J/A+A/693/A318ivo://CDS.VizieR/J/A+A/693/A318doi:10.26093/cds/vizier.36930318CDSKankkunen S.Tornikoski M.Hovatta T.Lahteenmaki A.2025-08-01T20:03:05Z2025-07-23T11:19:41ZCDS support team

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

cds-question@unistra.fractive-galactic-nucleiquasarsradio-sourcesWe present the results of analysing the long-term radio variability of active galactic nuclei at 37GHz using data of 123 sources observed in the Aalto University Metsahovi Radio Observatory. Our aim was to constrain the characteristic timescales of the studied sources and to analyse whether up to 42 years of monitoring was enough to describe their variability behaviour. We used a periodogram to estimate the power spectral density of each source. The power spectral density is used to analyse the power content of a time series in the frequency domain, and it is a powerful tool in describing the variability of active galactic nuclei. We were interested in finding a bend frequency in the power spectrum, that is, a frequency at which the slope {beta} of the spectrum changes from a non-zero value to zero. We fitted two models to the periodograms of each source, namely the bending power law and the simple power law. The bend frequency in the bending power law corresponds to a characteristic timescale. We were able to constrain a timescale for 11 out of 123 sources, with an average characteristic timescale xb=1300 days and an average power-law slope {beta}=2.3. The results suggest that up to 42 years of observations may not always be enough for obtaining a characteristic timescale in the radio domain. This is likely caused by a combination of both slow variability as well as sampling-induced effects. We also compared the obtained timescales to 43GHz very long baseline interferometry images. The maximum length of time a knot was visible was often close to the obtained characteristic timescale. This suggests a connection between the characteristic timescale and the jet structure.2025A&A...693A.318Khttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/693/A318CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicehttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/693/A318https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/A+A/693/A318http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/A+A/693/A318https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/A+A/693/A318https://vizier.iucaa.in/viz-bin/votable?-source=J/A+A/693/A318http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/A+A/693/A318GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/A+A/693/A318/tablea1 (*Results from the bending power-law fit (Eq. 4), simple power-law fit (Eq. 3), and bending power-law fit using {beta}_high_={beta}_bpl,best_ (Eq. 6))https://vizier.cds.unistra.fr/viz-bin/conesearch/J/A+A/693/A318/tablea1?https://vizier.iucaa.in/viz-bin/conesearch/J/A+A/693/A318/tablea1?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/A+A/693/A318/tablea1?GETtext/xml+votable180.050000true1.5578869-6.39314860.0055555555555555566/110 532 556 579 700 911 1263 1546 1701 1782 2331 2397 2414 2836 3024 3096 3675 3820 3886 4572 4695 4770 4820 5423 5597 5693 5767 5806 5817 6507 6641 6853 7181 7426 7570 7896 7969 8299 8487 8717 9442 9460 9612 9632-9633 9723 10163 10249 10422 11430 11715 12352 12580 12619 12896 13410 13496 13693 13927 14520 14737 14842 15067 15286 15494 15936 16059 16093 16281 16298 16301 17351 17579 18035 18624 18661 18669 19088 19101 19190 19370 19398 19567 19609 19831 20099 21358 21758 21768 21935 21968 21972 22363 22396 22917 22950 23099 23121 23127 23323 23416 24084 24123 24571 25630 25864 26131 26292 27060 27417 28083 28339 28479 28492 29570 29675 31190 31430 31664 31894 36785 44908 49071https://cdsarc.cds.unistra.fr/viz-bin/moc/J/A+A/693/A318?format=asciiRadiodefaultJ/A+A/693/A318/tablea1*Results from the bending power-law fit (Eq. 4), simple power-law fit (Eq. 3), and bending power-law fit using {beta}_high_={beta}_bpl,best_ (Eq. 6)recnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintSourceSource namemeta.id;meta.maincharONameOther namemeta.idcharNTotal number of data points in the light curvemeta.numberintTypeType of objectsrc.classcharbetabpl? Best-fit bending power-law slope {beta}_bpl_ (1)meta.crypticfloatnullablee_betabpl? Best-fit bending power-law slope {beta}_bpl_ error (lower value)stat.errorfloatnullableE_betabpl? Best-fit bending power-law slope {beta}_bpl_ error (upper value)stat.error;stat.maxfloatnullablexb? Best-fit bending power-law bend timescale (1)time.scale;meta.modelledintnullablee_xb? Best-fit bending power-law bend timescale error (lower value)stat.errorintnullableE_xb? Best-fit bending power-law bend timescale error (upper value)stat.error;stat.maxintnullablepbpl? Best-fit bending power-law slope p-value (1)stat.fit.goodnessfloatnullablebetaspl? Best-fit simple power-law slopemeta.crypticfloatnullablee_betaspl? Best-fit simple power-law slope error (lower value)stat.errorfloatnullableE_betaspl? Best-fit simple power-law slope error (upper value)stat.error;stat.maxfloatnullablepspl? Best-fit p-valuestat.fit.goodnessfloatnullablexb1? Best-fit bending power-law bend timescale (2)time.scale;meta.modelledintnullablee_xb1? Best-fit bending power-law bend timescale error (lower value)stat.errorintnullableE_xb1? Best-fit bending power-law bend timescale error (upper value)stat.error;stat.maxintnullablepbpl1? Best-fit bending power-law bend timescale p-value (2)time.scale;meta.modelledfloatnullable_RARight Ascension (J2000) from SIMBAD (not part of the original data)degpos.eq.ra;meta.main_DEDeclination (J2000) from SIMBAD (not part of the original data)degpos.eq.dec;meta.mainSimbadNameSimbad column added by the CDSmeta.idcharnullable