# Lithium abundance and 6Li/7Li ratio in the active giant HD123351 I. A comparative analysis of 3D and 1D NLTE line-profile fits [SSA]

Current three-dimensional (3D) hydrodynamical model atmospheres together with NLTE spectrum synthesis, permit to derive reliable atomic and isotopic chemical abundances from high-resolution stellar spectra. Not much is known about the presence of the fragile 6Li isotope in evolved solar-metallicity RGB stars, not to mention its production in magnetically active targets like HD123351. From fits of the observed CFHT spectrum with synthetic line profiles based on 1D and 3D model atmospheres, we seek to estimate the abundance of the 6Li isotope and to place constraints on its origin. We derive A(Li) and the 6Li/7Li isotopic ratio by fitting different synthetic spectra to the Li-line region of a high-resolution CFHT spectrum (R=120 000, S/R=400). The synthetic spectra are computed with four different line lists, using in parallel 3D hydrodynamical CO5BOLD and 1D LHD model atmospheres and treating the line formation of the lithium components in non-LTE (NLTE). We find A(Li)=1.69+/-0.11 dex and 6Li/7Li=8.0+/-4.4 % in 3D-NLTE, using the line list of Mel\’endez et al. (2012), updated with new atomic data for V I, which results in the best fit of the lithium line profile of HD123351. Two other line lists lead to similar results but with inferior fit qualities. Our 2-sigma detection of the 6Li isotope is the result of a careful statistical analysis and the visual inspection of each achieved fit. Since the presence of a significant amount of 6Li in the atmosphere of a cool evolved star is not expected in the framework of standard stellar evolution theory, non-standard, external lithium production mechanisms, possibly related to stellar activity or a recent accretion of rocky material, need to be invoked to explain the detection of 6Li in HD123351.

A. Mott, M. Steffen, E. Caffau, et. al.
Mon, 24 Apr 17
1/54

Comments: 16 pages, 11 figures. Accepted for publication in A&A

# GOLDRUSH. II. Clustering of Galaxies at $z\sim 4-6$ Revealed with the Half-Million Dropouts Over the 100 deg$^2$ Area Corresponding to 1 Gpc$^3$ [GA]

We present clustering properties from 579,492 Lyman break galaxies (LBGs) at $z\sim4-6$ over the 100 deg$^2$ sky (corresponding to a 1.4 Gpc$^3$ volume) identified in early data of the Hyper Suprime-Cam (HSC) Subaru strategic program survey. We derive angular correlation functions (ACFs) of the HSC LBGs with unprecedentedly high statistical accuracies at $z\sim4-6$, and compare them with the halo occupation distribution (HOD) models. We clearly identify significant ACF excesses in $10″<\theta<90″$, the transition scale between 1- and 2-halo terms, suggestive of the existence of the non-linear halo bias effect. Combining the HOD models and previous clustering measurements of faint LBGs at $z\sim4-7$, we investigate dark-matter halo mass ($M_\mathrm{h}$) of the $z\sim4-7$ LBGs and its correlation with various physical properties including the star-formation rate (SFR), the stellar-to-halo mass ratio (SHMR), and the dark-matter mass accretion rate ($\dot{M}\mathrm{h}$) over a wide-mass range of $M\mathrm{h}/M_\odot=4\times10^{10}-4\times10^{12}$. We find that the SHMR increases from $z\sim4$ to $7$ by a factor of $\sim4$ at $M_\mathrm{h}\simeq1\times10^{11}\ M_\odot$, while the SHMR shows no strong evolution in the similar redshift range at $M_\mathrm{h}\simeq1\times10^{12}\ M_\odot$. Interestingly, we identify a tight relation of $SFR/\dot{M}\mathrm{h}-M\mathrm{h}$ showing no significant evolution beyond 0.15 dex in this wide-mass range over $z\sim4-7$. This weak evolution suggests that the $SFR/\dot{M}\mathrm{h}-M\mathrm{h}$ relation is a fundamental relation in high-redshift galaxy formation whose star-formation activities are regulated by the dark-matter mass assembly.

