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Dynamical friction implies a consistency check on any system where dark matter particles are hypothesised to explain orbital dynamics requiring more mass under Newtonian gravity than is directly detectable. Introducing the assumption of a dominant dark matter halo will also imply a decay timescale for the orbits in question. A self-consistency constraint hence arises, such that the resulting orbital decay timescales must be longer than the lifetimes of the systems in question. While such constraints are often trivially passed, the combined dependencies of dynamical friction timescales on the mass and orbital radius of the orbital tracer and on the density and velocity dispersion of the assumed dark matter particles leads to the existence of a number of astronomical systems where such a consistency test is failed. Here, we review cases from stars in ultrafaint dwarf galaxies, galactic bars, satellite galaxies, and, particularly, the multi-period mutual orbits of the Magellanic Clouds, as recently inferred from the star formation histories of these two galaxies, as well as the nearby M81 group of galaxies, where introducing enough dark matter to explain observed kinematics leads to dynamical friction orbital decay timescales shorter than the lifetimes of the systems in question. Taken together, these observations exclude dark matter halos made of particles as plausible explanations for the observed kinematics of these systems.

Simulations of structure formation in the standard cold dark matter cosmological model quantify the dark matter halos of galaxies. Taking into account dynamical friction between dark matter halos, we investigate the past orbital dynamical evolution of the Magellanic Clouds in the presence of the Galaxy. Our calculations are based on a three-body model of rigid Navarro–Frenk–White profiles for dark matter halos but were verified in a previous publication by comparison to high-resolution N-body simulations of live self-consistent systems. Under the requirement that the LMC and SMC had an encounter within 20 kpc between 1 and 4 Gyr ago in order to allow the development of the Magellanic Stream, using the latest astrometric data, the dynamical evolution of the MW/LMC/SMC system is calculated backwards in time. With the employment of the genetic algorithm and a Markov-Chain Monte-Carlo method, the present state of this system is unlikely, with a probability of <10−9 (6σ complement), because the solutions found do not fit into the error bars for the observed plane-of-sky velocity components of the Magellanic Clouds. This implies that orbital solutions that assume dark matter halos, according to cosmological structure formation theory, to exist around the Magellanic Clouds and the Milky Way are not possible with a confidence of more than 6 sigma.

Understanding the diversity of star formation histories (SFHs) of galaxies is key to reconstructing their evolutionary paths. Traditional models often assume parametric forms such as delayed-τ or exponentially declining models, which may not reflect the actual variety of formation processes. We aim to assess what types of SFHs are consistent with the observed present-day star formation rates (SFR0) and time-averaged star formation rates (⟨SFR⟩) of galaxies in the Local Volume, without assuming any fixed functional form. We construct a non-parametric framework by generating large ensembles of randomized SFHs for each galaxy in the sample. For each SFH, we compute its predicted stellar mass and present-day SFR and retain only those consistent with the observed values within a 20% tolerance. We then infer the statistical distribution of power-law slopes η (fitted as SFR(t)∝(t−tstart)η) and 50% stellar mass formation times t50. Across the full sample of 555 galaxies, we find that ≈70% have flat SFHs (|η|≤0.01), ≈24% are mildly declining (η<−0.01), and ≈6% are rising (η>0.01). In the low-mass bin (M★<3×109M⊙), rising SFHs slightly increase (≈7%) but remain a minority as the majority have flat SFHs. Both η and t50 correlate strongly with the SFR ratio (Spearman ρ>0.75, p≪10−16), indicating that the shape and timing of star formation are primarily governed by this ratio. The t50 distribution shows sharp spikes near 7.74 and 7.86 Gyr, which we attribute to grid discretization combined with filtering, rather than a physical bimodality. Our results confirm that strongly declining SFH templates are disfavored in the Local Volume: most systems are consistent with flat long-term SFHs, with only mild decline or occasional rising. Importantly, this is demonstrated through a fully model-independent, data-driven approach, with per-galaxy uncertainties quantified using the standard error of η and t50 from the ensemble of accepted SFHs.

We investigate the shape and morphology of early-type galaxies (ETGs) within the framework of Modified Newtonian Dynamics (MOND). Building on our previous studies, which demonstrated that the monolithic collapse of primordial gas clouds in MOND produces galaxies (noted throughout as ‘model relics’ in the context of this work) with short star formation timescales and a downsizing effect as observationally found, we present new analyses on the resulting structural and morphological properties of these systems. Initially, the monolithically formed galaxies display disk-like structures. In this study, we further analyze the transformations that occur when these galaxies merge, observing that the resulting systems (noted throughout as ‘merged galaxies’ in the context of this work) take on elliptical-like shapes, with the (Vrot/Vσ)–ellipticity relations closely matching observational data across various projections. We extend this analysis by examining the isophotal shapes and rotational parameter (λR) of both individual relics and merged galaxies. The results indicate that ETGs may originate in pairs in dense environments, with mergers subsequently producing elliptical structures that align well with the observed kinematic and morphological characteristics. Finally, we compare both the model relics and merged galaxies with the fundamental plane and Kormendy relation of observed ETGs, finding close agreement. Together, these findings suggest that MOND provides a viable physical framework for the rapid formation and morphological evolution of ETGs.

