Papers for Friday, Nov 14 2025

Asymmetries in the observed rotational splittings of a multiplet contain information about the star's rotation profile and internal magnetic field. However, to exploit this information, highly accurate theoretical predictions are needed. We aim to quantify the difference in the predicted mode asymmetries between a 1D perturbative method, and a 2D method that includes a 2D stellar structure model, which takes rotation into account. We then put these differences in the context of asteroseismic measurements of internal magnetic fields. We couple the 1D pulsation codes GYRE and StORM to the 2D stellar structure code ESTER and compare the oscillation predictions with the results from the 2D TOP pulsation code. We focus on ZAMS models representative of rotating $\beta$~Cephei pulsators, going up to 20% of the critical rotation rate. We find a generally good agreement between the oscillation frequencies resulting from the 1D and 2D pulsation codes. Since the magnetic asymmetries are small compared to the differences in the rotational asymmetries resulting from the 1D and 2D predictions, accurate measurements of the magnetic field are in most cases challenging. Differences in the predicted mode asymmetries between 1D perturbative methods and 2D non-perturbative methods can greatly hinder accurate measurements of internal magnetic fields in main-sequence pulsators with low-order modes. Nevertheless, reasonably accurate measurements could be possible with $n_{pg} \ge 2$ modes if the internal rotation is roughly below 10% of the critical rotation frequency for (aligned) magnetic fields on the order of a few hundred kG. While the differences between the 1D and 2D predictions are mostly too large for internal magnetic field detections, the rotational asymmetries predicted by StORM are in general accurate enough for asteroseismic modelling of the stellar rotation in main-sequence stars.

We use the highest-resolution FLAMINGO hydrodynamical simulation to quantify cosmic variance and large-scale coherence in the evolution of massive galaxies at high redshift. FLAMINGO combines a $(1\,\mathrm{cGpc})^3$ volume with baryonic resolution sufficient to identify ${\gtrsim}\,10^3$ independent JWST-like survey volumes of $(100\,\mathrm{cMpc})^3$, providing unprecedented statistics to characterize the extremes of cosmic variance. At $z\,{\simeq}\,6$, the total variance in the number of haloes with $M_{200}\,{\simeq}\,10^{11.5}\,\mathrm{M_\odot}$ (or $M_\ast\,{\simeq}\,10^{10}\,\mathrm{M_\odot}$) is 2--3 times the Poisson expectation, while this ratio decreases with redshift. Similarly, at $z\,{\gtrsim}\,4$, the variance in the most massive halo per JWST-like field is twice the Poisson prediction. We find a pronounced large-scale \emph{conformity}: in volumes ranked by the stellar mass of their most massive galaxy ($M_{\ast,\mathrm{max}}$), the stellar-to-halo mass relation and star-formation efficiency are coherently elevated or suppressed throughout the full $(100\,\mathrm{cMpc})^3$ volume. When accounting for galaxies outside the volume, this signal persists only to radii $\lesssim 50\,\mathrm{cMpc}$, demonstrating that the detectable conformity is enhanced by the survey footprint. Moreover, $M_{\ast,\mathrm{max}}$ is a better predictor of the volume-wide efficiency of massive galaxies than the total number counts, which mainly trace clustering. Finally, the stellar fraction of the most massive galaxies peaks at $f_\ast\,{=}\,M_\ast\,/\,(M_{200}f_{\rm b,cosmic})\,{\simeq}\,0.2$ at $z\,{\simeq}\,5$, with a narrower dispersion in $f_\ast$ at fixed redshift and stronger redshift evolution than commonly assumed. These results show that both cosmic variance and footprint-confined conformity must be modelled when interpreting early massive galaxy populations in JWST fields.

The sulfur chemistry in protoplanetary disks influences the properties of nascent planets, including potential habitability. Although the inventory of sulfur molecules in disks has gradually increased over the last decade, CS is still the most commonly-observed sulfur-bearing species and it is expected to be the dominant gas-phase sulfur carrier beyond the water snowline. Despite this, few dedicated multi-line observations exist, and thus the typical disk CS chemistry is not well constrained. Moreover, it is unclear how that chemistry - and in turn, the bulk volatile sulfur reservoir - varies with stellar and disk properties. Here, we present the largest survey of CS to date, combining both new and archival observations from ALMA, SMA, and NOEMA of 12 planet-forming disks, covering a range of stellar spectral types and dust morphologies. Using these data, we derived disk-integrated CS gas excitation conditions in each source. Overall, CS chemistry appears similar across our sample with rotational temperatures of ${\approx}$10-40 K and column densities between 10$^{12}$-10$^{13}$ cm$^{-2}$. CS column densities do not show strong trends with most source properties, which broadly suggests that CS chemistry is not highly sensitive to disk structure or stellar characteristics. We do, however, identify a positive correlation between stellar X-ray luminosity and CS column density, which indicates that the dominant CS formation pathway is likely via ion-neutral reactions in the upper disk layers, where X-ray-enhanced S$^+$ and C$^+$ drive abundant CS production. Thus, using CS as a tracer of gas-phase sulfur abundance requires a nuanced approach that accounts for its emitting region and dependence on X-ray luminosity.

Mixing between dark photons and visible photons leads to substantial anisotropies in the cosmic microwave background due to resonant conversions of visible photons into dark photons in baryonic matter found in dark matter halos. In this Letter, we forecast the sensitivity of the Square Kilometre Array (SKA) to this signal. We find that SKA could be the first experiment to discover dark photons with a mass between $10^{-13}$ and $5\times 10^{-12}$ eV and kinetic mixing parameter $\epsilon$ as small as $\sim 10^{-8}$ by cross-correlating their data with a low-redshift galaxy survey, potentially improving on the sensitivity from a similar analysis using Planck data by a factor of 4 in $\epsilon$. This improvement is largely due to an enhancement of the signal at low frequencies and the unique experimental advantages of radio telescopes such as small beam sizes.

Saturnian moon Titan presents a compelling testbed for probing prebiotic chemistry beyond early Earth. Impact-generated melt pools provide transient aqueous habitats in an otherwise cryogenic environment. We use Cantera equilibrium models to assess whether mixtures of hydrogen cyanide (HCN), acetylene (C2H2), and ammonia (NH3) can drive amino acid synthesis in Selk-sized craters. Across twenty-one amino acids (twenty proteinogenic plus beta-alanine), NH3-free systems yield only proline, alanine, and beta-alanine, whereas adding as little as 1% NH3 (relative to H2O) renders almost the full suite accessible, with yields peaking at 2% and tapering thereafter. The NH3-free alanine result implies alternative pathways beyond classical Strecker or aminonitrile hydrolysis, suggesting acetylene, abundant on Titan but scarce on early Earth, as a plausible feedstock. We identify acrylonitrile (detected on Titan) as a thermodynamically favorable intermediate that can convert to alanine under aqueous conditions in an NH3-free pathway. For glycine and alanine production from nitrile hydrolysis, comparison with laboratory kinetics shows that our equilibrium models predict near-complete conversion, while observed rates yield only partial products over weeks. Yet estimated chemical equilibration times (years-centuries) are far shorter than melt lifetimes, supporting plausibility of equilibrium in situ. These predictions are directly testable with Dragonfly mass spectrometer (DraMS), for which we recommend pre-flight standards to test proline, alanine, beta-alanine, cysteine, and methionine. The first three offer the best chances for amino acid detection regardless of ammonia availability; the latter two offer diagnostic tools for determining the presence of reactive sulfur in post-impact Titan ponds.

This is the second part in a pair of papers forecasting the sensitivity of the Square Kilometre Array (SKA) to dark photons, a highly motivated, simple extension of the Standard Model. Through a kinetic mixing term, visible photons from the cosmic microwave background can resonantly convert into dark photons, generating new temperature anisotropies in the sky. In this work, we detail the entire analysis pipeline that we use to compute SKA's sensitivity, focusing on resonant conversions that occur in the intergalactic medium. We also discuss the sensitivity of 21-cm experiments to dark photons. Our results show that both SKA in combination with galaxy surveys and 21-cm experiments could discover dark photons with masses between $5\times 10^{-15}$ and $5\times 10^{-12}$ eV, and kinetic mixing parameter $\epsilon$ as low as $10^{-8}$.

Here we introduce the SEEDZ simulations, a suite of cosmological hydrodynamic simulations exploring the formation and growth of the first massive black holes in the Universe. SEEDZ includes models for Population III star formation, supernovae explosions and the resulting formation of light seed black holes, metal enrichment and subsequent Population II star formation, heavy seed black hole formation, Eddington and super-Eddington accretion schemes as well as black hole feedback. In this paper, we cover the overall methodologies employed and present our current results at $z=15$. Our main result so far is that black holes initially grow faster than their host galaxy, and hence over-massive black holes are a feature of the high-redshift Universe. The fundamental black hole-galaxy relationships we observe at $z = 0$ (especially the M$_{\rm BH}$ - M$_*$ relationship) likely only emerge in more mature galaxies. At high-redshift, that relationship has not yet been established. We find that even at these high redshifts, MBHs can grow from their initial heavy seed mass of $\sim$10$^4$ M$_\odot$ up to 10$^6$ M$_\odot$. At the high end of our MBH masses, our simulated galaxy M$_{\rm BH}$ - M$_*$ relations match the observed high redshift trends i.e. over-massive BHs with M$_{\rm BH}$/M$_{\rm star} \sim 10^{-2}$. This initial set of simulations will continue to run down to $z=10$, where we will perform a comprehensive comparison of simulated MBH number densities and M$_{\rm BH}$ - M$_*$ relations with JWST observations. Further simulations with higher resolution will then follow.

We present Chandra X-ray Observatory and Hubble Space Telescope (HST) follow-up observations of 12 dwarf galaxies from Reines et al. (2020) that are potential hosts of radio-selected active galactic nuclei (AGNs), eight of which are non-nuclear and possible ``wandering" black holes (BHs). Our multi-wavelength analysis indicates a heterogeneous sample with five radio sources detected at both X-ray and optical wavelengths within positional uncertainties and non-detections for the remaining objects. Of the radio objects detected in the X-ray/optical, three have multi-wavelength evidence for hosting nuclear massive BHs and one object is consistent with an extreme compact starburst. Only one of the off-nuclear radio sources has a significant optical counterpart and we present Palomar spectroscopy that identifies this object as a background AGN. We cannot definitively determine if the seven remaining off-nuclear radio sources are wandering massive BHs in the target dwarf galaxies or background AGNs, although the three sources with the largest offsets have compact radio cores detected with the Very Large Baseline Array and are consistent with expectations for background AGNs (Sargent et al 2022). Our HST sensitivity limits also allow for wandering massive BHs in the target dwarf galaxies that are hosted by stellar clusters with masses $\lesssim 10^6 M_\odot$.

Quantitative morphology provides a key probe of galaxy evolution across cosmic time and environments. However, these metrics can be biased by changes in imaging quality - resolution and depth - either across the survey area or the sample. To prepare for the upcoming Rubin LSST data, we investigate this bias for all metrics measured by statmorph and single-component Sérsic fitting with Galfit. We find that geometrical measurements (ellipticity, axis ratio, Petrosian radius, and effective radius) are fairly robust at most depths and resolutions. Light concentration measurements ($C$, Gini, $M_{20}$) systematically decrease with resolution, leading low-mass or high-redshift bulge-dominated sources to appear indistinguishable from disks. Sérsic index $n$, while unbiased, suffers from a 20-40% uncertainty due to degeneracies in the Sérsic fit. Disturbance measurements ($A$, $A_S$, $D$) depend on signal-to-noise and are thus affected by noise and surface-brightness dimming. We quantify this dependence for each parameter, offer empirical correction functions, and show that the evolution in $C$ observed in JWST galaxies can be explained purely by observational biases. We propose two new measurements - isophotal asymmetry $A_X$ and substructure $St$ - that aim to resolve some of these biases. Finally, we provide a Python package statmorph-lsst implementing these changes and a full dataset that enables tests of custom functions (see text for links).

We demonstrate the necessity of fractional calculus for modeling anomalous diffusion in stellar dynamics, specifically Resonant Relaxation (RR) near a supermassive black hole (SMBH). Standard transport theories rely on the local Fokker-Planck (FP) equation, a formalism restricted to Gaussian processes governed by the Central Limit Theorem (CLT). This approach fails for RR, which is a superdiffusive Lévy flight characterized by non-local transport and governed by the Generalized Central Limit Theorem (GCLT). We apply the space-fractional Fokker-Planck equation (FFPE), utilizing non-local Riemann-Liouville operators, to resolve major discrepancies between local theory and observations. In transient regimes, the FFPE predicts an immediate, linear flux ($\Gamma(t) \propto t$), consistent with high Tidal Disruption Event (TDE) rates in post-starburst galaxies, whereas local FP models predict an unphysical exponential delay ($\Gamma(t) \propto \exp(-C/t)$). Furthermore, we prove mathematically that the non-local integral operators permit ``barrier jumping''. This mechanism nullifies transport bottlenecks like the proposed Schwarzschild Barrier (SB). Local models incorrectly interpret the SB as severely suppressing Extreme Mass-Ratio Inspiral (EMRI) rates. We validate our theoretical findings using direct-summation $N$-body simulations incorporating relativistic corrections. The simulations confirm that particle flux remains continuous across the SB in the regime where RR dominates, demonstrating that the barrier does not inhibit EMRI production. The fractional framework provides the correct physical description for non-local transport, resolving long-standing problems concerning TDE and EMRI rates.

