We review recent advances and ongoing work in evolving the NASA/IPAC Extragalactic Database (NED) beyond an object reference database into a data mining discovery engine. Updates to the infrastructure and data integration techniques are enabling more than a 10-fold expansion; NED will soon contain over a billion objects with their fundamental attributes fused across the spectrum via cross-identifications among the largest sky surveys (e.g., GALEX, SDSS, 2MASS, AllWISE, EMU), and over 100,000 smaller but scientifically important catalogs and journal articles. The recent discovery of super-luminous spiral galaxies exemplifies the opportunities for data mining and science discovery directly from NED’s rich data synthesis. Enhancements to the user interface, including new APIs, VO protocols, and queries involving derived physical quantities, are opening new pathways for panchromatic studies of large galaxy samples. Examples are shown of graphics characterizing the content of NED, as well as initial steps in exploring the database via interactive statistical visualizations.

To understand mass loss history and mass loss and dust formation history of massive AGB stars, we carried out observations of three bipolar planetary nebulae (BPNe) in 30 micron bands from a ground-based telescope. All of our targets have a compact strong emission source in the mid-infrared (MIR) around the position of the central star of planetary nebula (CSPN). These detected emissions can be originated from cool dust. Our results show that the cool dust component is compactly distributed and much more massive than previous studies indicated. These findings suggest that they experienced a strong mass loss into the equatorial direction in past.

We explore photometric redshift estimation of quasars with the SDSS DR12 quasar sample. Firstly the quasar sample is separated into three parts according to different redshift ranges. Then three classifiers based on Extreme Learning Machine (ELM) are created in the three redshift ranges. Finally k-Nearest Neighbor (kNN) approach is applied on the three samples to predict photometric redshifts of quasars with multiwavelength photometric data. We compare the performance with different input patterns by ELM-KNN with that only by kNN. The experimental results show that ELM-KNN is feasible and superior to kNN (e.g. rms is 0.0751 vs. 0.2626 for SDSS sample), in other words, the ensemble method has the potential to increase regressor performance beyond the level reached by an individual regressor alone and will be a good choice when facing much more complex data.

We analysed the Spitzer 8μm and WISE 22μm images of the PN IRAS 18333-2357 using a 3D RT code. We describe its morphology with a H-poor disk and a spherical shell around it.

Some key physical processes that impact the evolution of Earth's atmosphere on time-scale from days to millennia, such as the EUV emissions, are determined by the solar magnetic field. However, observations of the solar spectral irradiance are restricted to the last few solar cycles and are subject to large uncertainties. We present a physics-based model to reconstruct short-term solar spectral irradiance (SSI) variability. The coronal magnetic field is estimated to employ the Potential Field Source Surface extrapolation (PFSS) based on observational synoptic charts and magnetic flux transport model. The emission is estimated to employ the CHIANTI atomic database 8.0. The performance of the model is compared to the emission observed by TIMED/SORCE.

This paper comments on the use Gaia in studying the internal dynamics and morphologies of Planetary Nebulae (PN). It is noted that the second and subsequent releases of Gaia data, will have significant potential in unravelling PN morphologies.

Compressive Sensing is an emerging technology for data compression and simultaneous data acquisition. This is an enabling technique for significant reduction in data bandwidth, and transmission power and hence, can greatly benefit space-flight instruments. We apply this process to detect exoplanets via gravitational microlensing. We experiment with various impact parameters that describe microlensing curves to determine the effectiveness and uncertainty caused by Compressive Sensing. Finally, we describe implications for space-flight missions.

Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because of its high level of abstraction with little human intervention, deep learning appears to be a promising approach. Deep learning is a rapidly growing discipline that models high-level patterns in data as complex multilayered networks. In this work we test the ability of deep convolutional networks to provide parametric properties of Hubble Space Telescope like galaxies (half-light radii, Sérsic indices, total flux etc..). We simulate a set of galaxies including point spread function and realistic noise from the CANDELS survey and try to recover the main galaxy parameters using deep-learning. We compare the results with the ones obtained with the commonly used profile fitting based software GALFIT. This way showing that with our method we obtain results at least equally good as the ones obtained with GALFIT but, once trained, with a factor 5 hundred time faster.

We present METAPHOR (Machine-learning Estimation Tool for Accurate PHOtometric Redshifts), a method able to provide a reliable PDF for photometric galaxy redshifts estimated through empirical techniques. METAPHOR is a modular workflow, mainly based on the MLPQNA neural network as internal engine to derive photometric galaxy redshifts, but giving the possibility to easily replace MLPQNA with any other method to predict photo-z’s and their PDF. We present here the results about a validation test of the workflow on the galaxies from SDSS-DR9, showing also the universality of the method by replacing MLPQNA with KNN and Random Forest models. The validation test include also a comparison with the PDF’s derived from a traditional SED template fitting method (Le Phare).

The post-asymptotic giant branch (AGB) phase is arguably one of the least understood phases of the evolution of low- and intermediate- mass stars. The recent post-AGB evolutionary sequences computed by Miller Bertolami (2016) are at least three to ten times faster than those previously published by Vassiliadis & Wood (1994) and Blöcker (1995) which have been used in a large number of studies. This is true for the whole mass and metallicity range. The new models are also ~0.1–0.3 dex brighter than the previous models with similar remnant masses. In this short article we comment on the main reasons behind these differences, and discuss possible implications for other studies of post-AGB stars or planetary nebulae.

We present the results of the search of variable sources and transient events in the archive data of the sky surveys conducted on 3.9 GHz on the RATAN-600 radio telescope of the Special Astrophysical Observatory of the Russian Academy of Sciences (SAO RAS) in 1980-1994. 17% of the total studied sources can be attributed to the variables in radio range. About half of them has significant variations in optical brightness according to the data of the catalogs. At the level of 3-5 r.m.s. we found three transient events. Two weak events probably associated with AGN activities or with cataclysmic events such as GRB and a supernova flash. The nature of the third event has not been established. According to our estimation the surface density of radio transients is 0.03 on one square angular degree with the detection level 8–11 mJy on 3.94 GHz.

