681 research outputs found

    The SAMI Galaxy Survey: Shocks and Outflows in a normal star-forming galaxy

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    We demonstrate the feasibility and potential of using large integral field spectroscopic surveys to investigate the prevalence of galactic-scale outflows in the local Universe. Using integral field data from SAMI and the Wide Field Spectrograph, we study the nature of an isolated disk galaxy, SDSS J090005.05+000446.7 (z = 0.05386). In the integral field datasets, the galaxy presents skewed line profiles changing with position in the galaxy. The skewed line profiles are caused by different kinematic components overlapping in the line-of-sight direction. We perform spectral decomposition to separate the line profiles in each spatial pixel as combinations of (1) a narrow kinematic component consistent with HII regions, (2) a broad kinematic component consistent with shock excitation, and (3) an intermediate component consistent with shock excitation and photoionisation mixing. The three kinematic components have distinctly different velocity fields, velocity dispersions, line ratios, and electron densities. We model the line ratios, velocity dispersions, and electron densities with our MAPPINGS IV shock and photoionisation models, and we reach remarkable agreement between the data and the models. The models demonstrate that the different emission line properties are caused by major galactic outflows that introduce shock excitation in addition to photoionisation by star-forming activities. Interstellar shocks embedded in the outflows shock-excite and compress the gas, causing the elevated line ratios, velocity dispersions, and electron densities observed in the broad kinematic component. We argue from energy considerations that, with the lack of a powerful active galactic nucleus, the outflows are likely to be driven by starburst activities. Our results set a benchmark of the type of analysis that can be achieved by the SAMI Galaxy Survey on large numbers of galaxies.Comment: 17 pages, 15 figures. Accepted to MNRAS. References update

    Source finding, parametrization and classification for the extragalactic Effelsberg-Bonn HI Survey

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    Context. Source extraction for large-scale HI surveys currently involves large amounts of manual labor. For data volumes expected from future HI surveys with upcoming facilities, this approach is not feasible any longer. Aims. We describe the implementation of a fully automated source finding, parametrization, and classification pipeline for the Effelsberg-Bonn HI Survey (EBHIS). With future radio astronomical facilities in mind, we want to explore the feasibility of a completely automated approach to source extraction for large-scale HI surveys. Methods. Source finding is implemented using wavelet denoising methods, which previous studies show to be a powerful tool, especially in the presence of data defects. For parametrization, we automate baseline fitting, mask optimization, and other tasks based on well-established algorithms, currently used interactively. For the classification of candidates, we implement an artificial neural network which is trained on a candidate set comprised of false positives from real data and simulated sources. Using simulated data, we perform a thorough analysis of the algorithms implemented. Results. We compare the results from our simulations to the parametrization accuracy of the HI Parkes All-Sky Survey (HIPASS) survey. Even though HIPASS is more sensitive than EBHIS in its current state, the parametrization accuracy and classification reliability match or surpass the manual approach used for HIPASS data.Comment: 13 Pages, 13 Figures, 1 Table, accepted for publication in A&

    Dissecting Galaxies: Separating Star Formation, Shock Excitation and AGN Activity in the Central Region of NGC 613

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    The most rapidly evolving regions of galaxies often display complex optical spectra with emission lines excited by massive stars, shocks and accretion onto supermassive black holes. Standard calibrations (such as for the star formation rate) cannot be applied to such mixed spectra. In this paper we isolate the contributions of star formation, shock excitation and active galactic nucleus (AGN) activity to the emission line luminosities of individual spatially resolved regions across the central 3 ×\times 3 kpc2^2 region of the active barred spiral galaxy NGC\sim613. The star formation rate and AGN luminosity calculated from the decomposed emission line maps are in close agreement with independent estimates from data at other wavelengths. The star formation component traces the B-band stellar continuum emission, and the AGN component forms an ionization cone which is aligned with the nuclear radio jet. The optical line emission associated with shock excitation is cospatial with strong H2H_2 and [Fe II] emission and with regions of high ionized gas velocity dispersion (σ>100\sigma > 100 km s1^{-1}). The shock component also traces the outer boundary of the AGN ionization cone and may therefore be produced by outflowing material interacting with the surrounding interstellar medium. Our decomposition method makes it possible to determine the properties of star formation, shock excitation and AGN activity from optical spectra, without contamination from other ionization mechanisms.Comment: 16 pages, 12 figures. Accepted for publication in MNRA