Galaxy groups and clusters are excellent probes of large-scale structure and are shaped by some of the most energetic physical processes in the Universe. They follow a tight scaling relation of X-ray luminosity with halo mass. However, predicting the dependence of the scatter in this relation on mass and redshift is challenging, due to the statistical requirement of large simulation volumes. Using the large volume cosmological hydrodynamical simulations for galaxy cluster physics FLAMINGO and TNG300+TNG-Cluster, we fit this relation and its scatter, focusing on $M_{\rm 500c}>10^{13}~\mathrm{M_\odot}$ and $z \leq 2$. We find qualitatively similar, but quantitatively different results for the two models. For the first time, we study ways to reduce the scatter using properties beyond X-ray luminosity, namely six ICM, six galaxy, and eleven dark matter halo properties. For both FLAMINGO and TNG300+TNG-Cluster, the gas fraction and thermal Sunyaev-Zel'dovich (SZ) signal correlate strongest with X-ray scatter, reducing it by over 50% when accounting for their partial correlations. Galaxy and halo properties correlate weakly with X-ray scatter, typically reducing it by 10-20%. Our results are qualitatively robust across different FLAMINGO feedback variations, though the correlations weaken for stronger feedback and with increasing redshift. Differences between FLAMINGO and TNG300+TNG-Cluster are only apparent at the high-mass end - where e.g. the galaxy stellar age correlates strongly for FLAMINGO, but not for TNG300+TNG-Cluster - confirming robustness across physics implementations. We provide fitting formulas for the scatter and its corrections, for direct application to cosmological analyses and observational data.

The aim of extensive air shower (EAS) analysis is to reconstruct the physical parameters of the primary particle that initiated the shower. The TAIGA experiment is a hybrid detector system that combines several imaging atmospheric Cherenkov telescopes (IACTs) and an array of non-imaging Cherenkov detectors (TAIGA-HiSCORE) for EAS detection. Because the signals recorded by different detector types differ in physical nature, the direct merging of data is unfeasible, which complicates multimodal analysis. Currently, to analyze data from the IACTs and TAIGA-HiSCORE, a set of auxiliary parameters specific to each detector type is calculated from the recorded signals. These parameters are chosen empirically, so there is no certainty that they retain all important information and are the best suited for the respective problems. We propose to use autoencoders (AE) for the analysis of TAIGA experimental data and replace the conventionally used auxiliary parameters with the parameters of the AE latent space. The advantage of the AE latent space parameters is that they preserve essential physics from experimental data without prior assumptions. This approach also holds potential for enabling seamless integration of heterogeneous IACT and HiSCORE data through a joint latent space. To reconstruct the parameters of the primary particle of the EAS from the latent space of the AE, a separate artificial neural network is used. In this paper, the proposed approach is used to reconstruct the energy of the EAS primary particles based on Monte Carlo simulation data for TAIGA-HiSCORE. The dependence of the energy determination accuracy on the dimensionality of the latent space is analyzed, and these results are also compared with the results obtained by the conventional technique. It is shown that when using the AE latent space, the energy of the primary particle is reconstructed with satisfactory accuracy.

We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmological simulations, we show that our algorithm is able to determine whether ``observed'' data is consistent with its training domain, returning confidence estimates as well as accurate parameter estimations. We apply our algorithm to two-dimensional images of galaxy clusters from the BAHAMAS-SIDM and DARKSKIES simulations with the aim to measure the self-interaction cross-section of dark matter. Through deep compact clustering we construct an informative latent space where galaxy clusters are mapped to the latent space forming ``latent-clusters'' for each simulation, with the location of the latent-cluster corresponding to the macroscopic parameters, such as the cross-section, $\sigma_{\rm DM}/m$. We then pass through mock observations, where the location of the observed latent-cluster informs us of which properties are shared with the training data. If the observed latent-cluster shares no similarities with latent-clusters from the known simulations, we can conclude that our simulations do not represent the observations and discard any parameter estimations, thus providing us with a method to measure machine learning confidence. This method serves as a blueprint for transparent and robust inference that is in demand in scientific machine learning.

Light scattering by dust particles is often modeled assuming the dust is spherical for numerical simplicity and speed. However, real dust particles have highly irregular morphologies that significantly affect their scattering properties. We have developed glitterin, a neural network trained to predict light scattering from irregularly shaped dust grains, offering a computationally efficient alternative to Lorenz-Mie theory. We computed scattering properties using the Discrete Dipole Approximation code ADDA for irregularly shaped particles across size parameters x from 0.1 to 65, covering a range in complex refractive index m that includes astrosilicates, pyroxene, enstatite, water-ice, etc. The neural network operates at millisecond timescales while maintaining superior accuracy compared to linear interpolation. Irregular grains exhibit x-dependent deviations from spherical predictions. At small x, cross-sections approach volume-equivalent spheres for low m. At large x, irregular grains show enhanced cross-sections due to greater geometric extension. Increasing m also enhances the absorption cross-section relative to the volume-equivalent spheres. This differential x and m dependence creates mid-IR solid-state features distinct from predictions from spherical grains. Validation against laboratory measurements of forsterite and hematite demonstrates that our neural network captures both qualitative and quantitative behaviors more accurately than spherical models. Millimeter-wavelength applications reveal that spherical grains produce opposite polarization signatures compared to irregular grains, potentially relaxing stringent ~100um grain size constraints in protoplanetary disks. glitterin is publicly available and alleviates the computational barriers to incorporating emission and scattering of realistic grain morphologies.

Context. The presence of a stellar companion can strongly influence the architecture and long-term stability of planetary systems. Motivated by the discovery of exoplanets exhibiting extremely high eccentricities (e >= 0.8) in systems with a binary companion, we investigate how planetary orbits around one star (S-type configuration) evolve under the gravitational perturbations of the companion. Aims. We aim to assess the role of a stellar companion in shaping the orbital evolution of S-type planets and to explore whether dynamical interactions in such environments can account for the formation of highly eccentric planets. Methods. We performed a suite of N-body simulations, modeling systems initially composed of three Jupiter-mass planets on nearly circular, coplanar orbits around the primary star. We systematically varied the semi-major axis, eccentricity, and inclination of the stellar companion, to characterize the conditions under which extreme eccentricities can be excited. Results. Our results show that dynamical processes such as planet-planet scattering and secular mechanisms--including the von Zeipel-Kozai-Lidov effect induced by the binary--often act together to produce abrupt and significant changes in planetary orbital evolution, with the outcome strongly dependent on the binary separation. The binary's eccentricity primarily dictates the number of surviving planets, while its inclination not only governs the final eccentricities of those survivors but also drives their orbits to align with the binary plane. Our simulations successfully reproduce the high eccentricities and compact orbits observed in four observed systems, showing close agreement between the modeled configurations and the actual systems.

Here we describe a Jupyter notebook demonstrating methods for the reduction and analysis of exoplanet transit observations taken with the WFC3/UVIS G280 grism. Released on Space Telescope's hst_notebooks GitHub repository, this notebook presents an example workflow for processing time-series observations taken with the G280 grism - from the calibrated flat-fielded spectra to transit light curves ready for fitting. The specific routines presented in the notebook are explained here, and are meant to highlight data reduction steps that users will typically apply to extract transit light curves. The steps include background subtraction, spatial and temporal cosmic ray correction, spectral trace fitting, spectral extraction, and light curve generation. The end products of the routines in the Jupyter notebook are the raw broadband and spectroscopic light curves, which can be ingested into publicly available light curve fitting tools to extract planetary transmission spectra.

We present a Physics-Informed Neural Network (PINN) framework for reconstructing the redshift-dependent Hubble parameter \(H(z)\) within the Tsallis Holographic Dark Energy (THDE) model extended by massive neutrinos. In this approach, the modified Friedmann equation is incorporated into the neural network loss function, enabling training on Cosmic Chronometers data up to \(z \leq 2\). The framework allows for the simultaneous estimation of the Hubble constant \(H_0\), the neutrino density parameter \(\Omega_\nu\), and the Tsallis non-extensivity index \(\delta\). Uncertainty quantification is performed through dropout simulations, resulting in statistically consistent \(1\sigma\) confidence bands. Our results show that the THDE+$\nu$ model, reconstructed via PINN, alleviates the statistical Hubble tension from the canonical \(\sim 5\sigma\) level down to a range of \(0.5\sigma \leq T \leq 2.2\sigma\), depending on the redshift sampling. Additionally, we constrain the total neutrino mass to \(\Sigma m_\nu < 0.11\,\text{eV}\). A detailed comparison with the traditional Markov Chain Monte Carlo (MCMC) analysis demonstrates the consistency of both methods, while highlighting the competitiveness of the PINN-based THDE framework as a robust, data-driven approach for non-parametric cosmological inference within generalized thermodynamics.

The CLEAR Space Weather Center of Excellence's solar energetic particle (SEP) prediction model, SOlar wind with FIeld lines and Energetic particles (SOFIE), was run and evaluated on-site during the Space Weather Prediction Testbed (SWPT) exercise at NOAA's Space Weather Prediction Center (SWPC) in May 2025. As a physics-based SEP simulation and prediction model, SOFIE simulates the acceleration and transport of energetic particles in the coronal mass ejection (CME) driven shock in the solar corona and inner heliosphere. It has been validated against historical events. However, questions remain regarding whether a physics-based model, traditionally considered computationally expensive, could meet operational needs. The SWPT exercise offered a valuable opportunity to evaluate SOFIE's performance under simulated real-time conditions. Interactive feedback during the exercise from SWPC forecasters, SRAG console operators, CCMC personnel, and M2M SWAO analysts led to significant strategic improvements in the model setup to meet operational requirements. The resolution of the simulation domain was optimized by combining a coarser background grid with higher-resolution regions along the CME path and facing toward Earth, reducing computational cost without compromising accuracy. In this work, we present the operational performance of SOFIE and its capability to predict SEP fluxes significantly faster than real time. SOFIE was able to complete a 4-day SEP simulation within 5 hours on a supercomputer with 1,000 CPU cores during the SWPT exercise. This marks a critical milestone in demonstrating both the robustness and operational usefulness of SOFIE to support future human space exploration.

Through 3D hydrodynamical simulations, we explore the impact of Type Ia supernova (SN) explosions on the star formation history and chemical properties of second-generation (SG) stars in young globular clusters with masses of 10^5-10^6 Msun. We assume that the SG is formed out of the asymptotic giant branch (AGB) ejecta of first-generation stars plus pristine interstellar medium gas which is modelled as a uniform gas moving at a constant velocity towards the cluster. We tested two values for the infalling gas density of 10^(-24) and 10^(23) g/cm^3. Type Ia SNe start to explode together with the release of gas from the most massive AGB stars. Three simulated models are analyzed. In the low-mass and low-density scenario, we find that SNe Ia quench star formation which however restarts when the gas cools down again in between two explosions. SG stars are dominated by a He-rich population (Y>0.33), which is poorly diluted by pristine gas. In the high-mass models, star formation is mildly affected, while the He composition is significantly altered as exploding SNe prevent the accretion of pristine gas and therefore extremely helium-rich stars form. In the high-density model, such weak gas accretion leads to a maximum enhancement in helium mass fraction much larger than the observed one and not correlating with the initial cluster mass as found in models without Type Ia SNe. As for the iron content, small spreads have been found in all models, but the SG is less homogeneous than the FG, at variance with current observations.

We present five datasets of high-resolution optical emission spectra of the ultra-hot Jupiter KELT-20 b with the PEPSI spectrograph. Using a Bayesian retrieval framework, we constrain its dayside pressure-temperature profile and abundances of Fe, Ni, and Ca, providing the first measurements for Ni and Ca for KELT-20 b in emission. We retrieve the pre- and post-eclipse datasets separately (corresponding to the evening and morning sides, respectively), and compare the constraints on their thermal structures and chemical abundances. We constrain lower abundances in the pre-eclipse datasets compared to the post-eclipse datasets. We interpret these results with an equilibrium chemistry model which suggests ~10-30x supersolar refractory abundances. Due to the well-known degeneracy between absolute abundances and continuum opacities, the abundance ratios are more precise probes of the planetary abundances. Therefore we measure the abundance ratios [Ni/Fe] and [Ca/Fe] across these datasets and find they agree within 1-sigma. We constrain [Ni/Fe] to be consistent with solar within 2-sigma, and [Ca/Fe] to be 0.001-0.01x solar, not accounting for ionization. We compare these abundance ratios with literature results for KELT-20 b in transmission, and find they agree within 2-sigma, suggesting that even though the abundances vary significantly as a function of phase, the abundance ratios of these species remain relatively constant. We find a ~100 K difference in temperature at the top of the thermal inversion, suggesting a hotter evening side than morning side and underscoring the importance of considering 3D effects when studying ultra-hot Jupiters.

