Papers for Monday, Feb 23 2026

In the search for extraterrestrial intelligence (SETI), the highly incomplete sampling of the technosignature search space is often considered as a plausible explanation for the persistent lack of detections over six decades of searches. If correct, this would imply that technosignatures may already have reached Earth without being detected or correctly identified. Here, we explore this possibility using a Bayesian inference framework to estimate present-day detectability given $n\ge 1$ undetected contacts over the past 65 years -- the period since the first SETI experiment. We show that achieving high detectability of technosignatures emitted within a few hundred light-years of Earth would require implausibly large $n$ values, even exceeding the population of habitable planets within that range. More conservative estimates can be obtained only assuming that emitters are tightly clustered near Earth or that their population in the Milky Way has undergone a very recent and sudden boost. This tension is further exacerbated for short-lived technosignatures and persists whether they are omnidirectional, as in Dysonian megastructures, or directional, as in intentional communication attempts. These findings suggest that, if undetected past contacts from the Milky Way have indeed occurred, the best prospects of detection may lie in searches extending over several thousand light-years, though only a few detectable technoemissions would be expected.

Gradual crustal deformation can generate strongly twisted magnetic fields around magnetars, potentially triggering giant flares with total energies exceeding $10^{44}\,\mathrm{erg}$. In this Letter, we present the first relativistic magnetohydrodynamic simulation of a surface shear-driven magnetar eruption, capturing reconnection-driven plasma heating, the ejection of relativistically hot plasma, and the formation of a hot fireball confined within the inner magnetosphere. We find that magnetic reconnection in the equatorial current sheet launches a hot trailing outflow capable of powering the initial spike observed in giant flares, while simultaneously leaving behind a thermally stratified fireball with sufficient thermal energy to produce the pulsating, decaying tail. Together, these features provide a self-consistent physical framework for understanding the observed energetics of magnetar giant flares. The eruption also expels a magnetically dominated giant plasmoid carrying up to $\sim 9\%$ of the magnetosphere's total magnetic energy. Furthermore, our simulation demonstrates how the plasmoid drives the formation of a blast wave -- an important ingredient in models linking magnetar eruptions to fast radio bursts.

Gravitational wave (GW) spectral sirens offer a promising method for measuring cosmological parameters using GW data only - without relying on external redshift information such as electromagnetic counterparts or galaxy catalogs - by exploiting distributional features in the population of GW sources. The advent of third-generation detectors like the Einstein Telescope (ET) will provide catalogs three orders of magnitudes larger than current ones, raising questions about the scalability and robustness of existing inference pipelines. We present a blinded mock data challenge that tests three public pipelines with distinct numerical implementations, namely, $\texttt{ICAROGW}$, $\texttt{CHIMERA}$, and $\texttt{pymcpop-gw}$, on simulated ET observations containing the best $\mathcal{O}(10^4)$ binary black hole mergers that can be observed in 1 year. We assess their computational performance, validate their agreement in a blinded setting, and forecast cosmological constraints. We find that, thanks to GPU acceleration, these pipelines can process the events expected from ET within a manageable timeframe. All pipelines recover consistent cosmological and population parameters. Assuming a flat $\Lambda$CDM model, we measure $H(z)$ at $z\sim1.5$ with 2.4% precision, and achieve a mean precision on $H(z)$ of 2.8% across $0.7<z<1.8$ with a catalog of $\sim 12,000$ high-S/N events. This corresponds to joint constraints of $\sim 10%$ on $H_0$ and $\sim 26%$ on $\Omega_{\rm m,0}$. We also identify the events that contribute mostly to constraining cosmological parameters, showing that low-distance sources near population features drive the constraining power on all cosmological parameters, while higher-distance events primarily constrain $\Omega_{\rm m,0}$. Our results establish a validated, performance-tested framework for spectral siren cosmology in the era of third-generation GW observatories.

We perform a comprehensive analysis of cosmic-ray propagation using the time-dependent AMS-02 flux measurements covering a full solar cycle, with particular emphasis on the role of solar modulation. We fit two representative Galactic propagation scenarios, convection- and re-acceleration-dominated models, in combination with three solar modulation prescriptions: the standard force-field approximation, an extended force-field model with a rigidity break, and the heliospheric propagation code $\texttt{HelMod}$. The inclusion of time-resolved antiproton data provides a unique probe of charge-sign-dependent modulation effects and low-energy systematics. We find that the force-field approximation can describe positively charged nuclei reasonably well outside the solar maximum in convection-dominated models, but fails during periods of high solar activity and for antiprotons at all times. In re-acceleration scenarios, strong degeneracies between solar modulation and low-energy propagation lead to unphysical results when simple modulation models are employed. Across all models, we identify systematic uncertainties of order 10-15% in the reconstructed local interstellar spectra and propagation parameters, driven by limitations in current solar modulation modelling. Compared to the percent level error of current measurements, these uncertainties significantly limit the precision of cosmic-ray studies. Future time-dependent measurements spanning a full 22-year solar cycle will be crucial to reduce these uncertainties.

The measurement of exoplanet masses using the radial velocity (RV) technique is currently limited by stellar activity, which introduces quasiperiodic variability signals that must be modeled and removed to enhance the sensitivity of the RV measurements to exoplanet signals. Neural networks have previously been demonstrated effective in modeling stellar activity signals in HARPS-N solar data using white light cross correlation functions (CCFs). Building on this work, we train a neural network on six years of HARPS-N solar data with additional parameters commonly associated to stellar activity, including chromatic CCFs, line shape metrics, spectral activity indicators, total solar irradiance (TSI) light curves from SORCE and TSIS-1, and TSI time derivatives. Our results show that parameters such as the bisector inverse slope and Na D equivalent widths do not significantly improve the neural network's ability to predict activity-induced RV variations compared to using the white light CCFs alone. However, parameters such as unsigned magnetic flux, the TSI and its time derivative, S-index, H-alpha equivalent width, chromatic CCFs, contrast, and full width at half maximum do improve the neural network's ability to predict RV scatter. Our new model reduces the RV scatter in a held-out test set from 147.1 cm/s to 93.3 cm/s, consistent with supergranulation noise levels reported in previous studies. These results suggest that finding effective tracers for (super)granulation will be critical to train models capable of further mitigating RV jitter, and necessary for characterizing Earth analogues.

Young massive clusters (YMCs) provide favorable environments for frequent stellar collisions, potentially leading to the formation of very massive stars (VMSs) and seeds of intermediate-mass black holes (IMBHs). We investigate the role of repeated stellar collisions in YMCs using TITANS, a new suite of 18 direct $N$-body simulations. Our models span cluster masses $10^5 - 10^6\,\rm M_\odot$, half-mass densities $\rho_{\rm h}=100 - 10^5\,\rm M_\odot\,pc^{-3}$, and include high primordial binary fractions, consistent with observations of massive stars in young clusters. Overall, our simulations assume cluster properties that are typical of YMCs in the low-redshift Universe. We find that repeated stellar collisions are efficient only in the densest clusters with short relaxation times and are absent in systems with $\rho_{\rm h}<500\,\rm M_\odot\,pc^{-3}$ and $t_{\rm rh}>1.3\,\rm Gyr$. Rapid mass segregation allows massive stars to sink to the cluster center, merge, and undergo subsequent collisions, even in clusters with long core-collapse times. However, collision chains are typically triggered by primordial binary mergers and usually involve only two collisions. In our simulations, only three VMSs form through repeated collisions and reach $m_*>330\,\rm M_\odot$, while most VMSs have $m_*<300\,\rm M_\odot$ and form through primordial binary mergers. None constitute viable IMBH seeds, as their helium cores fall in the (pulsational) pair-instability regime. We form five IMBHs from stellar collisions involving stars at different evolutionary stages, while the dominant channel is the merger of stellar-mass black holes, producing twelve IMBHs. For properties typical of local YMCs, stellar collision chains are therefore inefficient in producing IMBHs more massive than $140\,\rm M_\odot$, as most collisionally formed VMSs attain masses that fall in the pair-instability regime.

Star formation within filaments may arise due to the growth of cores according to linear perturbation theory. This implies a minimum core separation, as shorter modes would not be able to grow. While many observations agree with core separations by theoretical predictions, some observations also show star forming cores which lie closer together than the minimum wavelength given by perturbation theory. We explore whether non-linear effects during the late stages of core growth can explain the discrepancy between theory and observations. We perform three-dimensional hydrodynamical simulations with the Ramses code to follow the evolution of initial perturbations within filaments and compare the measured growth rates to expectations from theoretical models. Non-linear evolution sets in as soon as the core mass reaches a value where the gravitational potential is not any longer dominated by the cylindrical potential of the filament but by the spherical potential of the Bonnor-Ebert sphere. Consequently, core collapse is not triggered by the loss of hydrostatic stability of the filament but by the loss of hydrostatic stability of the Bonnor-Ebert sphere. As the core is embedded in the filament, the maximum core mass is given by the pressure within the filament which results in a constant line-mass threshold for core collapse. As core collapse is triggered as soon as overdensities reach a certain line-mass, cores which form as large line-mass perturbations during filament formation can go into direct collapse even if their separation is closer than predicted by linear perturbation theory. Therefore, our result can explain the discrepancy between theory and observations.

