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We investigate the geometry of extreme Kerr-Newman black holes and its role in selecting distinct black hole states. Motivated by Smarr's question of what physical information is encoded in event-horizon symmetries, we identify, besides the Smarr extreme family, a special family in which the mass, charge, angular momentum, and irreducible mass are constrained by a single irrational number. In the Christodoulou diagram, this family is selected by a discrete symmetry of appropriately scaled charge and angular-momentum variables. The local differential geometry of the event horizon provides an additional selection principle, which, up to the discrete symmetries (Q \rightarrow\pm Q) and (J \rightarrow\pm J), identifies a unique extreme Kerr-Newman black hole exhibiting the highest degree of local spherical symmetry compatible with the rotating Kerr-Newman geometry. Remarkably, for this distinct extreme configuration, all relevant physical and geometrical quantities, including the energy, electric charge, angular momentum, and irreducible mass, are solely related through the golden ratio. We also examine reversible and irreversible transformations and the associated extractable energy. Intrinsic horizon geometry can therefore constrain the macroscopic parameters and single out distinct extreme Kerr-Newman configurations.

Sulfur is the tenth most abundant element in space, yet it is strongly depleted in the gas phase of dense interstellar regions, suggesting sequestration in dust grain components that are difficult to detect. We study whether UV irradiation and thermal processing of H2S-containing interstellar-ice analogues can produce refractory sulfur species, and whether water-dominated ice enhances their formation. We performed UV irradiation and warm-up experiments on H2S-containing ice analogues with and without water, and the resulting refractory residues were analysed ex situ. Refractory sulfur species, including the sulfur allotropes S6-S8, are formed during UV irradiation and thermal processing of H2S-containing interstellar-ice analogues. Water enhances the formation of these sulfur allotropes by two orders of magnitude. We propose a formation mechanism in which ionic intermediates stabilised by the water-ice matrix promote chain growth and cyclisation, yielding predominantly S8. The combined detection in our residues of sulfur allotropes and polythionic species, also reported in meteorites and samples returned from asteroids, supports their formation in pre-cometary ice mantles covering dust grains. Because these species can incorporate multiple sulfur atoms per molecule, they constitute an efficient solid-phase reservoir for the missing sulfur in dense cloud environments where young stars are born. Refractory sulfur can therefore serve as a tracer of water-ice environments in space.

Gaia DR3 revealed a new class of neutron stars (NSs) in au-scale orbits with solar-type companions. How these 'Gaia NSs' form remains unclear, and constraining their intrinsic population properties is a necessary step toward understanding their origin. However, the current sample of 27 Gaia NS candidates is strongly biased by Gaia's astrometric sensitivity. In this work, we carefully model the Gaia selection function and incorporate it into a hierarchical Bayesian framework to infer the \textit{intrinsic} demographics of the Gaia NS population. We find that the population favors a decreasing period distribution with power-law slope $\alpha_P=-0.75 \pm 0.35$, a visible-star mass distribution peaked near $M_1\approx 0.85~{\rm M_\odot}$ ($\sigma_{M_1} \approx 0.2~{\rm M_\odot}$), an NS mass distribution peaked near $M_{\rm NS}\approx 1.3~{\rm M_\odot}$ with a tail towards higher masses, and an eccentricity distribution weighted toward moderate-to-large eccentricities. The intrinsic space density is $n\approx120~{\rm kpc^{-3}}$ within 2 kpc, implying that only $\sim3\%$ of the local Gaia NS population has been discovered so far. Our forecasts predict that Gaia DR4 will increase the sample to $\sim300$-650 NS candidates, including access to longer orbital periods that will provide direct tests of formation models. Finally, we place Gaia NSs in the context of the broader Galactic NS population by comparing their intrinsic birth rate, lifetime, and size to other classes of isolated and binary NSs. Only 0.01% - 1% of all NSs are born into au-scale orbits with solar-type companions, making the birth rate of Gaia NSs 10 - 100 times smaller than that of high-mass X-ray binaries and broadly comparable to symbiotic X-ray binaries.

