Papers

Models of escaping planetary atmospheres require neutral and ion species with distinct velocities and thermal pressures, coupled by photoionization, recombination, radiation, and collisions. Implementing and extending such coupled models is often hindered when species definitions and stiff interactions are embedded in solver-specific kernels. We present Xenia, a table-driven code for astrophysical multi-fluid hydrodynamics designed to lower this barrier. Species, coupling channels, chemistry, heating and cooling, and radiation channels are declared in Python, compiled to symbolic tapes, and passed through a versioned interface to shared C/Kokkos kernels; changing a problem therefore changes data rather than kernel code. For ionized configurations, electrons provide a pressure-only quasi-neutral closure: electron density follows from ion populations, electron mass and momentum are not advanced, and only electron pressure is transported. Stiff coupling is treated by operator splitting into a radial radiation scan, hyperbolic transport, and a cell-local implicit source solve. The same symbolic tapes yield an analytic finite-difference-free Jacobian for a direct dense LU solve. The public v0.1 release is validated with acoustic convergence, dustybox drag relaxation, conservation and closure contracts, two-fluid cloud-shock coupling, curvilinear geometry bookkeeping, three escape chains, and 394 passing tests. Conservation and positivity are not claimed to match mature production codes; radiation uses a radial Beer-Lambert prefix product rather than a general solver; escape chains are reproducibility checks rather than new science predictions; and backend evidence is limited to functional deployment and equivalence fingerprints. Xenia is released under GPLv2 at https://github.com/YFG-tec/xenia.

Context. Modeling the global dynamics of the Sun requires numerical frameworks capable of simulating the highly turbulent convective envelope and its coupling with the stable radiative interior. Simulating such spherical domains in standard cartesian finite-volume codes presents significant topological challenges. Aims. The goal is to extend the cartesian Adaptive Mesh Refinement (AMR) framework Dyablo to non-cartesian geometries in order to perform global solar convection simulations that extend all the way down to the stellar core. Methods. We introduced a mapped grid approach within the Dyablo framework to build Dyablo Whole Sun (DWS) code. We implemented an $\alpha-\beta$ well-balanced scheme to preserve hydrostatic equilibrium. Furthermore, we present a robust methodology to generate fully integrated solar background profiles from $r=0$ to the surface. Results. We validated the implementation using standard hydrodynamic tests and ran high-resolution 2D global solar convection simulations on a disk grid. Conclusions. Our models successfully capture the turbulent convective broad slow upflows and narrow fast downflows and the excitation of acoustic waves and p modes. The interaction of strong downflowing plumes with the top of the radiative zone, successfully excites internal gravity waves in the radiative interior.

We present the first calculation showing that a material-asymmetric Sagnac speed meter can improve quantum-noise-limited sensitivity to $B-L$ vector dark matter by nearly two orders of magnitude over a Fabry–Perot Michelson position meter at the low-mass end of the band. We introduce material contrast into a dual-ring interferometer to probe composition-dependent $B-L$ forces and compare the two configurations at equal incident power, input-mirror transmissivity, and cavity round-trip length. For sapphire mirrors and a one-week benchmark, the quantum-noise-only median expected $95\%$ CL upper limit reaches $1.2\times10^{-27}$ at $m_A=4.1\times10^{-14}\,\mathrm{eV}/c^2$ ($10\,\mathrm{Hz}$), a factor-$57$ improvement. This band-edge forecast assumes negligible classical noise; sensitivity at $10\,\mathrm{Hz}$ is not established for a realizable suspension and isolation system. The material-induced displacement is essentially identical in both configurations, with the gain arising from reduced low-frequency quantum backaction. These results identify speed-meter readout as a promising route to lower-mass vector-dark-matter searches.

Black-hole (BH) quasinormal modes encode the properties of merger remnants and provide powerful tests of strong-field gravity. The BH spectroscopy has predominantly treated them as independent linear oscillations. Nonlinear ringdown can additionally reveal how these modes interact and which intermediate states mediate their interactions. Inspired by cosmological collider physics, we introduce quasinormal-mode collider spectroscopy (QCS), a framework for organizing and predicting nonlinear BH responses. We establish two structural results. First, at an isolated, nondegenerate intermediate pole, a cubic strain residue factorizes into an excitation amplitude and a quadratic conversion coefficient. This factorization imposes rank constraints across output channels and choices of second-order initial data, providing consistency tests of the intermediate-mode description. Second, the intermediate pole residue can be reconstructed from its horizon and infinity radiation. With the first-order field and third-order data held fixed, this reconstruction extends to the full cubic waveform difference generated by changing the second-order initial data. QCS thus connects lower-order radiation to higher-order observables and provides a framework for probing the interaction structure of nonlinear ringdown.