We present high spectral resolution $L$ band (2.91--3.85 $\mu$m) observations of the warm Neptune GJ 436 b from Keck II/KPIC. KPIC's single-mode fiber feed reduces the $L$ band sky background by a factor of 100, significantly improving sensitivity compared to a seeing-limited spectrometer and enabling a tentative ($\rm SNR = 3-4$) cross-correlation detection of GJ 436 b with a thermally inverted atmospheric model. In contrast with recent results from $JWST$ and high-resolution transmission spectroscopy, our retrieval analysis prefers the presence of H$_2$O, and possibly CH$_4$, molecular features in emission. The broad-band continuum flux associated with the maximum-likelihood model is substantially higher than expected based on both the $\sim670\rm\ K$ equilibrium temperature of GJ 436 b and previous results from low-resolution spectroscopy. We demonstrate that the loss of continuum information during the processing of high-resolution spectra makes our analysis effectively insensitive to the absolute continuum level of the planet, and that scaling the maximum-likelihood model to match the broad-band flux measured from low-resolution observations of GJ 436 b results in a detection of similar strength in cross-correlation. These results could be explained by a thermal inversion arising above a haze layer in the upper atmosphere of \gjb. Further observations, ideally post-eclipse in order to break the $K_p - \Delta v_{sys}$ degeneracy, are needed to clarify this possible detection. This work demonstrates the potential of $L$ band high-resolution spectroscopy for characterizing significantly smaller and cooler exoplanets compared with hot Jupiters.

Small-scale jet-like eruptions, such as picoflare jets and jetlets, are recognized as potential contributors to coronal heating and solar wind acceleration, yet their physical origin is still not fully established. Using ultra-high-resolution extreme ultraviolet imaging datasets from the Extreme Ultraviolet Imager on board the Solar Orbiter mission, we investigate tiny coronal jets observed off-limb in the Sun's polar regions. Visual inspection reveals that the majority of these jets exhibit distinct morphological features, including a bright spire accompanied by a dark eruptive jet component. We analyzed eleven of these jets in detail and found that their spatial and temporal scales are comparable to previously reported jetlets, while their kinetic energies are two to three orders of magnitude lower, placing them in the picoflare regime. The bright and dark components show distinct dynamics, with the dark structures generally displaying lower speeds. A comparison with coordinated Interface Region Imaging Spectrograph and the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory data, together with 2.5D radiative-MHD simulations performed with the Bifrost code, reveals a one-to-one morphological correspondence between the dark counterparts and cool chromospheric surges accompanying the bright jet spire. This association suggests that flux emergence and magnetic reconnection at low atmospheric heights may produce coupled bright-dark structures, providing a plausible mechanism for the generation of picoflare jets. Our results demonstrate Solar Orbiter's ability to resolve the dynamics of small-scale jets and place new constraints on their origin.

The overwhelming majority of eclipsing white dwarf (WD) binary systems show quasi-periodic variations in eclipse timings on many year timescales. Currently, the mechanism behind these eclipse time variations (ETVs) is not known, with the main competing theories being the planetary hypothesis and the Applegate/Lanza mechanisms. Here, we present a comprehensive study of 43 WD binary systems, the vast majority of which have more than a decade of eclipse timing measurements, analysing their global properties to determine which driving force is the likely origin of the observed ETVs. Long-term, high-speed photometry data obtained with ULTRACAM, ULTRASPEC and HiPERCAM have allowed us to track the evolution of the ETVs in these systems, and analyse any previously unseen trends. From this analysis, we find a clear difference in the level of observed ETVs past the fully convective boundary, where systems with partially radiative companion stars consistently showing high levels of variation. While some systems may be affected by the presence of an unknown planet, the results from this study strongly indicates that an Applegate- or Lanza-like mechanism is the most likely driving force for the timing variations seen in the majority of systems in this sample. However, as found in previous studies, the Applegate/Lanza mechanisms are still not able to reproduce the large and rapid timing variations seen in the vast majority of systems, with the companion star to the WD unable to provide sufficient energy on these short timescales.

We present a new approach to identify satellite trails (or other linear artifacts) in ACS/WFC imaging data using a modified Radon Transform. We demonstrate that this approach is sensitive to features with mean brightness significantly below the background noise level, and it is resistant to the influence of bright astronomical sources (e.g., stars, galaxies) in most cases. Comparing with a set of satellite trails identified by eye, we find a trail recovery rate of 85\% and a false detection rate (after removing diffraction spikes that are easily filtered) of 2.5\%. By performing an analysis using a much larger ACS/WFC data set where false trails are identified by their persistence across multiple images of the same field, we identify the Radon Transform parameter space and image properties where our algorithm is unreliable, and estimate a false detection rate of $\sim10\%$ elsewhere. We apply our method to ACS/WFC data taken between 2002 and 2022 to determine both the frequency of satellite trail contamination in science data and also the typical trail brightness as a function of time. We find the rate of satellite trail contamination has increased by approximately a factor of two in the last two decades, but there is no clear systematic evolution in the typical trail brightness. Our satellite trail identification program is available as part of the \texttt{acstools} package.

Sterile neutrinos in the keV mass range have long been considered a well-motivated dark matter (DM) candidate. In this work, we explore a sterile neutrino production mechanism through active neutrino self-interactions in the early universe, assuming that they constitute the full DM abundance. We implement a self-consistent treatment of the sterile-neutrino free streaming and the active-neutrino self-interactions on structure formation, which yield a unique scale-dependent modification to the linear matter power spectrum. We then set bounds on this scenario using a combination of the cosmic microwave background and Ly$\alpha$ forest constraints. Specifically, we utilize the two recent likelihoods derived from eBOSS data: (i) an effective field theory (EFT) based full-shape likelihood and (ii) a compressed likelihood obtained from the PRIYA-simulation emulator. We produce some of the most stringent observational constraints to date on sterile neutrino DM, comparable to the bounds from the most stringent laboratory constraints.

The Ninth Catalogue of Spectroscopic Binary Orbits (SB9) is a comprehensive compilation of spectroscopic binaries (SBs) with orbital parameters sourced from literature, comprising approximately 4000 systems (2800 single-lined and 1200 double-lined). This work presents the latest status of SB9 after two decades of development, detailing the statistical properties of SBs through orbital period distributions and eccentricity-period diagrams categorized by spectral type and evolutionary stage. We performed a rigorous cross-match with Gaia Data Release 3 (DR3) to update astrometric parameters and compare SB9 with the Gaia DR3 Non-Single Star (NSS) catalogue. Our methodology utilized positional separations, magnitudes, and proper-motion back-propagation for identification. The final SB9 version updated by D. Pourbaix includes 4003 systems, including higher-order multiples: 152 triples, 71 quadruples, and 14 higher-order systems. Of these, 3976 have Gaia DR3 identifiers; 21 are too bright and six too faint for detection. Ten SB9 systems with periods exceeding 1180 days were spatially resolved by Gaia DR3. We identified a common sample of 827 binaries cross-matched with Gaia NSS, with 655 considered highly reliable based on period and eccentricity differences under 10%. The limited overlap (20-30% of SB9) results from NSS selection cuts, brightness limits, and temporal baselines. This study highlights the complementary strengths of both catalogues and establishes a benchmark sample for binary star research. Finally, this work marks the transition of SB9 into SBX (The eXtended Catalogue of Spectroscopic Binary Orbits), featuring a modern relational database, improved web interface, and Virtual Observatory access standards to enhance data quality and accessibility for the stellar community.

To gain deeper insights into galaxy evolution and the mechanisms driving transitions between different galaxy morphologies, we analyse the connection between star formation rate and stellar mass for 231 galaxies spanning Hubble types E1-Sdm from the Calar Alto Legacy Integral Field Spectroscopy Area survey using three complementary classification schemes. The Hubble classification provides structural information, the circular velocity curve classification$-$based on principal component analysis$-$ traces the total gravitational potential, and the Quenching classification$-$derived from H$_{\alpha}$ equivalent width maps$-$indicates the spatial extent of quenched regions relative to star-forming areas. We find a clear separation of galaxy populations on the star formation rate-stellar mass plane. Late-type spirals with slow-rising circular velocity curves, represented by star-forming and quiescent-nuclear-ring galaxies, dominate the blue cloud. Early-type spirals with flat or round-peaked circular velocity curves belonging to centrally quiescent or mixed class populate the green valley, representing a transitional stage. Elliptical and lenticular galaxies with round- or sharp-peaked circular velocity curves from nearly retired or fully retired QSs reside on the red sequence. Furthermore, our results indicate that the morphological groups Sc-Scd, Sd-Sdm, and E1-E3 are characterized by a unique set of QSs and circular velocity curves, while galaxies with morphologies such as Sa-Sbc spread over multiple QSs and circular velocity curves. The distribution of the classification classes shows a tight link between galaxy structure, gravitational potential, and suppression of star-formation in the galaxies.

