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<ri:Resource created="2023-01-26T14:31:43Z" status="active" updated="2025-06-13T15:25:00Z" version="1.2" xmlns:cs="http://www.ivoa.net/xml/ConeSearch/v1.0" xmlns:ri="http://www.ivoa.net/xml/RegistryInterface/v1.0" xmlns:vr="http://www.ivoa.net/xml/VOResource/v1.0" xmlns:vs="http://www.ivoa.net/xml/VODataService/v1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.ivoa.net/xml/ConeSearch/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/ConeSearch.xsd http://www.ivoa.net/xml/VOResource/v1.0 http://vo.ari.uni-heidelberg.de/docs/schemata/VOResource.xsd http://www.ivoa.net/xml/VODataService/v1.1 http://vo.ari.uni-heidelberg.de/docs/schemata/VODataService.xsd" xsi:type="vs:CatalogService"><title>Galactic pulsar with proper motions</title><shortName>J/ApJ/916/100</shortName><identifier>ivo://CDS.VizieR/J/ApJ/916/100</identifier><altIdentifier>doi:10.26093/cds/vizier.19160100</altIdentifier><curation><publisher ivo-id="ivo://CDS">CDS</publisher><creator><name>Ronchi M.</name></creator><creator><name>Graber V.</name></creator><creator><name>Garcia-Garcia A.</name></creator><creator><name>Rea N.</name></creator><creator><name>Pons J.A.</name></creator><date role="Updated">2023-02-15T07:46:27Z</date><date role="Created">2023-01-26T14:31:43Z</date><contact><name>CDS support team</name><address>CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France</address><email>cds-question@unistra.fr</email></contact></curation><content><subject>pulsars</subject><subject>proper-motions</subject><subject>stellar-distance</subject><subject>neutron-stars</subject><subject>visible-astronomy</subject><subject>trigonometric-parallax</subject><description>We explore the possibility of inferring the properties of the Galactic population of neutron stars through machine learning. In particular, in this paper we focus on their dynamical characteristics and show that an artificial neural network is able to estimate with high accuracy the parameters that control the current positions of a mock population of pulsars. For this purpose, we implement a simplified population-synthesis framework (where selection biases are neglected at this stage) and concentrate on the natal kick-velocity distribution and the distribution of birth distances from the Galactic plane. By varying these and evolving the pulsar trajectories in time, we generate a series of simulations that are used to train and validate a suitably structured convolutional neural network. We demonstrate that our network is able to recover the parameters governing the distribution of kick velocity and Galactic height with a mean relative error of about 10^-2^. We discuss the limitations of our idealized approach and study a toy problem to introduce selection effects in a phenomenological way by incorporating the observed proper motions of 216 isolated pulsars. Our analysis highlights that by increasing the sample of pulsars with accurate proper-motion measurements by a factor of ~10, one of the future breakthroughs of the Square Kilometre Array, we might succeed in constraining the birth spatial and kick-velocity distribution of the neutron stars in the Milky Way with high precision through machine learning.</description><source format="bibcode">2021ApJ...916..100R</source><referenceURL>https://cdsarc.cds.unistra.fr/viz-bin/cat/J/ApJ/916/100</referenceURL><type>Catalog</type><contentLevel>Research</contentLevel><relationship><relationshipType>IsServedBy</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/TAP">TAP VizieR generic service</relatedResource></relationship><relationship><relationshipType>IsServedBy</relationshipType><relatedResource>Conesearch service</relatedResource></relationship><relationship><relationshipType>related-to</relationshipType><relatedResource ivo-id="ivo://CDS.VizieR/B/psr">B/psr : ATNF Pulsar Catalogue (Manchester+, 2005)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/328/17">J/MNRAS/328/17 : Parkes Multi-Beam Pulsar Survey (Manchester+, 2001)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/353/1311">J/MNRAS/353/1311 : Long-term timing obs. of 374 pulsars (Hobbs+, 2004)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/360/974">J/MNRAS/360/974 : Proper motionsof pulsars (Hobbs+, 2005)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/MNRAS/372/777">J/MNRAS/372/777 : Parkes Multibeam Pulsar Survey. 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(Lorimer+, 2006)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/ApJ/885/131">J/ApJ/885/131 : ~200 high-mass SFR plx &amp; PM with VLBI (Reid+, 2019)</relatedResource><relatedResource ivo-id="ivo://CDS.VizieR/J/other/Sci/365.478">J/other/Sci/365.478 : Milky Way classical Cepheids sample (Skowron+, 2019)</relatedResource><relatedResource>http://www.atnf.csiro.au/research/pulsar/psrcat/ : Online ATNF catalog</relatedResource></relationship></content><rights>https://cds.unistra.fr/vizier-org/licences_vizier.html</rights><capability><interface xsi:type="vr:WebBrowser"><accessURL use="full">https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/ApJ/916/100</accessURL><mirrorURL title="VizieR at IUCAA: Pune, India">https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/ApJ/916/100</mirrorURL><mirrorURL title="VizieR at SAAO: SAAO, South Africa">http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/ApJ/916/100</mirrorURL></interface></capability><capability><interface 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