Since its original publication in 2020, the SWAN-SF dataset has been cited in over 300 research publications. Here we describe a comprehensive update to the original multivariate time series (MVTS) dataset extracted from solar photospheric vector magnetograms in the Spaceweather HMI Active Region Patch (SHARP) series. As was performed in the original release, our dataset includes a cross-checked NOAA solar flare catalog that facilitates the comparative evaluation of methods designed for solar flare prediction. We discuss the methods used for data collection, cleaning, and pre-processing of the solar active region and flare data, which includes improvements to the data integration and sampling methodology. Additional parameters have been derived from the Solar Dynamics Observatory's Atmospheric Imaging Assembly to augment the original features derived from magnetogram data. Our dataset expands the period of observations to cover 7,730 MVTS data collections from active regions occurring between May 2010 and December 2025, each of which is composed of 182 flare-predictive parameters. We continue to integrate flare reports, with over 39,000 multi-source verified flare reports providing flaring history information about the source active regions. The primary tasks enabled by the disseminated dataset continue to include optimization of solar flare prediction and detailed investigation for elusive flare predictors or precursors, with both operational (research-to-operations), and basic research (operations-to-research) benefits.

We investigate the damping rate of Alfvén waves by means of the linear analysis of the two-fluid ten-moments system. To treat effects of viscosity in a wide frequency range, we take account of the time evolution of the traceless part of the pressure tensor. In addition, to treat effects of viscosity in a wide range of the ionization degree, we consider interactions between hydrogen atoms and between protons and hydrogen atoms in the equation of the traceless part of the pressure tensor. We find approximate analytical solutions to the dispersion relation for some limits. Our analysis in the low-frequency limit shows that the viscous damping dominates over the frictional damping in the high-beta plasma, which is independent of the ionization degree. Therefore, the viscosity of hydrogen gas significantly affects cosmic-ray propagation in a partially ionized high-beta plasma.

The long observational record of He I 10830 Å offers a means to investigate solar morphology before modern extreme-ultraviolet (EUV) imaging. We adapt the Surya solar foundation model to predict Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) 94, 193, and 304 Å images and a coronal hole (CH) probability map from full-disk helium observations. A convolutional input adapter, low-rank backbone updates, and dedicated output decoders learn from temporally paired, geometrically registered observations, with Spatial Possibilistic Clustering Algorithm (SPOCA) catalog polygons providing CH supervision. On observations held out from downstream fine-tuning, the selected dedicated models achieve disk-restricted correlation coefficients (CCs) of 0.8196, 0.8885, and 0.8398 for the three AIA channels, respectively; the CH model achieves an intersection over union (IoU) of 0.4360. The predictions recover broad solar structure, although local agreement varies substantially by channel. An optional residual refiner addresses spatial detail, and its application on pre-SDO dates improves the correlation of synthetic AIA 304 with Solar and Heliospheric Observatory/Extreme-ultraviolet Imaging Telescope (SOHO/EIT) 304 references from 0.6511 to 0.7085. Together, these results support the feasibility of helium-conditioned EUV morphological proxies and motivate their use in historical reconstruction, within the scope of the downstream test and cross-instrument evaluation.

We describe the implementation and on-sky commissioning of a two-input spectrometer/correlator built on a Xilinx ZCU208 Radio Frequency System-on-Chip (RFSoC) and deployed on the Baryon Mapping eXperiment (BMX) interferometric array at Brookhaven National Laboratory. The system combines direct RF sampling, FPGA-based correlation, and 100 Gigabit Ethernet (GbE) visibility transport. Two inputs are digitized directly at 1050 MHz without analog downconversion and channelized into 2048 frequency channels. The correlator forms two autocorrelations and the real and imaginary parts of the cross-correlation, accumulates them in on-chip memory, and transmits the spectra as UDP packets at a fixed firmware-controlled rate. Two independent campaigns using 500 ms and 100 ms accumulation times produced 958,918 consecutive accumulations with no lost, duplicated, or malformed packets. A Cauchy-Schwarz bound is satisfied across all 1.96e9 channel-samples, confirming correct field identification and scaling. On-sky validation includes compact-source transits in six GNSS bands with the expected fringes, coherent detection of the Cygnus A zenith transit at the predicted time, and a Galactic HI plane crossing detected independently in autocorrelation on both dishes. The correlator is parameterizable in input count, with arithmetic scaling quadratically. For extension to BMX's full eight-input dual-polarization system, an occupancy model validated against the deployed firmware indicates that visibility buffering fits when moved to UltraRAM, while multi-tile synchronization, logic utilization, and timing closure remain to be demonstrated in an eight-input implementation.