Astronomical images often show sharp features that are caused by cosmic ray (CR) hits, hot pixels, or non-Gaussian noise. this http URL (van Dokkum 2001) is a widely used edge detection algorithm that identifies and replaces such features. Here we describe dfcosmic, a direct python port of this http URL utilizing PyTorch and C++ to enable efficient performance on both CPUs and GPUs. The code was developed for the MOTHRA array, which is projected to produce more than 1000 large format CMOS images every 15 minutes. Compared to previous python implementations, dfcosmic achieves a speed gain of at least 20%.

We investigate the kinematics of the potential ultra-faint dwarf galaxy (UFD) UMa III/U1 using Bayesian inference to search for the signal of any potential intrinsic rotation. The magnitude of rotation is relevant to estimating the total mass of UMa III/U1, which is critical in determining whether or not UMa III/U1 is in fact a UFD, or possibly a star cluster home to a significant binary fraction. A non-rotating model and a rotational model are fitted for the current total population of member stars of UMa III/U1, finding that a non-rotating model was preferred by a factor of $\sim 5-12 \times$. This was repeated on a reduced population of UMa III/U1, where potential contaminant stars were removed. A similar preference for non-rotation was found for these reduced populations. We calculate a lower-bound rotational mass estimate for UMa III/U1 and a corresponding lower bound mass-to-light ratio of $ 734.4^{+339.0}_{-176.2} \mathrm{M_\odot} / \mathrm{L_\odot} $ for the total population. We conclude that UMa III/U1 still remains an ambiguous object with viable arguments for both the UFD and self-gravitating star cluster scenarios, however under both, UMa III/U1 is unlikely to be supported by rotational pressure.

We present a comprehensive radio polarization study of the Perseus molecular cloud using wideband L-band observations from the Karl G. Jansky Very Large Array. Our survey covers $\sim13.8$~deg$^2$ with a mean Stokes~$I$ sensitivity of $\sim80~\mu$Jy~beam$^{-1}$, enabling the detection of 1410 compact radio sources. From this population, we construct a catalog of source properties, including positions, integrated flux densities, and spectral indices measured across nine spectral windows. The majority of sources exhibit negative spectral indices, consistent with non-thermal synchrotron emission. Using RM Synthesis and RM CLEAN techniques, we detect 205 polarized background sources above an $8\sigma$ threshold. This corresponds to a sampling density of $\sim14.8$~deg$^{-2}$, representing more than an order-of-magnitude increase compared to previous NVSS-based measurements. The resulting rotation measures exhibit coherent large-scale variations across the surveyed region, with additional small-scale structure superimposed. The enhanced sensitivity, frequency coverage, and sampling density of our observations enable a substantially improved mapping of the line-of-sight magnetic field component toward the Perseus molecular cloud compared to previous surveys.

To date, there has been significant interest in globular cluster (GC)-rich ultra-diffuse galaxies (UDGs) and the evidence that they have formed via an unexpected, ``failed galaxy'' formation pathway. The majority of the evidence for ``failed galaxy'' UDGs originates from spectroscopic observations targeting passive GC-rich UDGs, with a focus on those residing in galaxy clusters. In this work, we study the gas-rich, GC-rich group UDG MATLAS-42 and derive its stellar population properties using the Keck Cosmic Web Imager. We measure a redshift for the galaxy ($V_{\rm R, \star}=2433\pm8$~km s$^{-1}$), confirming the previous assumptions that it is both part of the NGC~502 group and has an associated HI-reservoir ($V_{\rm R,HI}=2423\pm 15$~km s$^{-1}$). We measure integrated stellar populations and find the galaxy to be both young (mass-weighted age $=3.2^{+2.6}_{-1.5}$Gyr) and of average-to-low metallicity ($[M/H]=-1.19^{+0.42}_{-0.30}$ dex). When considering these properties in the context of the galaxy's formation, we note it likely does not follow the ``failed galaxy'' formation pathway commonly attributed to GC-rich, cluster UDGs, as it has experienced recent star formation. At most it started failed, however, it has recently rejuvenated its star formation. Finally, we build a toy model of the passive evolution of this galaxy, finding that its relative GC-richness (i.e., $M_{\rm GC}/M_\star$) will likely decrease with time as GCs slowly evaporate/disrupt to contribute to the stellar mass of the galaxy. Due to this, we hypothesise that it is likely not a low redshift analogue of the progenitor to a ``failed galaxy'' UDGs.

In orbital mechanics, Gauss's method for orbit determination (OD) is a popular, minimal assumption solution for obtaining the initial state estimate of a passing resident space object (RSO). Since much of the cislunar domain relies on three-body dynamics, a key assumption of Gauss's method is rendered incompatible, creating a need for a new, minimal assumption method for initial orbit determination (IOD). In this work, we present a framework for short and long term probabilistic target tracking in cislunar space which produces an initial state estimate with as few assumptions as possible. Specifically, we propose an IOD method involving the kinematic fitting of several series of noisy, consecutive ground-based observations. Once a probabilistic initial state estimate in the form of a particle cloud is formed, we apply the powerful Particle Gaussian Mixture (PGM) Filter to reduce the uncertainty of our state estimate over time. This combined IOD/OD framework is demonstrated for several classes of trajectories in cislunar space and compared to better-known filtering frameworks.

Galaxy mergers play a crucial role in shaping the morphology, the star formation, and the mass growth of galaxies across cosmic time. While mergers have been extensively investigated in the local Universe, the evolution of their frequency and physical properties in the early Universe has yet to be fully understood. We investigate the role of mergers in a large spectroscopic sample of 1233 galaxies in the range 5<z<14 with good detection (S/N-pixel > 3) in JWST imaging, covering six different extragalactic fields. We identify mergers from rest-frame optical disturbances in F444W, using a combination of Gini, M-20, and Asymmetry parameters. We find a morphological merger fraction f_m that does not strongly evolve with redshift from z=0 to z ~ 8. The average f_m of our primary major merger condition (Gini+0.14xM-20 > 0.33, A>0.35) is ~ 5 %, which increases to ~13 % for major+minor merger tracers. Accounting for the evolving observability timescale of each tracer, we find that the merger rate is strongly increasing from z=1 to 7 by more than 1 dex, averaging ~ 2 merger/galaxy/Gyr at 5<z<10 for major mergers (in agreement with photometric pair studies), and a factor of 3 higher for minor+major mergers. We also perform SED modeling using available HST+JWST photometry to infer stellar masses and SFRs, using a non parametric star-formation history. We find that mergers at z > 5 have a significant impact, although significantly lower than at z<1, on the SFR of galaxies. When averaged over 10 Myr (comparable to the observability timescale of morphological disturbances), their SFRs are a factor of 1.7 higher than a mass and redshift matched sample of non-mergers, suggesting that mergers trigger new star-formation through short-lived powerful bursty episodes. Despite this, mergers contribute only by 5% - 10% to the mass build-up of galaxies in the redshift range explored.

We model sunspot brightness temperature in the wavelength range 0.3-10mm using the Atacama Large Millimeter/submillimeter Array (ALMA) single-dish measurements together with other instruments. Our modeling idea starts from an existing model, the 1D semi-empirical Avrett-Tian-Landi-Curdt-Wülser (ATLCW) model for sunspots. The original model is then modified in density and temperature with a constant factor over all heights. A least-square fit in both density and temperature to the observed values yields an improved model for sunspot brightness temperature. Observations show that sunspots are darker than QS at wavelengths below 2 mm and brighter beyond, while fitting of the ATLCW sunspot model imply that sunspots should be darker than QS over the entireALMArange. The best-fitted sunspot brightness temperature profiles resulted in 3.6-4.0 times lower sunspot density compared to the original sunspot ATLCW model, or 1.4-1.8 times higher density compared to QS. The temperature came out around 1.2 times higher than the original ATLCW predictions for sunspots, or 1.2 times lower than QS temperature. Even with improved density and temperature parameters, the remaining discrepancy between the bestfitted models and observations indicated that additional improvements are needed in the ATLCW model and modeling assumptions.