Y. Harikane, M. Ouchi, Y. Ono, et. al.
Mon, 24 Apr 17
2/54

Comments: 31 pages, 25 figures, submitted to a special issue of PASJ

# Machine Learning Based Real Bogus System for HSC-SSP Moving Object Detecting Pipeline [IMA]

The machine learning techniques are widely applied in many modern optical sky surveys, i.e. Pan-STARRS1, PTF/iPTF and Subaru/Hyper Suprime-Cam survey, to reduce the human intervention for data verification. In this study, we have established a machine learning based real-bogus system to reject the false detections in the HSC-SSP source catalog. Therefore the HSC-SSP moving object detection pipeline can operate more effectively due to the much less false positives inputs. To train the real-bogus system, we use the stationary sources as the real training set and the `flagged’ data as the bogus set. The training set contains 49 features, which, in majority, are the photometry measurements and shape moments generating from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ~ 96% with a false positive rate (fpr) ~ 1% or tpr ~ 99% at fpr ~ 5%. Therefore we conclude that the stationary sources are decent real training samples, and using photometry measurements and shape moments can reject the false positives effectively.

H. Lin, Y. Chen, J. Wang, et. al.
Mon, 24 Apr 17
3/54

Comments: 16 pages, 4 figures, submitted to PASJ HSC special issue

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# SILCC-Zoom: The dynamical and chemical evolution of molecular clouds [GA]

We present 3D simulations of the formation process of two molecular clouds (MCs) within their larger-scale galactic environment. Using adaptive mesh refinement, we model the two MCs within the SILCC project with an unprecedented resolution of 0.06 pc combined with a chemical network for the formation of H$2$ and CO including (self-) shielding and important thermal processes. The MCs form within a few Myr with mass growth rates of up to 10$^{-2}$ M$\rm{sun}$ yr$^{-1}$ and final masses of $\sim$ 50000 M$\rm{sun}$. We show that the usage of different definitions for MCs by thresholds in density, H$_2$ or CO mass fraction significantly change the inferred cloud properties. While CO traces well the evolution of dense gas with $n \geq$ 300 cm$^{-3}$, H$_2$ is also found in gas with lower number density ($n \lesssim$ 30 cm$^{-3}$) due to turbulent mixing. The CO-to-H$_2$ ratio increases within the first 2 Myr reaching a value of $\sim$ 1.8 $\times$ 10$^{-4}$ at later stages. The $X\rm{CO}$ factor, however, is rather time-independent with values of 1 – 4 $\times$ 10$^{20}$ cm$^{-2}$ (K km s$^{-1}$)$^{-1}$. We show that a spatial resolution of $\sim$ 0.1 pc is required to accurately model the chemical, dynamical, and structural evolution of MCs. At a coarser resolution the mass, velocity dispersion, and chemical abundances of the clouds are underestimated. Furthermore, we show that the progressive increase of resolution has to occur over a time of 1 – 1.5 Myr. This ensures that the maximum refinement level is reached within the free-fall time of the densest structures and avoids the spurious formation large-scale, rotating objects by unresolved turbulent flows. In addition, the accelerated formation of chemical species in dense, turbulent environments is captured properly. Finally, we demonstrate that $\gtrsim$ 200 time steps should be spent on each refinement level to avoid grid artefacts.