Exoplanetary astronomy has entered its Golden Age, with humanity having found over 6000 exoplanets to date. The majority of these discoveries have been achieved through transit-photometry and radial-velocity (RV) techniques. While transit surveys lead in discovery numbers, the RV method persists as a vital and indispensable technique in exoplanetary science, particularly in the most prevalent stellar population – M dwarfs. Their low masses make them the theoretical favourites for RV detections, since exoplanet signals are stronger over the same period, and are therefore easier to detect and measure accurately. Nevertheless, the stellar activity M dwarfs exhibit introduces significant challenges, particularly when seeking RV semi-amplitudes to the order of 1 m$\,$s$^{-1}$, or lower. Stellar activity is known to mimic or suppress planetary signals, and its effects manifest across all time scales: from short-lived signals due to convective motion (lasting minutes to days), through active regions on the stellar surface (days to months), to long-term magnetic cycles (years to decades). These issues highlight the urgent need for robust methodologies that are capable of reliably disentangling stellar variability from genuine planetary signals. This doctoral dissertation explores these challenges through the application of Gaussian-process (GP) modelling. I present three distinct but interconnected publications that integrate high-precision spectroscopy and photometry with a unified GP-based approach in two cases, and that enable robust disentanglement of planetary signals from stellar activity. Together, these three studies illustrate how observations of different origin can be combined with appropriate statistical machinery for the sake of detecting exoplanets, with the possibility of interpreting stellar activity.

The Zel'dovich-inspired (ZI) transform is a local nonlinear transform of the density field that can Gaussianize the late-time matter field and recover information from higher-order $N$-point correlation functions through its power spectrum, with the parameter $\eta$ controlling the weighting of higher-order information. Using Fisher-matrix analyses of halo catalogs from the Quijote and Quijote-PNG simulations, we study the redshift-space monopole power spectrum of the ZI-transformed halo density field. The joint statistic $P_{\rm ZI,0}$, constructed from three representative transforms with $\eta=1$, $10$, and $+\infty$, yields substantially tighter constraints than the conventional halo power spectrum $P_{\rm h,0}$ on standard cosmological parameters, the summed neutrino mass, and primordial non-Gaussianity amplitudes, while outperforming the marked power spectrum for many parameters. We further calibrate a scale-dependent noise correction for the ZI power spectrum, with an effective noise amplitude that depends on wavenumber, and find that the correction further tightens the constraints. In particular, the noise-corrected $P_{\rm ZI,0}$ improves the constraints on $f_{\rm NL}^{\rm equil}$, $f_{\rm NL}^{\rm ortho}$, $M_\nu$, and $n_{\rm s}$ by factors of $5.6$, $5.5$, $5.2$, and $5.8$, respectively, relative to $P_{\rm h,0}$. These results demonstrate the potential of ZI power spectra as a complement to standard two-point statistics for extracting nonlinear cosmological information. Our forecasts may be conservative because the halo catalogs have substantially lower number densities than those expected from forthcoming galaxy surveys.

Pulsar glitches are thought to involve sudden unpinning and fast transport of large numbers of pinned vortices, possibly triggered by breaking of the neutron star crust solid. Such a vortex avalanche can take place on a fast timescale only if there are pathways for fast vortex motion. Formation of local vortex “traps” (regions containing larger than average density of pinned vortices) will provide vortex-free regions surrounding the traps, which can connect to form pathways for fast vortex motion. We propose a simple two-dimensional model for the neutron star crust superfluid, with the vortex pinning landscape tiled into traps and surrounding vortex-free regions which can connect to azimuthal pathways for fast vortex motion. The trap and tile sizes are estimated from the physics of the crust solid and vortex pinning, namely the critical strain angle of the crust solid and the critical velocity for vortex unpinning. Unpinned vortices move with the superfluid flow in the azimuthal direction while also scattering radially outward, by a small angle, due to mutual friction. The model qualitatively explains the glitch parameters and their evolution in young pulsars and provides an explanation for the bi-modality in the distribution of glitch magnitudes. Laboratory experiments and simulations on vortex systems with spatially inhomogeneous vortex pinning landscapes are likely to be more realistic models for pulsar glitches. Breaking the spatial scale-invariance and monitoring the results may also lead to better understanding of collective behaviour in pinned vortex systems in general.

Breakthrough Listen, humanity's most ambitious search for technosignatures, or evidence of extraterrestrial technology, is carrying out surveys across the sky and across the electromagnetic spectrum, in images, spectra, time series, catalogs, and alerts. Classical techniques still play a major role in the search, but the recent rapid growth in the capabilities of artificial intelligence is enabling new and more powerful algorithms and approaches to be deployed across enormous datasets. Surveys designed to look for technosignatures are still a major focus for the Breakthrough Listen program, but excitingly, the new strategies also enable comprehensive mining of archives and of general-purpose real-time data streams. We outline how artificial intelligence and machine learning are being used to scale up the search, including with the newly-commissioned Vera C. Rubin Observatory, in addition to radio telescopes around the planet. The chances of a detection have never been better.