The abundance and properties of low-mass dark matter subhalos can be inferred by measuring the density and velocity structure of stellar streams, testing physical models of dark matter. Which streams make the most promising dark matter detectors, and which subhalos would they encounter? We use the semi-analytic model galacticus to simulate the Milky Way's dark subhalos, including tidal stripping under the influence of the galactic disk. Deriving stream initial conditions that best match present-day observations, we forecast subhalo encounters for 24 globular cluster streams around the Milky Way. Over their lifetimes, the 10 most perturbed streams are predicted to each experience $\approx 2$-$12$ significant subhalo encounters with velocity kicks $v_\mathrm{kick} > 0.1$ km s$^{-1}$. Jet, AAU, GD-1, and Palomar 5 lead the list, with Jet encountering twice the subhalos of any other stream. The subhalos that encounter streams have been tidally stripped to $1$-$20\%$ of their peak mass and are twice as compact as previous works have assumed. A spectroscopic survey of streams with sub-km s$^{-1}$ precision could reveal the influence of dark subhalos below the threshold of galaxy formation. Predicting the abundance and scatter of low-mass subhalos that reach the inner galaxy remains a dominant uncertainty in connecting stellar streams to models of dark matter.

Most X-ray sources detected in nearby galaxies by the Chandra X-ray Observatory lack astrophysical classifications. We present XClass (X-ray Classifier for extragalactic sources), an end-to-end machine-learning pipeline that classifies extragalactic X-ray point sources into seven classes: AGN, LMXBs, HMXBs, CVs, low-mass and high-mass foreground stars, and supernova remnants. The key challenge is photometric heterogeneity: training sources are predominantly Galactic with photometry from wide-field surveys (PanSTARRS and 2MASS), while extragalactic targets require Hubble Space Telescope (HST) imaging in a disjoint filter system. We address this through a spectral energy distribution (SED) translation that fits class-appropriate spectral models to each training source and convolves the best-fit model through HST filter curves, producing synthetic magnitudes in a common feature space. The classifier uses an asymmetric two-stage Random Forest: Stage 1 separates broad categories (AGN, X-ray binaries, SNRs, stars) and Stage 2 resolves X-ray binaries into LMXBs and HMXBs using an augmented feature vector that includes Stage 1 probabilities. The training set is assembled from ten Galactic catalogs and extragalactic SNR catalogs, cross-matched with the Chandra Source Catalog v2.1. Features include X-ray hardness ratios, SED-translated HST colors, and X-ray-to-optical flux ratios. We restrict the training set to sources with at least one optical magnitude, avoiding imputation artifacts; the pipeline achieves 99.6% accuracy and balanced accuracy of 0.90 on the resulting 11,374-source optical baseline, with excellent calibration (ECE = 0.002). XClass is modular, generalizable to any HST filter configuration, and will be applied to M31 and M33 in a companion paper.

Current and forthcoming deep optical imaging surveys are reaching surface brightness levels fainter than 30 mag/arcsec$^2$, where Galactic cirrus emission becomes a significant contaminant. This poses a major challenge for the study of extremely low-surface-brightness extragalactic structures. We investigate the relationship between far-infrared emission, as traced by the Herschel 250 $\mu$m band, and optical surface brightness in the Sloan \textit{g}- and \textit{r}-bands. We find that, for Galactic cirrus with $\mu_g\gtrsim$ 27 mag/arcsec$^2$, a linear relation is consistent with the data, assuming optically thin dust, with optical cirrus emission amounting to $\sim$0.1\% of the far-infrared flux. Using Herschel far-infrared data to trace Galactic cirrus enables its identification over wide areas, but at the cost of significantly reducing spatial resolution. This limitation introduces source confusion and restricts the effective surface brightness depth that can be robustly probed in optical data. We show that, when cirrus emission is modeled using Herschel 250 $\mu$m data, the limiting surface brightness is $\mu_V\sim$ 28 mag/arcsec$^2$, substantially shallower than the nominal depth of surveys such as LIGHTS or the 10-year coadd LSST ($\mu_V\sim$ 30.5 mag/arcsec$^2$). These results highlight a fundamental limitation in the use of currently available far-infrared data for cirrus mitigation in ultra-deep optical imaging, and emphasize the need for higher-resolution cirrus tracers to fully exploit the depth of upcoming surveys.