In the past two decades, the observed large-scale magnetic field of the active M dwarf star AD Leo has evolved from strongly to mildly negative, raising a suspicion that it might switch polarity. Although magnetic field reversals are observed every 11 years for the Sun, such reversals are poorly understood for M dwarfs. Further, no reversals have been observed for fast-rotating M dwarfs. We examine the properties of AD Leo's large-scale magnetic field and investigate how its evolution affects the space weather environment. We analysed spectropolarimetric data collected by ESPaDOnS and SPIRou in late-2022 and early-2023. With the optical and near-infrared data we computed the longitudinal magnetic field, and with the near-infrared data reconstructed the large-scale magnetic field using Zeeman-Doppler imaging. Using five magnetograms, from 2019 to 2023, we simulated three-dimensional Alfven wave-driven stellar winds using the space weather code SWMF. Although we see an evolution of the large-scale magnetic field of AD Leo, we find no polarity reversal. Rather, we see a restoration of the field to a simpler configuration with consistently negative values for the longitudinal magnetic field strength. Our new large-scale field reconstruction for AD Leo is characterised by a highly axisymmetric, poloidal-dipolar field with an increased mean large-scale field strength. SWMF simulations find the stellar mass loss rates to be, on average, an order of magnitude greater than that of the Sun. Additionally, we find that the habitable zone resides beyond the Alfven surface. Hypothetical magnetised habitable zone planets (with planetary field strengths greater than 0.34 G) would likely be shielded from the incident wind and atmospheric erosion would be negligible. Further, we find variable conditions across each epoch due to the evolving axisymmetry of the stellar large-scale magnetic field.

Several strong solar resonance lines show observable linear scattering polarization signals, holding a great potential for investigating the magnetism of the outer solar atmosphere. Accurately modeling these signals requires solving the radiative transfer (RT) problem for polarized radiation in comprehensive 3D models of the solar atmosphere, in non-local thermodynamic equilibrium, accounting for partial frequency redistribution (PRD) effects. This problem has so far been computationally inaccessible. We present the first scientific application of TRIP, a novel software for the massively parallel solution of the 3D non-LTE RT problem for polarized radiation, including scattering polarization and PRD. We aim to verify the code and explore the combined action of PRD and the 3D structure of the solar atmosphere on scattering polarization. We run TRIP to synthesize the Stokes profiles of the Ca I line at 4227 Å in a 3D model of the solar atmosphere extracted from a radiation magneto-hydrodynamic simulation. We efficiently solve the resulting large-scale problem, with up to $4 \times 10^{10}$ degrees of freedom, with a state-of-the-art preconditioned Krylov method, using up to 20 thousand parallel CPUs. After including verification tests, we find that the joint impact of PRD effects and the detailed 3D structure of the atmospheric model produce disk-center scattering polarization signals in the line wings. These signals are sensitive to the magnetic field, via magneto-optical effects, and to bulk velocity gradients. We also show that the CRD approximation underestimates the amplitude of disk-center line-core signals. This achievement represents a crucial step forward for diagnosing the magnetism of the solar chromosphere and transition region through the quantitative comparisons of synthetic and observational data.

Early studies of ionization in hot Jupiter atmospheres suggest that magnetic coupling can shape their dynamics. These effects may be most pronounced in ultra-hot Jupiters that sustain global magnetic fields. WASP-18 b hosts an ionized dayside atmosphere extending deep enough to be strongly influenced by magnetic forces. Phase curve observations suggest effective magnetic drag, yet its impact on the atmospheric circulation remains poorly constrained. This work explores how magnetic drag in an inhomogeneously ionized atmosphere shapes local and global dynamics to provide a pathway to constrain the planet's magnetic field strength. An analytical parameterization for anisotropic magnetic drag, including both Pedersen and Hall drag components, and associated frictional heating in the globally neutral atmosphere, is implemented in the 3D General Circulation Model ExoRad to study WASP-18 b's atmosphere. Climate characteristics are compared for different drag formulations to assess whether anisotropic physics is required to capture magnetic coupling effects. Anisotropic magnetic drag and frictional heating, both set by local ionization, strongly affect wind strength and direction in the upper atmosphere, modify the day-night circulation, and produce observable temperature asymmetries. They enhance the evening-morning terminator temperature difference near 0.1 bar and generate two off-equator hotspots with reduced eastward shift. The terminator regions are particularly sensitive to how magnetic drag is modeled. Anisotropic magnetic drag damps and redirects dayside-to-nightside winds, partially decoupling the equatorial flow at the morning terminator while maintaining the nightside jet. Locally varying drag forces and frictional heating create asymmetric temperature patterns manifesting as primary and secondary hotspot regions.

The Equation of State (EoS) of dense nuclear matter remains one of the most compelling open questions in high-energy astrophysics. While static EoS models are increasingly well-constrained by observations of binary neutron star (BNS) inspirals, the possibility of a dynamic phase transition occurring during the coalescence has been thus far deferred from standard gravitational-wave (GW) analyses. In this work, we investigate the detectability of such a phase transition, manifesting as a macroscopic shift in the tidal deformability parameter $\Lambda$, using GWs from Neutron Star-Black Hole (NSBH) coalescences. We argue that NSBH systems serve as a cleaner laboratory for this phenomenology than BNS systems due to the absence of the $\tilde{\Lambda}(\Lambda_1,\Lambda_2)$ degeneracy, allowing for the isolation of single-body tidal evolution. We introduce a phenomenological waveform model, TROYE (Transitional Representation Of varYing Equation-of-state), which stitches together two waveform approximants in the time domain to simulate a smooth but rapid transition between two equations of state during the late inspiral. We perform a comprehensive Bayesian injection and recovery campaign on 100 simulated events using the bilby inference library. Our results demonstrate that a phase transition corresponding to a tidal shift of $|\Delta\Lambda| \gtrsim 400$ is detectable with Advanced LIGO design sensitivity, yielding decisive statistical evidence ($\ln B > 5$). We further identify a "V-shape" asymmetry in detectability, where "softening" transitions (decreasing $\Lambda$) are systematically easier to detect than "stiffening" ones due to the specific phase evolution of the tidal sector. Finally, we present "stress tests" showing that the transition remains recoverable even when marginalized over uncertainties in the stitching time and binary mass ratio.

Increasing interest in young exoplanets is leading to a growing effort to understand the formation and evolutionary processes responsible for their different architectures. One interesting target is TOI-5734, a relatively young K3-K4 dwarf star ($500_{-150}^{+300}$ Myr) showing a transiting candidate in photometric observations followed up with high-resolution spectroscopic data. Using Transiting Exoplanet Survey Satellite (TESS) photometry and High Accuracy Radial velocity Planet Searcher for the Northern hemisphere (HARPS-N) radial-velocity (RV) data, we aim to validate the presence of the companion TOI-5734b, measure its planetary mass, size, and its orbital parameters after having characterised its host star. We then aim to study its possible planetary composition and atmospheric evolution. By simultaneously modelling photometry and high-cadence RVs, we measured the radius, mass, and density of TOI-5734b precisely. In particular, we employed Gaussian processes (GPs) with a flexible kernel to discriminate between the stellar activity of the young host and planetary signals. We confirmed the planetary nature of TOI-5734b and measured its orbital period ($P_{\rm b}\sim6.18$ d), radius ($R_{\rm b} = 2.10^{+0.12}_{-0.12}$ $R_\oplus$), and mass ($M_{\rm b}=9.1^{+2.6}_{-2.6}$ $M_\oplus$). By measuring its density ($\rho_{\rm b}=0.98_{-0.30}^{+0.36}$ $\rho_\oplus$), we infer that TOI-5734b is close to having a rocky composition and an almost completely depleted primary envelope. Our results point toward the possibility of considering the target for atmospheric studies with present and future ground- and space-based facilities.

Large main-belt asteroids (diameter $D \gtrsim 120\ \mathrm{km}$) exhibit a surface composition gradient as a function of heliocentric distance, ranging from anhydrous bodies to those rich in hydrated and, possibly, ammoniated materials. Their primordial nature holds key clues to the evolution of the Solar System. It has been suggested that the volatile-rich bodies formed in the outer Solar System and were implanted into the main belt. Alternatively, volatiles may have been delivered via inward-drifting icy pebbles in the protosolar disk. Here, we examine whether in-situ formed rocky embryos can acquire volatiles through pebble accretion as the snowline migrated inward. With the turbulence strength of the disk, radial pebble flux, and the dimensionless stopping time of pebbles (St) as parameters, we calculate the growth of large asteroids. The results are then compared with mass and compositional constraints based on asteroid observations. We find that a moderate pebble flux ($\lesssim18~M_\oplus / \text{Myr}$) is required to enable volatile delivery while preventing the largest asteroids from becoming more massive than Ceres. Water accretion is feasible with $\mathrm{St} \sim 10^{-3}$ ($\sim 1$ mm). However, only the largest asteroids (D > 200 km) can accumulate sufficient ammonia under such conditions. For most asteroids with D between 100 and 200 km, ammonia ice accretion requires $\mathrm{St} \sim 10^{-4}$ ($\sim 100\,\mu$m). Such small particle sizes may pose both theoretical and observational challenges. Thus, we propose that the intermediate-sized, potentially ammonia-bearing asteroids serve as a record of the Solar System's dynamic evolution.