We present a multi-wavelength study of an extended molecular cloud hosting the LDN 1204, Sh2 145, and Sh2 140 regions to investigate the interplay between stellar feedback, cloud dynamics, and star formation. Infrared images reveal two semi-arc/shell-like structures (extent 14-18 pc) associated with known massive O-type stars. Herschel temperature and column density maps identify one hub-filament system (HFS) candidate toward both LDN 1204A and LDN 1204B sub-regions, with peak column densities of 3.1 x 10^23 and 1.3 x 10^23 cm^-2, respectively. These sub-regions are located at the periphery of the Sh2-145 H ii region. Molecular line data reveal a large arc-/shell-like cloud resolved into two kinematically distinct components spanning -15 to -9.5 km s^-1 and -9 to -3 km s^-1. Each component exhibits an arc-/shell-like morphology, is centered on one of the massive stars, and displays an inverted C-shaped position-velocity structure, indicating expansion driven by its associated H ii region. Both LDN sub-regions are located at the projected interface of the two expanding cloud components. Young stellar objects (YSOs), particularly Class I YSOs, are concentrated toward these sub-regions, while moment 2 maps reveal enhanced velocity dispersion, suggesting increased turbulent motions at the interface. Altogether, the presence of dense filaments, candidate hub-filament systems, and active star formation in LDN 1204 sub-regions demonstrates that feedback driven shell expansion and interaction compressed the gas at the interface, establishing the necessary conditions for filaments and ongoing star formation. These results highlight the important role of feedback-driven cloud interactions in regulating dense structure formation and star formation in molecular clouds.

Ultraluminous infrared galaxies (ULIRGs) are the remnants of the major mergers of gas-rich galaxies. They are dusty systems and are extremely luminous in the infrared. Both starbursts and active galactic nucleus (AGN) activity supply power in these systems, but it is not clear how these two activities are related to the overall evolution of the merger remnant. Studies suggest that there may be an evolutionary link between ULIRGs and radio galaxies. Radio observations of ULIRGs are a useful tool for understanding this evolutionary path as well as studying the energy contributions from starbursts and AGN. We perform a systematic census of these signatures in 38 ULIRGs using upgraded Giant Metrewave Radio Telescope observations and archival radio data. In the sample, 30 sources have enough frequency coverage to obtain their radio spectrum. Of these, 17 sources show a turnover frequency between 63 and 509 MHz and a spectral age variation from 0.009 to 44 Myr. Also, eight sources have extended structures with projected linear sizes varying from 0.7 to 11 kpc. Our results indicate that the primary energy source in these systems is the AGN rather than star formation. The majority of the ULIRGs in our sample, particularly those in the post-merger stage, exhibit gigahertz-peaked spectrum or compact steep spectrum-like characteristics, suggesting that they are evolving into young radio galaxies. We note that six sources with high star formation activity show a low-frequency turnover and a smaller spectral age; we confirm these six sources host buried AGN. This study enables us to trace the evolutionary link between ULIRGs and radio galaxies.

The Einstein Probe (EP) has discovered a fast X-ray transient, EP260321a, whose optical counterpart was subsequently classified as a broad-lined Type Ic supernova. Its observed rise time of about 690 seconds is inconsistent with theoretical predictions for shock breakout (SBO) from a Wolf-Rayet star, which is typically regarded as the progenitor of envelope-stripped supernovae. In this paper, we propose that EP260321a arose from a SBO within extended circumstellar matter (CSM), where breakout photons were initially trapped, then diffused out of the unshocked CSM as the ejecta expanded and the opacity decreased. We modeled this photon diffusion process using both Monte Carlo simulations and an analytical approach to describe the temperature evolution. Through Markov Chain Monte Carlo sampling, we obtain the best-fit CSM parameters of log10(Mcsm/Msun) = -3.3 for the total CSM mass, Rin = 160 Rsun for the inner CSM radius, and Rout = 612 Rsun for the outer CSM radius. The presence of such a dense CSM indicates that the progenitor of EP260321a underwent episodic mass loss just days before the explosion, providing new observational constraints on the late-stage evolution of massive stars.

