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Register a new userConstraining the Galactic structure parameters with the XSTPS-GAC and SDSS photometric surveys
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Photometric data from the Xuyi Schmidt Telescope Photometric Survey of the Galactic Anticentre (XSTPS-GAC) and the Sloan Digital Sky Survey (SDSS) are used to derive the global structure parameters of the smooth components of the Milky Way. The data, which cover nearly 11,000 deg$^2$ sky area and the full range of Galactic latitude, allow us to construct a globally representative Galactic model. The number density distribution of Galactic halo stars is fitted with an oblate spheroid that decays by power law. The best-fit yields an axis ratio and a power law index $kappa=0.65$ and $p=2.79$, respectively. The $r$-band differential star counts of three dwarf samples are then fitted with a Galactic model. The best-fit model yielded by a Markov Chain Monte Carlo analysis has thin and thick disk scale heights and lengths of $H_{1}=$ 322,pc and $L_{1}=$2343,pc, $H_{2}=$794,pc and $L_{2}=$3638,pc, a local thick-to-thin disk density ratio of $f_2=$11,per,cent, and a local density ratio of the oblate halo to the thin disk of $f_h=$0.16,per,cent. The measured star count distribution, which is in good agreement with the above model for most of the sky area, shows a number of statistically significant large scale overdensities, including some of the previously known substructures, such as the Virgo overdensity and the so-called north near structure, and a new feature between 150degr $< l < $ 240degr~and $-1$5degr $< b < $ $-$5degr, at an estimated distance between 1.0 and 1.5,kpc. The Galactic North-South asymmetry in the anticentre is even stronger than previously thought.
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The Xuyi Schmidt Telescope Photometric Survey of the Galactic Anti-center (XSTPS-GAC) is a photometric sky survey that covers nearly 6 000 deg^2 towards Galactic anti-center in g r i bands. Half of its survey field locates on the Galactic Anti-center disk, which makes XSTPS-GAC highly suitable for searching new open clusters in the GAC region. In this paper, we report new open cluster candidates discovered in this survey, as well as properties of these open cluster candidates, such as age, distance and reddening, derived by isochrone fitting in the color-magnitude diagram (CMD). These open cluster candidates are stellar density peaks detected in the star density maps by applying the method from Koposov et al. (2008). Each candidate is inspected on its true color image composed from XSTPS-GAC three band images. Then its CMD is checked, in order to identify whether the central region stars have a clear isochrone-like trend differing from the background stars. The parameters derived from isochrone fitting for these candidates are mainly based on three band photometry of XSTPS-GAC. Meanwhile, when these new candidates are able to be seen clearly on 2MASS, their parameters are also derived based on 2MASS (J-H, J) CMD. Finally, there are 320 known open clusters rediscovered and 24 new open cluster candidates discovered in this work. Further more, the parameters of these new candidates, as well as another 11 known recovered open clusters, are properly determined for the first time.
Upcoming large-area narrow band photometric surveys, such as J-PAS, will enable us to observe a large number of galaxies simultaneously and efficiently. However, it will be challenging to analyse the spatially-resolved stellar populations of galaxies from such big data to investigate galaxy formation and evolutionary history. We have applied a convolutional neural network (CNN) technique, which is known to be computationally inexpensive once it is trained, to retrieve the metallicity and age from J-PAS-like narrow band images. The CNN was trained using mock J-PAS data created from the CALIFA IFU survey and the age and metallicity at each data point, which are derived using full spectral fitting to the CALIFA spectra. We demonstrate that our CNN model can consistently recover age and metallicity from each J-PAS-like spectral energy distribution. The radial gradients of the age and metallicity for galaxies are also recovered accurately, irrespective of their morphology. However, it is demonstrated that the diversity of the dataset used to train the neural networks has a dramatic effect on the recovery of galactic stellar population parameters. Hence, future applications of CNNs to constrain stellar populations will rely on the availability of quality spectroscopic data from samples covering a wide range of population parameters.
