J/A+A/671/A63ivo://CDS.VizieR/J/A+A/671/A63doi:10.26093/cds/vizier.36710063CDSGu C.Heidrich-Meisner V.Wimmer-Schweingruber R.F.Yao S.2024-11-28T20:02:39Z2023-03-06T08:29:14ZCDS support team

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

cds-question@unistra.frthe-sunastronomical-modelsCoronal Mass Ejections (CMEs) are extremely dynamical large scale events. If a CME is detected in-situ by a spacecraft located in the interplanetary medium, it is then called an Interplanetary Coronal Mass Ejection (ICME). Charge states of heavy ions reflect important information about the coronal temperature profile due to the freeze-in effect and it is estimated that Iron ions freeze in at the heights of ~5 solar radii. To identify different populations of Iron charge state composition of ICMEs and determine their sources,we developed a model which independently uses two, three, and four populations of Iron ions to fit the measured charge state distribution in ICMEs detected by the Advanced Composition Explorer (ACE) at 1AU. Three parameters are used to identify a certain population, i.e., freeze-in temperature, relative abundance and kappa value which together describe the potential non-Maxwellian kappa-distributions of coronal electrons. Our method chooses the reduced chi-squared to describe the goodness of fit of the model to the observations.The parameters of our model are optimized with the Covariance Matrix Adaptation Evolution Strategy(CMA-ES). Two major types of ICMEs are identified according to the existence of hot material,and both cool type and hot type have two main sub-types. Different populations in those types have their own features related to freeze-in temperature and kappa.The electron velocity distribution function usually contains a significant hot tail in typical coronal material and hot material while Maxwellian distribution appears more frequently in mid-temperature material.2023A&A...671A..63Ghttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/671/A63CatalogResearchIsServedByTAP VizieR generic servicehttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/671/A63https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/671/A63http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/671/A63https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/671/A63https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/671/A63http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/671/A63GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapdefaultJ/A+A/671/A63/tablea1Model results of the 310 ICMEsrecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintNumber[1/310] Case numbermeta.idintStartTimeICME plasma/field start timestime.epochnullablelogT1Temperature 1log(K)phys.temperaturefloatlogT2Temperature 2log(K)phys.temperaturefloatlogT3? Temperature 3log(K)phys.temperaturefloatnullablelogT4? Temperature 4log(K)phys.temperaturefloatnullableRA1Relative abundance 1phys.abundRA2Relative abundance 2phys.abundRA3? Relative abundance 3phys.abundnullableRA4? Relative abundance 4phys.abundnullablek1Kappa value 1stat.fit.paramfloatk2Kappa value 2stat.fit.paramfloatk3? Kappa value 3stat.fit.paramfloatnullablek4? Kappa value 4stat.fit.paramfloatnullablechi2Reduced chi squarestat.fit.chi2float