A subset of Post-AGB (PAGB) objects are the highly luminous RV Tauri variables that show similarities to Type-II Cepheids. By using a sample of known RV Tauri stars from the Magellanic Clouds we are able to determine period luminosity relationships (PLRs) in various bands that have been used to determine the luminosities of their Galactic counterparts. We have gathered all available photometry in order to generate an SED for each object and determine the total integrated flux. This total flux combined with a calculated or inferred intrinsic luminosity leads to a distance (Vickers et al. 2015). This distance catalogue has allowed us to begin to constrain the physical parameters of this poorly understood evolutionary phase and to determine links between these physical characteristics as a function of their stellar population.

For the vast amounts of spectra produced by LAMOST, the pipeline basing on PCAZ method is limited by the bad flux calibration and low S/N data. This work focuses on the study of the efficient recognition methods of galaxy spectra of LAMOST basing on spectral lines information. The new method searches spectral lines and extracts the information of spectral lines (position, height, and width et al.) automatically. Using the spectral lines information which are less influenced by the quality of flux calibration and the S/N ratio, galaxy spectra are recognized with the redshift measured through spectral lines matching method. The experiment verified it is feasible for the LAMOST galaxy spectra: the correct recognition rate > 80% for the data with SNR_g > 5, and > 90% for the data with SNR_r > 5. Compared with the redshift of SDSS, the systematic error of our method is 0, and the standard deviation of the error is 0.0002.

We present studies using different observational techniques, along different frequencies, aiming to resolve and investigate jets, outflows, as well as compact and innermost regions of asymmetric planetary nebulae (PNe) and objects in transition to PN. All the information gathered allow us to explore the kinematics and other important properties of the structures that play a crucial role in the shaping of complex PNe morphologies, in particular, we explore the role of disks/tori as collimating engine of extreme axisymmetric PNe.

Due to limitations in available instrumentation and observation time, a spectroscopic determination of distance is not feasible for all objects in the sky. Therefore statistical methods that estimate redshifts, based on photometric measurement are of tremendous importance to many astrophysical questions. Determining cosmological parameters and understanding evolutionary processes in the universe are just two examples. When perform astrophysical analyses, it is necessary to treat the uncertainties of the estimates correctly. Over-simplification of results and the usage of wrong tools to evaluate the performance of probabilistic redshift estimates were commonly found in the literature. We present proper tools for evaluating uncertain redshift estimates and discuss the necessity of multimodal redshift distributions.

We present a 3D magnetohydrodynamic study of the effect that stellar and planetary magnetic fields have on the calculated Lyα absorption during the planetary transit, employing parameters that resemble the exoplanet HD209458b. We assume a dipolar magnetic field for both the star and the planet, and use the Parker solution to initialize the stellar wind. We also consider the radiative processes and the radiation pressure.

We use the numerical MHD code Guacho to run several models varying the values of the planetary and stellar magnetic moments within the range reported in the literature.

We found that the presence of magnetic fields influences the escaping neutral planetary material spreading the absorption Lyα line for large stellar magnetic fields.

Observations of various solar-type stars along decades showed that they could have magnetic cycles, just like our Sun. These observations yield a relation between the rotation period P rot and the cycle length P cycle of these stars. Two distinct branches for the cycling stars were identified: active and inactive, classified according to stellar activity level and rotation rate. In this work, we determined the magnetic activity cycle for 6 active stars observed by the Kepler telescope. The method adopted here estimates the activity from the excess in the residuals of the transit light curves. This excess is obtained by subtracting a spotless model transit from the light curve, and then integrating over all the residuals during the transit. The presence of long term periodicity is estimated from the analysis of a Lomb-Scargle periodogram of the complete time series. Finally, we investigate the rotation-cycle period relation for the stars analysed here.

Solar-like stars influence their environments through their coronal emis- sion and winds. These processes are linked through the physics of the stellar magnetic field, whose strength and geometry has now been explored for a large number of stars through spectropolarimetric observations. We have now detected trends with mass and rotation rate in the distribution of magnetic energies in different geometries and on also different length scales. This has implications both for the dynamo processes that generate the fields and also for the dynamics and evolution of the coronae and winds. Modelling of the surface driving processes on stars of various masses and rotation rates has revealed tantalising clues about the dynamics of stellar coronae and their ejecta. These new observations have also prompted a resurgence in the modelling of stellar winds, which is now uncovering the range of different interplanetary conditions that exoplanets might experience as they evolve.

Upcoming HI surveys will deliver such large datasets that automated processing using the full 3-D information to find and characterize HI objects is unavoidable. Full 3-D visualization is an essential tool for enabling qualitative and quantitative inspection and analysis of the 3-D data, which is often complex in nature. Here we present SlicerAstro, an open-source extension of 3DSlicer, a multi-platform open source software package for visualization and medical image processing, which we developed for the inspection and analysis of HI spectral line data. We describe its initial capabilities, including 3-D filtering, 3-D selection and comparative modelling.

This work presents the first results of a study about possible effects on the surface temperature during short periods of lower fluxes of Galactic Cosmic Rays at Earth, called Forbush Decreases. There is a hypothesis that the Galactic Cosmic Ray flux decreases cause changes on the physical-chemical properties of the atmosphere. We have conducted a study to investigate these possible effects on several latitudinal regions, around the ten strongest FDs occurred from 1987 to 2015. We have found a possible increase on the surface temperature at middle and high latitudes during the occurence of these events.