    Automated Source Extraction for the Next Generation of Neutral Hydrogen Surveys

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    This thesis is a first step to develop the necessary tools to automatically extract and parameterize sources from future HI surveys with ASKAP, WSRT/Apertif, and SKA. The current approach to large-scale HI surveys, that is, automated source finding followed by manual classification and parametrization, is no longer feasible in light of the data volumes expected for future surveys. We use data from EBHIS to develop and test a completely automated source extraction pipeline for extragalactic HI surveys. We apply a 2D-1D wavelet de-noising technique to HI data and show that it is well adapted to the typical shapes of sources encountered in HI surveys. This technique allows to reliably extract sources even from data containing defects commonly encountered in single-dish HI surveys. Automating the task of false-positive rejection requires reliable parameters for all source candidates generated by the source-finding step. For this purpose, we develop a reliable, automated parametrization pipeline that combines time-tested algorithms with new approaches to baseline estimation, spectral filtering, and mask optimization. The accuracy of the algorithms is tested by performing extensive simulations. By comparison with the uncertainty estimates from HIPASS we show that our automated pipeline gives equal or better accuracy than manual parametrization. We implement the task of source classification using artificial neural networks using the automatically determined parameters of the source candidates as inputs. The viability of this approach is verified on a training data set comprised of parameters measured from simulated sources and false positives extracted from real EBHIS data. Since the number of true positives from real data is small compared to the number of false positives, we explore various methods of training artificial neural networks from imbalanced data sets. We show that the artificial neural networks trained in this way do not achieve sufficient completeness and reliability when applied to the source candidates detected from the extragalactic EBHIS survey. We use the trained artificial neural networks in a semi-supervised manner to compile the first extragalactic EBHIS source catalog. The use of artificial neural networks reduces the number of source candidates that require manual inspection by more than an order of magnitude. We compare the results from EBHIS to HIPASS and show that the number of sources in the compiled catalog is approximately half of the sources expected. The main reason for this detection inefficiency is identified to be mis-classification by the artificial neural networks. This is traced back to the limited training data set, which does not cover the parameter space of real detections sufficiently, and the similarity of true and false positives in the parameter space spanned by the measured parameters. We conclude that, while our automated source finding and parametrization algorithms perform satisfactorily, the classification of sources is the most challenging task for future HI surveys. Classification based on the measured source parameters does not provide sufficient discriminatory power and we propose to explore methods based on machine vision which learns features of real sources from the data directly

    Galaxy-Wide Shocks in Late-Merger Stage Luminous Infrared Galaxies

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    We present an integral field spectroscopic study of two nearby Luminous Infrared Galaxies (LIRGs) that exhibit evidence of widespread shock excitation induced by ongoing merger activity, IC 1623 and NGC 3256. We show the importance of carefully separating excitation due to shocks vs. excitation by HII regions and the usefulness of IFU data in interpreting the complex processes in LIRGs. Our analysis focuses primarily on the emission line gas which is extensive in both systems and is a result of the abundant ongoing star formation as well as widespread LINER-like excitation from shocks. We use emission-line ratio maps, line kinematics, line-ratio diagnostics and new models as methods for distinguishing and analyzing shocked gas in these systems. We discuss how our results inform the merger sequence associated with local U/LIRGs and the impact that widespread shock excitation has on the interpretation of emission-line spectra and derived quantities of both local and high-redshift galaxies.Comment: 14 pages, 11 figures, Accepted to Ap

    Radio Frequency Interference Mitigation

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    Radio astronomy observational facilities are under constant upgradation and development to achieve better capabilities including increasing the time and frequency resolutions of the recorded data, and increasing the receiving and recording bandwidth. As only a limited spectrum resource has been allocated to radio astronomy by the International Telecommunication Union, this results in the radio observational instrumentation being inevitably exposed to undesirable radio frequency interference (RFI) signals which originate mainly from terrestrial human activity and are becoming stronger with time. RFIs degrade the quality of astronomical data and even lead to data loss. The impact of RFIs on scientific outcome is becoming progressively difficult to manage. In this article, we motivate the requirement for RFI mitigation, and review the RFI characteristics, mitigation techniques and strategies. Mitigation strategies adopted at some representative observatories, telescopes and arrays are also introduced. We also discuss and present advantages and shortcomings of the four classes of RFI mitigation strategies, applicable at the connected causal stages: preventive, pre-detection, pre-correlation and post-correlation. The proper identification and flagging of RFI is key to the reduction of data loss and improvement in data quality, and is also the ultimate goal of developing RFI mitigation techniques. This can be achieved through a strategy involving a combination of the discussed techniques in stages. Recent advances in high speed digital signal processing and high performance computing allow for performing RFI excision of large data volumes generated from large telescopes or arrays in both real time and offline modes, aiding the proposed strategy.Comment: 26 pages, 10 figures, Chinese version accepted for publication in Acta Astronomica Sinica; English version to appear in Chinese Astronomy and Astrophysic