Chemical abundance determinations from stellar spectra are challenged by observational noise, limitations in stellar models, and departures from simplifying assumptions. While traditional and supervised machine learning methods have made remarkable progress in estimating atmospheric parameters and chemical compositions within existing physical models, these factors still constrain our ability to fully exploit the vast data sets provided by modern spectroscopic surveys. We aim to develop a self-supervised, disentangled representation learning framework that extracts chemically meaningful features directly from spectra, without relying on externally imposed label catalogs. We build a variational autoencoder-based representation learning model with physics-inspired structure: multiple decoders each focus on spectral regions dominated by a particular element, enforcing that each latent dimension maps to a single abundance. To evaluate the potential application of our framework, we trained and validated the model on low-resolution, low signal-to-noise synthetic spectra focusing on $\rm [Fe/H]$, $\rm [C/Fe]$, and $\rm [\alpha/Fe]$. We then demonstrate how the trained model can be used to flag stars as chemically enhanced or depleted in these abundances based on their position within the latent distribution. Our model successfully learns a representation of spectra whose axes correlate tightly with the target abundances ($r=0.92\pm0.01$ for $\rm [Fe/H]$, $r=0.92\pm0.01$ for $\rm [C/Fe]$, $r=0.82\pm0.02$ for $\rm [\alpha/Fe]$). The disentangled representations provide a robust means to distinguish stars based on their chemical properties, offering an efficient and scalable solution for large spectroscopic surveys.

We present an analysis of atmospheric pressure variability inside Jezero Crater on Mars based on measurements from the MEDA meteorological station aboard NASA's Perseverance rover. Pressure data from Sols 182, 361, 504, and 658 reveal seasonal and diurnal fluctuations linked to solar insolation, CO2 condensation and sublimation cycles, and local geomorphology. During Sol 504, an unexpected pressure increase was recorded despite coinciding with the onset of northern winter, suggesting the influence of perihelion and dust-related thermal tides. Statistical parameters such as mean, standard deviation, and amplitude show that Jezero exhibits larger diurnal pressure swings than Gale Crater, mainly due to its lower latitude and topographic confinement. These results demonstrate the strong coupling between Martian atmospheric dynamics, orbital configuration, and local topography, and illustrate the value of MEDA data for characterizing short-term and seasonal variations in the Martian boundary layer.

Long-period radio transients (LPTs) are a recently identified phenomenon that challenge our current understanding of compact objects and coherent radio emission mechanisms. These objects emit radio pulses similar to those of pulsars, but at much longer periods -- on the order of minutes to hours. With duty cycles of only a few percent, individual pulses have been observed to last between 10 and 1000 seconds. This places LPTs in a timescale gap between the two main techniques used in transient radio searches: time-series analysis at millisecond to second timescales, and image-plane searches sensitive to variability on the scale of days. As a result, LPTs remained undetected until recently, and only a handful are currently known. To increase the sample of known LPTs, we conducted a dedicated search using 200 hours of archival data from the ASKAP Evolutionary Map of the Universe survey, covering 750 deg$^2$ of sky at the shortest possible imaging time step of 10-seconds. This represents the first large-scale search using ASKAP data at second-scale resolution. Although no LPTs were detected, we identified flares from six stars, at least one had never been detected in the radio regime before. We placed a lower limit on the transient surface density of $2.21\times10^{-6}$ deg$^{-2}$ at a 10-second timescale, with a sensitivity of 16.9 mJy. Our findings evaluate the feasibility of detecting radio transients using 10-second imaging with ASKAP and provide insights into improving detection pipelines and observation strategies for LPTs.

We use the GALPROP cosmic ray (CR) propagation framework to model the diffuse neutrino and gamma-ray emissions from the Galaxy. A collection of realistic bounding models are developed and predictions of the resulting neutrino and gamma-ray signals are compared to the IceCube and LHAASO data up to PeV energies. We find that all the GALPROP models are consistent with the neutrino data within uncertainties. They are also consistent with expectations of neutrino emissions derived from LHAASO data when accounting for possible gamma-ray point source contamination. The new models present state-of-the-art predictions for the VHE neutrino emissions from the Galaxy that may be used for future neutrino searches.

Modeling the contact surfaces formed by pebble collisions is crucial to understanding the formation process of comets, which are thought to be composed of pebbles. In this paper, we develop a new model to estimate the contact surface radius and the number of contact points as functions of collision velocity, and examine the formation process of comet 67P/Churyumov--Gerasimenko. Our model is based on the compressive strength of dust aggregates obtained from numerical simulations and assumes that all the impact energy of the pebbles is used for their mutual compression. We compare our model with numerical simulations of pebble collisions, in which we prepare the initial pebbles in the form of compressed dust aggregate spheres and measure the contact surface and pebble radii using two- and three-dimensional characteristic radii, respectively. We also apply our model to the formation scenario of comet 67P, whose tensile strength and bulk density have already been estimated in the literature. We find that its low tensile strength points to formation via pebble collisions at velocities below $\sim10\mathrm{\ cm\ s^{-1}}$ when a microscopic filling factor of pebbles is lower than 0.6, suggesting that inelastic bouncing collisions played a role in damping the collision velocities. By assuming that the pebble collision velocity is determined by the transition velocity between bouncing and sticking, we estimate the pebble radius inside comet 67P to be 130 $\mathrm{\mu m}$ or smaller.

GRB 250702B shows ultra long, episodic prompt activity, with three hard gamma ray episodes over about 3.2 h with quasi regular spacing P ~ 2825 s, preceded by a soft X ray flare about one day earlier. We interpret these phenomena with a unified scenario in which a stellar mass black hole accretes from a massive, misaligned debris disk and launches a magnetically dominated, precessing, structured (spine sheath) jet. The engine clock arises from Lense Thirring precession of the outer annulus of a geometrically thick inner torus at radius r ~ 250 to 300 gravitational radii, while the hard spectra reflect magnetic reconnection dissipation in the spine. A slightly off axis viewing geometry resolves the apparent opening angle tension without invoking late energy injection. "Missing" pulses in the second and third cycles occur naturally when low amplitude nutation causes the beaming cone to miss the line of sight. The model yields concrete, falsifiable predictions, providing a self consistent explanation of GRB 250702B radiative and outflow anomalies.

This study investigates the evolution of the star-forming fraction ($F_{\mathrm{sf}}$) of Brightest Cluster Galaxies (BCGs) at $z<0.8$, using the galaxy clusters identified from the Legacy Imaging Surveys from the Dark Energy Spectroscopic Instrument (DESI). Star-forming galaxies are identified using the $g-z$ color, and $F_{\mathrm{sf}}$ is measured as a function of redshift, cluster halo mass, and galaxy stellar mass. Field galaxies are used as a comparison sample to reduce selection effects. For BCGs, $F_{\mathrm{sf}}$ increases with redshift, showing a slow rise below $z \sim 0.4 - 0.5$ and a more rapid increase above this range. In contrast, $F_{\mathrm{sf}}$ decreases with increasing cluster halo mass and BCG stellar mass. At the low stellar mass end, BCGs exhibit higher star-forming fractions than field galaxies, suggesting enhanced star formation likely fueled by cold gas accretion from the intracluster medium. Also, star-forming BCGs tend to show larger projected offsets from the optical cluster density peak than quenching BCGs, indicating ongoing assembly. The analysis of the specific star formation rate (sSFR) further indicates a transition in the dominant mechanism driving star formation in BCGs: cooling flows are likely responsible at low redshift, while gas-rich mergers play a greater role at higher redshift. The shift in dominance occurs around $z \sim 0.5$, aligning with the steep rise in $F_{\mathrm{sf}}$ of BCG.

POLAR-2 is a next-generation space astronomy platform led by China, with its core scientific objective focused on high-precision polarization measurements of gamma-ray bursts. As one of its key payloads, the Low-energy Polarization Detector (LPD) is designed to perform wide-field surveys to capture X-ray polarization information from gamma-ray bursts in the 2-10 keV energy range. This paper presents Topmetal-L, a dedicated charge-sensitive pixel sensor developed for the LPD prototype upgrade. Fabricated in a 130 nm CMOS process in 2024, the chip integrates a 356 $\times$ 512 pixel array with a pixel pitch of 45 $\mu$m. Each pixel incorporates a 26 $\times$ 26 $\mu$m^2 charge-collecting electrode window and is capable of simultaneously outputting both energy and position information of deposited charges. Topmetal-L has been systematically optimized for power consumption, noise performance, and readout efficiency. It exhibits an input dynamic range of 0-4 ke-, a typical charge-to-voltage conversion gain of 76.04 $\mu$V/e-, an average equivalent noise charge of approximately 22.8 e-, a sensitive area exceeding 3.6 cm^2, and a total power consumption of 720 mW per chip. To meet the requirements of large-area, high-frame-rate readout for gas-based polarization detectors, a sentinel-scanning readout scheme is proposed, reducing the full-frame readout time to 730 $\mu$s. A prototype Topmetal-L-based gas polarization detection system was evaluated across key energies: it exhibited a residual modulation of 0.26% $\pm$ 0.45% at 5.90 keV, a modulation factor of 66.67% $\pm$ 0.45% for a linearly polarized 8.0 keV source, and a counting rate saturated at 15 k counts/(cm^2$\cdot$s) when tested at 5.4 keV.

Bars are ubiquitous morphological features in the observed distribution of galaxies. There are similarly many methods for classifying these features and, without a strict theoretical definition or common standard practice, this is often left to circumstance. So, we were concerned whether astronomers even agree on the bar which they perceive in a given galaxy and whether this could impact perceived scientific results. As an elementary test, we twenty-one astronomers with varied experience in studying resolved galaxies and circumstances, have each assessed 200 galaxy images, spanning the early phase of bar evolution in two different barred galaxy simulations. We find variations exist within the classification of all the standard bar parameters assessed: bar length, axis-ratio, pitch-angle and even whether a bar is present at all. If this is indicative of the wider community, it has implications for interpreting morphological trends, such as bar-end effects. Furthermore, we find that it is surprisingly not expertise but gender, followed by career stage, which gives rise to the largest discrepancies in the reported bar parameters. Currently, automation does not seem to be a viable solution, with bar classifications from two automated bar-finding algorithms tested and failing to find bars in snapshots where most astronomers agree a bar must exist. Increasing dependence on machine learning or crowdsourcing with a training dataset can only serve to obfuscate any existing biases if these originate from the specific astronomer producing the training material. On the strength of this small sample, we encourage an interim best practice to reduce the impact of any possible classification bias and set goals for the community to resolve the issue in the future.

We present imaging spectroscopy of the "supernebula" in the nearby dwarf galaxy NGC 5253 with the MIRI-MRS integral field spectrometer of the JWST. NGC 5253 is host to an luminous ($L\sim 10^9~\rm L_\odot$) HII region, powered by a giant young star cluster, a possible local analogue to super star cluster formation at Cosmic Dawn and Noon. In this paper, the first in a series about the mid-infrared line and continuum emission in the center of NGC 5253, we present an overview and continuum spectra. The mid-infrared images reveal four sources of continuum emission from hot dust that we identify as luminous HII regions, which are used to define spectral apertures. The dominant continuum source is the pc-scale supernebula core seen at radio wavelengths. We find that the MIR to radio continuum flux ratio for all regions is identical to that of Galactic HII regions. The 9.7 silicate feature is present and strongest in absorption toward the supernebula. Silicate emission is seen in another HII region. PAH features are present, although weak, particularly in the supernebula; the strongest emission is in an HII region only 15 pc from the supernebula core. PAH features at 6.2$\mu$m and 11.3$\mu$m are detected in all sources. Comparison of the luminosity implied by the ionization to the observed infrared luminosity suggest that at least 25% ofthe photons are escaping the embedded supernebula core, in spite of its high, $A_V\gtrsim 15$, extinction.

The nearby dwarf starburst NGC 5253 is dominated by a compact radio-infrared supernebula powered by a very young and bright embedded Super Star Cluster (SSC) of $\sim 10^9 L_\odot$. We observed this source and its surroundings over the 5-25$\mu$m range with MIRI/MRS on JWST and in Paper I presented the JWST view of the region and its continuum features. We now present the more than 70 emission lines of HI, $H_2$ and metal ions detected by MIRI/MRS. We derive the extinction by comparing HI recombination to the free-free radio continuum and find that it is very flat, i.e., almost independent of wavelength, over this spectral range. Nebular conditions are consistent with young ($\lesssim5\times10^6$ years) and very massive stars. All regions show high excitation, but the spatial distribution of the high excitation lines suggests that photons with energies close to 50eV are escaping the supernebula core in spite of 35 magnitudes of visual extinction.

Recent cosmological bounds on the sum of neutrino masses, M_nu = sum m_nu, are in tension with laboratory oscillation experiments, making cosmological tests of neutrino free-streaming imperative. In order to study the scale-dependent clustering of massive neutrinos, we develop a fast linear response method, FAST-nu f, applicable to neutrinos and other non-relativistic hot dark matter. Using it as an accurate linear approximation to help us reduce the dynamic range of emulator training data, based upon a non-linear perturbation theory for massive neutrinos, we improve the emulator's accuracy at small M_nu and length scales by a factor of two. We significantly sharpen its momentum resolution for the slowest neutrinos, which, despite their small mass fraction, dominate small-scale clustering. Furthermore, we extend the emulator from the degenerate to the normal and inverted mass orderings. Applying this new emulator, Cosmic-Enu-II, to large halos in N-body simulations, we show that non-linear perturbation theory can reproduce the neutrino density profile in the halo outskirts, 2R_vir < r < 10R_vir , to better than 10%.