Abridged. We aim to extend Paper I to the eccentric secondary orbit case and now analyse the elliptic restricted three-body problem (ERTBP). Our secondary masses include Ceres, Mercury, Earth, and Neptune so that we can help infer the presence of both large asteroids and planets through our analysis. We study dust particles on both planar (2D-ERTBP) and non-coplanar (3D-ERTBP) orbits. We computed families of 1/1 resonant symmetric and asymmetric periodic orbits in the 2D-ERTBP and 3D-ERTBP. Doing so produces novel results in their own right and diagnostic tools for precise guidance for our next steps. Based on them, we generated detailed phase portraits. Finally, we run suitably seeded $N$-body simulations to compare with the periodic orbits, and to provide observational links with debris close to WDs. New families of asymmetric periodic orbits, called $E^A_{41}$, $E^A_{42}$, and $E^A_{43}$ in the high-eccentricity 2D-ERTBP regime were discovered. They are generated by the new bifurcation point, $B_T^4$, along the new $A_2$ family, showcased in Paper I. Moreover, new isolated families of asymmetric periodic orbits, namely $E^A_{44}$, $E^A_{45}$, and $E^A_{46}$ were discovered. Families of short- and long- period asymmetric orbits starting from $L_4$, called $E^A_S$ and $E^A_L$, were also computed. In both the 2D- and 3D-ERTBP regimes, highly eccentric motion is exhibited for the dust particles in the majority of the families of either symmetric or asymmetric periodic orbits. The $N$-body simulations reveal that over ten years, the orbital period deviations of the dust are higher than in the circular restricted three-body problem (Paper I); in some architectures, Mercury-mass planets can regularly generate deviations exceeding $\sim$100 s, which potentially aids observational inferences of hidden asteroids or planets orbiting WDs.

We present two decades of X-ray monitoring of the eclipsing accreting pulsar Hercules X-1 with Fermi/GBM, Swift/BAT and MAXI/GSC, centred on the extended low state (ELS) that began in 2025 May (the first such event in 22 years) and is still ongoing at the time of writing, $\sim$480~d after its onset. The 35-d superorbital clock does not simply stop in the ELS; it fades. The surviving modulation stays phase-locked to the pre-ELS clock until the flux of the main high state (the bright phase of the 35-d cycle) has decayed to a few per cent of its normal level. The in-phase coherence is then lost, around 2026 January–March. We classify the pre-ELS pulse-frequency history into three torque states: spin-up, spin-down and flat. The spin derivative correlates positively with the main-high hard X-ray flux (Pearson $r\simeq0.7$), and the ELS hosts the longest sustained spin-down of the record, $\dot{\nu}\approx-4.7\times10^{-13}$~Hz~s$^{-1}$ over the $\gtrsim$380~d of \fer/GBM coverage. The 8–50 keV pulse-profile morphology is statistically indistinguishable across the torque states at fixed superorbital phase, and the shape parameters show no secular drift over the 18-yr record. These results show that the precessing warped accretion disc keeps its rhythm while the pulsar fades from direct view: the clock keeps its phase, the torque keeps tracking the accretion flux, and the beam keeps its shape. No free precession of the neutron star is required by the current monitoring data.

We present a machine-learning pipeline for determining stellar parameters and chemical abundances from spectra observed by the Dark Energy Spectroscopic Instrument (DESI). Building on the model-driven Payne framework, we train an artificial neural network on ~370,000 synthetic spectra spanning FGK stars, and fit the network directly to the flux-calibrated, un-normalised spectral energy distribution (SED) of each star, rather than to a continuum-normalised spectrum as done by DESI's official Stellar Parameter (SP) pipeline. Internal accuracy tests show a median interpolation error of less than 0.3% for 90% of a synthetic verification sample, and the full fitting workflow recovers input labels to high accuracy even at low signal-to-noise ratio (S/N). Validating our method on cross-matched samples of 6719 APOGEE and 3455 GALAH stars observed by DESI with S/N > 20, we recover Teff and logg with smaller systematic offsets than the DESI SP pipeline, an improvement we attribute to fitting the full SED shape rather than a normalised spectrum. We further recover 12 elemental abundances (Na, Mg, Al, Si, Ca, Ti, V, Cr, Mn, Ni, Ba, and Y) to an accuracy that matches or exceeds SP where a comparison is possible, and provide four abundances, Mn, V, Ba, and Y, that SP does not report at all. Applying this pipeline to the DESI Data Release 1 stellar sample, we deliver a catalogue of stellar parameters and abundances for 3.2 million stars.