    Obscuration in AGNs: near-infrared luminosity relations and dust colors

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    We combine two approaches to isolate the AGN luminosity at near-infrared wavelengths and relate the near-IR pure AGN luminosity to other tracers of the AGN. Using integral-field spectroscopic data of an archival sample of 51 local AGNs, we estimate the fraction of non-stellar light by comparing the nuclear equivalent width of the stellar 2.3 micron CO absorption feature with the intrinsic value for each galaxy. We compare this fraction to that derived from a spectral decomposition of the integrated light in the central arc second and find them to be consistent with each other. Using our estimates of the near-IR AGN light, we find a strong correlation with presumably isotropic AGN tracers. We show that a significant offset exists between type 1 and type 2 sources in the sense that type 1 sources are 7 (10) times brighter in the near-IR at log L_MIR = 42.5 (log L_X = 42.5). These offsets only becomes clear when treating infrared type 1 sources as type 1 AGNs. All AGNs have very red near-to-mid-IR dust colors. This, as well as the range of observed near-IR temperatures, can be explained with a simple model with only two free parameters: the obscuration to the hot dust and the ratio between the warm and hot dust areas. We find obscurations of A_V (hot) = 5 - 15 mag for infrared type 1 sources and A_V (hot) = 15 - 35 mag for type 2 sources. The ratio of hot dust to warm dust areas of about 1000 is nicely consistent with the ratio of radii of the respective regions as found by infrared interferometry.Comment: 17 pages, 10 Figures, 3 Tables, accepted by A&

    The Shape of LITTLE THINGS Dwarf Galaxies DDO 46 and DDO 168: Understanding the stellar and gas kinematics

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    We present the stellar and gas kinematics of DDO 46 and DDO 168 from the LITTLE THINGS survey and determine their respective Vmax/sigma_z,0 values. We used the KPNO's 4-meter telescope with the Echelle spectrograph as a long-slit spectrograph. We acquired spectra of DDO 168 along four position angles by placing the slit over the morphological major and minor axes and two intermediate position angles. However, due to poor weather conditions during our observing run for DDO 46, we were able to extract only one useful data point from the morphological major axis. We determined a central stellar velocity dispersion perpendicular to the disk, sigma_z,0, of 13.5+/-8 km/s for DDO 46 and of 10.7+/-2.9 km/s for DDO 168. We then derived the maximum rotation speed in both galaxies using the LITTLE THINGS HI data. We separated bulk motions from non-circular motions using a double Gaussian decomposition technique and applied a tilted-ring model to the bulk velocity field. We corrected the observed HI rotation speeds for asymmetric drift and found a maximum velocity, Vmax, of 77.4 +/- 3.7 and 67.4 +/- 4.0 km/s for DDO 46 and DDO 168, respectively. Thus, we derived a kinematic measure, Vmax/sigma_z,0, of 5.7 +/- 0.6 for DDO 46 and 6.3 +/- 0.3 for DDO 168. Comparing these values to ones determined for spiral galaxies, we find that DDO 46 and DDO 168 have Vmax/sigma_z,0 values indicative of thin disks, which is in contrast to minor-to-major axis ratio studies

    Deep learning denoising by dimension reduction: Application to the ORION-B line cubes

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    Context. The availability of large bandwidth receivers for millimeter radio telescopes allows the acquisition of position-position-frequency data cubes over a wide field of view and a broad frequency coverage. These cubes contain much information on the physical, chemical, and kinematical properties of the emitting gas. However, their large size coupled with inhomogenous signal-to-noise ratio (SNR) are major challenges for consistent analysis and interpretation.Aims. We search for a denoising method of the low SNR regions of the studied data cubes that would allow to recover the low SNR emission without distorting the signals with high SNR.Methods. We perform an in-depth data analysis of the 13 CO and C 17 O (1 -- 0) data cubes obtained as part of the ORION-B large program performed at the IRAM 30m telescope. We analyse the statistical properties of the noise and the evolution of the correlation of the signal in a given frequency channel with that of the adjacent channels. This allows us to propose significant improvements of typical autoassociative neural networks, often used to denoise hyperspectral Earth remote sensing data. Applying this method to the 13 CO (1 -- 0) cube, we compare the denoised data with those derived with the multiple Gaussian fitting algorithm ROHSA, considered as the state of the art procedure for data line cubes.Results. The nature of astronomical spectral data cubes is distinct from that of the hyperspectral data usually studied in the Earth remote sensing literature because the observed intensities become statistically independent beyond a short channel separation. This lack of redundancy in data has led us to adapt the method, notably by taking into account the sparsity of the signal along the spectral axis. The application of the proposed algorithm leads to an increase of the SNR in voxels with weak signal, while preserving the spectral shape of the data in high SNR voxels.Conclusions. The proposed algorithm that combines a detailed analysis of the noise statistics with an innovative autoencoder architecture is a promising path to denoise radio-astronomy line data cubes. In the future, exploring whether a better use of the spatial correlations of the noise may further improve the denoising performances seems a promising avenue. In addition
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