We present two new radio continuum images from the ASKAP POSSUM survey in the direction of the Small Magellanic Cloud. The two new source lists contain 36,571 radio continuum sources detected at 944 MHz and 15,227 sources at 1367 MHz, with beam sizes of approximately 14.5 by 12.2 arcsec and 8.7 by 8.2 arcsec, respectively. We used the Aegean software package to generate these point source catalogues, and together with the previously published MeerKAT catalogue, we estimated spectral indices for the full set of matched radio point sources. By cross-matching our ASKAP catalogues with the MeerKAT data, we identified 21,442 and 12,654 common point sources at 944 MHz and 1367 MHz, respectively, using a 2 arcsec matching radius. These new catalogues improve our understanding of the Small Magellanic Cloud and demonstrate the capability of current radio telescopes such as ASKAP to investigate diverse galactic source populations

Applying a new estimator to the Dark Energy Survey (DES) Y3 weak lensing shape catalog, we map the galaxies' orientation field and report the first detection of a large-scale axial intrinsic alignment (LAIA) on dipolar angular scales. Ellipticals' semi-major axes and spirals' semi-minor axes coherently point toward a common direction, (RA,Dec)=$(306^{+6}_{-4},52^{+3}_{-3})^\circ$ and $(296^{+10}_{-18},50^{+6}_{-2})^\circ$, respectively, with amplitudes in the expected tidal-torquing hierarchy. This pattern could be produced by a horizon-scale tidal field imprinted by primordial inhomogeneities during galaxy assembly and can probe deviations from statistical isotropy. The signal persists across spatial and redshift splits and is difficult to attribute to survey systematics. LAIA offers a new sky-wide compass linking galaxy evolution and cosmology.

Warm inflation is a well-motivated and generalized framework of inflation, describing a coupled inflaton-radiation bath. In this work, we investigate a warm inflation model with a quartic potential and a composite dissipation coefficient $\Upsilon(\phi, T) = C_1 \frac{T^3}{M_{\text{Pl}}^2} + C_2 \frac{T^3}{\phi^2}.$ The two terms in $\Upsilon$ dominate at different scales: the first term governs the early inflationary dynamics at large (CMB) scales, while the second term becomes significant at smaller scales. The model features two distinct stages of inflation: an initial phase where strong dissipation ($Q \gg 1$) generates a red-tilted primordial spectrum consistent with CMB observations (from ACT), followed by a second phase producing a blue-tilted spectrum with a significant amplification of power at small scales, leading to primordial black hole formation. We analyze the effects of key parameters -- like the duration of each inflationary phase, the slow-roll parameter at the end of the first phase, the dissipation strength at the pivot scale, and the choice of the growth function -- on the primordial power spectrum and its spectral index. Additionally, we examine the consistency of the model with the swampland distance conjecture and trans-Planckian conjecture, needed for embedding these models with some UV complete theories. This work highlights the potential of warm inflation with a composite dissipation coefficient to reconcile large-scale CMB measurements with small-scale structure formation.

Context: The Milky Way contains a thick and a thin disc that differ in chemical, kinematic, structural, and spatial properties. There is significant overlap in the distributions of these properties, especially so at higher metallicities. Distinguishing between these major structural components is crucial for understanding the formation and evolution of the Galaxy. Multiple selection methods exist to classify stars as thin or thick disc stars, each with its own advantages and limitations. Aims: We investigate how different classification methods for categorising stars into the thick and thin disc populations influence the determination of structural properties of the two discs. Methods: We apply five different selection methods. Two methods use cuts in the [$\alpha$/Fe]-[Fe/H] and [Mg/Mn]-[Al/Fe] planes; one uses a dynamical separation in $J_\phi$ -$J_Z$ space; one uses an age-based cut; and the last one uses a kinematic likelihood method. For each method, we derive relative density profiles of each component as functions of height above the Galactic plane and Galactocentric radius, and fit these to a simple two-exponential disc model. We use red giant stars from APOGEE DR17 and stellar ages from astroNN. Results: Methods based on abundance or age data produce the cleanest separations, while kinematic and dynamical methods suffer higher contamination due to difficulties in separating well-mixed populations. The thin disc scale heights show a clear flaring as they increase with radius, while the thick disc stays approximately constant at around 1 kpc over most radii for all methods. All methods find the thin disc to have a longer scale length than the thick disc, with the difference being greatest for the chemical selection methods. A scale length of the thick disc of 2.0 kpc leads to one of between 2.3 and 3.0 kpc for the thin disc.

In this work we study the rotational velocities of a sample of blue straggler stars (BSSs) and reference stars belonging to the Galactic globular cluster NGC 1851, using high-resolution spectra acquired with FLAMES-GIRAFFE at the ESO/VLT. After field decontamination based on radial velocities and proper motions, the final sample of member stars is composed of 15 BSSs and 45 reference stars populating the red giant and horizontal branches of the cluster. In agreement with previous findings, the totality of reference stars has negligible rotation (lower than 15 km/s). In contrast, we find high values of rotational velocity (up to $\sim$ 150 km/s) for a sub-sample of BSSs. By defining the threshold for fast rotating BSSs at 40 km/s, we found 4 fast-rotating BSSs out of 15, corresponding to a percentage of 27 $\pm$ 14 %. This results delineates a monotonically decreasing trend (instead of a step function) between the percentage of fast spinning BSSs and the central concentration and density of the host cluster, supporting a scenario where recent BSS formation preferentially occurs in low-density environments from the evolution of binary systems.

We present the first broadband spectral analysis of NGC 470 HLX1, a hyperluminous X-ray source that exhibits significant flux variability over different epochs. We investigate the feasibility of synchrotron radiation with varying latitude from a magnetized neutron star to explain the source's spectra. We also shed light on the particle acceleration mechanisms and maximum Lorentz factor of electrons within the neutron star magnetospheric plasma under super-Eddington accretion conditions. In our broadband spectral modeling, the detection of a blackbody-like component suggests the presence of a disk near the corotation radius or an outflow ejected from the disk. The viability of synchrotron emission in an HLX system offers new insights about the nature of these sources, motivating further sample studies to assess whether most of these sources are powered by accreting neutron stars.

We analyze observational data on methanol masers in the disks of young massive stellar objects in the massive star formation regions: NGC6334I, G33.641-0.228, G12.89+0.49. Special attention is paid to analysis of the magnetic fields and their possible connection with maser flares. For this purpose, we estimate the distance from star to maser, the magnetospheric radius and magnetic field strength in the region of this radius. The distances from stars to masing regions lie in range from 380 to 620 au. Stellar and disk's magnetic field strengths are comparable at the magnetosphere boundary and lie in the range from 590 to 1880 G for considered objects. Our estimates show that the magnetic fields may play an important role in the considered regions. In particular, observed luminosity bursts and maser flares may be related to magnetic reconnection events near the stars.

To unravel the formation history of the Milky Way, we estimate the accretion times of six phase-space substructures in the stellar halo, using the orbital frequencies toward two spatial directions ($r, \phi$) in spherical coordinates. These substructures, identified in our previous studies, are located in the solar neighbourhood and therefore have high-precision astrometry from Gaia. The uncertainties of the results are determined using the Monte Carlo method, and the significance is established through comparison with random halo samples. The results for the substructure GL-1 in both directions show good consistency and high significance ($4.4\sigma$ and $4.5\sigma$), yielding a combined accretion time of $5.59^{+0.07}_{-0.08}$ Gyr ago. The substructures GL-4 and GR-1, with smaller pericenters, exhibit higher significance in the less massive potential of the Milky Way, implying that the more massive potential may overestimate the central mass, especially the bulge. The accretion times of GL-4 and GR-1 are $4.0 \pm 0.2$ Gyr with a confidence of $3.3\sigma$, and $2.3 \pm 0.1$ Gyr with a confidence of $3.7\sigma$, respectively. Further constraints on the accretion times of phase-space substructures require more precise astrometric data, e.g., by Gaia DR4, China Space Station Survey Telescope and Roman space telescope.

Massive black holes surrounded by a gaseous disk have been a prevailing model to explain a wide spectrum of astrophysical phenomena related to active galactic nucle (AGNs). However, direct and precise measurements of the disk density profiles remain elusive for current telescopes. In this work, we demonstrate that it is possible to pinpoint the gas density if an inspiralling stellar mass binary black hole is embedded in the AGN disk. Furthermore, if the barycenter of the pair follows an eccentric orbit around an AGN, then space-borne gravitational wave detectors can measure the density of the surrounding disk with multi-year observations by tracking the gravitational wave evolution. The error between the inferred density profile and the injected truth can be constrained to below $2\times10^{-11}\rm g/cm^3$. Our work opens up an exciting new channel to investigate the very center of galaxies, where disk gas density distributions $\rho(r)$ can be recovered by analyzing time-dependent environmental imprints in gravitational waveforms.

Changing-look active galactic nuclei (CLAGNs) are a unique population of AGNs that exhibit the appearance (turn-on) or disappearance (turn-off) of broad emission lines. This study aims to explore the intrinsic mechanisms of CLAGNs by investigating their photometric variability using data from the Zwicky Transient Facility (ZTF), which has provided high-cadence observations over the past five years. By visual inspections, we construct a sample of 152 CLAGNs from the literature, all of which show spectral transitions and large optical variability in their ZTF light curves. By analyzing 90 of these CLAGNs and the control samples of Type 1 AGNs, Type 2 AGNs, and extremely variable quasars (EVQs), matched in redshift ($0.2<z<0.8$) and supermassive black hole mass, we compare the color variability, structure function (SF), and variability metric $\sigma_{\mathrm{QSO}}$, which quantifies how closely the light curves resemble a damped random walk (DRW) model. We find that while CLAGNs and EVQs differ from typical Type 1 and Type 2 AGNs in bolometric luminosity and Eddington ratio, the on/off-state CLAGNs share similar variability patterns with the overall CLAGN population, and distinct from EVQ, Type 1 and Type 2 AGNs. This suggests that 'on' and 'off' CLAGNs are not simply equivalent to Type 1 and Type 2 AGNs, respectively. Instead of undergoing genuine transitions between two AGN types, CLAGNs may inhabit a critical state where moderate fluctuations in accretion rate lead to the temporary spectral changes.

Most our knowledge about rocky exoplanets is based on their measure of mass and radius. These two parameters are routinely measured and are used to categorise different populations of observed exoplanets. They are also tightly linked to the planet's properties, in particular those of the interior. As such they offer the unique opportunity to interpret the observations and potentially infer the planet's chemistry and structure. Required for the interpretation are models of planetary interiors, calculated a priori, constrained using other available data, and based on the physiochemical properties of mineralogical phases. This article offers an overview of the current knowledge about exoplanet interiors, the fundamental aspects and tools for interior modelling and how to improve the contraints on the models, along with a discussion on the sources of uncertainty. The origin and fate of volatiles, and their role in planetary evolution is discussed. The chemistry and structure of planetary interiors have a pivotal role in the thermal evolution of planets and the development of large scale properties that might become observables with future space missions and ground-based surveys. As such, having reliable and well constrained interior models is of the utmost importance for the advancement of the field.

Context. True spin-orbit obliquities {\Psi} offer valuable insights into the evolutionary history of exoplanetary systems. Previous studies have suggested that exoplanets tend to occupy either aligned or perpendicular orbits. However, recent research has indicated potential biases caused by the low sample, questioning whether this dichotomy would persist with a larger dataset. Simultaneously, a similar dichotomous behavior has been suggested for Neptune-sized planets. Aims. We aim to investigate the distribution of true spin-orbit obliquities {\Psi} with an enlarged sample, looking for confirmation of the disputed dichotomy previously found, with a focus also on the obliquities of Neptunes. Methods. Starting from a sample of 264 projected obliquities {\lambda}, we homogeneously compute true obliquities {\Psi} for 116 planets using the rotation period method. We combine them with 4 further values gathered from literature and we then study their distribution, also as a function of various star-planet system parameters. Results. Our data-driven work based on 120 true obliquities {\Psi} - the largest sample to date - strongly confirms the presence of a single cluster of aligned planets, followed by an isotropic distribution of misaligned planets with no preferred misalignment. This result is based on a uniform distribution of stellar inclinations {i_\star} , for which non-uniformity could have biased previous interpretations of the arrangement of true obliquities. We confirm that Neptunians show a tentative dichotomous distribution with data available today, but its veracity needs confirmation with an enlarged sample, also because an anisotropic distribution of stellar inclination may be one of the factors hindering the real distribution.

