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Abstract We examine lengthy radio light curves of the flat spectrum radio galaxy 3C 454.3 for possible quasiperiodic oscillations (QPOs). The data used in this work were collected at five radio frequencies, 4.8, 8.0, 14.5, 22.0, and 37.0 GHz between 1979 and 2013 as observed at the University of Michigan Radio Astronomical Observatory, Crimean Astrophysical Observatory, and Aalto University Metsähovi Radio Observatory. We employ generalized Lomb–Scargle periodogram and weighted wavelet transform analyses to search for periodicities in these light curves. We confirm a QPO period of ∼2000 days to be at least 4σsignificant using both methods at all five radio frequencies between 1979 and 2007, after which a strong flare changed the character of the light curve. We also find a ∼600 day period, which is at least 4σsignificant, but only in the 22.0 and 37.0 GHz light curves. We briefly discuss physical mechanisms capable of producing such variations. 

Abstract The modeling of weather and climate has been a success story. The skill of forecasts continues to improve and model biases continue to decrease. Combining the output of multiple models has further improved forecast skill and reduced biases. But are we exploiting the full capacity of state-of-the-art models in making forecasts and projections? Supermodeling is a recent step forward in the multimodel ensemble approach. Instead of combining model output after the simulations are completed, in a supermodel individual models exchange state information as they run, influencing each other’s behavior. By learning the optimal parameters that determine how models influence each other based on past observations, model errors are reduced at an early stage before they propagate into larger scales and affect other regions and variables. The models synchronize on a common solution that through learning remains closer to the observed evolution. Effectively a new dynamical system has been created, a supermodel, that optimally combines the strengths of the constituent models. The supermodel approach has the potential to rapidly improve current state-of-the-art weather forecasts and climate predictions. In this paper we introduce supermodeling, demonstrate its potential in examples of various complexity, and discuss learning strategies. We conclude with a discussion of remaining challenges for a successful application of supermodeling in the context of state-of-the-art models. The supermodeling approach is not limited to the modeling of weather and climate, but can be applied to improve the prediction capabilities of any complex system, for which a set of different models exists. 

Abstract We report the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ 287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The firstI-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in theR-band. There is a big change in theR–Ispectral index by 1.0 ± 0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ 287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ 287 as well as the dense monitoring sample of Krakow. 

Abstract We study the optical flux and polarization variability of the binary black hole blazar OJ 287 using quasi-simultaneous observations from 2015 to 2023 carried out using telescopes in the USA, Japan, Russia, Crimea, and Bulgaria. This is one of the most extensive quasi-simultaneous optical flux and polarization variability studies of OJ 287. OJ 287 showed large amplitude, ∼3.0 mag flux variability, large changes of ∼37% in degree of polarization, and a large swing of ∼215° in the angle of the electric vector of polarization. During the period of observation, several flares in flux were detected. Those flares are correlated with a rapid increase in the degree of polarization and swings in electric vector of polarization angle. A peculiar behavior of anticorrelation between flux and polarization degree, accompanied by a nearly constant polarization angle, was detected from JD 2,458,156 to JD 2,458,292. We briefly discuss some explanations for the flux and polarization variations observed in OJ 287. 

Abstract Due to its peculiar and highly variable nature, the blazar 3C 454.3 has been extensively monitored by the WEBT team. Here, we present for the first time these long-term optical flux and color variability results using data acquired inB,V,R, andIbands over a time span of about two decades. We include data from WEBT collaborators and public archives such as SMARTS, Steward Observatory, and Zwicky Transient Facility. The data are binned and segmented to study the source over this long term when more regular sampling was available. During our study, the long-term spectral variability reveals a redder-when-brighter trend, which, however, stabilizes at a particular brightness cutoff of ∼14.5 mag in theIband, after which it saturates and evolves into a complex state. This trend indicates increasing dominance of jet emission over accretion disk (AD) emission until jet emission completely dominates. Plots of the variation in spectral index (followingF_ν∝ν^−α) reveal a bimodal distribution using a one-day binning. These correlate with two extreme phases of 3C 454.3, an outburst or high-flux state and a quiescent or low-flux state, which are respectively jet- and AD-dominated. We have also conducted intraday variability studies of nine light curves and found that six of them are variable. Discrete correlation function analysis between different pairs of optical wave bands peaks at zero lags, indicating cospatial emission in different optical bands. 

The Cosmic Ray Extremely Distributed Observatory (CREDO) pursues a global research strategy dedicated to the search for correlated cosmic rays, so-called Cosmic Ray Ensembles (CRE). Its general approach to CRE detection does not involve any a priori considerations, and its search strategy encompasses both spatial and temporal correlations, on different scales. Here we search for time clustering of the cosmic ray events collected with a small sea-level extensive air shower array at the University of Adelaide. The array consists of seven one-square-metre scintillators enclosing an area of 10 m × 19 m. It has a threshold energy ~0.1 PeV, and records cosmic ray showers at a rate of ~6 mHz. We have examined event arrival times over a period of over 2.5 years in two equipment configurations (without and with GPS timing), recording ~300 k events and ~100 k events. We determined the event time spacing distributions between individual events and the distributions of time periods which contained specific numbers of multiple events. We find that the overall time distributions are as expected for random events. The distribution which was chosen a priori for particular study was for time periods covering five events (four spacings). Overall, these distributions fit closely with expectation, but there are two outliers of short burst periods in data for each configuration. One of these outliers contains eight events within 48 s. The physical characteristics of the array will be discussed together with the analysis procedure, including a comparison between the observed time distributions and expectation based on randomly arriving events.