The mass composition of ultra-high-energy cosmic rays (UHECRs) is commonly inferred from the first two moments of the depth of shower maximum, $X_{\rm max}$, measured by fluorescence and hybrid detectors. Such analyses require fast and accurate mappings between the moments of $X_{\rm max}$ and those of the logarithmic mass, $\ln A$, based on realistic air-shower simulations. In this work we provide updated parametrizations of the $X_{\rm max}$ moments and distributions for air showers initiated by nuclei from proton to iron, simulated with CONEX for three state-of-the-art hadronic interaction models: Epos LHC-R, Sibyll 2.3e, and QGSJet-III-01. We parametrize the mean depth $\langle X_{\rm max}\rangle$ and the variance $\sigma^2(X_{\rm max})$ as functions of energy and mass. For the variance we compare a second-order polynomial model with an exponential model. In addition, we model the full $X_{\rm max}$ distributions with a three-parameter generalized Gumbel function. The Gumbel parameters are fitted using an unbinned likelihood and are validated by comparing the implied mean and variance with the raw CONEX samples and with the moment parametrizations. Across the full energy range considered, residuals between the parametrizations (or the Gumbel representation) and the simulations are at the level of a few g cm$^{-2}$ for the mean and a few (g cm$^{-2}$)$^2$ for the variance, making these parametrizations suitable for precision UHECR composition studies and forward-folding analyses of $X_{\rm max}$ distributions.

By cross-matching the eclipsing binary catalog provided by Prsa et al. (2022) with LAMOST medium resolution spectra, we obtained 11 targets. Combining light and radial velocity curves analysis, we have derived accurate physical parameters for these 11 targets. The results indicate that there are 3 deep contact binaries, 3 moderate ones, and 5 shallow ones. Among them, 3 targets exhibit the O'Connell effect, which is attributed to the presence of star-spot on the component's surface. One target is a low-mass ratio deep contact binary and may be contact binary merging candidates. The evolutionary status of these 11 targets was studied using the mass-luminosity and mass-radius relation diagrams. Based on the O-C (Observed minus Calculated) analysis of 10 targets, we found that the orbital periods of 5 contact binaries show a long-term decreasing trend, likely due to the combined effects of mass transfer between the two components and loss of angular momentum. Meanwhile, the orbital periods of the other 4 stars are continuously increasing, which is attributed to mass transfer. Besides, the O-C curves of 3 targets show clear periodic changes, which might result from the Applegate mechanism or the light travel time effect.

Untargeted neutral hydrogen (HI) surveys are well suited to identifying low surface brightness galaxies (LSBGs) that are gas rich, and they offer a complementary view to optically selected populations. We examined the LSBG population as identified via stellar and gaseous content using the MIGHTEE HI XMM-LSS early science data and the publicly available catalogs of optically identified LSBGs. There is currently little overlap between these datasets, with only three galaxies commonly detected. We performed surface brightness photometry of selected MIGHTEE HI detections to find 29 LSBGs, and 26 of these meet the size requirement (R_eff > 1.5 kpc) to be ultra-diffuse galaxies (UDGs). Furthermore, we extracted HI spectra at the location of all optically identified galaxies, placing upper limits on the HI-to-stellar mass ratio in these systems. While the HI-identified population overall tends toward bluer colors, the HI-identified and the optically selected samples mostly overlap in mean effective surface brightness, effective radii, and color. Although it is not straightforward to discern why the HI-identified LSBGs were missed in optical searches, this work highlights the utility of HI surveys in finding these faint systems. The HI-identified LSBGs are gas rich compared to the general HI-selected population. Furthermore, three out of four HI-selected UDGs with available kinematics show no systematic offset from the baryonic Tully-Fisher relation, although we are biased away from sources with low rotational velocities due to the low spectral resolution of the data. This work demonstrates the utility of HI observations for finding and characterizing the low surface brightness Universe.

Solar intensity power spectra are usually characterised by coloured noise, with the spectral energy following a segmented power-law function of frequency, $S(f)\propto f^{-\alpha}$, over different frequency ranges. Typically, the power-law index exceeds 1 in the low-frequency part ($\alpha_\mathrm{lf}$) and is around 0 at high frequencies ($\alpha_\mathrm{hf}$). This work investigates the spatial and temporal evolution of the power-law indices of coronal EUV intensity power spectra in flare-hosting active regions. The spatial distribution of the power-law index in the low-frequency domain ($\alpha_\mathrm{lf}$) closely mirrors EUV intensity images, indicating that $\alpha_\mathrm{lf}$ can reveal the dynamics of coronal plasma structures. Temporally, $\alpha_\mathrm{lf}$ remains stable in quiescent active regions, but it exhibits significant variability before the flare onset. Motivated by this behaviour, we analysed 14 flare events, quantifying the temporal variation of the indices $\alpha_\mathrm{lf}$ and $\alpha_\mathrm{hf}$ as potential flare precursors. In all flare events considered, notable deviations of $\alpha_\mathrm{lf}$ beyond a defined threshold consistently occurred at the flare site within a few minutes before the flare. In some cases, the change in the value of $\alpha_\mathrm{lf} - \alpha_\mathrm{hf}$ was detected within 30--90\, minutes before the flare. This proof-of-concept study suggests that the temporal variation of the power-law indices in coronal EUV intensity power spectra could potentially serve as short-term precursors of solar flares, which needs to be validated on a larger flare sample.

The existence of a distinct mass boundary between the heaviest neutron stars and the lightest black holes remains in question. It is an artefact of our ignorance of the properties of matter at supra-nuclear densities, which exist in the cores of neutron stars. The study addresses these problems with a physics-informed machine learning approach, guided by astrophysical observations. The Transformer model is trained on an agnostically generated ensemble of equations of state. Two geometric parameters are defined on the mass-radius sequence of a neutron star--the front bending and the back bending. The transformer provides a two-step solution: first, the model predicts the maximum mass and radius using the bending parameters. Second, it predicts the square of the sound speed profile, completing the inverse mapping. The prediction is that massive neutron stars form when the sound speed peaks at low density, leading to strong back-bending and an early phase transition to quark matter. Massive stars favour a stiff equation of state at low density, and the density of matter at the star's core is sufficiently small. The maximum mass for a neutron star predicted by the astrophysical constrained transformer model is $2.477$ solar masses, and a minimum radius of about $11.498$ km for a neutron star of $1.4$ solar masses.

DMPP is a radial-velocity survey that aims to detect planets around stars exhibiting anomalous activity signatures, consistent with the presence of close-in evaporating planets. Here, we report the discovery of 7 new planetary signals in 5 different systems: DMPP-2c & d, HD67200/DMPP-6b & c, HD118006/DMPP-7b, HD191122/DMPP-8b, and HD200133/DMPP-9b. We update the orbital parameters of the DMPP-1, DMPP-2, and DMPP-3 systems, along with those of the planetary systems orbiting HD181433, HD39194, and HD89839. We derive detection limits for all 24 targets in our sample with adequate observational coverage, and test the DMPP hypothesis by calculating the occurrence rates for planets in this configuration. We find that the occurrence rates of planets in our sample with orbital periods shorter than $50~\mathrm{d}$ and masses in the range $3$-$10$ M$_\oplus$ are $83.0^{+27.1}_{-24.4}\%$, for $10$-$30$ M$_\oplus$ are $27.0^{+15.0}_{-11.2}\%$, and for $30$-$100$ M$_\oplus$ are $13.9^{+11.8}_{-7.5}\%$. This is significantly higher than the occurrence rates reported by other radial velocity surveys, providing strong support for the DMPP hypothesis.

Ionised regions around OB-type stars are formed at an early stage of their evolution and are important to investigate the formation process of these objects. However, so far only few observations of their physical structure and interaction with the parental molecular cloud have been made. The high resolution and sensitivity of new instruments such as ALMA and the upgraded VLA allow us to fill this gap in our knowledge. We investigate the well known core-halo ultracompact HII region G31.41+0.31 and the surrounding molecular clump with the aim to determine the density and temperature of both the ionised and neutral gas, and possibly obtain a 3D picture of their spacial distribution. We take advantage of the full-band frequency coverage at 3 mm obtained with ALMA for the GUAPOS project to image the emission of a plethora of hydrogen recombination lines towards the G31.41+0.31 HII region as well as several molecular transitions which are tracers of medium-density ($\sim$$10^4$--$10^6$ cm$^{-3}$) gas. The line data are complemented by continuum measurements obtained with the VLA at 1 cm and 7 mm. By fitting these lines also using a model that takes into account non-LTE effects we can investigate the density and temperature structure and the velocity field of the region. Our findings, based on a model fit accounting for non-LTE effects, indicate that the electron temperature of the HII region is mostly spanning a range between 5000 and 6000 K, while the density varies between 2500 and 7500 cm$^{-3}$. All in all, the distribution of these parameters as well as the corresponding velocity field hint at a cometary shaped HII region expanding away from the observer to the NW. The molecular gas appears to be still infalling towards the peak of the UC HII region, and its density and temperature are consistent with pressure confinement of the ionised gas to the SE.