Modelling cold dark matter as dust makes the matter congruence geodesic and therefore removes any intrinsic dipole from the local Hubble flow. The dust model breaks down as stream crossing develops, whereas a collisionless gas accommodates stream crossing via velocity dispersion in phase space. We develop a covariant kinetic framework for this regime without assuming a background spacetime or any geometrical symmetry. Starting from the exact massive Vlasov hierarchy, we construct its energy-integrated moments and organise these by velocity weight. A self-consistent truncation at the quadrupole closes the dynamics on the matter energy density, isotropic pressure and anisotropic pressure. Their gradients generate a matter-frame 4-acceleration, for which we find an exact nonlinear solution of the momentum constraint, valid in the general case without truncation. This goes beyond previous work in which an arbitrary 4-acceleration is introduced. Velocity dispersion also sources vorticity through the curl of 4-acceleration, and we derive the nonlinear expression for vorticity evolution. We then propagate the non-geodesic matter flow into covariant local cosmography, where the 4-acceleration is the intrinsic Hubble dipole and also enters the deceleration multipoles. Our construction provides a covariant kinetic completion of dust cosmography and identifies the quantities required to test collisionless matter directly with local distance–redshift data. A companion paper specialises the hierarchy to perturbed FLRW spacetime and predicts the size of the resulting cosmographic signals.

A dark-matter core and a soft nuclear equation of state can produce similar mass–radius signatures, motivating a complementary probe through the $f$-mode spectrum. We compute quadrupolar $f$-mode frequencies and gravitational-wave damping times in full general relativity for cold, nonrotating neutron stars admixed with self-interacting bosonic dark matter (DM). Our two-fluid survey spans 21 nuclear equations of state covering nucleonic, hyperonic, $\Delta$-admixed, and combined hyperon–$\Delta$ compositions at $F_{\rm DM}=1$–$20\%$. The main sequences use $\lambda=\pi$ and boson masses of $500$ and $100\,\mathrm{MeV}$ for the core and halo studies, respectively. Independent normal-matter (NM) and DM displacements couple through the metric, yielding NM-led and DM-led $f$-mode branches whose radiative damping is determined by outgoing-wave boundary conditions. At $1.4\,M_\odot$, the core DM-led damping time decreases from order $10^3\,\mathrm{s}$ at $F_{\rm DM}=1\%$ to order $1\,\mathrm{s}$ at $20\%$, approximately following an empirical $F_{\rm DM}^{-2}$ dependence, while NM-led damping times remain within $0.12$–$0.33\,\mathrm{s}$. Halo DM-led damping instead increases with dark fraction: at the same stellar mass and $F_{\rm DM}=20\%$, dark radii approach $88\,\mathrm{km}$, frequencies fall to $0.14\,\mathrm{kHz}$, and damping times reach approximately $450\,\mathrm{s}$. Selected high-mass core sequences exhibit strong DM-led damping-time upturns not reproduced by the leading mass-quadrupole diagnostic. Representative core calculations show greater DM-led sensitivity to the bosonic self-coupling and retain both branches at $\ell=3$. Under the adopted nonrotating, circular-binary prescriptions, no evaluated configuration satisfies all geometric and perturbative conditions for a controlled linear tidal resonance.

The Galileo Project operates three autonomous multi-camera observing sites near Las Vegas, Nevada, separated by baselines of $2$ and $10\,$km, with the goal of characterizing the populations of natural and human-made objects that cross the sky and thereby isolating any event that fits none of them. Each site carries an array of eight long-wave infrared (LWIR) cameras arranged in a fixed dome-like structure, an IR-Dalek, providing $360^{\circ}$ azimuthal coverage. We report the commissioning of the three arrays and present the triangulation pipeline built on them. Because our targets are not assumed to follow any particular trajectory, we depart from the parametric fits standard in meteor work and estimate the instantaneous three-dimensional position at each time step as the point that minimizes the weighted sum of squared distances to the simultaneous lines of sight, weighting each camera by its own pointing uncertainty and by its range to the object. We describe the intrinsic and extrinsic calibration procedure, which uses Automatic Dependent Surveillance-Broadcast (ADS-B) aircraft as reference sources in the absence of stars or fixed landmarks in the LWIR field of view, and the multi-sensor track association scheme that decides which detections belong to the same object. Using one week of data (2026 May 24-30; $1{,}650$ camera-hours, $2.1\times10^{8}$ detections and $5.3\times10^{6}$ tracks), we validate the recovered positions, speeds and accelerations against ADS-B records, recovering distances to within $5$% for $99$% of the aircraft solved from three sites and for $83$% of those solved from a single site pair and speeds to within $5$% for $78$% and $63$% of them respectively. We characterize the identification completeness of the array, which is set by apparent size: the $50$% identification threshold falls at $1.8$ pixels of apparent wingspan.

