J/A+A/693/A318      AGN radio variability at 37GHz            (Kankkunen+, 2025)

Long-term radio variability of active galactic nuclei at 37 GHz. Kankkunen S., Tornikoski M., Hovatta T., Lahteenmaki A. <Astron. Astrophys. 693, A318 (2025)> =2025A&A...693A.318K 2025A&A...693A.318K (SIMBAD/NED BibCode)
ADC_Keywords: Active gal. nuclei ; QSOs ; Radio sources Keywords: methods: data analysis - galaxies: active - quasars: general Abstract: We 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 β 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 β=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. Description: We analysed the long-term radio variability of 123 sources observed by the Metsahovi Radio Observatory in 37GHz. We utilised the longest monitoring periods in the 37 GHz band to date, maximum of which extended to 42 years of observations with an average monitoring period of 34.5 years. Our sample of 123 sources was also exceptionally large for such analysis, allowing unique insights into the long-term radio variability of AGNs. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file tablea1.dat 107 123 *Results from the bending power-law fit (Eq. 4), simple power-law fit (Eq. 3), and bending power-law fit using βhighbpl,best (Eq. 6) -------------------------------------------------------------------------------- Note on tablea1.dat: All values are reported with their 90% confidence regions, where the slope and timescale constraints for the bending power-law fits (Eq. 4) are the minimum and maximum values obtained from some combination of the two parameters within the bending power-law fit 90% confidence region. A missing value in the table indicates a rejection confidence of over 90%. The probed limits for the timescales were xb,min=100 days and xb,max=7000 days, and the probed limits for the slopes were βmin=1 and βmax=3.5. -------------------------------------------------------------------------------- Byte-by-byte Description of file: tablea1.dat -------------------------------------------------------------------------------- Bytes Format Unit Label Explanations -------------------------------------------------------------------------------- 1- 9 A9 --- Source Source name 12- 23 A12 --- OName Other name 25- 28 I4 --- N Total number of data points in the light curve 30- 37 A8 --- Type Type of object 40- 42 F3.1 --- betabpl ? Best-fit bending power-law slope βbpl (1) 44- 46 F3.1 --- e_betabpl ? Best-fit bending power-law slope βbpl error (lower value) 48- 50 F3.1 --- E_betabpl ? Best-fit bending power-law slope βbpl error (upper value) 52- 55 I4 --- xb ? Best-fit bending power-law bend timescale (1) 57- 60 I4 --- e_xb ? Best-fit bending power-law bend timescale error (lower value) 62- 65 I4 --- E_xb ? Best-fit bending power-law bend timescale error (upper value) 67- 70 F4.2 --- pbpl ? Best-fit bending power-law slope p-value (1) 72- 74 F3.1 --- betaspl ? Best-fit simple power-law slope 76- 78 F3.1 --- e_betaspl ? Best-fit simple power-law slope error (lower value) 80- 82 F3.1 --- E_betaspl ? Best-fit simple power-law slope error (upper value) 84- 87 F4.2 --- pspl ? Best-fit p-value 89- 92 I4 --- xb1 ? Best-fit bending power-law bend timescale (2) 94- 97 I4 --- e_xb1 ? Best-fit bending power-law bend timescale error (lower value) 99-102 I4 --- E_xb1 ? Best-fit bending power-law bend timescale error (upper value) 104-107 F4.2 --- pbpl1 ? Best-fit bending power-law bend timescale p-value (2) -------------------------------------------------------------------------------- Note (1): Best-fit bending power-law slope βbpl and bend timescale xb (Only the timescales for the 11 constrained sources should be considered reliable. For the other sources more observations are needed.) using Eq. 4, as well as the corresponding p-values (pbpl). Note (2): For the case with βlow=1 using Eq. 6, we give the best-fit bending power-law bend timescale (xb1) where βhighbpl,best. The corresponding p-values are given by pbpl1. -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Patricia Vannier [CDS] 21-May-2025
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