The stellar initial mass function (IMF) is the key to understanding the matter cycle in the Universe. Edwin Salpeter’s paper of 1955 founded this research field. Evidence today, however, challenges the initial mass function as an invariant probability distribution function.

It was found that satellites of nearby galaxies can form flattened co-rotating structures called disks of satellites or planes of satellites. Their existence is not expected by the current galaxy formation simulations in the standard dark matter-based cosmology. On the contrary, modified gravity offers a promising alternative: the objects in the disks of satellites are tidal dwarf galaxies, that is, small galaxies that form from tidal tails of interacting galaxies. After introducing the topic, we review here our work on simulating the formation of the disks of satellites of the Milky Way and Andromeda galaxies. The initial conditions of the simulation were tuned to reproduce the observed positions, velocities and disk orientations of the galaxies. The simulation showed that the galaxies had a close flyby 6.8 Gyr ago. One of the tidal tails produced by the Milky Way was captured by Andromeda. It formed a cloud of particles resembling the disk of satellites at Andromeda by its size, orientation, rotation and mass. A hint of a disk of satellites was formed at the Milky Way too. In addition, the encounter induced a warp in the disk of the simulated Milky Way that resembles the real warp by its magnitude and orientation. We present here, for the first time, the proper motions of the members of the disk of satellites of Andromeda predicted by our simulation. Finally, we point out some of the remaining open questions which this hypothesis, for the formation of disks of satellites, brings up.

The Large and Small Magellanic Clouds (LMC and SMC) form the closest interacting galactic system to the Milky Way, therewith providing a laboratory to test cosmological models in the local Universe. We quantify the likelihood for the Magellanic Clouds (MCs) to be observed within the ΛCDM model using hydrodynamical simulations of the IllustrisTNG project. The orbits of the MCs are constrained by proper motion measurements taken by the Hubble Space Telescope and Gaia. The MCs have a mutual separation of dMCs=24.5kpc and a relative velocity of vMCs=90.8kms−1, implying a specific phase-space density of fMCs,obs≡(dMCs·vMCs)−3=9.10×10−11km−3s3kpc−3. We select analogues to the MCs based on their stellar masses and distances in MW-like halos. None of the selected LMC analogues have a higher total mass and lower Galactocentric distance than the LMC, resulting in >3.75σ tension. We also find that the fMCs distribution in the highest resolution TNG50 simulation is in 3.95σ tension with observations. Thus, a hierarchical clustering of two massive satellites like the MCs in a narrow phase-space volume is unlikely in ΛCDM, presumably because of short merger timescales due to dynamical friction between the overlapping dark matter halos. We show that group infall led by an LMC analogue cannot populate the Galactic disc of satellites (DoS), implying that the DoS and the MCs formed in physically unrelated ways in ΛCDM. Since the 20∘ alignment of the LMC and DoS orbital poles has a likelihood of P=0.030 (2.17σ), adding this χ2 to that of fMCs gives a combined likelihood of P=3.90×10−5 (4.11σ).

A model of a particle in finite space is developed and the properties that the particle may possess under this model are studied. The possibility that particles attract each other due to their own wave nature is discussed. The assumption that the particles are spatially confined oscillations (SCO) in the medium is used. The relation between the SCO and the refractive index of the medium in the idealized universe is derived. Due to the plane wave constituents of SCOs, the presence of a refractive index field with a nonzero gradient causes the SCO to accelerate. The SCO locally changes the refractive index such that another SCO is accelerated towards it, and vice versa. It is concluded that the particles can attract each other due to their wave nature and an inverse-square-type acceleration emerges. The constant parameter in the inverse-square-type acceleration is used to compare with the gravitational constant GN, and the possibility of non inverse-square-type behavior is preliminary discussed.

We summarise the properties and nature of a peculiar group of B-type stars called FS CMa stars. These stars show the B[e] phenomenon, i.e., their spectra exhibit both forbidden emission lines and infrared excess. Such properties point to an extended circumstellar gas and dust component. Although the phenomenon has been explained in most B[e] stars, the origin and nature of FS CMa stars is disputed. Here, we focus on the merger hypothesis, for which evidence has recently been discovered.

The availability of large image data sets has been a crucial factor in the success of deep learning-based classification and detection methods. Yet, while data sets for everyday objects are widely available, data for specific industrial use-cases (e.g., identifying packaged products in a warehouse) remains scarce. In such cases, the data sets have to be created from scratch, placing a crucial bottleneck on the deployment of deep learning techniques in industrial applications. We present work carried out in collaboration with a leading UK online supermarket, with the aim of creating a computer vision system capable of detecting and identifying unique supermarket products in a warehouse setting. To this end, we demonstrate a framework for using data synthesis to create an end-to-end deep learning pipeline, beginning with real-world objects and culminating in a trained model. Our method is based on the generation of a synthetic dataset from 3D models obtained by applying photogrammetry techniques to real-world objects. Using 100K synthetic images for 10 classes, an InceptionV3 convolutional neural network was trained, which achieved accuracy of 96% on a separately acquired test set of real supermarket product images. The image generation process supports automatic pixel annotation. This eliminates the prohibitively expensive manual annotation typically required for detection tasks. Based on this readily available data, a one-stage RetinaNet detector was trained on the synthetic, annotated images to produce a detector that can accurately localize and classify the specimen products in real-time.