We propose a dynamical dark energy model based on a canonical scalar field with a hybrid potential of the form $V(\phi) = V_{0}e^{-\lambda\phi} + V_{1}\phi^{n}$. We constrain the model's 11-dimensional parameter space using a comprehensive combination of cosmological data, including the Planck 2018 Cosmic Microwave Background (CMB) power spectra, Baryon Acoustic Oscillations (BAO), the Pantheon+ supernova sample, and the matter power spectrum from SDSS. The model provides an excellent fit to the data, with a reduced chi-squared of $\chi^2_{\text{red}} = 0.987$, while successfully alleviating the Hubble constant tension. Our analysis yields a Hubble constant of $H_0 = 70.0$ km/s/Mpc, reducing the discrepancy between early and late-universe measurements. The data favor a negative power-law index of $n \approx -0.92$. A model comparison using the Bayesian Information Criterion finds that the standard $\Lambda$CDM model is still slightly preferred ($\Delta\text{BIC} = 2.178$) due to its fewer parameters. Nevertheless, our results demonstrate that this hybrid potential model is a compelling, physically motivated alternative to a cosmological constant.

We present an extensive analysis of the multi-wavelength data of the low-synchrotron-peaked BL Lac object CGRaBS J0211+1051, which has been gathered over more than ten years with many observatories. Two major gamma-ray flares have been observed during the Fermi era: one in January 2011 and other in June 2019. During these events, CGRaBS J0211+1051 was also bright in other energy bands. On the other hand, there are also examples of optical activity that do not exhibit any comparable gamma-ray variability. Here, we study the temporal and spectral characteristics of the object in an attempt to understand the emission mechanisms operating in this source. A peculiar feature in its spectrum is the X-ray domain, which is unusually soft considering its object class. Interestingly, the relatively soft UV and optical spectrum does not extrapolate well to the X-rays. To mimic the observed SEDs during quiescent and flaring periods, we use both a purely leptonic and a hadro-leptonic modeling approach to reproduce four broadband SEDs from various epochs. When taking into account the steep optical-UV spectrum, we find that the hadro-leptonic scenarios better explains the SEDs compared to the purely leptonic model. The hadro-leptonic interpretation of the two gamma-ray flares suggests that CGRaBS J0211+1051 could be both a potential neutrino emitter and TeV-bright (E>10 TeV). Thus, it may offer a unique test bed to check for hadro-leptonic contributions to the multi-messenger emission in blazar jets.

Our study investigates the properties of Alfvén waves in partially ionised solar plasmas in the presence of steady, field-aligned, flows of charged and neutral particles. Our work aims to understand how such flows modify wave propagation and damping in environments where ion-neutral collisions are significant. We employ a two-fluid model that treats ions and neutrals as separate, colliding fluids and incorporates background steady flows for both species. Using a combination of analytical dispersion analysis and numerical solutions, we examine the impact of these flows on the behaviour of Alfvén waves. Our results show that steady flows lead to substantial modifications of wave properties, including Doppler shifts, propagation direction reversal, flow-dependent changes in damping rates, and the appearance of a new mode associated with neutral flow and collisional coupling. We also identify conditions under which flow-driven mode conversion can arise. Our results offer new insights into the interplay between plasma flows and particle collisions in the regions of the solar atmosphere where partial ionisation is relevant.

The Extreme Universe Space Observatory on a Super Pressure Balloon 2 (EUSO-SPB2) mission launched from Wanaka New Zealand on May 13, 2023. The mission ended after 36 h due to a balloon leak that resulted in the payload being lost in the Pacific Ocean. Over the course of the mission, the onboard Cherenkov Telescope (CT) was pointed just below the Earth's limb to search for optical signals from upward-moving extensive air showers that were induced by decaying tau-leptons that were generated by the conversion of $>10$ PeV tau-neutrinos in Earth. Such very-high energy (VHE) neutrinos may be produced in several classes of astrophysical sources that are suspected of possibly accelerating particles to ultra-high energies. In this contribution, we discuss the EUSO-SPB2 Target-of-Opportunity (ToO) campaign to search for VHE neutrino signals coming from astrophysical sources that crossed the CT's field of view ($6.4^\circ \times 12.8^\circ$). We also present a new software tool designed for scheduling observations, the Neutrino Target Scheduler, that we developed to support the ToO campaign. We also calculate upper limits on the neutrino fluences from sources observed during the ToO campaign. Our observations demonstrate the viability of conducting ToO follow-up observations from a near space environment with future balloon missions, such as the pathfinder mission POEMMA-Balloon with Radio.

Radio emission from star planet interactions (SPI) beyond our solar system has yet to be firmly detected, primarily due to challenges such as weak signals, directional beaming effects, and low frequency emissions that are blocked by the ionosphere of Earth. Addressing these obstacles calls for strategic target selection. This proof of concept study aims to improve SPI target prioritization by simulating SPI induced radio emission frequencies and estimating associated radio power to identify systems most likely to produce detectable signals. We combine Zeeman Doppler Imaging (ZDI) maps with 3D magnetohydrodynamic (MHD) stellar wind simulations and use the ExPRES code to model SPI driven radio emissions. We also estimate the intensity of these emissions using the Radio Magnetic Scaling Law, based on the magnetic field and plasma density parameters from the 3D wind models. This approach is applied to systems such as Tau Boo, HD 179949, and HD 189733 to assess their detectability with current and future radio telescopes. This framework, tested on benchmark systems, is applicable to any star planet system with available ZDI maps and wind models. As magnetic field reconstructions and wind simulations improve, the method will become more robust. It provides a data driven approach to prioritize targets and optimize telescope scheduling. This shall enable systematic exploration of magnetic SPI radio emissions across a wide range of exoplanetary systems.

Ginnungagap is a fully parallel (MPI+OpenMP) code designed to generate cosmological initial conditions for simulations involving very large numbers of particles. It operates in several modes, including the creation of initial conditions with either uniform or spatially varying resolution (for "zoom-in" simulations). The initial conditions can be fully random or derived by extending the resolution of existing ones while preserving the large-scale structures. Ginnungagap is open source and modular, consisting of a collection of independent tools that can be used for a variety of tasks. In this paper, we describe the main features of Ginnungagap and present test results for different types of simulations prepared with it.

Current spatially resolved kinematic measurements of supermassive black hole (SMBH) masses are largely confined to the local Universe (distances $\lesssim100$ Mpc). We investigate the potential of the Extremely Large Telescope's (ELT) first-light instruments, MICADO and HARMONI, to extend these dynamical measurements to galaxies at redshift $1\lesssim z\lesssim2$. We select a sample of five bright, massive, quiescent galaxies at these redshifts, adopting their Sérsic profiles from HST photometry as their intrinsic surface brightness distributions. Based on these intrinsic models, we generate mock MICADO images using SimCADO and mock HARMONI integral-field spectroscopic data cubes using HSIM. The HARMONI simulations utilize input stellar kinematics derived from Jeans Anisotropic Models (JAM). We then process these mock observations: the simulated MICADO images are fitted with Multi-Gaussian Expansion to derive stellar mass models, and stellar kinematics are extracted from mock HARMONI cubes with pPXF. Finally, these derived stellar mass models and kinematics are used to constrain JAM dynamical models within a Bayesian framework. Our analysis demonstrates that SMBH masses can be recovered with an accuracy of $\sim$10%. We find that MICADO can provide detailed stellar mass models with $\sim$1 hour of on-source exposure. HARMONI requires longer minimum integrations for reliable stellar kinematic measurements of SMBHs. The required on-source time scales with apparent brightness, ranging from 5-7.5 hours for galaxies at $z\approx1$ (F814W, 20-20.5 mag) to 5 hours for galaxies at $1<z\lesssim2$ (F160W, 20.8 mag). These findings highlight the ELT's capability to push the frontier of SMBH mass measurements to $z\approx2$, enabling crucial tests of SMBH-galaxy co-evolution at the top end of the galaxy mass function.

Dynamical models are used to study dark matter (DM) in galaxies, how galaxies assemble through mergers, and to test galaxy formation models. Despite its widespread use, there has been no systematic study quantifying how much information can be obtained from just two on-sky positions and line-of-sight velocities, which are typically available for nearby external galaxies. In this work, we introduce axisymmetric, action-based dynamical models that use the positions and velocities of stellar halo stars to jointly constrain the total mass distribution of galaxies and the underlying DM component, as well as the stellar halo phase-space distribution. We rigorously test the method using both idealised equilibrium galaxy mocks and cosmological hydrodynamical simulations from the Auriga suite, systematically assessing how its performance degrades as the available phase-space information is progressively reduced. We further examine the impact of galaxy inclination, modelling assumptions, and methodological systematics on the recovered mass profiles. A crucial development in this work is the improved marginalisation of the model likelihood over missing phase-space dimensions. Our models successfully recover the total and DM mass distributions, as well as the kinematic properties of the stellar tracers, within the derived confidence intervals. However, we find that with limited (3D or 4D) phase-space information, the flattening of the DM halo cannot be constrained with any degree of certainty. Nevertheless, the recovered mass profile is insensitive to the flattening. This finding is independently validated by Schwarzschild modelling tests.

Accurate null depth retrieval is critical in nulling interferometry. However, achieving accurate null depth calibration is challenging due to various noise sources, instrumental imperfections, and the complexity of real observational environments. These challenges necessitate advanced calibration techniques that can efficiently handle such uncertainties while maintaining a high accuracy. This paper aims to incorporate machine-learning techniques with a Bayesian inference to improve the accuracy and efficiency of null depth retrieval in nulling interferometry. Specifically, it explores the use of neural posterior estimation (NPE) to develop models that overcome the computational limitations of conventional methods, such as numerical self-calibration (NSC), providing a more robust solution for accurate null depth calibration. An NPE-based model was developed, with a simulator that incorporates real data to better represent specific conditions. The model was tested on both synthetic and observational data from the LBTI nuller for evaluation. The NPE model successfully demonstrated improved efficiency, achieving results comparable to current methods in use. It achieved a null depth retrieval accuracy down to a few $10^{-4}$ on real observational data, matching the performance of conventional approaches while offering significant computational advantages, reducing the data retrieval time to one-quarter of the time required by self-calibration methods. The NPE model presents a practical and scalable solution for null depth calibration in nulling interferometry, offering substantial improvements in efficiency over existing methods with a better precision and application to other interferometric techniques.

We investigate the correlations of CO (2-1) emission (${I_{\rm CO}}$) with PAH (${I_{\rm F770W, PAH}}$ and ${I_{\rm F1130W}}$) and dust (${I_{\rm F2100W}}$) emission down to scales of $\lesssim$ 100 pc, by applying \raddest, a novel regression technique recently developed by T. Jing & C. Li (2025) that effectively handles uncertainties and outliers in datasets, to 19 nearby star-forming galaxies in the PHANGS sample. We find that for the majority of the data points in all galaxies, the scaling of ${I_{\rm CO}}$ with ${I_{\rm F770W, PAH}}$, ${I_{\rm F1130W}}$, and ${I_{\rm F2100W}}$ can be well described by log-linear relations, though with substantial dependence on ionization conditions (i.e., HII-like, composite-like, and AGN-like). Under given ionization conditions, significant galaxy-to-galaxy variations are identified, and are primarily attributed to variations of intercept $b$, which exhibits clear bimodality. This bimodality is related to the overall host galaxy star formation strength. The differences in slope $k$ and intrinsic scatter $\sigma$ across different MIR bands (${I_{\rm F770W, PAH}}$, ${I_{\rm F1130W}}$, and ${I_{\rm F2100W}}$) are minor compared to their galaxy-to-galaxy variations. All parameters ($k$, $b$, and $\sigma$) depend on the spatial scale of measurement, suggesting that the coupling among CO, PAH, and dust is regulated by different mechanisms at varying scales. We identify non-log-linear behaviors in the brightest regions, where deviations are primarily characterized by flattening of slope. No significant (3$\sigma$) correlations are found between global properties and the best-fit parameters. We discuss the comparison to previous studies and plausible physics behind the statistical results obtained in this work.

X-ray binaries exhibit complex variability patterns studied in the power-spectrum. These include the broad-band noise (BBN) components and various types of narrow components called quasi-periodic oscillations (QPOs). There is currently no consensus about either what determines the presence/absence of the BBN or what generates the QPOs. Many believe the latter is due to frame-dragging effects caused by Lense-Thirring torques. We wish to investigate the potential impact of those frame-dragging effects on the accretion disk itself. In particular, we focus on its impact on the observed variability and the presence (and types) of QPOs associated. We make analytical estimates to assess the potential presence of a geometric warp in the inner accretion disk during state transitions. We show that the presence of a warp can modify the spectral-timing properties in a way that matches the observed transition between QPO types during outbursts. We also discuss the peculiar case of Cyg X-1, as well as how the hard-to-soft transition could be driven by the warp itself. The (expected) emergence of a warp provides a consistent explanation for the evolution of both the BBN and the QPO properties during state transitions. This offers a first path toward unifying the variability of black hole X-ray binary.

