Large area astronomical surveys will almost certainly contain new objects of a type that have never been seen before. The detection of ‘unknown unknowns’ by an algorithm is a difficult problem to solve, as unusual things are often easier for a human to spot than a machine. We use the concept of apparent complexity, previously applied to detect multi-component radio sources, to scan the radio continuum Evolutionary Map of the Universe (EMU) Pilot Survey data for complex and interesting objects in a fully automated and blind manner. Here we describe how the complexity is defined and measured, how we applied it to the Pilot Survey data, and how we calibrated the completeness and purity of these interesting objects using a crowd-sourced ‘zoo’. The results are also compared to unexpected and unusual sources already detected in the EMU Pilot Survey, including Odd Radio Circles, that were found by human inspection.

. Post-starburst galaxies (PSBs) have quenched (significant decline in star formation rate) both recently and rapidly (≲Gyr). They are thus promising in providing insights into activities that are happening at the early stage of quenching. While studies have suggested that black hole feedback in the form of active galactic nuclei (AGN) and outflows play important roles in quenching, the details of how they impact the host galaxies and their interplay with other quenching mechanisms are still not fully understood. We find that PSBs commonly show signatures of AGN activity but they appear to be weak and/or heavily obscured. These AGN might be able to drive outflows but they are likely not strong enough to remove gas from the host galaxy. Direct evidence of AGN quenching the star formation of the host galaxy is still missing and AGN likely quench by disturbing rather than expelling the gas.

We investigate flare activity using photometric data obtained with the Transiting Exoplanet Survey Satellite (TESS). Long-term seasonal period analysis was applied on our APT (Automatic Photoelectric Telescopes af Fairborn observatory, Arizona) time series to study changes in the rotational period. We also looked for activity cycle-like changes with short-term Fourier-transform. We also studied the phase and frequency distribution of hand-selected flares on the available TESS data. The MUlti-SIte Continuous Spectroscopy (MUSICOS) campaign was designed in 1998 to achieve high-resolution, multi-wavelength spectroscopic observations from many sites around the globe, which meant that uninterrupted phase coverage of EI Eri became available. We use these data to reconstruct successive surface-temperature maps of the star in order to study the changes of starspots on a very short timescale. We applied our multi-line Doppler imaging code to reconstruct four consecutive Doppler images. These images were also used to measure surface differential rotation with our cross-correlation technique.

Determination of membership of star clusters is a very important criterion in their study as they effect determination of cluster parameters like radius, age, distance, mass functions, etc. In an earlier study, we used published membership data of nine open star clusters as a training set to find new members from Gaia DR2 data using a supervised Random Forest (RF) model with a precision of around 90%. The number of new members found was almost double the published number. In this work, we would like to compare the earlier results with results obtained by applying the unsupervised method of Gaussian Mixture Modelling (GMM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to study the membership of open star clusters of varying ages and locations in the Galaxy using Gaia DR2 and EDR3 data. We shall discuss these techniques and focus on the caveats involved.

Cosmological simulations fail to reproduce realistic galaxy populations without energy injection from active galactic nuclei (AGN) into the interstellar medium (ISM) and circumgalactic medium (CGM); a process called ‘AGN feedback’. Consequently, observational work searches for evidence that luminous AGN impact their host galaxies. Here, we review some of this work. Multi-phase AGN outflows are common, some with potential for significant impact. Additionally, multiple feedback channels can be observed simultaneously; e.g., radio jets from ‘radio quiet’ quasars can inject turbulence on ISM scales, and displace CGM-scale molecular gas. However, caution must be taken comparing outflows to simulations (e.g., kinetic coupling efficiencies) to infer feedback potential, due to a lack of comparable predictions. Furthermore, some work claims limited evidence for feedback because AGN live in gas-rich, star-forming galaxies. However, simulations do not predict instantaneous, global impact on molecular gas or star formation. The impact is expected to be cumulative, over multiple episodes.

Tidal forces in close binaries and multiple systems that contain magnetically active component are supposed to influence the operation of magnetic dynamo. Through synchronization the tidal effect of a close companion helps maintain fast rotation, thus supporting an efficient dynamo. At the same time, it can also suppress the differential rotation of the convection zone, or even force the formation of active longitudes at certain phases fixed to the orbit. V815 Her is a four-star system consisting of two close binaries orbiting each other, one of which contains an active G-type main-sequence star. Therefore, the system offers an excellent opportunity to investigate the influence of gravitational effects on solar-type magnetic activity using different methods.