We identified X-ray binary (XRB) candidates in the galaxy NGC 6946 using archival Chandra data. A total of 98 XRB candidates were detected within the 0.3$-$8 keV energy range, with luminosities between 10$^{36}$ and 10$^{40}$ erg~s$^{-1}$. X-ray color-color diagrams were constructed for these sources, classifying 57 as high-mass X-ray binaries (HMXBs) and 8 as low-mass X-ray binaries (LMXBs). The X-ray temporal variability of the sources was analyzed, revealing that 40 sources exhibit variability and 26 are classified as transient sources. Possible optical counterparts for 57 sources were identified using Hubble Space Telescope (HST) images. Based on the color-magnitude diagrams (CMDs), 40 sources were found to have masses greater than 8M$_{\odot}$ and were classified as HMXBs. Seventeen sources with masses between 5 and 8M$_{\odot}$ were classified as intermediate-mass X-ray binaries (IMXBs). The remaining sources, for which optical counterparts could not be identified, were assumed to be LMXBs. The X-ray luminosity functions (XLFs) derived for HMXBs and LMXBs, identified through both X-ray and optical classification, were best described by a single power-law model ($\alpha \sim$ 1.3$-$1.6). We supplemented traditional classification methods with a machine learning (ML) approach based on multiwavelength photometry. While traditional methods identified no AGN candidates, the ML approach detected a significant AGN population. The spatial resolution of the observing instruments and the limits of the training database hinder the reliability of the ML classifications, thus highlighting a key challenge in combining these methods for extragalactic X-ray source

We explore the dynamics of a Vlasov gas propagating in an external axisymmetric potential consisting of a central potential with an additional quadrupolar component which gives rise to two potential wells along the symmetry axis. Employing independently $N$-particle simulations and statistical methods, we show that an initially homogeneous and isotropic configuration evolves to an inhomogeneous final state with overdensities located at the wells. The quadrupolar component is chosen such that the equations of motion form an integrable Hamiltonian system, which allows one to compute the final state of the gas analytically. On the one hand, this allows one to compare the late-time behaviour of the simulations with an analytic prediction and on the other hand to understand the relaxation process through phase space mixing. Our model constitutes a Newtonian analogue of the particle motion in a Kerr spacetime, and we discuss possible applications to recently observed astrophysical phenomena.

In this paper we investigate whether geometrically aligned astronomical representations are also scientifically interchangeable. We analyze every layer's representation from 36 pretrained models using cross-matched optical images, infrared images, and spectra. All 139 analyzed model-survey comparisons show significant local-neighborhood alignment somewhere in the network after accounting for the search over depth. However, alignment does not generally increase with network depth and can be stronger for the changes between consecutive computational blocks than for the block outputs themselves. We find that geometry-selected stages under-perform label-selected stages in every image-transfer comparison; moreover, every final HSC-COSMOS-Web model pair is aligned while every redshift transfer has negative R^2. Models can therefore recover a similar cross-survey geometry among astronomical objects without recovering a survey-invariant linear encoding of the physical properties tested here.

The search for extraterrestrial intelligence (SETI) is conducted across the electromagnetic spectrum to understand the prevalence and distribution of intelligent life in the universe. At radio frequencies, this effort focuses on searching for "technosignatures", observable indicators of technological activity consistent with our understanding of an advanced civilization. Historically, the microwave regime from 1-10 GHz has been the primary frequency range searched for these technosignatures, but recent SETI experiments utilizing low-frequency radio telescopes, such as the Low Frequency Array (LOFAR), Murchison Widefield Array, and MeerKAT radio telescope have explored the insufficiently studied frequency range below 1 GHz. However, the lowest radio frequencies ($<$100 MHz) have been even less explored for technosignatures, despite significant human communication signals occupying this band. The Long Wavelength Array (LWA) is a low-frequency (3-88 MHz) interferometer array telescope collaboration comprised of dipole 'stations' distributed across the Southwestern United States, and the LWA Swarm is the aperture synthesis telescope consisting of interconnected LWA stations operating as a long baseline interferometer. Here we present a narrowband technosignature pipeline using the Breakthrough Listen Interesting Signal Search algorithm for raw beamformed single-station LWA data and outline its planned extension to correlated visibilities from the LWA Swarm. We demonstrate the pipeline on a limited selection of fast radio burst observations to evaluate the data processing and spatial coincidence filtering for a future observing campaign of exoplanet systems.

We present off-limb spectroscopy using low-straylight data from the Sunrise Spectropolarimeter and Imager (SUSI) onboard the Sunrise III stratospheric solar observatory. A spatial scan with SUSI's slit almost parallel to the local limb reached from within the solar disc to 6.5 Mm off-limb. The wavelength range spanned from 407.6 to 410.25 nm. We detected a total of 174 spectral lines in emission off-limb, a 2.5-fold increase over previous reports. Surprisingly, 122 of these lines begin to appear in emission already on the disc, although close to the limb. In addition, one-fifth of relatively prominent emission lines are due to rare-earth and heavy elements and molecules, where the absorption lines of these transitions are typically weak on-disc.

