Open cluster parameters with ANN J/AJ/167/12 ivo://CDS.VizieR/J/AJ/167/12 doi:10.26093/cds/vizier/be-57-c CDS Cavallo L. Spina L. Carraro G. Magrini L. Poggio E. Cantat-Gaudin T.,Pasquato M. Lucatello S. Ortolani S. Schiappacasse-Ulloa J. 2026-07-02T11:44:43Z 2023-12-07T13:03:40Z CDS support team CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France cds-question@unistra.fr milky-way-galaxy open-star-clusters astrometry astronomical-models With the unprecedented increase of known star clusters, quick and modern tools are needed for their analysis. In this work, we develop an artificial neural network trained on synthetic clusters to estimate the age, metallicity, extinction, and distance of Gaia open clusters. We implement a novel technique to extract features from the colour-magnitude diagram of clusters by means of the QuadTree tool and we adopt a multi-band approach. We obtain reliable parameters for ~5400 clusters. We demonstrate the effectiveness of our methodology in accurately determining crucial parameters of Gaia open clusters by performing a comprehensive scientific validation. In particular, with our analysis we have been able to reproduce the Galactic metallicity gradient as it is observed by high-resolution spectroscopic surveys. This demonstrates that our method reliably extracts information on metallicity from colour-magnitude diagrams (CMDs) of stellar clusters. For the sample of clusters studied, we find an intriguing systematic older age compared to previous analyses present in the literature. This work introduces a novel approach to feature extraction using a QuadTree algorithm, effectively tracing sequences in CMDs despite photometric errors and outliers. The adoption of ANNs, rather than Convolutional Neural Networks, maintains the full positional information and improves performance, while also demonstrating the potential for deriving clusters' parameters from simultaneous analysis of multiple photometric bands, beneficial for upcoming telescopes like the Vera Rubin Observatory. The implementation of ANN tools with robust isochrone fit techniques could provide further improvements in the quest for open clusters' parameters. 2024AJ....167...12C https://cdsarc.cds.unistra.fr/viz-bin/cat/J/AJ/167/12 Catalog Research IsServedBy TAP VizieR generic service IsServedBy Conesearch service related-to J/A+A/673/A114 : Improving the open cluster census. II. (Hunt+, 2023) https://cds.unistra.fr/vizier-org/licences_vizier.html https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/AJ/167/12 https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/AJ/167/12 http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/AJ/167/12 https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/AJ/167/12 https://vizier.iucaa.in/viz-bin/votable?-source=J/AJ/167/12 http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/AJ/167/12 GET text/xml+votable https://tapvizier.cds.unistra.fr/TAPVizieR/tap Cone search capability for table J/AJ/167/12/catalog (Clusters analysed by our ANNs (update version, 18/10/2024)) https://vizier.cds.unistra.fr/viz-bin/conesearch/J/AJ/167/12/catalog? https://vizier.iucaa.in/viz-bin/conesearch/J/AJ/167/12/catalog? http://vizieridia.saao.ac.za/viz-bin/conesearch/J/AJ/167/12/catalog? GET text/xml+votable 180.0 50000 true 249.8571817326409 -28.391465066157 0.005555555555555556 4/1388 2357 2487 5/324 347 353 358 445 447 450 456 482 756 759-761 763-766 814-815 820 826-827 830 840 899 901-903 905 909 928 930 932 935-936 3246 3515 3518 3559 3563 3565 3567 3571 3574-3576 3578 3580 3582 3588-3590 3600 3603 3606-3607 3612-3613 3650-3651 3656-3657 3661 3666-3667 3672 3674 3677-3679 3683 3841 3843-3844 3846-3849 3857 3859 3863 3905 3913 3920 5204-5205 5237 5377-5379 5382 5384 5387 5390 5408 5410-5412 5414 5417 5420-5421 5509 5511 5530 5540 5561 5563 5905 5941 5984 5987 5995-5996 6081 6091-6094 6113 6121 6125 6136 7179 7201-7202 7207 7218 7222 7225 7228-7229 7273 7277 7291 7365 7377 7380-7381 7555 7558 7560-7561 7564 7567 7672 7677 9333 9335 9337 9341-9342 9433-9434 9436 9462 9465-9468 9470 9473 9475-9476 9481-9484 9504-9505 9512 9634 9809 9811 9817-9819 9831 9843-9844 9847 9849 9851-9852 9937-9940 9942 