Context: The scattering polarization of the infrared (IR) triplet of neutral oxygen (O\,\textsc{i}) near 777\,nm provides a powerful diagnostic of solar atmospheric conditions. However, interpreting such polarization requires a rigorous treatment of isotropic depolarizing collisions between O\,\textsc{i} atoms and neutral hydrogen. Aims: We aim to investigate the combined effects of collisional and magnetic depolarization in shaping the alignment of O\,\textsc{i} levels (and thus the polarization of the O\,\textsc{i} IR triplet). Methods: We compute, for the first time, a comprehensive set of collisional depolarization and polarization transfer rates for the relevant O\,\textsc{i} energy levels. These rates are incorporated into a multi-level atomic model, and the statistical equilibrium equations (SEE) are solved to quantify the impact of collisions and magnetic fields on atomic alignment. Results: Our calculations indicate that elastic collisions with neutral hydrogen, together with the Hanle effect of turbulent magnetic fields stronger than about 20 G, efficiently suppress the bulk of the atomic alignment in deep photospheric conditions where hydrogen densities exceed $n_{\mathrm{H}} \sim 10^{16}$ cm$^{-3}$. In the chromosphere, however, the lower hydrogen density weakens collisional depolarization, allowing polarization to persist. Conclusions: Our results are consistent with a chromospheric origin for the linear polarization signals of the O I IR triplet. Future studies should combine accurate non-LTE radiative transfer with reliable collisional rates in order to achieve fully consistent modeling.

There is abundant observational evidence for the hierarchical, interconnected nature of filaments in the interstellar medium (ISM) extending from galactic down to sub-parsec scales. New JWST images of NGC 628 in particular, show clusters forming along the two spiral arms of this galaxy. In this paper we investigate filament and cluster properties in an NGC 628-like multi-scale high-resolution magnetohydrodynamic simulation. We use a filament finding tool to identify filaments and derive the probability density functions (PDFs) for the filament lengths and masses. Using a clustering algorithm we identify star clusters formed between 268 to 278 Myr and follow this population as the galaxy evolves for 60 Myr, calculating their mass PDFs, average radius growth rate, and average mass loss rate. We find a power-law index of alpha_m = -1.35 for the filament masses. Calculating the power-law index from our cluster mass PDF, we find a value of alpha_{c,m} = -1.35 when the clusters first form, exactly our filament mass power-law index. This shows that properties of young clusters arise from the gravitational fragmentation of their host filaments. We track the post-formation evolution of the clusters as they become unbound, increase in radius and decrease in mass yielding an ever steeper mass power-law index. After 60 Myr, the mass power-law index is alpha_{c,m} = -1.55, matching other simulations and observations.

The Luminosity Oscillations Imager (LOI) of the Variability of Solar Irradiance and Gravity Oscillations (VIRGO) instrument aboard the SoHO mission has been operating for almost the past 30 years. I report on the effect of solar activity upon mode frequencies, linewidths, height and energy rate. I report on the variation as a function of frequency for frequency, $a_2$ coefficient and linewidth changes, as well as the average over the degree and the frequency of these changes. Using the 29-year time series, I report on the frequencies, linewidths and mode height fitted with \texttt{progFIT}. Using the collapsogram technique, I also report on the detection of modes below 1600 $\mu$Hz, making the lowest frequencies detected with an instrument observing the Sun in intensity. I also report on the detection of p mode in the high voltage and guiding pixel signals with a mode height about 5 to 10 times larger than what is observed in the Sun-as-a-star signal for $l=1$. The ratios of the observed mode visibilities for the different signals are provided following a calibration of the size of the guiding pixels. While the visibility ratios for the signals excluding the limb are in good agreement with theory, those covering the solar limb are in strong disagreement.

The 21-cm signal from neutral hydrogen is anticipated to reveal critical insights into the formation of early cosmic structures during the Cosmic Dawn and the subsequent Epoch of Reionization. However, the intrinsic faintness of the signal, as opposed to astrophysical foregrounds, poses a formidable challenge for its detection. Motivated by the recent success of machine learning based Gaussian Process Regression (GPR) methods in LOFAR and NenuFAR observations, we perform a Bayesian comparison among five GPR models to account for the simulated 4-hour tracking observations with the SKA-Low telescope. The simulated sky is convolved with the instrumental beam response and includes realistic radio sources and thermal noise from 122 to 134 MHz. A Bayesian model evaluation framework is applied to five GPR models to discern the most effective modelling strategy and determine the optimal model parameters. The GPR model with wedge parametrization ($\textit{Wedge}$) and its extension ($\alpha\textit{Noise}$) with noise scaling achieve the highest Bayesian evidence of the observed data and the least biased 21-cm power spectrum recovery. The $\alpha\textit{Noise}$ and $\textit{Wedge}$ models also forecast the best local power-spectrum recovery, demonstrating fractional differences of $-0.14\%$ and $0.47\%$ respectively, compared to the injected 21-cm power at $k = 0.32\ \mathrm{h\ cMpc}^{-1}$. We additionally perform Bayesian null tests to validate the five models, finding that the two optimal models also pass with the remaining three models yielding spurious detections in data containing no 21-cm signal.

We present 15 years of Nançay and Green Bank radio telescope timing observations for PSR J1231$-$1411. This millisecond pulsar is a primary science target for the Neutron Star Interior Composition Explorer telescope (NICER, which discovered its X-ray pulsations), has accumulated near-continuous $\gamma$-ray data since the Fermi-Large Area Telescope's launch, and has been studied extensively with the Green Bank and Nançay radio telescopes. We have undertaken a campaign with the Green Bank Telescope targeting specific orbital phases designed to improve our constraint on the pulsar's mass through the detection of a relativistic Shapiro delay. Both frequentist and Bayesian techniques -- the latter incorporating priors from white dwarf binary evolution models -- are applied to fifteen years of radio observations, yielding relatively weak constraints on the companion and pulsar masses of $0.23^{+0.09}_{-0.06}$ M$_{\odot}$ and $1.87^{+1.11}_{-0.67}$ M$_{\odot}$, respectively (68.3% CI from Bayesian fits); however, the orbital inclination is measured to better relative precision ($79.80^{+3.47}_{-4.70}$ degrees). Restricting the maximum allowed pulsar mass to 3 M$_{\odot}$ while simultaneously sampling the noise and timing models improves the constraint and lowers the measured mass to $1.62^{+0.73}_{-0.58}$ M$_{\odot}$. While our radio-derived inclination result has informed recent NICER X-ray studies of PSR J1231$-$1411, the lessons learned from this troublesome pulsar will also bolster future high-precision mass measurement campaigns and resulting constraints on the neutron star interior equation of state.

We present a novel framework for accurately reconstructing radial velocity (RV) curves of classical Cepheids (Cepheids) from sparsely sampled time-series data suitable for application in large spectroscopic surveys. The framework provides a set of priors for the principal components of RV curves established based on high-precision measurements from the VELOCE project; template RV curves of Cepheids can be readily extracted from our results. We demonstrate the ability of our framework to estimate unbiased pulsation average velocities, $v_\gamma$, to within $20-30$m/s, and peak-to-peak amplitudes, $P2P$, to within $\sim 2\%$. Subsampling the initial data set, we show that $v_\gamma$ and $P2P$ can be determined to within $\sim 0.35$ km/s and $\sim 6-7\%$, respectively, from as few as three observations. We fitted existing time-series RV data of Cepheids in the LMC and SMC using this framework and obtained typical RMSE of $0.5-2.0$ km/s. The typical total uncertainty on $v_\gamma$ achieved for the SMC Cepheids is $\sim 0.85$ km/s, providing sensitivity to spectroscopic binaries (SB). We identified 8 SB1 systems; two and one of which are new detections in the LMC and SMC, respectively. This yields a single-lined SB fraction of $\sim 25\%$ and $29\%$ in the two galaxies, similar to the Milky Way's SB fraction of $29\%$ established as part of VELOCE. Despite their relatively small number, LMC Cepheids reproduce the known line-of-sight component of the LMC's large-scale rotation, which differs in the extremes by more than $80$km/s. The kinematics of the SMC are more complex and not sufficiently sampled by the available Cepheids. Our framework is designed to yield accurate $v_\gamma$ and $P2P$ of Cepheids observed by large spectroscopic surveys, such as 4MOST, SDSS-V, and others, and will unlock new insights into the kinematics and multiplicity of evolved intermediate-mass stellar populations.

Microquasars have emerged as promising candidates to explain the cosmic-ray flux at petaelectronvolt energies. LHAASO observations revealed V4641~Sgr as the most extreme example so far. Using $\approx$100~h of H.E.S.S. data, we performed a spectro-morphological study of the gamma-ray emission around V4641~Sgr. We employed HI and dedicated CO observations of the region to infer the target material for cosmic-ray interactions. We detected multi-TeV emission around V4641~Sgr with a high significance. The emission region is elongated. We found a power-law spectrum with an index $\approx$1.8, and together with results from other gamma-ray instruments, this reveals a spectral energy distribution that peaks at energies of $\approx$100~TeV for the first time. We found indications (3$\sigma$) of a two-component morphology, with indistinguishable spectral properties. The position of V4641~Sgr is inconsistent with the best-fit position of the single-component model and with the dip between the two components. We found no significant evidence of an energy-dependent morphology. No dense gas was found at any distance towards V4641~Sgr. The peak of the SED at $\approx$100~TeV identifies V4641~Sgr as a candidate cosmic-ray accelerator beyond the so-called knee. The absence of dense target gas places stringent energetic constraints on hadronic interpretations, however. The H.E.S.S. measurement requires an unusually hard ($\approx 1.5$) spectral index for the protons. A leptonic scenario faces fewer obstacles if the particle transport is fast enough to avoid losses and to reproduce the observed energy-independent morphology. The absence of bright \xray emission across the gamma-ray emission region requires a magnetic field strength $\lesssim3$~$\mu$G, however. Our findings favour a leptonic origin of the gamma-ray emission. This conclusion does not exclude hadron acceleration in the V4641~Sgr system.

Since the first observations of interstellar molecules, astrochemical simulations have been employed to model and understand its formation and destruction path- ways. With the advent of high-resolution telescopes such as JWST and ALMA, the number of detected molecules has increased significantly, thereby creating a need for increasingly complex chemical reaction networks. To model such complex systems, we have developed Carbox, a new astrochemical simulation code that leverages the modern high-performance transformation framework Jax. With Jax enabling computational efficiency and differentiability, Carbox can easily utilize GPU acceleration, be used to study sensitivity and uncertainty, and interface with advances in Scientific Machine Learning. All of these features are crucial for modeling the molecules observed by current and next-generation telescopes.

The detection of high-energy astrophysical multimessengers establishes a connection between ultra-high-energy cosmic rays (UHECRs) and powerful cosmic accelerators. Interactions of UHECRs with radiation fields and interstellar matter generate very-high-energy (VHE) gamma rays and neutrinos, making them key components in the multimessenger framework. This study examines the cosmogenic gamma-ray and neutrino fluxes resulting from UHECR propagation in starburst galaxies with supernova remnants, with a particular focus on NGC 1068, a well-established high-energy neutrino source. Using extragalactic simulations, we calculate the upper limit on cosmic-ray luminosity, applying upper limits on gamma-ray fluxes derived from observations by H.E.S.S. and MAGIC observatories. Our analysis incorporates the effects of both extragalactic and galactic magnetic fields on particle propagation, constraining the maximum extragalactic magnetic field (EGMF) intensity to $10^{-14}~\mathrm{G}$ to ensure that at least 90\% of injected UHECRs successfully reach Earth. The results provide upper limits on gamma-ray and neutrino fluxes, estimates of UHECR luminosity for individual sources, and predictions for the detection capabilities of the Cherenkov Telescope Array Observatory regarding gamma-ray emission from NGC 1068. Combining gamma-ray, neutrino, and UHECR observations reinforces the importance of multimessenger approaches in understanding the nature of high-energy astrophysical sources and their role in cosmic-ray acceleration.

We use the extremely high-resolution ($m_{\rm bary}=4\rm{M}_\odot$) LYRA cosmological galaxy formation simulations of six dwarf galaxies with $M_{\rm 200c}\sim10^9\rm{M}_\odot$ at $z=0$ to investigate their stellar assembly histories. Based on the age of stars in these galaxies at $z=0$, $40-100\%$ of their stellar mass was formed by the time of reionization, when star formation (SF) abruptly shuts down. Depending on their halo mass evolution, some of the dwarfs reignite SF post-reionization (rejuvenators), while others remain quenched for the rest of cosmic time (reionization relics). However, the stellar mass of relics can still grow by more than $50\%$ through mergers post-reionisation. We find clear correlations between metallicity distributions of the galaxies and the fraction of stars formed post-reionization ($f_{\rm post-reio}^\star$) such that relics have lower median $\rm [Fe/H]$ with a more prominent low metallicity tail. Moreover, the shape of the galaxies at $z=0$ correlates with their $f_{\rm post-reio}^\star$, with rejuvenators showing more spherical stellar distribution than relics. This difference arises only post-reionization when rejuvenators become rounder with more SF activity. Similarly, the shape of dark matter (DM) halos in the inner regions display more spherical distributions in rejuvenators than in relics. The shape evolution shows that DM haloes in all galaxy formation simulations become rounder in comparison to their collision-less, DM-only counterparts. However, DM haloes of rejuvenators evolve more significantly. We do not find any correlation between SF activity and formation of shallow DM density cores in these galaxies. These predictions can be tested using upcoming observational data. In particular, our results indicate that the scatter in the mass-metallicity relation in the low mass regime is correlated with SF histories and the shape of galaxies.