This paper presents the first results from the Dandelion experiment, a directional detection, which searches for 1 meV dark photon dark matter. We use a spherical mirror to convert dark photons into standard millimeter-wavelength photons that can then be detected with an array of 221 Kinetic Inductance Detectors (KIDs) cooled down to 150 mK within the KISS (KIDs Interferometric Spectral Surveyor) camera and operating between 150 and 350 GHz. We used 1480 minutes of data to search for the signal of dark photons in the KID detectors, which is expected to be modulated due to the Earth's rotation. Our main challenge was to deal with a large background from room temperature and stray-light fluctuations. We used a de-correlation analysis to remove these background fluctuations. Templates of the background fluctuations were constructed from a Principal Component Analysis decomposition of detector measurements outside the expected Field of View trajectory of dark photons. We found that the dark photon signal was consistent with zero, giving a new upper limit on the dark photon's kinetic mixing, $\chi$, with masses between 0.6 meV and 1.4 meV. These are the first constraints on dark photons as a dark matter candidate using an array of KIDs at millimeter wavelength.

The Laser Interferometer Space Antenna (LISA) mission aims to detect gravitational waves by interferometrically measuring the change of separation between free-falling test masses (TMs). LISA's interferometers must deliver pm/rtHz sensitivity while accommodating beam tilts up to 1 mrad at the photodiodes, which degrade the interferometric amplitude and increase the induced readout noise coupling. This paper uses an analytical framework developed by the authors in a previous work, based on minimal and justified approximations, that relates beam tilt to the resulting heterodyne signal amplitude in a generic two-beam interferometer with circular-area photodiodes (PDs). A set of interferometric topologies is analyzed, all of high relevance for LISA. We derive the exact amplitude response for an infinite detector and a closed-form approximation for finite detectors, and we validate both against numerical simulations and experimental measurements on an ultra-stable LISA-representative testbed. We then use this model to quantify the phase-noise amplification arising from reduced signal-to-noise ratio (SNR) under tilt, showing that curvature mismatches between the interfering beams substantially enhance this effect. Finally, we introduce a compact function that captures the angular dependence of correlated and uncorrelated phase noises in quadrant photodiode (QPD)-based readouts. Here, a new noise feature, caused by wavefront curvature mismatch, is predicted and measured for the first time. These results indicate that controlling wavefront curvature mismatch in the test mass interferometer (TMI) is essential to limit excess phase noise. The models and results derived in this paper, although originating in the context of LISA, are general and can be applied to any interferometric topology undergoing tilts with pivot on the detector plane.

We present updated constraints on cosmic string and superstring parameters derived from Cosmic Microwave Background (CMB) anisotropies. The constraints are obtained via Markov Chain Monte Carlo (MCMC) analyses of the full \textit{Planck} temperature and polarization data combined with the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6). For ordinary cosmic strings, we constrain the string tension $G\mu$, the string wiggliness parameter $\alpha$, and the self-chopping efficiency $\tilde{c}$. For cosmic superstrings, we constrain the fundamental string tension $G\mu_F$, the string coupling $g_s$, and a parameter $w$ describing the volume of the compact extra dimensions. In both cases, we find significantly tighter bounds on the string tension compared to previous analyses, obtaining $2\sigma$ upper limits of $G\mu < 3.66\times10^{-8}$ and $G\mu_F < 1.38\times10^{-8}$. We also discuss the significant prior-dependence of these results. The computational pipeline used in this work, including a modified version of \texttt{CAMB} capable of computing CMB anisotropies sourced by any active network described via unequal-time correlators, is released publicly as \texttt{CAMBactive} \cite{Raidal_CAMBactive_CAMB_extension_2026}.

Detecting the global 21 cm signal from the epoch of reionization remains a major observational challenge due to bright foregrounds and instrumental systematics. As part of the Colombian Antarctic Telescopes for 21 cm Absorption during Reionization (CANTAR) initiative, we present a simulation and analysis framework to evaluate antenna chromaticity, optimize instrument design, and assess site suitability for global 21 cm experiments. Using frequency-dependent beam models and Haslam-based sky maps, we compute dynamic spectra for the EDGES blade dipole and a set of dipole and novel monopole antennas optimized via particle swarm optimization. The optimized designs exhibit improved spectral smoothness compared to EDGES, particularly in the 70-120 MHz range. We also evaluate latitude-dependent sky brightness and identify mid-latitude sites (-40° to +5°) as optimal for foreground suppression. We apply Bayesian inference together with posterior predictive model validation to the publicly released EDGES data, assessing statistical consistency rather than hypothesis testing or model comparison. We find that physically motivated foreground and ionospheric models are statistically consistent with the data only when a 21 cm absorption feature is excluded. From the validated posterior, we generate a statistically validated ensemble of foreground corrections for use in beam-sky simulations. These results support a two-phase strategy for CANTAR: Antarctic deployments for calibration and testing, and future science operations at mid-latitude sites. Our framework provides a validated path toward robust foreground modeling, antenna design, and systematics control for global 21 cm signal detection.

Deep radio surveys are now producing catalogues with millions of radio sources. Radio sources can have complex morphologies that depend both on the production mechanisms and the local environment. Recently, an unusual class of circular radio sources have been identified that were named "odd radio circles" (ORC). They have sizes of about 1', a circular/elliptical shape and appear edge brightened. Subsequent observations have suggested that this class may comprise a variety of sources. Despite various attempts to explain these sources, their origin remains unclear. The main goal of this work is to increase the number of known ORCs and derive common characteristics that can help identify the origin of these sources. We searched the LOFAR Two Metre Sky Survey (LoTSS) data release 3 (DR3) at 144 MHz for ORCs using a combination of parameter filtering on catalogue entries and visual inspection. We then identified possible optical counterparts and derived information such as redshift, physical size, and spectral index using further radio data at 54 and 1400 MHz. We isolated 18 sources with ORC structures. Four of these are double headed ORCs (ORCs with two rings), and two are new discoveries. We also found 5 new single headed ORCs and 9 candidate ORCs. With this work we significantly expanded the population of known ORCs. Our findings confirms that ORCs are a rare and heterogenous population of radio sources. We confirm the association with large ellipticals in most cases and we note a relation between the ORCs physical size and their integrated spectral index with small ORCs avoiding steep spectra.

We study the influence of the temperature-dependent interaction between dark matter (DM) and neutrinos on the measurement of cosmological parameters. We pay attention to the neutrino mass effects, so that the derivation of Boltzmann equations needs to specify the concrete form of interaction. We work in a model in which the DM-neutrino scatterings are induced by a dimension-six operator, and present the details for deriving the full Boltzmann hierarchy for DM and neutrinos, including a novel method to obtain the fluid approximation for modes entering the horizon. It is shown that our interaction can induce the dark acoustic oscillation in the DM-neutrino fluid, leaving distinct signatures on the CMB and matter power spectra. By using the latest CMB and BAO datasets from Planck, DESI and ACT, the constraint on today's DM-neutrino interaction parameter for the normal neutrino mass ordering reaches $u^0_{\chi-\nu} \lesssim {\cal O}(10^{-13})$, nearly nine orders stronger than that for temperature-independent case in the literature. This can be understood by noting that the scattering cross section increases nearly quadratically with cosmological temperature in the early universe, leading to enhanced effects. We have investigated alternative scenarios with different neutrino mass assumptions. In particular, models with degenerate neutrino masses give rise to weaker constraint of $u^0_{\chi-\nu} \lesssim {\cal O}(10^{-11})$, showing the importance to incorporate the realistic neutrino mass ordering in the fits. Finally, when employing the logarithmic flat prior for $u^0_{\chi-\nu}$, we have shown hints to a nonzero interaction at $95\%$ CL by combining Planck, DESI and ACT data.

A dynamic view of mass assembly is essential for understanding the formation of massive stars and clusters. Interpreting evolutionary diagnostics from Galactic-wide surveys, however, requires careful control of distance and environmental variations. The G316.8 filament provides an ideal laboratory: a 14-pc nearly linear structure composed of three contiguous subregions with comparable molecular gas reservoirs (~10,000 $M_\odot$ each) but spanning a clear evolutionary sequence from an infrared dark cloud (young) through a massive young stellar object (intermediate) to an HII region (evolved). As part of the Linear filament and nested cluster evolution tomography (LANCET) project, we mapped the full filament with the Atacama Compact Array at 1.3 mm, achieving 0.08 pc resolution over 17.1 pc$^2$. Combined with Herschel and APEX/ArTéMiS data, we derived high-resolution temperature and column-density maps. We quantify structural evolution using dense-fragment statistics, column-density PDFs, and $\Delta$-variance analysis. From young to evolved regions, the maximum fragment mass increases from 8 to 490 $M_\odot$, while the dense-gas mass fraction ($>0.5$ g cm$^{-2}$) rises from 0.4% to 9.6%. The N-PDF develops a secondary power-law tail and the $\Delta$-variance slope becomes progressively shallower, indicating ongoing assembly of dense sub-parsec structures. Our further ALMA 12m continuum and spectral line data will extend this dynamic scenarios down to 800 AU scale.