How planetesimals form is a major open question in studies of planet formation, as the growth of smaller solids must overcome barriers such as radial drift, fragmentation, and bouncing. The leading model is that planetesimals form by the gravitational collapse of dense particle clumps that have been aerodynamically collected via a process known as the streaming instability (SI). While the SI has passed several observational tests, a critical test remains: a successful comparison with the size distribution of Solar System planetesimals. In this work, we conducted a series of SI simulations for a range of input parameters and combine a more careful accounting of initial planetesimal mass with more advanced statistical techniques compared to previous studies in order to compare the simulation outcomes against observations of the most primordial population in the solar system: the Cold Classical Kuiper Belt (CCKB). Using both cumulative distribution function (CDF) model parameters and distribution comparison methods like the Kolomogorov-Smirnov test, we show that, when planetesimal masses are measured at formation and analyzed with modern statistical methods, the SI-predicted size distributions can quantitatively reproduce the high-mass end of the observed CCKB size distribution, though the extent of the agreement depends on the physical parameters chosen, providing further support for the SI theory of planetesimal formation.

General circulation models (GCMs) are the primary tool for simulating planetary atmospheres. They play a vital role in understanding Mars's atmosphere, as forecasting its unique weather is mission-critical for operations such as entry, descent, and landing. Mars poses unusual challenges for these models, as observations are sparse compared to Earth. In addition, a thin \co{} atmosphere alongside a radiatively active dust cycle creates a volatile atmosphere with large diurnal temperature swings and no true terrestrial analog for validation. Existing Mars GCMs, including the LMD PCM, the NASA Ames Mars GCM, and PlanetWRF, are mature and physically detailed but are implemented in legacy Fortran with finite-difference or finite-volume solvers, and they do not expose gradients for calibration or machine learning. Here we present AEGIS, a modular differentiable Mars climate model that couples Mars's unique atmospheric physics to the Dinosaur dynamical core, with interfaces for neural closures. We showcase stable ten-Mars-year simulations that reproduce the seasonal \co{} cycle while conserving the total \co{} inventory, capture realistic large-scale surface-temperature structure, and produce surface pressure that follows Mars Orbiter Laser Altimeter (MOLA) topography. Gradients through coupled trajectories agree with finite differences and support physical calibration and neural training. We compare with conventional GCMs, highlighting the framework's computational efficiency and differentiability.

Standard radiation spectra modeling of active galactic nuclei like Seyfert galaxies typically involves tuning the relative contributions from an optically thick disc, optically thin corona, dust torus, and outflow by hand to match observations. The physics that quantifies this relative partitioning is not precisely understood. Here we make progress toward improving this understanding by testing the implications of a conceptual paradigm that the corona is supplied from below only by magnetic fields whose scales are large enough to escape turbulent shredding on their buoyant rise time. We use a generalized mean field accretion disc theory that includes both local radial angular momentum transport and angular momentum transport into a corona. We then use previous numerical simulations of magnetized turbulent accretion disc energy spectra to connect the fraction of disc magnetic energy that would escape to the fraction of coronal to total luminosity. Without explicitly calculating detailed particle acceleration and radiative processes, we assume that the disc radiation spectrum is thermal and the coronal radiation spectrum is a power law. We then show that the aforementioned paradigm for corona formation constrains the allowed x-ray power law index to a narrow range which agrees with observations. For the three AGNs studied here the predicted mean photon index is $\overline{\Gamma}=1.76$, consistent with the mean observed value of $\overline{\Gamma}_{\rm obs}=1.73$, bolstering confidence in the paradigm.

Measuring the age and composition of interstellar objects is necessary to understand their origins. However, existing methods for measuring the age are either imprecise or require an unusually bright target, while the composition is confounded by the effects of Galactic cosmic rays, which drive chemical reactions in the cometary matrix. As the Vera C. Rubin Observatory expands the census of interstellar objects, measuring these properties will be critical to understanding the overall population. In this work, I derive a new methodology for simultaneously estimating the age and initial composition of an interstellar object from time-series observations of the coma. Measurements of both the composition and its gradient versus depth into the nucleus are shown to fully constrain both properties in most circumstances. A simple model using only CO and CO$_2$ is discussed and used to demonstrate the properties of this inference process. When applied to 3I/ATLAS, this simple model indicates that this object is at least 0.6 Gyr old and has an initial CO/CO$_2$ ratio of 1.5, supporting a formation outside the CO ice line. Further refinement of the chemical network and improved observational strategies will improve the precision and accuracy of these measurements, enabling a deeper understanding of the interstellar object population and extrasolar planet formation.