Ram-pressure stripping (RPS) is a process known to remove gas from satellite galaxies. Recent observational studies have found an increased ratio of active galactic nuclei (AGN) among the population of RPS galaxies compared to regular galaxies in the field. To test whether ram pressure (RP) can trigger an AGN, we perform a suite of hydrodynamical wind-tunnel simulations of a massive (Mstar = 1011 Mȯ) galaxy, with inclusion of star formation, stellar feedback and high resolution up to 39 pc. We find that RP increases the inflow of gas to the galaxy centre, which in turn can result in the enhanced BH accretion, as measured by the Bondi-Hoyle model. We also estimate pressure of outflows from our accretion rates and show that AGN feedback would play an important role on the early stages of stripping, while RP itself is not so strong.

Babcock–Leighton process, in which the poloidal field is generated through the decay and dispersal of tilted bipolar magnetic regions (BMRs), is observed to be the major process behind the generating poloidal field in the Sun. Based on this process, the Babcock–Leighton dynamo models have been a promising tool for explaining various aspects of solar and stellar magnetic cycles. In recent years, in the toroidal to poloidal part of this dynamo loop, various nonlinear mechanisms, namely the flux loss through the magnetic buoyancy in the formation of BMRs, latitude quenching, tilt quenching, and inflows around BMRs, have been identified. While these nonlinearities tend to produce a stable magnetic cycle, the irregular properties of BMR, mainly the scatter around Joy’s law tilt, make a considerable variation in the solar cycle, including grand minima and maxima. After reviewing recent developments in these topics, I end the presentation by discussing the recent progress in making the early prediction of the solar cycle.

Massive spectroscopic surveys targeting tens of millions of galaxies are starting to dominate the observational landscape in the 2020 decade. For instance, a night of observation with the Dark Energy Spectroscopic Instrument (DESI) can measure around of 100,000 spectra, with each spectrum sampled over 2,000 wavelength points. Assessing the quality of such a massive data flow requires new approaches to complement visual inspection by humans. In this work, we explore the Uniform Manifold Approximation and Projection (UMAP) as a technique to assess the data quality of DESI. We use UMAP to project DESI data into a 2-dimensional space. In this space, we are able to find outliers that correspond to instrument fluctuations that can be fully diagnosed by inspecting the raw data. These results pave the way for to use machine learning to monitor the health of massive spectroscopic surveys automatically.

Solar activity shows an 11-year (quasi)periodicity with a pronounced, but limited variability of the cycle amplitudes. The properties of active region (AR) emergence play an important role in the modulation of solar cycles and are our central concern in building a model for predicting future cycle(s) in the framework of the Babcock–Leighton (BL)-type dynamo. The emergence of ARs has the property that strong cycles tend to have higher mean latitudes and lower tilt angle coefficients. Their non-linear feedbacks on the solar cycle are referred to as latitudinal quenching and tilt quenching, respectively. Meanwhile, the stochastic properties of AR emergence, e.g., rogue ARs, limit the scope of the solar cycle prediction. For physics-based prediction models of the solar cycle, we suggest that uncertainties in both the observed magnetograms assimilated as the initial field and the properties of the AR emergence should be taken into account.

Recent observations have established that dwarf galaxies can host black holes of intermediate mass (IMBH, 100Mȯ < MIMBH ≲ 105 Mȯ). With modern numerical models, we can test the growth of IMBHs as well as their evolutionary impact on the host galaxy. Our novel subsolar-mass (0.8 solar mass) resolution simulations of dwarf galaxies (M* = 2 × 107 Mȯ) have a resolved three-phase interstellar medium and account for non-equilibrium heating, cooling, and chemistry processes. The stellar initial mass function is fully sampled between 0.08–150 Mȯ while massive stars can form HII regions and explode as resolved supernovae. The stellar dynamics around the IMBH is integrated accurately with a regularization scheme. We present a viscous accretion disk model for the IMBH with momentum, energy, and mass conserving wind feedback. We demonstrate how the IMBH can grow from accretion of the cold and warm gas phase and how the presence of the IMBH and its feedback impacts the gas phase structure.

In this paper, we present a convolutional neural network (CNN)-based architecture trained on a dataset of meteorites and terrestrial rocks and another dataset trained on meteors and light sources. For meteorites, the dataset comprises augmented images from the meteorite collection at the Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST). For meteors, the images are taken from the United Arab Emirates (UAE) Meteor Monitoring Network (MMN). Such a project’s significance is to expand machine learning applications in astronomy to include the solar system’s small bodies upon contact with the Earth’s atmosphere. This, in return, acts as deep learning research, which examines a computer’s ability to mimic a human’s brain in recognizing meteorites from rocks, and meteors from airplanes and other noise sources. When testing the CNN models, results have shown that both the meteorite and meteor models reached an accuracy of above 80%.