Context. Low-power FRI-like radio jets dominate the AGN population, yet the main mechanism of heating the intracluster medium (ICM) and its efficiency remain a matter of debate. Aims. We investigate the impact of intermediate-power FRI-like relativistic jets on the inner region of realistic ICM, focusing on the role of weak shocks on heating and the environmental coupling in regulating energy deposition. Methods. We present six three-dimensional relativistic-hydrodynamic simulations of (1e44 - 1e45) erg/s FRI-like jets propagating through the central regions of realistic ICM environments extracted from cosmological GADGET-3 runs. Each simulation tracks 20 Myr of continuous jet activity with radiative cooling included. Results. Despite their intermediate power and mildly relativistic speed at injection, they decelerate rapidly to trans-sonic velocities (average Mach numbers   2.3) and generate weak bow shocks that dominate the energy transfer. Approximately, 80% of the injected kinetic power is converted into internal energy of the ambient ICM, and bremsstrahlung cooling noticeably reduces the temperature of the shocked shells as they expand. Conclusions. Our results demonstrate that heating of the intergalactic and intracluster medium is highly efficient even in the case of weak shocks in FRI-like sources. This finding suggests low-power jets are a viable solution to the long-standing cooling-flow problem and likely regulate star formation across diverse galaxy cluster environments.

The propagation of star formation throughout a molecular cloud complex can tell us much about its physical drivers and the importance of environmental versus intrinsic processes. We reconstruct the star formation history (SFH) of the Orion star-forming complex using the highest-resolution age map currently available. It comprises 47 co-spatial and co-moving groups identified by the SigMA clustering algorithm, with homogeneously derived ages and group memberships. We find four periods of increased star formation, separated by  5 Myr each. The two periods of highest increase, at 6.4 and 11.3 Myr, can be statistically localized, together hold ca. 59% of all stars, and are robust against resampling and changes to the age fitting. The two older, smaller increases at 16.2 and 21.4 Myr can be identified in the age distribution, but cannot be shown to be robust at this point. The  5 Myr spacing between the episodes of increased star formation is the same as found for the nearby Scorpius-Centaurus (Sco-Cen) star-forming region. We find no methodological bias that could produce the SFH structure. We identify spatio-temporally connected structures, including three cluster-chain candidates. We conclude that star formation in Orion seems to occur on the same timescales but with a different pattern than in Sco-Cen. The cause of the  5 Myr separations remains a mystery, and its detection in two distinct star-forming regions needs further investigation.

Particle splitting can increase the dynamic range in Lagrangian astrophysical simulations by several orders of magnitude. However, such methods can introduce numerical noise that may affect the rate of convergence, particularly for collapse problems where fragmentation could be artificially suppressed or enhanced. Thus it is necessary to determine how these errors propagate to key quantities of interest, and to correct or mitigate them where possible. Using GIZMO's MFM-MHD method, we perform a set of $\approx 220$ simulations of a uniform-density turbulent gas sphere undergoing collapse, systematically varying the cloud mass and radius, feedback physics, initial resolution, the pace and cadence at which we split particles and the sink (accreting) or single-age stellar population (SSP; non-accreting) particle formation prescription. Crucially, we compare with control runs that start with uniformly-high resolution without splitting. While we find no evidence for artificial fragmentation caused by splitting particles, particle splitting runs have a smoother density field than their non-splitting counterparts. Due to this, particle splitting runs exhibit minor differences in the density and turbulence statistics. However, they form about the same total stellar mass as the control non-splitting runs, albeit with a slightly different mass spectrum. As a result, particle splitting runs have a different evolutionary history, compared to runs without particle splitting, especially when stellar feedback is present. Despite the changes seen in runs where we split particles, the numerical solution lies within the scatter inherently present in these chaotic systems, which we model by modifying the initial turbulent velocity field. Our results here argue that particle splitting generally “works" for star formation applications, despite some systematic differences in the specifics.