The secondary-to-primary B/C ratio is widely used to study Galactic cosmic-ray propagation processes. The 2H/4He and 3He/4He ratios probe a different Z/A regime, therefore testing the `universality of propagation. We revisit the constraints on diffusion-model parameters set by the quartet (1H, 2H, 3He, 4He), using the most recent data as well as updated formulae for the inelastic and production cross-sections. The analysis relies on the USINE propagation package and a Markov Chain Monte Carlo technique to estimate the probability density functions of the parameters. Simulated data are also used to validate analysis strategies. The fragmentation of CNO cosmic rays (resp. NeMgSiFe) on the ISM during their propagation contributes to 20% (resp. 20%) of the 2H and 15% (resp. 10%) of the 3He flux at high energy. The C to Fe elements are also responsible for up to 10% of the 4He flux measured at 1 GeV/n. The analysis of 3He/4He (and to a less extent 2H/4He) data shows that the transport parameters are consistent with those from the B/C analysis: the diffusion model with delta~0.7 (diffusion slope), Vc~20 km/s (galactic wind), Va~40 km/s (reacceleration) is favoured, but the combination delta~0.2, Vc~0, and Va~80 km/s is a close second. The confidence intervals on the parameters show that the constraints set by the quartet data are competitive with those brought by the B/C data. These constraints are tighter when adding the 3He (or 2H) flux measurements, and the tightest when further adding the He flux. For the latter, the analysis of simulated and real data show an increased sensitivity to biases. Using secondary-to-primary ratio along with a loose prior on the source parameters is recommended to get the most robust constraints on the transport parameters.
We apply clustering-based redshift inference to all extended sources from the Sloan Digital Sky Survey photometric catalogue, down to magnitude r = 22. We map the relationships between colours and redshift, without assumption of the sources spectral energy distributions (SED). We identify and locate star-forming, quiescent galaxies, and AGN, as well as colour changes due to spectral features, such as the 4000 AA{} break, redshifting through specific filters. Our mapping is globally in good agreement with colour-redshift tracks computed with SED templates, but reveals informative differences, such as the need for a lower fraction of M-type stars in certain templates. We compare our clustering-redshift estimates to photometric redshifts and find these two independent estimators to be in good agreement at each limiting magnitude considered. Finally, we present the global clustering-redshift distribution of all Sloan extended sources, showing objects up to z ~ 0.8. While the overall shape agrees with that inferred from photometric redshifts, the clustering redshift technique results in a smoother distribution, with no indication of structure in redshift space suggested by the photometric redshift estimates (likely artifacts imprinted by their spectroscopic training set). We also infer a higher fraction of high redshift objects. The mapping between the four observed colours and redshift can be used to estimate the redshift probability distribution function of individual galaxies. This work is an initial step towards producing a general mapping between redshift and all available observables in the photometric space, including brightness, size, concentration, and ellipticity.
Studies of stellar populations, understood to mean collections of stars with common spatial, kinematic, chemical, and/or age distributions, have been reinvigorated during the last decade by the advent of large-area sky surveys such as SDSS, 2MASS, RAVE, and others. We review recent analyses of these data that, together with theoretical and modeling advances, are revolutionizing our understanding of the nature of the Milky Way, and galaxy formation and evolution in general. The formation of galaxies like the Milky Way was long thought to be a steady process leading to a smooth distribution of stars. However, the abundance of substructure in the multi-dimensional space of various observables, such as position, kinematics, and metallicity, is by now proven beyond doubt, and demonstrates the importance of mergers in the growth of galaxies. Unlike smooth models that involve simple components, the new data reviewed here clearly show many irregular structures, such as the Sagittarius dwarf tidal stream and the Virgo and Pisces overdensities in the halo, and the Monoceros stream closer to the Galactic plane. These recent developments have made it clear that the Milky Way is a complex and dynamical structure, one that is still being shaped by the merging of neighboring smaller galaxies. We also briefly discuss the next generation of wide-field sky surveys, such as SkyMapper, Pan-STARRS, Gaia and LSST, which will improve measurement precision manyfold, and comprise billions of individual stars. The ultimate goal, development of a coherent and detailed story of the assembly and evolutionary history of the Milky Way and other large spirals like it, now appears well within reach.
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