In most of the Babcock–Leighton (BL) type solar dynamo models, the toroidal magnetic field is assumed to be generated in the tachocline. However, magnetic activity of fully convective stars and MHD simulations of global stellar convection have recently raised serious doubts about the importance of the tachocline in the generation of the toroidal field. We have developed a BL-type dynamo model operating in the bulk of the convection zone, and are extending this model to solar-type stars. In this study, we aim at exploring how the starspot properties affect the stellar magnetic cycle. Observations show that faster rotating stars tend to have stronger magnetic activity and shorter magnetic cycles. By considering the higher latitudes and larger tilt angles of starspots for faster rotators, our simulations reproduce observations that faster rotating stars have shorter magnetic cycle and stronger activity.

The Gaia mission DR3 provides accurate data of around two billion stars in the Galaxy, including a classification based on astronomical classes of objects. In this work we present a web visualization tool to analyze one of the products published in the DR3, the Outlier Analysis Self-Organizing Map†.

Feedback and outflows associated with a quasar phase are expected to be critical in quenching the most massive galaxies at high-z. Observations targeting the cool molecular and atomic phases, which dominate the mass and momentum budget of massive galaxy outflows and remove the direct fuel for star formation are, however, severely limited in high-z QSO hosts. We discuss two recent ALMA programs: one targeting molecular outflows in 3 z ∼ 6 QSO hosts using the OH 119 μm absorption line and another targeting the diffuse, predominantly atomic gas in the halos surrounding 5 QSO host between z ∼ 2 – 4 using the OH+(11 – 10) absorption line. Outflows are successfully detected in both samples and compared with outflows driven by high-z star-forming galaxies observed in the same lines. Both studies indicate that observing QSOs during the blow-out phase is crucial for studying the impact of the active nucleus on the ejection of gas from the host galaxy.

Planetary influence on a stellar convective shell can result in a periodic modulation of stellar dynamo drivers. Similar modulation can arise in stellar binary systems. Using the Parker low-mode dynamo model we investigate the properties of nonlinear parametric resonance. This model is a system of four ordinary differential equations and, in the first approximation, describes the processes of generation and oscillation of large-scale magnetic fields in stellar systems. In the absence of nonlinear suppression effects, the problem, by analogy with a system of harmonic oscillations, allows an asymptotic selection of multiple resonant frequencies. Despite the fact that at first glance at these frequencies it is reasonable to expect an increase in the amplitude, the behavior of the system can be just the opposite. All this stuff deserves a systematic analysis of swing excitation in the dynamo sistems in comparison with classical swing excitation in the framework of the Mathieu equation.

The first quasars at the Reionisation Epoch, z ∼ 6-7.5, probe the early stages of supermassive black holes and host galaxy assembly. In this paper, we present recent results, exploiting VLT, ALMA and NOEMA observations, that allow us to constrain the onset of strong black hole feedback, the dust properties and star formation rates in high redshift quasars with unprecedented accuracy. These results highlight the strategic importance of ALMA high frequency (i.e. Band 9 and 8) observations to obtain a reliable overview of the host galaxy and supermassive black hole growth out to the highest redshifts.

One of the best and most direct ways to study planet formation processes is to observe young planets while they are forming within their birth protoplanetary disks. As they form, planets tidally interact with their parental disk and produce observable signatures. Recent observations have demonstrated that kinematic planetary signatures (KPS), the perturbed velocity fields of the gas in the protoplanetary disk in the vicinity of the planet, can be observed with the Atacama Large Millimeter/submillimeter Array (ALMA). Here, I introduce a machine learning-based tool KPSFinder (Kinematic Planetary Signature Finder), which aims to find KPS robustly and efficiently.

A striking feature of the solar cycle is that at the beginning, sunspots appear around mid-latitudes, and over time the latitudes of emergences migrate towards the equator. The maximum level of activity varies from cycle to cycle. For strong cycles, the activity begins early and at higher latitudes with wider sunspot distributions than for weak cycles. The activity and the width of sunspot belts increase rapidly and begin to decline when the belts are still at high latitudes. However, in the late stages of the cycles, the level of activity, and properties of the butterfly wings all have the same statistical properties independent of the peak strength of the cycles. We have modelled these features using Babcock–Leighton type dynamo model and shown that the toroidal flux loss from the solar interior due to magnetic buoyancy is an essential nonlinearity that leads to all the cycles decline in the same way.