considered by the CIG isolation criteria as potential companions, which may have a considerable influence on the evolution of the central CIG galaxy.

Context. Hickson Compact Group (HCG) 16 is a prototypical compact group of galaxies in an intermediate stage of the evolutionary sequence proposed by Verdes-Montenegro et al. (2001), where its galaxies are losing gas to the intra-group medium (IGrM). The group hosts galaxies that are H i-normal, H i-poor, centrally active with both AGN and starbursts, as well as a likely new member and a ∼160 kpc long H i tidal feature. Despite being a well-studied group at all wavelengths, no previous study of HCG 16 has focused on its extraordinary H i component. Aims. The characteristics of HCG 16 make it an ideal case study for exploring which processes are likely to dominate the late stages of evolution in compact groups, and ultimately determine their end states. In order to build a coherent picture of the evolution of this group we make use of the multi-wavelength data available, but focus particularly on H i as a tracer of interactions and evolutionary phase. Methods. We reprocess archival VLA L-band observations of HCG 16 using the multi-scale CLEAN algorithm to accurately recover diffuse features. Tidal features and galaxies are separated in 3 dimensions using the SlicerAstro package. The H i deficiency of the separated galaxies is assessed against the benchmark of recent scaling relations of isolated galaxies. This work has been performed with particular attention to reproducibility and is accompanied by a complete workflow to reproduce all the final data products, figures, and results. Results. Despite the clear disruption of the H i component of HCG 16 we find that it is not globally H i deficient, even though HCG 16a and b have lost the majority of their H i and almost 50% of the group's H i is in the IGrM. The H i content of HCG 16d shows highly disturbed kinematics, with only a marginal velocity gradient that is almost perpendicular to its optical major axis. The ∼160 kpc long tail extending towards the South-East appears to be part of an even larger structure which spatially and kinematically connects NGC 848 to the North-West corner of the group.Conclusions. This study indicates that in the recent past (∼1 Gyr) galaxies HCG 16a and b likely underwent major interactions that unbound gas without triggering significant star formation. This gas was then swept away by a high speed, close encounter with NGC 848. The starburst events HCG 16c and d, likely initiated by their mutual interaction, have triggered galactic winds which, in the case of HCG 16d, appears to have disrupted its H i reservoir. The tidal features still connected to all these galaxies indicate that more H i will soon be lost to the IGrM, while that which remains in the discs will likely be consumed by star formation episodes triggered by their on-going interaction. This is expected to result in a collection of gas-poor galaxies embedded in a diffuse H i structure, which will gradually (over several Gyr) be evaporated by the UV background, resembling the final stage of the evolutionary model of compact groups.

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We present dispel4py a versatile data-intensive kit presented as a standard Python library. It empowers scientists to experiment and test ideas using their familiar rapid-prototyping environment. It delivers mappings to diverse computing infrastructures, including cloud technologies, HPC architectures and specialised data-intensive machines, to move seamlessly into production with large-scale data loads. The mappings are fully automated, so that the encoded data analyses and data handling are completely unchanged. The underpinning model is lightweight composition of fine-grained operations on data, coupled together by data streams that use the lowest cost technology available. These fine-grained workflows are locally interpreted during development and mapped to multiple nodes and systems such as MPI and Storm for production.We explain why such an approach is becoming more essential in order that data-driven research can innovate rapidly and exploit the growing wealth of data while adapting to current technical trends. We show how provenance management is provided to improve understanding and reproducibility, and how a registry supports consistency and sharing. Three application domains are reported and measurements on multiple infrastructures show the optimisations achieved. Finally we present the next steps to achieve scalability and performance.

Context. We present a study of the 3D environment for a sample of 386 galaxies in the Catalogue of Isolated Galaxies (CIG, Karachentseva 1973) using the Ninth Data Release of the Sloan Digital Sky Survey (SDSS-DR9). Aims. We aim to identify and quantify the effects of the satellite distribution around a sample of galaxies in the CIG, as well as the effects of the large-scale structure (LSS). Methods. To recover the physically bound galaxies we first focused on the satellites that are within the escape speed of each CIG galaxy. We also propose a more conservative method using the stacked Gaussian distribution of the velocity difference of the neighbours. The tidal strengths affecting the primary galaxy were estimated to quantify the effects of the local and LSS environments. We also defined the projected number density parameter at the fifth nearest neighbour to characterise the LSS around the CIG galaxies. Results. Out of the 386 CIG galaxies considered in this study, at least 340 (88% of the sample) have no physically linked satellite. Following the more conservative Gaussian distribution of physical satellites around the CIG galaxies leads to upper limits. Out of the 386 CIG galaxies, 327 (85% of the sample) have no physical companion within a projected distance of 0.3 Mpc. The CIG galaxies are distributed following the LSS of the local Universe, although presenting a large heterogeneity in their degree of connection with it. When present around a CIG galaxy, the effect of physically bound galaxies largely dominates (typically by more than 90%) the tidal strengths generated by the LSS. Conclusions. The CIG samples a variety of environments, from galaxies with physical satellites to galaxies without neighbours within 3 Mpc. A clear segregation appears between early-type CIG galaxies with companions and isolated late-type CIG galaxies. Isolated galaxies are in general bluer, with probably younger stellar populations and very high star formation compared with older, redder CIG galaxies with companions. Reciprocally, the satellites are redder and with an older stellar populations around massive early-type CIG galaxies, while they have a younger stellar content around massive late-type CIG galaxies. This suggests that the CIG is composed of a heterogeneous population of galaxies, sampling from old to more recent, dynamical systems of galaxies. CIG galaxies with companions might have a mild tendency (0.3−0.4 dex) to be more massive, and may indicate a higher frequency of having suffered a merger in the past.

New scientific instruments are starting to generate an unprecedented amount of data. The Low Frequency Array (LOFAR), one of the Square Kilometre Array (SKA) pathfinders, is already producing data on a petabyte scale. The calibration of these data presents a huge challenge for final users: a) extensive storage and computing resources are required; b) the installation and maintenance of the software required for the processing is not trivial; and c) the requirements of calibration pipelines, which are experimental and under development, are quickly evolving. After encountering some limitations in classical infrastructures like dedicated clusters, we investigated the viability of cloud infrastructures as a solution.We found that the installation and operation of LOFAR data calibration pipelines is not only possible, but can also be efficient in cloud infrastructures. The main advantages were: (1) the ease of software installation and maintenance, and the availability of standard APIs and tools, widely used in the industry; this reduces the requirement for significant manual intervention, which can have a highly negative impact in some infrastructures; (2) the flexibility to adapt the infrastructure to the needs of the problem, especially as those demands change over time; (3) the on-demand consumption of (shared) resources. We found that a critical factor (also in other infrastructures) is the availability of scratch storage areas of an appropriate size. We found no significant impediments associated with the speed of data transfer, the use of virtualization, the use of external block storage, or the memory available (provided a minimum threshold is reached).Finally, we considered the cost-effectiveness of a commercial cloud like Amazon Web Services. While a cloud solution is more expensive than the operation of a large, fully-utilised cluster completely dedicated to LOFAR data reduction, we found that its costs are competitive if the number of datasets to be analysed is not high, or if the costs of maintaining a system capable of calibrating LOFAR data become high. Coupled with the advantages discussed above, this suggests that a cloud infrastructure may be favourable for many users.

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