Cosmological simulations allow us to study galaxy-progenitor stream populations, allowing comparisons with observations to constrain galaxy formation physics. Previous work found that present-day galaxy-progenitor streams in FIRE have larger pericenters than observed in the MW, which might indicate that they tidally disrupt at larger distances, where the Galactic tides are weaker, than in the MW. One possible explanation is that they tidally disrupt too quickly because of limited resolution. At lower resolution, low-mass dwarf galaxies can be puffier and more susceptible to disruption. We build and compare dwarf-galaxy stream catalogs in two FIRE-2 cosmological zoom-in simulations with identical initial conditions (m12i) but different particle mass resolution (7070 $M_\odot$ and 880 $M_\odot$). The higher-resolution run yields a larger dwarf galaxy stream population (22 streams versus 14) using the same cutoff of 100 star particles, primarily because it resolves lower-mass streams (down to $\sim10^{5}$ $M_\odot$). Both simulations form streams at galactocentric radii < 50 kpc, but the higher-resolution Triple Latte simulation produces more streams at these small radii. We find that dwarf galaxies in the higher-resolution simulation begin disrupting at smaller pericenters than in the lower-resolution simulation. By cross-matching stream candidates, we identify counterparts for $\sim$89$\%$ of the systems in the lower-resolution simulation. For matched systems that remain on similar orbits, the higher-resolution counterparts remain intact for longer. The orbital properties of streams in the higher-resolution simulation are broadly consistent with the MW dwarf-galaxy stream population, in contrast to the lower-resolution simulation.

We present an environmental analysis and overdensity catalog for a large sample of submillimeter galaxies (SMGs) in the COSMOS field in order to understand whether SMGs are signposts of megaparsec-scale overdensity structures. We apply the Poisson Probability Method (PPM) protocluster finder to characterize the significance ($\sigma$) and overdensity value ($\delta$) of any overdense structures surrounding specific 'beacon' galaxies. These beacons include 449 SMGs from A3COSMOS (including 168 with spectroscopic redshifts, 52 of which have CO or [CII] 158$\mu$m line detections), as well as a control sample of over 5000 main-sequence star-forming galaxies (SFGs) selected from the 40-band photometric-redshift catalog in COSMOS2025. We successfully reproduce 15 known protoclusters and clusters in COSMOS (including Hyperion large-scale structure, CL J1001+0220 at z 2.5, and AzTEC-3 protocluster at z 5.3), and report 26 new PPM-based high-overdensity ($\delta$ $\geq$ 5), high-significance ($\sigma$ $\geq$ 5), robust candidates. We measure an overdensity fraction of 11.5-71.2% (1.3-61.0%) in the CO/[CII] 52 SMG (full 449 SMG) sample with different criterion categories, confirming that SMGs are signposts of overdensities compared to the control SFG sample. We also notice that the fraction is lower than 100%, indicating that not all SMGs are associated with overdensities. We thus inspect the JWST morphology and argue that the triggering of starburst in SMGs must have non-environmental mechanisms, for instance, merger and violent disk instability. Finally, we further conduct a spatial distribution analysis, finding that the location of SMGs in overdensities has a redshift evolution, with SMGs being more concentrated in the inner regions of overdensities at higher redshift.

Supernova remnant (SNR) may shape the physical and chemical properties of star formation. By releasing refractory elements into the gas phase, they inject material of pre-biotic relevance into molecular clouds. Such elements may be inherited by planetary systems and become relevant for the emergence of life. We investigate the presence of P-bearing species in molecular clouds impacted by SNR-shocks. P is a crucial biological element, but its presence and reservoir in molecular clouds remain elusive. We present high-sensitivity 3 mm observations obtained with the IRAM 30m, toward the interaction sites between the SNRs W44 and IC443 and their associated molecular clouds. Focusing on PO+(2-1) and PN(2-1), we derive molecular column densities and abundances in local thermodynamic equilibrium. We investigate the correlation between P-bearing species and the shock tracer Silicon Monoxide (SiO). We detect, for the first time, PO+ toward SNRs, with abundances X(PO+) 8e-12-5e-11, but no significant PN emission. PO+ toward both SNRs is associated with strong SiO emission, showing similar linewidths but velocity offsets, suggesting that PO+ preferentially traces the most compressed and more strongly ionised layers of the shock. By comparing the derived abundances with those reported in literature, we suggest that the PO+ abundance mainly depends on a combination of shock strength and shocked medium density. Our results indicate that P-chemistry in SNR shocks is shifted toward an ion-dominated regime, likely driven by enhanced cosmic-ray ionisation rates. In this scenario, neutral species such as PN are efficiently destroyed, while ion-molecule reactions favour the production of PO+. This suggests that SNR shocks may play a role in processing P-bearing material and shaping gas-phase P chemistry in molecular clouds, with potential implications for the chemical inventory of star-forming environments.