Warm ionized gas is ubiquitous at the centers of X-ray bright elliptical galaxies. While it is believed to play a key role in the feeding and feedback processes of supermassive black holes, its origins remain under debate. Existing studies have primarily focused on the morphology and kinematics of warm ionized gas. This work aims to provide a new perspective on warm (10,000 K) ionized gas and its connection to X-ray-emitting hot gas (>10^6 K) by measuring and comparing their metallicities. We conducted a joint analysis of 13 massive elliptical galaxies using MUSE/VLT and Chandra observations. Emission-line ratios were measured for the warm ionized gas using MUSE observation, and used to infer the ionization mechanisms and derive metallicities of the warm ionized gas using HII, and LIN(E)R calibrations. We also computed the warm phase metallicity using X-ray/EUV, and pAGB stars models. For two sources at higher redshift, direct Te method was also used to measure warm gas metallicities. Our observations reveal that most sources exhibit composite ionization, with contributions from both star formation and LINER-like emission. A positive linear correlation was found between the gas-phase metallicities of the warm and hot phases, ranging from 0.3 to 1.5 Zsun, and suggest the intimate connection between the two gas phases, likely driven by gas cooling and/or mixing. In some sources the warm gas metallicity shows a central drop. A similar radial trend has been reported for the hot gas metallicity in some galaxy clusters. The ionization mechanisms of cooling flow elliptical galaxies are diverse, suggesting multiple channels for powering the warm ionized gas. The large variation in the warm gas metallicity further suggests that cold gas mass derived under the assumption of solar metallicity for the CO-to-H2 conversion factor needs to be revised by approximately an order of magnitude.

We study the $(w_0, \, w_a)$ parametrization of the dark energy (DE) equation of state, with and without the effective field theory of dark energy (EFTofDE) framework to describe the DE perturbations, parametrized here by the braiding parameter $\alpha_B$ and the running of the Planck mass $\alpha_M$. We combine the EFTofLSS full-shape analysis of the power spectrum and bispectrum of BOSS data with the tomographic angular power spectra $C_\ell^{gg}$, $C_\ell^{\kappa g}$, $C_\ell^{Tg}$ and $C_\ell^{T\kappa}$, where $g$, $\kappa$ and $T$ stand for the DESI luminous red galaxy map, Planck PR4 lensing map and Planck PR4 temperature map, respectively. To analyze these angular power spectra, we go beyond the Limber approximation, allowing us to include large-scales data in $C_\ell^{gg}$. The combination of all these probes with Planck PR4, DESI DR2 BAO and DES Y5 improves the constraint on the 2D posterior distribution of $\{w_0, \, w_a\}$ by $\sim 50 \%$ and increases the preference for evolving dark energy over $\Lambda$ from $3.8 \sigma$ to $4.6 \sigma$. When we remove BAO and supernovae data, we obtain a hint for evolving dark energy at $2.3 \sigma$. Regarding the EFTofDE parameters, we improve the constraints on $\alpha_B$ and $\alpha_M$ by $\sim 40 \%$ and $50 \%$ respectively, finding results compatible with general relativity at $\sim 2 \sigma$. We show that these constraints do not depend on the choice of the BAO and supernovae likelihoods.

Previous studies have examined the holographic principle as a means of producing dark energy. Here we propose instead the possibility of holographic dark matter. In this case, dark matter does not arise in the framework of particle physics but is derived from the infrared cutoff set by the horizon scale. Using the Ricci cutoff, and a universe containing only baryons and radiation, we can account for the dark matter and naturally explain the coincidence between baryonic and nonbaryonic contributions to the density. In the presence of a pre-existing vacuum energy density our model reverses the sign of this density, thus accounting for the fact that certain string theories generically predict a negative vacuum energy, but observations require a positive value.

The DESI collaboration reports a significant preference for a dynamic dark energy model ($w_0w_a$CDM) over the cosmological constant ($\Lambda$CDM) when their data are combined with other frontier cosmological probes. We present a direct Bayesian model comparison using nested sampling to compute the Bayesian evidence, revealing a contrasting conclusion: for the key combination of the DESI DR2 BAO and the Planck CMB data, we find the Bayesian evidence modestly favours $\Lambda$CDM (log-Bayes factor $\ln B = -0.57{\scriptstyle\pm0.26}$), in contrast to the collaboration's 3.1$\sigma$ frequentist significance in favoring $w_0w_a$CDM. Extending this analysis to also combine with the DES-Y5 supernova catalogue, our Bayesian analysis reaches a significance of $3.07{\scriptstyle\pm0.10}\,\sigma$ in favour of $w_0w_a$CDM. By performing a comprehensive tension analysis, employing five complementary metrics, we pinpoint the origin: a significant ($\approx 2.95\sigma$), low-dimensional tension between DESI DR2 and DES-Y5 that is present only within the $\Lambda$CDM framework. The $w_0w_a$CDM model is preferred precisely because its additional parameters act to resolve this specific dataset conflict. The convergence of our findings with independent geometric analyses suggests that the preference for dynamic dark energy is primarily driven by the resolution of inter-dataset tensions, warranting a cautious interpretation of its statistical significance.

Upcoming weak-lensing surveys will probe the matter distribution at a few percent level on nonlinear scales (k > 1 h/Mpc) where baryonic feedback from galaxy formation modifies the clustering of matter. Using the IllustrisTNG hydrodynamical simulations, we quantify the mass and radial dependence of baryonic suppression of the matter power spectrum by selectively replacing halos in the collisionless run with their full-physics counterparts. We find that group-scale halos with log $M_{200m}/h^{-1} M_{sun}$ in [13, 14] dominate the suppression, contributing a large fraction of the total reduction in power at k ~ 5-30 h/Mpc. The suppression is smaller on either side of this mass bin. Correctly reproducing the full suppression of the power spectrum requires accounting for matter redistribution (while enforcing mass conservation) beyond the virial radius of each halo. Crucially, the same group-scale regime produces the strongest and most detectable deviations in group-galaxy lensing, making stacked group lensing a powerful observational test of feedback models. Our results motivate emulators that jointly predict the matter power spectrum and halo-matter correlations including baryonic effects, enabling unbiased cosmological inference from small scales.

We introduce Synference, a new, flexible Python framework for galaxy SED fitting using simulation-based inference (SBI). Synference leverages the Synthesizer package for flexible forward-modelling of galaxy SEDs and integrates the LtU-ILI package to ensure best practices in model training and validation. In this work we demonstrate Synference by training a neural posterior estimator on $10^6$ simulated galaxies, based on a flexible 8-parameter physical model, to infer galaxy properties from 14-band HST and JWST photometry. We validate this model, demonstrating excellent parameter recovery (e.g. R$^2>$0.99 for M$_\star$) and accurate posterior calibration against nested sampling results. We apply our trained model to 3,088 spectroscopically-confirmed galaxies in the JADES GOODS-South field. The amortized inference is exceptionally fast, having nearly fixed cost per posterior evaluation and processing the entire sample in $\sim$3 minutes on a single CPU (18 galaxies/CPU/sec), a $\sim$1700$\times$ speedup over traditional nested sampling or MCMC techniques. We demonstrate Synference's ability to simultaneously infer photometric redshifts and physical parameters, and highlight its utility for rapid Bayesian model comparison by demonstrating systematic stellar mass differences between two commonly used stellar population synthesis models. Synference is a powerful, scalable tool poised to maximise the scientific return of next-generation galaxy surveys.

We build upon previous analytical treatments of scalar perturbations in curved inflationary universes to obtain analytical templates for the primordial tensor power spectrum in models with non-zero primordial spatial curvature. These templates are derived without assuming a particular inflaton potential, thereby isolating the universal imprints of curvature on tensor modes. Our results predict characteristic large-scale features -- including low-$\ell$ cut-offs and oscillatory patterns -- that are consistent with numerical solutions and provide a clear physical interpretation of how curvature modifies the underlying dynamics. In particular, we show that curvature effects manifest mathematically as systematic shifts in the dynamically relevant wavevectors, mirroring the behaviour previously identified in the scalar power spectrum. These features translate into distinctive signatures in the large-angle $B$-mode polarisation spectrum, offering a potential discriminant for spatial curvature in forthcoming CMB observations.

Astrophysical nuclear reaction rates in stellar environments are governed by the Gamow window, where Maxwell-Boltzmann distributions and quantum tunneling probabilities combine to produce effective reactivity. However, this conventional formulation is inadequate for the non-thermal ion distributions generated in ultra-intense laser-plasma interactions. Here, we introduce an analytical framework, based on a Target Normal Sheath Acceleration (TNSA) mechanism, to evaluate nuclear reaction rates under these non-equilibrium conditions. We identify a new effective energy window and analytical expression of the fusion reactivity distinct from the conventional Gamow window, providing a predictive tool for laboratory astrophysics experiments designed to replicate astrophysical nuclear processes using laser-driven nuclear reactions.

Cosmic inflation is the leading theory to explain early Universe history and structure formation. Non-oscillatory inflation is a class of models which can naturally introduce a post-inflationary stiff period of the Universe's evolution which boosts the signal of primordial gravitational waves (GWs), making it possible to observe them in forthcoming GW experiments. However, this pushes the GW energy density high enough to destabilise the process of Big Bang Nucleosynthesis (BBN). This problem can be overcome by "softening" the stiff period, so that the field is gradually tending towards freefall from a frozen start. Here, we consider a modified hybrid inflation model where the stiff period is driven by the waterfall field, allowing the barotropic parameter of the Universe to vary, so that it does not violate the BBN constraint but produces a characteristic gravitational wave spectrum soon to be observable.

We showcase cosmology's ability to constrain long-range forces between dark matter particles. Specifically, we consider a fermionic dark matter interacting via a Yukawa-coupled light scalar, focusing on regimes where the dark forces are stronger than gravitational and yet unconstrained. We show that the dark sector dynamics, both at the background and perturbation levels, is far richer than what can be captured with just the static interparticle Yukawa potential. The background dynamics includes an attractor that funnels a wide range of initial conditions onto an evolution unique to each parameter space. In a large swath of parameter space beyond existing limits, the dark sector deviates drastically from cold dark matter in observable epochs. We rule out this parameter space using existing constraints on dark-sector equation of state and small-scale cosmic perturbations, thus setting the strongest constraints yet on dark matter self-interactions at length scales shorter than 100 kpc. In addition, we briefly discuss repulsive dark forces and place cosmological limits that are stricter than in the attractive case.

We study the phenomenology of a sub-GeV $L_\mu-L_\tau$ gauge boson. We find discrepancies with existing literature in sensitivity projections for the upcoming SHiP experiment and in the treatment of supernovae cooling constraints. We present a quantitative analysis of different production modes in beam dumps and compare our results to previous work. In the context of supernovae, we re-evaluate the standard supernova cooling bounds from SN1987A and analyze additional supernova-based probes: diffusive cooling, constraints from the existence of low-energy supernovae, and the absence of a high-energy neutrino signal from SN1987A.

We introduce a novel class of bosonic dark matter candidates that we dub wallions, featuring boundaries in field space. The wallion mass is exponentially suppressed when the separation between boundaries far exceeds their intrinsic width and remains radiatively stable under self-interactions. We study the early-universe evolution of wallions and the associated cosmological signatures. Finally, we show that instanton effects can dynamically generate field-space boundaries and discuss possible experimental probes once the wallion couples to Standard Model fields.

The presence of multiple light axions in the infrared is a generic feature of many ultraviolet (UV) scenarios. In many cases the number of axions ${\cal N}$ is ${\cal O}(10-100)$ or more. Even in the scenario where these axions interact very weakly with the Standard Model (SM), the presence of ${\cal N}$ light axions poses a challenge to the stringent constraint on the number of relativistic degrees of freedom $N_{\rm eff}$. In order to remain agnostic about the UV, we adopt an effective field theory (EFT) approach, and parametrize the interactions of ${\cal N}$ axions with the SM to quantify the contribution to $N_{\rm eff}$. We consider operators up to dimension six, uncovering one previously-unconsidered charge radius operator, and pay particular attention to the flavor structure of the axion-SM fermion couplings and consider EFTs based on anarchy, textures, and minimal flavor violation. For various choices of such EFTs, we identify the discovery space for current and future cosmic microwave background surveys, including the Simons Observatory and CMB-HD. We show this discovery space depends sensitively on the flavor structure and exhibits a rich interplay with terrestrial and astrophysical probes.

Can a dynamically robust (\textit{aka} stable) $Q$-ball reproduce the rotation curve of a disk galaxy? In an astrophysical environment, $Q$-balls are non-topological solitons that are transparent and only perceived by their gravitational effects. Traditionally, scalar $Q$-balls are modelled with a polynomial potential, but axion-like periodic potentials are also expected to support such solitonic configurations. In the presence of angular momentum, $Q$-balls acquire a toroidal structure with a central density void, qualitatively resembling the structure of disk galaxies. Motivated by this similarity, we investigate whether rotating scalar $Q$-balls can reproduce the observed galactic rotation curves. In this work, we use a recently developed hybrid numerical framework that combines a high-accuracy pseudo-spectral method with a physics-informed neural network approach to construct both static and rotating $Q$-ball solutions. We then assess their ability to act as the dark matter halos in galaxies by fitting the observed rotation curves of a sample of disk galaxies from the SPARC catalogue. Our simplified model provides an overall good agreement with observational data; we have further found an average constraint on the scalar field particle's mass $m\sim 10^{-27}$ eV, in agreement with similar galactic-scale soliton solutions.