9944-9945 9970 9972-9973 10152 10154-10155 10398-10399 10405 10412-10413 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41795 41800-41802 41804-41805 41807 41812-41814 41816-41817 41823 41825 41827 41829-41831 41833-41834 41836 41841 41846-41848 41852 41856-41858 41860-41861 41863-41864 41873-41874 41878 41880 41893 41922 41928 41932 41944 41995 42026 42029 42046 42076 42095 42111 42127 42135 42141-42143 42145 42150-42151 42161-42163 42172-42174 42176-42177 42190 42192 42195 42197 42201-42203 42212-42214 42221 42228-42230 42232-42234 42238-42239 42249 42268 42274 42278 42286 42290 42300 42303 42314 42320 42328 42331-42332 42334-42336 42340 42342-42343 42346-42347 42351 42353 42356 42364-42365 42367 42369-42370 42372 42374 42381-42383 42389-42392 42394-42395 42400 42402 42405 42407 42415-42417 42420-42421 42427 42441-42443 42447 42456 42458 42468-42470 42472 42478 42481 42483-42484 42486-42487 42493 42496-42497 42499 42505 42512-42513 42516 42519 42522 42528 42548 42555 42565-42566 42570 42581 42583 42589 42598 42600 42610 42614 42619 42656 42685-42686 42697 42700 42761 42770 42789 42798 42836 42841 42846 42850 42862 42864 42944 42955-42956 42958 42964 42979 42983 42990 43002 43009 43011 43020-43022 43036 43038 43044 43046-43047 43052-43053 43055 43057 43059 43062 43064 43066 43073 43079 43088 43094 43104-43105 43125 43136-43137 43140 43146 43148 43153 43191 43193 43218 43227 43282 43295 43301 43401 43444 43450 43461 44086 44109 44220 44310 44361 44378 44389 44427 44511 45000 45115 45307 45515 45602 45742 46857 47125 47145 47164 47620 47723 47729 47777 47784 47788 47805 47825 47834 47866 47868 47903 47916 47935 47967 47971 48035 48063 48104 48434 48444 48532 48698 48952 48993 49099 49115 https://cdsarc.cds.unistra.fr/viz-bin/moc/J/AJ/167/12?format=ascii default J/AJ/167/12/catalog Clusters analysed by our ANNs (update version, 18/10/2024) recno Record number assigned by the VizieR team. Should Not be used for identification. meta.record int Cluster Cluster name meta.id;meta.main char RA_ICRS Mean right ascension (ICRS) at Ep=2016.0 of cluster's members deg pos.eq.ra;meta.main DE_ICRS Mean declination (ICRS) at Ep=2016.0) of cluster's members deg pos.eq.dec;meta.main kind [omg] Type of object from Hunt & Reffert (2023A&A...673A.114H, Cat. J/A+A/673/A114) (1) src.class char plx Mean parallax of cluster's members mas pos.parallax;stat.mean float e_plx Error on the parallax mas stat.error;pos.parallax float CMDclass [0/1] 50th percentile of CMD class from Hunt & Reffert (2023A&A...673A.114H, Cat. J/A+A/673/A114) meta.code float Quality [0/3] Quality of the predictions (2) meta.code.qual int logAge16 16th percentile of logAge predictions of the ANNs log(yr) time.age float logAge50 50th percentile of logAge predictions of the ANNs log(yr) time.age float logAge84 84th percentile of logAge predictions of the ANNs log(yr) time.age float [Fe/H]16 16th percentile of [Fe/H] predictions of the ANNs phys.abund.Fe float [Fe/H]50 50th percentile of [Fe/H] predictions of the ANNs phys.abund.Fe float [Fe/H]84 84th percentile of [Fe/H] predictions of the ANNs phys.abund.Fe float AV16 16th percentile of V-band extinction predictions of the ANNs mag phys.absorption float AV50 50th percentile of V-band extinction predictions of the ANNs mag phys.absorption float AV84 84th percentile of V-band extinction predictions of the ANNs mag phys.absorption float dMod16 16th percentile of distance module predictions of the ANNs mag phot.mag.distMod float dMod50 50th percentile of distance module predictions of the ANNs mag phot.mag.distMod float dMod84 84th percentile of distance module predictions of the ANNs mag phot.mag.distMod float X X coordinate in galactocentric galactic coordinates (as predicted by the ANNs) kpc pos.cartesian.x;pos.galactic;pos.galactocentric double Y Y coordinate in galactocentric galactic coordinates (as predicted by the ANNs) kpc pos.cartesian.y;pos.galactic;pos.galactocentric double Z Z coordinate in galactocentric galactic coordinates (as predicted by the ANNs) kpc pos.cartesian.z;pos.galactocentric;pos.galactic double Rgc Distance from Galactic centre (as predicted by the ANNs and assuming Sun Rgc=8.122kpc) kpc pos.distance float