J/ApJ/899/15ivo://CDS.VizieR/J/ApJ/899/15doi:10.26093/cds/vizier.18990015CDSMurray C.E.Peek J.E.G.Kim C.-G.2023-06-16T15:37:35Z2021-11-09T10:33:57ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frinterstellar-mediumh-i-line-emissiongalaxiesradio-spectroscopyResolving the phase structure of neutral hydrogen (HI) is crucial for understanding the life cycle of the interstellar medium (ISM). However, accurate measurements of HI temperature and density are limited by the availability of background continuum sources for measuring HI absorption. Here we test the use of deep learning for extracting HI properties over large areas without optical depth information. We train a 1D convolutional neural network using synthetic observations of 3D numerical simulations of the ISM to predict the fraction (f_CNM_) of cold neutral medium (CNM) and the correction to the optically thin HI column density for optical depth (R_H_I__) from 21cm emission alone. We restrict our analysis to high Galactic latitudes (|b|>30{deg}), where the complexity of spectral line profiles is minimized. We verify that the network accurately predicts f_CNM_ and R_H_I__ by comparing the results with direct constraints from 21cm absorption. By applying the network to the GALFA-HI survey, we generate large-area maps of f_CNM_ and R_H_I__. Although the overall contribution to the total HI column of CNM-rich structures is small (~5%), we find that these structures are ubiquitous. Our results are consistent with the picture that small-scale structures observed in 21cm emission aligned with the magnetic field are dominated by CNM. Finally, we demonstrate that the observed correlation between HI column density and dust reddening (E(B-V)) declines with increasing R_H_I__, indicating that future efforts to quantify foreground Galactic E(B-V) using HI, even at high latitudes, should increase fidelity by accounting for HI phase structure.2020ApJ...899...15Mhttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/899/15CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/ApJS/145/329 : Millennium Arecibo 21-cm Survey (Heiles+, 2003)J/ApJ/793/132 : Perseus cloud sources Gaussian parameters (Stanimirovic+,2014)J/A+A/594/A116 : HI4PI spectra and column density maps (HI4PI team+, 2016)J/ApJS/234/2 : The GALFA-HI survey data release 2 (Peek+, 2018)J/A+A/633/A14 : GaussPy+ decomposition of Galactic Ring Survey (Riener+, 2020)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/899/15https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/899/15http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/899/15https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/ApJ/899/15https://vizier.iucaa.in/viz-bin/votable?-source=J/ApJ/899/15http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/ApJ/899/15GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/ApJ/899/15/tabled1 (Parameters for the 58 {tau}HI(v) sightlines used for verifying the CNN model)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/ApJ/899/15/tabled1?https://vizier.iucaa.in/viz-bin/conesearch/J/ApJ/899/15/tabled1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/ApJ/899/15/tabled1?GETtext/xml+votable180.050000true10.20610.0640.0055555555555555566/18 50 64 162 245 392 556 4285 4366 4377 5284 5311 8264 8812 8989 9009 9347 9442 10288 10355 10432 10440 18365 18895 19177 19398 19543 20099 20111 23167 23281 23469 26100 26292 26415 26491 27060 27514 27532 27767 27851 28063 28185 28249 28279 28315 31346 31423 32394https://cdsarc.cds.unistra.fr/viz-bin/moc/J/ApJ/899/15?format=asciiRadiodefaultJ/ApJ/899/15/tabled1Parameters for the 58 {tau}HI(v) sightlines used for verifying the CNN modelSimbadNameSimbad column added by the CDSmeta.idcharnullablerecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSourceSource namemeta.id;meta.maincharRef[1/2] Reference (1)meta.ref;pos.frameintRAJ2000[10.2/350] Right Ascension (J2000)degpos.eq.ra;meta.mainDEJ2000[1.29/35] Declination (J2000)degpos.eq.dec;meta.mainNHI-thin[0.84/12] HI column density in the optically-thin limit, Equation 41e+20cm**-2phys.columnDensityfloate_NHI-thin[0.04/0.8] Uncertainty in NHI-thin1e+20cm**-2phys.columnDensityfloatNHI-iso[0.84/15] Total HI column density, Equation 31e+20cm**-2phys.columnDensityfloate_NHI-iso[0.04/0.7] Uncertainty in NHI-iso1e+20cm**-2phys.columnDensityfloatfCNM[0/0.77] Fraction of Cold Neutral Medium observed, Equation 8stat.fit.paramfloate_fCNM[0/0.3] Uncertainty in fCNMstat.errorfloatfCNM-CNN[0.01/0.33] Fraction of Cold Neutral Medium predicted by the CNNstat.fit.paramfloate_fCNM-CNN[0.01/0.1] Uncertainty in fCNM-CNNstat.errorfloatRHI[1/1.56] Column Density Correction Factor, Equation 5phys.columnDensityfloate_RHI[0/0.01] Uncertainty in RHIphys.columnDensityfloatRHI-CNN[1/1.2] Column Density Correction Factor predicted by the CNNphys.columnDensityfloate_RHI-CNN[0.02/0.07] Uncertainty in RHI-CNNphys.columnDensityfloat