Gravitational waves emitted after neutron star binary coalescences and the information they carry about dense matter are a high-priority target for next-generation detectors. Even though such detectors are expected to observe millions of signals, detectable post-merger emission will remain rare. In this work, we explore post-merger detectability and inference through an alternative detector readout scheme for data dominated by quantum-noise, which is the case above $1$\,kHz: photon-counting. In such a readout, signals and noise become quantized into discrete distributions corresponding to the detection of single photons measured in a chosen basis of modes. Through simulated data, we demonstrate that photon counting can be efficient even for weak signals. We find ${\sim}1$ in 100 signals with a post-merger signal-to-noise ratio of 0.2 can result in a single photon and thus be detected. Furthermore, after $2\times10^4$ signals -- equivalent to $10^{-2}$ to $1.5$ years of observation -- photon counting results in a twofold improvement in the measurement of the radius of a $1.6\,M_\odot$ neutron star. Constraints can be further tightened if the detector classical noise is reduced. Photon counting offers a promising alternative to traditional homodyne readout techniques for extracting information from low signal-to-noise ratio post-merger signals.

Strong evidence for an isotropic, Gaussian gravitational wave background (GWB) has been found by multiple pulsar timing arrays (PTAs). The GWB is expected to be sourced by a finite population of supermassive black hole binaries (SMBHBs) emitting in the PTA sensitivity band, and astrophysical inference of PTA data sets suggests a GWB signal that is at the higher end of GWB spectral amplitude estimates. However, current inference analyses make simplifying assumptions, such as modeling the GWB as Gaussian, assuming that all SMBHBs only emit at frequencies that are integer multiples of the total observing time, and ignoring the interference between the signals of different SMBHBs. In this paper, we build analytical and numerical models of an astrophysical GWB without the above approximations, and compare the statistical properties of its induced PTA signal to those of a signal produced by a Gaussian GWB. We show that interference effects introduce non-Gaussianities in the PTA signal, which are currently unmodeled in PTA analyses.

Screened scalars are ubiquitous in many dark-sector models. They give rise to non-trivial fifth forces whilst evading experimental constraints through density-dependent screening mechanisms. We propose equipping a 10\,m-scale long-baseline atom interferometer with an annular planar source mass inside the vacuum chamber to search for such screened fifth forces. Two key challenges arise: distinguishing the static fifth force from backgrounds, and isolating it from the plate's Newtonian gravity. We introduce the `$Q$-flip protocol', which alternates between interferometry sequences to induce controllable time-dependence, aiding signal extraction and de-trending of transient noise. We further develop an \emph{in situ} calibration procedure to characterise the plate's Newtonian gravity and reach shot-noise-limited sensitivity. We show that our proposal could test theoretically motivated parameter space, advancing existing bounds in chameleon and symmetron screened scalar models by $1$ to $1.5$ orders of magnitude. Our proposal is directly applicable to forthcoming experiments, such as AION-10 or VLBAI, and is readily extensible to broader theoretical models and longer baselines.

Magnetohydrodynamic (MHD) simulations of subsonic (Mach number~$<1$) turbulence are crucial to our understanding of several processes including oceanic and atmospheric flows, the amplification of magnetic fields in the early universe, accretion discs, and stratified flows in stars. In this work, we demonstrate that conventional numerical schemes are excessively dissipative in this low-Mach regime. We demonstrate that a new numerical scheme (termed `USM-BK' and implemented in the FLASH MHD code) reduces the dissipation of kinetic and magnetic energy, constrains the divergence of magnetic field to zero close to machine precision, and resolves smaller-scale structure than other, more conventional schemes, and hence, is the most accurate for simulations of low-Mach turbulent flows among the schemes compared in this work. We first compare several numerical schemes/solvers, including Split-Roe, Split-Bouchut, USM-Roe, USM-HLLC, USM-HLLD, and the new USM-BK, on a simple vortex problem. We then compare the schemes/solvers in simulations of the turbulent dynamo and show that the choice of scheme affects the growth rate, saturation level, and viscous and resistive dissipation scale of the dynamo. We also measure the numerical kinematic Reynolds number (Re) and magnetic Reynolds number (Rm) of our otherwise ideal MHD flows, and show that the new USM-BK scheme provides the highest Re and comparable Rm amongst all the schemes compared.

Space weather at Earth, driven by the solar activity, poses growing risks to satellites around our planet as well as to critical ground-based technological infrastructure. Major space weather contributors are the solar wind and coronal mass ejections whose variable density, speed, temperature, and magnetic field make the automated classification of those structures challenging. In this work, we adapt a foundation model for solar physics, originally trained on Solar Dynamics Observatory imagery, to create embeddings suitable for solar wind structure analysis. These embeddings are concatenated with the spacecraft position and solar magnetic connectivity encoded using Fourier features which generates a neural field-based model. The full deep learning architecture is fine-tuned bridging the gap between remote sensing and in situ observations. Labels are derived from Parker Solar Probe measurements, forming a downstream classification task that maps plasma properties to solar wind structures. Although overall classification performance is modest, likely due to coarse labeling, class imbalance, and limited transferability of the pretrained model, this study demonstrates the feasibility of leveraging foundation model embeddings for in situ solar wind tasks. As a first proof-of-concept, it lays the groundwork for future improvements toward more reliable space weather predictions. The code and configuration files used in this study are publicly available to support reproducibility.

This work explores using the physics-inspired AI Feynman symbolic regression algorithm to automatically rediscover a fundamental equation in astronomy -- the Equation of the Centre. Through the introduction of observational and inductive biases corresponding to the physical nature of the system through data preprocessing and search space restriction, AI Feynman was successful in recovering the first-order analytical form of this equation from lunar ephemerides data. However, this manual approach highlights a key limitation in its reliance on expert-driven coordinate system selection. We therefore propose an automated preprocessing extension to find the canonical coordinate system. Results demonstrate that targeted domain knowledge embedding enables symbolic regression to rediscover physical laws, but also highlight further challenges in constraining symbolic regression to derive physics equations when leveraging domain knowledge through tailored biases.

We investigate the emergence of a resonant behavior in axion-trapped misalignment models featuring finite-temperature potential barriers. As the temperature decreases and the field is released from its trapped configuration, inhomogeneities are exponentially amplified through an instability in their equation of motion, leading to the fragmentation of the axion field. We show that this process constitutes a novel source of gravitational waves (GWs), analogous to those generated in zero-temperature axion fragmentation, but with distinct characteristics. We quantify the resulting GW spectrum, identifying the peak frequency and amplitude associated with the inhomogeneous axion dynamics. Our results indicate that the GW signal can be enhanced by up to two orders of magnitude compared to the standard fragmentation scenario, while exhibiting a markedly different spectral shape. The parameter space featuring both strong GW signals and reproducing the correct dark matter abundance is, however, limited.

Based on a comprehensive analysis of recent observational data-a combination of DESI DR1, Planck CMB, and Pantheon+ SN Ia-this study critically evaluates the two dark energy (DE) proposals within Harada's Conformal Killing Gravity (CKG) model. The model in question predicts either a dominant phantom-type effective DE component with EoS $\omega = -5/3$ or a hybrid scenario combining a cosmological constant ($\omega = -1$) with a subdominant $\omega = -5/3$ fluid (around $5\%$) to address the Hubble tension (HT) and late-time acceleration. An analysis based on the Trans-Planckian Censorship Conjecture (TCC) demonstrates that the pure CKG fluid scenario $\omega = -5/3$ is excluded, whereas the hybrid model remains only marginally compatible. Our Markov Chain Monte Carlo (MCMC) analysis constrains the effective DE density parameter to $\Omega_{\text{eff}} = 0.009^{+0.006}_{-0.007}$ ($68\%$ CL), consistent with zero and ruling out the around $5\%$ contribution required by Harada's CKG. The resulting Hubble expansion history $H(z)$ and effective EoS $\omega_{\text{eff}}(z)$ are indistinguishable from those of $\Lambda$CDM. Bayesian model comparison via the Akaike Information Criterion (AIC) shows no statistical preference for CKG over $\Lambda$CDM ($\Delta \text{AIC} = +2.6$), disfavoring the additional complexity of the CKG model. The key output of this study is that both DE proposals in Harada's CKG are ruled out by current cosmological data, and HT remains unresolved.

Despite heat flux's role in regulating energy conversion in collisionless plasmas, its properties and evolution in the magnetosheath downstream of the Earth's bow shock are scarcely explored. We use MMS in situ measurements to quantify and characterize the electron heat flux in the magnetosheath. We find that the heat flux is shaped by the magnetosheath magnetic field as it drapes around the magnetosphere. While it is affected by solar wind upstream conditions and increases with magnetic field strength, it is not substantially changed by local magnetosheath processes. Also, the heat flux is limited by whistler instability thresholds.

We explore the cosmological dynamics of a supercooled first-order phase transition in the classically conformal $U(1)_{B-L}$ extension of the Standard Model, where radiative symmetry breaking simultaneously generates the right-handed neutrino (RHN) masses, and a strong stochastic gravitational-wave (GW) background. The slow decay of the scalar field into RHNs can induce an early matter-dominated (EMD) era whose duration is sensitive to the RHN mass and gauge coupling $g^\prime$. This non-standard cosmological phase reshapes the GW spectrum and leaves a distinctive RHN-mass-dependent spectral distortion that correlates with the flavour regime of thermal leptogenesis. Within this framework, one RHN can serve as a dark matter candidate produced nonthermally from scalar decays, while the remaining states generate the baryon asymmetry via thermal leptogenesis. For $g^\prime=0.5$, we identify such a parameter region, and show that with singlet extensions, even with a smaller gauge coupling, one can realise this mechanism for the three-flavour regime. The resulting GW signals, amplified by supercooling and modified by EMD, provide a unique window to probe the scale and flavour structure of leptogenesis in future high-frequency GW observations.

In standard (symmetry-breaking) first-order phase transitions, the frictional pressure on expanding bubble walls can be dominated by transition radiation -- the emission of a gauge boson with phase-dependent masses as particles present in the thermal plasma pass through bubble walls. This process is enhanced in the soft limit, and is known to produce a significant frictional effect that is proportional to the Lorentz factor $\gamma$ of the bubble wall, thereby prohibiting runaway behavior. We calculate the analogous pressure for phase transitions with symmetry restoration. In such transitions, we show that the pressure due to this process can be $\textit{negative}$, producing the opposite effect. However, when the Lorentz factor of the wall gets very large, the result approaches the same scaling as the standard scenarios. Therefore, phase transitions with symmetry restoration can feature an intermediate negative friction regime even in the presence of significant interactions with the plasma, and the bubble wall terminal Lorentz factor can be significantly larger (by more than an order of magnitude) than in the corresponding symmetry-breaking scenarios. This can carry important implications for various phenomenological applications, from gravitational waves to physics beyond-the-Standard-Model.

While Dark Matter (DM) is typically assumed to interact only very weakly with the particles of the Standard Model, many direct detection experiments are currently exploring regions of parameter space where DM can have a large scattering cross section. In this scenario, DM may scatter in the atmosphere and Earth before reaching the detector, leading to a distortion of the DM flux and a daily modulation of the signal rate as the detector is shielded by more or less of the Earth at different times of day. This modulation is a distinctive signature of strongly-interacting DM and provides a powerful method of discriminating against time-independent backgrounds. However, the calculation of these Earth-scattering effects by Monte Carlo methods is computationally intensive, inhibiting a systematic exploration of the DM parameter space. Here, we present a semi-analytic formalism for calculating Earth-scattering effects, for models of MeV-mass DM which interacts via a dark photon mediator, and release the associated code Verne2. This formalism assumes that DM travels along straight-line trajectories until it scatters and is reflected back along its incoming path, along us to taking into account the affects of both attenuation and reflection in the Earth. We compare this formalism with the results of full Monte Carlo simulations for cross sections within reach of current and future DM-electron scattering searches. We find that Verne2 is accurate to better than 10-30%, making it suitable for performing signal modeling in the search for daily modulation, while reducing the computational cost by a factor of $\sim10^4$ compared to full Monte Carlo simulations.

We introduce a novel mechanism where the kinetic energy of a rotating axion can be dissipated by the interactions with dark magnetic monopoles. This mechanism leads to a framework where the QCD axion and dark monopoles account for the dark matter density, and the observed baryon asymmetry is generated through the rotating QCD axion via axiogenesis. The monopoles acquire masses from a nonzero axion field, and they can transition between different quantized dyonic levels in the presence of a rotating axion field. The axion kinetic energy is dissipated by the transition, and thus the axion abundance is depleted to the observed dark matter abundance. We predict that the axion decay constant should be below $10^9$ GeV to explain the observed dark matter and baryon densities.