Modern spectroscopic surveys obtain spectra for millions of stars. However, classical spectroscopic methods can often be computationally expensive, rendering them impractical for the analysis of large datasets. We introduce a novel simulation-based deep-learning approach for the efficient analysis of high-resolution stellar spectra to be obtained with the upcoming high-resolution 4MOST spectrograph. We used a suite of synthetic non-local thermodynamic equilibrium (NLTE) spectra generated with Turbospectrum to mimic 4MOST observations and trained a conditional invertible neural network (cINN) for the purpose of predicting self-consistently stellar surface parameters and chemical abundances. The cINN is a neural network architecture that estimates full posterior distributions for the target stellar properties, providing an intrinsic uncertainty estimate. We evaluated the predictive performance of the trained cINN model on both synthetic data and observed spectra of stars. We found that our new cINN trained on NLTE synthetic spectra is capable of recovering stellar parameters with average errors ($\sigma$) of $33$ K for $T_\mathrm{eff}$, $0.16$ dex for $\log(g)$, and $0.12$ dex for [Fe/H], $0.1$ dex for [Ca/Fe], $0.11$ for [Mg/Fe], and $0.51$ dex for [Li/Fe], respectively, at a signal to noise ratio of 250 per Angstrom. From the analysis of the observed spectra of Gaia-ESO / 4MOST / PLATO benchmark stars, we verified that our NLTE estimates for stellar parameters and abundances are consistent with results obtained with the independent code TSFitPy. We conclude that the NLTE cINN is robust and can, theoretically, evaluate 4 million high-resolution 4MOST spectra in less than a day, using GPU acceleration.

Previous numerical simulations have shown that cold clumps can form within hot accretion flows, offering insights into the detailed processes of the state transition in black hole X-ray binaries. However, the evolution of the cold clumps has not been investigated in detail yet. In this paper, we conduct hydrodynamic simulations to investigate the evolution of the cold clumps. In addition to previous result that when the accretion rate is high enough the cold clumps emerge within the hot accretion flow, we found that instead of directly moving toward to the black hole, the clumps moves outward when they initially form. The reason should be the combination of viscous torque and the condensation of hot gas from larger radii, which lead to the slightly super-Keplerian angular momentum of the clumps. After reaching the equilibrium position, the clumps begin to fragment at the inner edge with each fragment moving inward sequentially. Generally, the azimuthal movement of the clumps are quasi-Keplerian, being closer to the outer detached Keplerian cold disk rather than the surrounding sub-Keplerian hot accretion flow, which agrees well with the semi-analytical results for weak coupling case in Wang et al. (2012).

Integral Field Spectroscopy (IFS) surveys offer a unique new landscape in which to learn in both spatial and spectroscopic dimensions and could help uncover previously unknown insights into galaxy evolution. In this work, we demonstrate a new unsupervised deep learning framework using Convolutional Long-Short Term Memory Network Autoencoders to encode generalized feature representations across both spatial and spectroscopic dimensions spanning $19$ optical emission lines (3800A $< \lambda <$ 8000A) among a sample of $\sim 9000$ galaxies from the MaNGA IFS survey. As a demonstrative exercise, we assess our model on a sample of $290$ Active Galactic Nuclei (AGN) and highlight scientifically interesting characteristics of some highly anomalous AGN.

We present X-ray proper motion (PM) measurements of 19 pulsars using new and archival data from the Chandra X-ray Observatory, including pulsar wind trails and X-ray filaments. Precise X-ray PMs are often limited by uncertainties in aligning observations to a common reference frame. Our analysis uses unresolved X-ray flux from stars in the Gaia catalog in addition to X-ray bright point sources for alignment, improving uncertainties. We obtain absolute positions referenced to Gaia with typical astrometric precision $\sim$10 mas and PM statistical uncertainties down to 1.3 mas yr$^{-1}$, the most precise X-ray PM achieved to date. With our improved frame alignment, PM accuracies are now limited by the pulsar flux in most cases. These results reveal a new X-ray filament and illuminate the wind nebula structures and origins of several of these pulsars.

The current canonical approach to publishing cross-section data is to unfold the reconstructed distributions. Detector effects like efficiency and smearing are undone mathematically, yielding distributions in true event properties. This is an ill-posed problem, as even small statistical variations in the reconstructed data can lead to large changes in the unfolded spectra. This work presents an alternative or complementary approach: the response-matrix-centred forward-folding approach. It offers a convenient way to forward-fold model expectations in truth space to reconstructed quantities. These can then be compared to the data directly, similar to what is usually done with full detector simulations within the experimental collaborations. For this, the detector response (efficiency and smearing) is parametrised as a matrix. The effects of the detector on the measurement of a given model is simulated by simply multiplying the binned truth expectation values by this response matrix. Systematic uncertainties in the detector response are handled by providing a set of matrices according to the prior distribution of the detector properties and marginalising over them. Background events can be included in the likelihood calculation by giving background events their own bins in truth space. To facilitate a straight-forward use of response matrices, a new software framework has been developed: the Response Matrix Utilities (ReMU). ReMU is a Python package distributed via the Python Package Index. It only uses widely available, standard scientific Python libraries and does not depend on any custom experiment-specific software. It offers all methods needed to build response matrices from Monte Carlo data sets, use the response matrix to forward-fold truth-level model predictions, and compare the predictions to real data using Bayesian or frequentist statistical inference.

Ideally, all analyses of normally distributed data should include the full covariance information between all data points. In practice, the full covariance matrix between all data points is not always available. Either because a result was published without a covariance matrix, or because one tries to combine multiple results from separate publications. For simple hypothesis tests, it is possible to define robust test statistics that will behave conservatively in the presence on unknown correlations. For model parameter fits, one can inflate the variance by a factor to ensure that things remain conservative at least up to a chosen confidence level. This paper describes a class of robust test statistics for simple hypothesis tests, as well as an algorithm to determine the necessary inflation factor for model parameter fits and Goodness of Fit tests and composite hypothesis tests. It then presents some example applications of the methods to real neutrino interaction data and model comparisons.

Bayesian analyses require that all variable model parameters are given a prior probability distribution. This can pose a challenge for analyses where multiple experiments are combined if these experiments use different parametrisations for their nuisance parameters. If the parameters in the two models describe exactly the same physics, they should be 100% correlated in the prior. If the parameters describe independent physics, they should be uncorrelated. But if they describe related or overlapping physics, it is not trivial to determine what the joint prior distribution should look like. Even if the priors for each experiment are well motivated, the unknown correlations between them can have unintended consequences for the posterior probability of the parameters of interest, potentially leading to underestimated uncertainties. In this paper we show that it is possible to choose a prior parametrisation that ensures conservative posterior uncertainties for the parameters of interest under some very general assumptions.

A very common task in data visualization is to plot many data points with some measured y-value as a function of fixed x-values. Uncertainties on the y-values are typically presented as vertical error bars that represent either a Frequentist confidence interval or Bayesian credible interval for each data point. Most of the time, these error bars represent a 68\% confidence/credibility level, which leads to the intuition that a model fits the data reasonably well if its prediction lies within the error bars of roughly two thirds of the data points. Unfortunately, this and other intuitions no longer work when the uncertainties of the data points are correlated. If the error bars only show the square root of diagonal elements of some covariance matrix with non-negligible off-diagonal elements, we simply do not have enough information in the plot to judge whether a drawn model line agrees well with the data or not. In this paper we will demonstrate this problem and discuss ways to add more information to the plots to make it easier to judge the agreement between the data and some model prediction in the plot, as well as glean some insight where the model might be deficient. This is done by explicitly showing the contribution of the first principal component of the uncertainties, and by displaying the conditional uncertainties of all data points.

Radiative transfer in absorbing-scattering media requires solving a transport equation across a spectral domain with 10^5 - 10^6 molecular absorption lines. Line-by-line (LBL) computation is prohibitively expensive, while existing approximations sacrifice spectral fidelity. We show that the Young-measure homogenization framework produces solution tensors I that admit low-rank tensor-train (TT) decompositions whose bond dimensions remain bounded as the spectral resolution Ns increases. Using molecular line parameters from the HITRAN database for H2O and CO2, we demonstrate that: (i) the TT rank saturates at r = 8 (at tolerance e = 10^-6) from Ns = 16 to 4096, independent of single-scattering albedo, Henyey-Greenstein asymmetry, temperature, and pressure; (ii) quantized tensor-train (QTT) representations achieve sub-linear storage scaling; (iii) in a controlled comparison using identical opacity data and transport solver, the homogenized approach achieves over an order of magnitude lower L2 error than the correlated-k distribution at equal cost; and (iv) for atomic plasma opacity (aluminum at 60 eV, TOPS database), the TT rank saturates at r = 15 with fundamentally different spectral structure (bound-bound and bound-free transitions spanning 12 decades of dynamic range), confirming that rank boundedness is a property of the transport equation rather than any particular opacity source. These results establish that the spectral complexity of radiative transfer has a finite effective rank exploitable by tensor decomposition, complementing the spatial-angular compression achieved by existing TT and dynamical low-rank approaches.