D. Seifried, S. Walch, P. Girichidis, et. al.
Mon, 24 Apr 17
4/54

# Galaxy Zoo: The interplay of quenching mechanisms in the group environment [GA]

Does the environment of a galaxy directly influence the quenching history of a galaxy? Here we investigate the detailed morphological structures and star formation histories of a sample of SDSS group galaxies with both classifications from Galaxy Zoo 2 and NUV detections in GALEX. We use the optical and NUV colours to infer the quenching time and rate describing a simple exponentially declining SFH for each galaxy, along with a control sample of field galaxies. We find that the time since quenching and the rate of quenching do not correlate with the relative velocity of a satellite but are correlated with the group potential. This quenching occurs within an average quenching timescale of $\sim2.5~\rm{Gyr}$ from star forming to complete quiescence, during an average infall time (from $\sim 10R_{200}$ to $0.01R_{200}$) of $\sim 2.6~\rm{Gyr}$. Our results suggest that the environment does play a direct role in galaxy quenching through quenching mechanisms which are correlated with the group potential, such as harassment, interactions or starvation. Environmental quenching mechanisms which are correlated with satellite velocity, such as ram pressure stripping, are not the main cause of quenching in the group environment. We find that no single mechanism dominates over another, except in the most extreme environments or masses. Instead an interplay of mergers, mass & morphological quenching and environment driven quenching mechanisms dependent on the group potential drive galaxy evolution in groups.

R. Smethurst, C. Lintott, S. Bamford, et. al.
Mon, 24 Apr 17
5/54

# Refining mass formulas for astrophysical applications: a Bayesian neural network approach [CL]

Exotic nuclei, particularly those near the driplines, are at the core of one of the fundamental questions driving nuclear structure and astrophysics today: what are the limits of nuclear binding? Exotic nuclei play a critical role in both informing theoretical models as well as in our understanding of the origin of the heavy elements. Our purpose is to refine existing mass models through the training of an artificial neural network that will mitigate the large model discrepancies far away from stability. The basic paradigm of our two-pronged approach is an existing mass model that captures as much as possible of the underlying physics followed by the implementation of a Bayesian Neural Network (BNN) refinement to account for the missing physics. Bayesian inference is employed to determine the parameters of the neural network so that model predictions may be accompanied by theoretical uncertainties. Despite the undeniable quality of the mass models adopted in this work, we observe a significant improvement (of about 40%) after the BNN refinement is implemented. Indeed, in the specific case of the Duflo-Zuker mass formula, we find that the rms deviation relative to experiment is reduced from rms =0.503MeV to rms=0.286 MeV. These newly refined mass tables are used to map the neutron drip lines (or rather “drip bands”) and to study a few critical r-process nuclei. The BNN approach is highly successful in refining the predictions of existing mass models. In particular, the large discrepancy displayed by the original “bare” models in regions where experimental data is unavailable is considerably quenched after the BNN refinement. This lends credence to our approach and has motivated us to publish refined mass tables that we trust will be helpful for future astrophysical applications.

R. Utama and J. Piekarewicz
Mon, 24 Apr 17
6/54

We have modified the iterative procedure introduced by Lin et al. (2016), to systematically combine the submm images taken from ground based (e.g., CSO, JCMT, APEX) and space (e.g., Herschel, Planck) telescopes. We applied the updated procedure to observations of three well studied Infrared Dark Clouds (IRDCs): G11.11-0.12, G14.225-0.506 and G28.34+0.06, and then performed single-component, modified black-body fits to derive $\sim$10$”$ resolution dust temperature and column density maps. The derived column density maps show that these three IRDCs exhibit complex filamentary structures embedding with rich clumps/cores. We compared the column density probability distribution functions (N-PDFs) and two-point correlation (2PT) functions of the column density field between these IRDCs with several OB cluster-forming regions. Based on the observed correlation and measurements, and complementary hydrodynamical simulations for a 10$^{4}$ $\rm M_{\odot}$ molecular cloud, we hypothesize that cloud evolution can be better characterized by the evolution of the (column) density distribution function and the relative power of dense structures as a function of spatial scales, rather than merely based on the presence of star-forming activity. Based on the small analyzed sample, we propose four evolutionary stages, namely: {\it cloud integration, stellar assembly, cloud pre-dispersal and dispersed-cloud.} The initial {\it cloud integration} stage and the final {\it dispersed cloud} stage may be distinguished from the two intermediate stages by a steeper than $-$4 power-law index of the N-PDF. The {\it cloud integration} stage and the subsequent {\it stellar assembly} stage are further distinguished from each other by the larger luminosity-to-mass ratio ($>$40 $\rm L_{\odot}/M_{\odot}$) of the latter.