J/MNRAS/464/3796ivo://CDS.VizieR/J/MNRAS/464/3796doi:10.26093/cds/vizier.74643796CDSTeimoorinia H.Ellison S.L.Patton D.R.2024-08-16T20:19:34Z2018-08-29T13:29:08ZCDS support team

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

cds-question@unistra.frgalaxiescatalogsh-i-line-emissionThe application of artificial neural networks (ANNs) for the estimation of HI gas mass fraction (M_HI_/M*) is investigated, based on a sample of 13 674 galaxies in the Sloan Digital Sky Survey (SDSS) with HI detections or upper limits from the Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA). We show that, for an example set of fixed input parameters (g-r colour and i-band surface brightness), a multidimensional quadratic model yields M_HI_/M* scaling relations with a smaller scatter (0.22dex) than traditional linear fits (0.32dex), demonstrating that non-linear methods can lead to an improved performance over traditional approaches. A more extensive ANN analysis is performed using 15 galaxy parameters that capture variation in stellar mass, internal structure, environment and star formation. Of the 15 parameters investigated, we find that g-r colour, followed by stellar mass surface density, bulge fraction and specific star formation rate have the best connection with M_HI_/M*. By combining two control parameters, that indicate how well a given galaxy in SDSS is represented by the ALFALFA training set (PR) and the scatter in the training procedure ({sigma}_fit_), we develop a strategy for quantifying which SDSS galaxies our ANN can be adequately applied to, and the associated errors in the M_HI_/M* estimation. In contrast to previous works, our M_HI_/M* estimation has no systematic trend with galactic parameters such as M*, g-r and star formation rate. We present a catalogue of M_HI_/M* estimates for more than half a million galaxies in the SDSS, of which ~150000 galaxies have a secure selection parameter with average scatter in the M_HI_/M* estimation of 0.22dex.2017MNRAS.464.3796Thttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/464/3796CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-toJ/AJ/133/2569 : Arecibo legacy fast ALFA survey III. (Giovanelli+, 2007)J/MNRAS/436/34 : GALEX Arecibo SDSS survey final data release (Catinella+ 2013)https://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/MNRAS/464/3796https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/MNRAS/464/3796http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/MNRAS/464/3796https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/MNRAS/464/3796https://vizier.iucaa.in/viz-bin/votable?-source=J/MNRAS/464/3796http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/MNRAS/464/3796GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/MNRAS/464/3796/table2 (Catalogue of ANN estimated MHI/M* along with all the control parameters described in this paper)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/MNRAS/464/3796/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/MNRAS/464/3796/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/MNRAS/464/3796/table2?GETtext/xml+votable180.050000true224.236249928.144174430.0055555555555555561/8 10 27 2/16 19 21-23 103 107 3/68-70 72-73 75 80-81 83 100 102-103 112 114 116 144 146-147 152-153 155 176 178 184 407 409-411 421 423 427 494 4/284-285 287 297 299 328 330-331 389-391 399 404-405 407 452 454-455 460-462 468-469 472 580 582-583 592 594 600 602 616-617 619 624 708 710-711 716 718 740 744-746 1373 1375 1621-1623 1625-1627 1691 1703 1707 1961-1963 1965-1967 1980 1982-1983 2027 5/136 138 1144-1146 1184-1185 1187 1193 1317-1319 1540-1541 1549 1552-1553 1555 1585 1588-1589 1624-1626 1685 1728-1729 1732-1733 1812 1814-1815 1852 1880-1882 1884 1896-1898 1900-1901 2325 2327 2472-2473 2475 2504-2506 2515 2518 2521 2523-2524 2526 2528 2530 2536 2545 2547-2548 2550 2553 2556 2837 2839 2868 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19116-19118 19120-19122 19136-19138 19144 19200-19202 19319 19322-19323 19359 19371 19373-19375 19378-19379 19397-19399 19420 19428-19430 19432-19434 19440 19456-19458 19582-19583 19645-19647 19661-19663 19665-19667 19681-19683 19700 19704 19725-19727 19729-19731 19747 19764 19768 19780 19784 19844 19848 19979 19985-19987 20012-20014 20016-20018 20036 20040 20096-20097 21843 21848-21849 21883 21959 21963 21991 21997 21999 22341 22360-22361 22363 22385 22485 22487 22710-22711 22713-22715 22760 22762-22763 23043 23064-23066 23068 23076-23077 23080 23095 23101-23104 23138 23150 23185-23187 23192-23193 23195-23198 23201-23204 23206-23207 23212-23214 23232-23234 23236 25559 25575 25579 25585-25587 25821-25823 25835 25837-25839 25841-25843 25885-25887 25901-25903 25905-25907 25922-25923 25985-25987 26135 26139 26151 26155 26157-26159 26161-26163 26877-26879 26903 26909-26911 26933 26941-26943 27021-27023 27025-27027 27041-27043 27197-27199 27213-27215 27217-27219 27233-27235 27277-27279 27281-27283 27297-27299 29973 30016 30044-30046 30053 31286 31289-31291 31330-31331 31340 31342 31357-31359 31363 31429-31431 31548 31550-31551 31594 31598-31599 31611 31710 32391 32402-32403 32406-32407 32425-32427 32460 32462 32478 32484 32486 32492 32494-32495 32497 32499 32505 32672 32674 32678 32684 32686 36607 36702-36703 36715 36721-36723 36732-36734 36758-36759 36761-36763 36771 36773-36775 36788-36790 36792-36794 36796 36812 36816-36818 36832 36861-36863 40957 40959 45023 45039 45043 48983 48987 49005-49007 49010-49011 49020 49022 49055 49077-49079 49081 49091 49108 49112 49114 49124-49126 49147https://cdsarc.cds.unistra.fr/viz-bin/moc/J/MNRAS/464/3796?format=asciiRadiodefaultJ/MNRAS/464/3796/table2Catalogue of ANN estimated MHI/M* along with all the control parameters described in this paperrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSDSSSDSS identification numbermeta.id;meta.maincharRAJ2000SDSS right ascension (J2000)degpos.eq.ra;meta.mainindexedDEJ2000SDSS declination (J2000)degpos.eq.dec;meta.mainindexedzSDSS redshiftsrc.redshiftdoublelogM*Stellar masslog(solMass)phys.massfloatlogMHI/M*Ratio of HI-to-stellar massphys.mass;arith.ratiodoubleCfgasConfidence of the MHI/M* estimation (C_fgas_) (1)stat.fit.goodnessdoublePR[0/1] Pattern recognition detection metricstat.fit.goodnessdoublesigmafitN[0/1] Inverse normalized uncertainty on the ANN estimationstat.errordoublesigmafit[0/4.5] Uncertainty on the ANN estimationstat.errordoublesigmafgas[0/1] Uncertainty on the MHI/M* estimationstat.errordoubleSloanDisplay the SDSS data for this objectmeta.ref.urlchar