Environmental effects such as hierarchical triple motion can introduce cumulative phase modulation in gravitational-wave signals through time-dependent line-of-sight acceleration. Whether such smooth time-warp distortions are observable depends jointly on deformation strength and signal-to-noise ratio (SNR), yet this relationship has not been quantified in a template-free framework. We study the detectability of these distortions using time-frequency representations derived from the continuous wavelet transform. Instead of reconstruction error alone, we examine trajectory-based statistics, in particular the evolution of the power-weighted frequency centroid. We find that environmental modulation can be detected using a single-sample statistic referenced to an isolated-binary distribution, without requiring matched templates. Across a grid of cumulative phase distortions and SNR, detection performance collapses onto a single scaling parameter defined as the product of phase distortion and SNR. The ROC-AUC follows a sigmoid transition in this parameter. Moderate distortions are detectable at low SNR, whereas smaller distortions require higher SNR. These results indicate that smooth environmental phase modulation is not generically absorbed by intrinsic waveform variability; instead, detectability is governed by a simple scaling between cumulative phase distortion and signal strength.

Minimal electroweak dark matter models are compelling due to their simplicity, though calculations of their freezeout abundance are complicated by nonperturbative effects due to Sommerfeld enhancement and bound-state formation. It has been shown that all individual multiplet scenarios beyond the doublet lead to direct-detection signals above the neutrino floor and thus within the reach of next-generation experiments. If no signals are found, would minimal dark matter be excluded? Yes for the simplest models, but it has been unknown for the important extension of two multiplets coupled by Higgs interactions (Higgs-coupled minimal dark matter). We present a generalized framework for calculating nonperturbative effects for such models that also covers the case of individual multiplets. In this framework, we calculate nonperturbative effects on freezeout as well as the prospects for direct detection, correcting shortcomings and omissions in the literature. Importantly, for the mixed Majorana (odd) and Dirac (even) multiplet combinations 3M2D, 5M4D, and 7M6D, we find that the predicted direct-detection signals can extend below the neutrino floor. Fully testing minimal dark matter will thus require more than direct-detection experiments.

We establish a new SU(N) symmetric model of interaction between the fields of four types: the multiplet of vector fields, which describes the so-called color aether, the multiplet of pseudoscalar fields, which is associated with the multi-component cosmic dark matter, the gauge and gravitational fields. The extended Lagrangian of the model contains a new constructive element, which is based on the covariant SU(N) symmetric divergence of the multiplet of vector fields; this new element, being the multiplet of scalars from the point of view of spacetime transformations and the color vector from the point of view of the SU(N) group space, gives us the possibility to formulate properly the multi-axionic extension of the Peccei-Quinn theory. The hypothesis of a spontaneous polarization of the multi-axionic color aether in the early Universe is presented. The set of self-consistent master equations of the model is derived. An application to cosmology is considered: the obtained master equations are solved for the truncated test model based on the Bianchi-I spacetime platform.

We provide a systematic discussion of the phenomenology of Dark Photon iDM (A$^{\prime}$iDM) where the Standard Model (SM) is extended by a dark sector containing an additional $U(1)_D$ gauge symmetry under which all SM particles are neutral, and that couples to the SM hypercharge gauge boson through a kinetic mixing parameter $\epsilon$. The model contains two Majorana states $\chi_1$ and $\chi_2$ with $\delta=M_{\chi_2}-M_{\chi_1}>0$ and $\chi_1$ the dark matter candidate, and a dark photon $A^{\prime}$ with mass $M_{A^{\prime}}$. Our analysis represents an integration of existing ones, where only specific benchmarks of the A$^{\prime}$iDM scenario have been discussed. In particular, we fix the $U(1)_D$ coupling $\alpha_D$ equal to the electromagnetic one $\alpha_{EM}$ and $\epsilon$ to its experimental upper bound, and perform a complete scan of the remaining parameters $(M_{\chi_1},\delta, M_{A^{\prime}})$, discussing the $\chi_1$ relic abundance, its direct and indirect searches, as well as potential signals from astrophysics and accelerators. Our systematic scan shows that $\alpha_D$ = $\alpha_{EM}$ is not disfavored, as some previous analyses, limited to specific benchmarks, may suggest. We also find that when the $\chi_1$ relic density matches observation direct and indirect searches are not kinematically accessible. On the other hand we find that the projected luminosity of FASER, a detector searching for Long Lived Particles (LLP) decay at the LHC, can probe or rule out the parameters space of the model for $M_{\chi_1}\lesssim$ 7 GeV, 100 MeV $\lesssim \delta\lesssim$ 300 MeV and $M_{A^{\prime}}\lesssim$ 25 GeV. This range of parameter could be significantly extended by the FASER 2 upgrade proposed for the High-Luminosity phase at the LHC. The parameter space probed by LLP seaches partially overlaps with that probed by $\chi_1$ capture in neutron stars.

We present general-relativistic radiation magnetohydrodynamics simulations of binary neutron star mergers performed with GR-Athena++. Neutrino transport is treated using a moment-based, energy-integrated scheme (M1), augmented by neutrino number density evolution (N0). Our implementation is validated through an extensive suite of standard tests and demonstrated to perform robustly under adaptive mesh refinement. As a first application, we simulate the gravitational collapse of a uniformly rotating, magnetized neutron star, demonstrating stable radiation evolution through apparent-horizon formation using a novel excision technique based on the tapering of state vector evolution inside the horizon. To further test robustness in highly dynamic environments, we apply our code to two demanding binary neutron star merger scenarios. We investigate a long-lived remnant with the DD2 equation of state, evolved with full general-relativistic magnetohydrodynamics and M1 neutrino transport. Following this, a gravitational collapse scenario with the SFHo equation of state is explored. We showcase long-term stable evolution on neutrino cooling time-scales, demonstrating robust handling of excision and stable evolution of the post-collapse accretion phase in three-dimensional mergers with magnetic fields and neutrino radiation.

Terrestrial double-$\Lambda$ hypernuclear data and astronomical observations of neutron stars provide complementary constraints on the $\Lambda\Lambda$ interaction. In this work, we investigate the $\Lambda\Lambda$ interaction within a Skyrme energy density functional framework based on the KIDS (Korea-IBS-Daegu-SKKU) models. We employ a Skyrme-type $\Lambda\Lambda$ interaction that includes the standard $s$- and $p$-wave terms, as well as a density-dependent term that effectively represents an $N\Lambda\Lambda$ three-body force. The $s$-wave terms are constrained using data on double-$\Lambda$ hypernuclei supplemented by pseudodata obtained from core + $2\Lambda$ three-body model calculations including heavier hypernuclei. We show that the data on heavier systems are essential to simultaneously constrain the two $s$-wave parameters. We further explore the impact of the $p$-wave and $N\Lambda\Lambda$ components on the neutron-star properties and find that appropriate repulsive contributions of these terms yield consistency with current neutron-star mass-radius observations. These results indicate that the present framework provides phenomenologically acceptable equations of state for dense $(N,\Lambda)$ matter over a wide range of densities and highlight the importance of future experimental data on heavier double-$\Lambda$ hypernuclei.

The possibility of detecting solar oscillation modes using space-based gravitational-wave detectors has been investigated in the context of gravitational-wave interferometry, with Polnarev \cite{Polnarev:2009xf} demonstrating that low-frequency solar modes could, in principle, produce detectable signals in a LISA-type interferometer. Motivated by this work, I revisit the problem using current solar models, updated detector sensitivities, and improved theoretical and observational constraints on mode amplitudes. In this study, I compute the gravitational response of solar oscillation modes using standard solar models generated with \texttt{MESA}, and mode eigenfrequencies and eigenfunctions calculated with \texttt{GYRE}. I focus primarily on solar $g$ modes, evaluating their responses for degree $l=2$ and azimuthal orders $m=0$ and $m=2$. The analysis incorporates both the earlier proposed and the current updated LISA sensitivity curves, and I perform a comparative assessment with the TianQin mission in the relevant low-frequency band. To assess the robustness of the predicted signals, I estimate the gravitational responses using two different standard solar models based on the GS98 and AGSS09 abundance compilations. I find that the resulting signal responses are nearly identical for the two models, indicating that uncertainties in solar metallicity have a negligible impact on the detectability of solar $g$ modes by space-based interferometers.