We present a long-term X-ray spectral and timing analysis of the TeV blazar Mrk 421 based on nearly a quarter century of archival \textit{XMM-Newton}/pn observations obtained between 2000 and 2025. Our sample comprises 76 epochs obtained with the pn instrument in both IMAGING and TIMING modes, allowing us to trace the source's variability and spectral evolution. Mrk 421 exhibits flux variations by approximately an order of magnitude, with prominent flaring periods interspersed with low-activity states. A clear harder-when-brighter trend is observed, accompanied by scatter in the hardness ratio (HR), suggesting flux alone does not uniquely determine the spectral state. Fractional variability in the hard band ($2-10$ keV) correlates tightly with that in the soft band ($0.3-2$ keV), with a steeper slope indicating pronounced variability at higher energies. The flux distribution is non-Gaussian and lognormal-like, dominated by moderate flux levels with a tail of bright flares. Spectral analysis shows that power-law model is not sufficient; 59 epochs are best described by a broken power-law (BPL) and 17 by a log-parabola (LP). This fluctuation between BPL and LP models suggests the emission region transitions between a distinct acceleration shockfront and downstream stochastic turbulence. The spectral break energy of BPL remains predominantly clustered around $2$ keV across all flux states, while the average spectral steepening above the break is mild ($\Delta \Gamma \approx 0.19$), inconsistent with standard one-zone cooling models. Our results support structured jet scenarios or energy-dependent electron escape, providing key constraints on the long-term behavior of relativistic jets in high-synchrotron-peaked blazars.

The small scale density distribution of the cold circumgalactic medium (CGM) plays a central role in galaxy evolution, yet it is still poorly understood. We provide new constraints on the cold CGM density distribution by comparing the CGM emission from MUSE observations of quasar (QSO) nebulae at $z \sim 3.8$ with mock observations generated from the new DaLya simulation suite under the assumption of maximal fluorescence. These are further complemented by mock observations generated from the COLIBRE (m5 and m6 resolutions) and HELLO simulations. We first investigate the distribution of the observed and simulated Ly$\alpha$ surface brightness (SB) values, which directly depend on the cold gas density distribution under our assumption, finding stark differences between observations and upper limits provided by simulations with the exception of the COLIBRE higher-resolution run (m5). The observations generally show a much larger covering fraction of regions with relatively large Ly$\alpha$ SB values and suggest that densities reaching at least 10 cm$^{-3}$ must be present in the CGM of QSOs within a radial distance of 50 to 200 ckpc. To understand the origin of this discrepancy, we study the cold CGM density distribution finding in all cases simulated PDFs consistent with skewed lognormal ones with medians $\sim 10^{-2}$ cm$^{-3}$ and clumping factors between 16 and 102. We compare the broadness of these distributions to the one implied by the observed HeII/Ly$\alpha$ CGM ratio, which is independent on the assumption of maximum fluorescence. Assuming lognormal PDFs with median values similar to the simulations, the observed ratio requires a broader PDF with a clumping factor at least 8 times larger than predicted by simulations. These results suggest that higher resolution and/or additional physical mechanisms are needed to reproduce the observed CGM of QSOs at these redshifts.

Context. Ultraluminous X-ray sources (ULXs) are thought to be powered, in many cases, by super-Eddington accretion onto compact objects. While soft X-ray lags have been detected in several ULXs, hard lags remain rare and poorly understood. Aims. We investigate the temporal and energy dependence of X-ray lags in NGC 7456 ULX-1 to constrain their physical origin and probe the super-Eddington accretion flow. Methods. We analyzed the two deepest XMM-Newton observations, taken in 2018 and 2023. Hard (1-10 keV) and soft (0.3-1 keV) light curves were cross-correlated using adaptive-binning techniques optimized for Poissonian low-count data. We measured lags over consecutive 10 ks intervals and investigated their energy dependence. Spectra were modeled using thermal and Comptonization models. Results. We detect significant hard X-ray lags in both observations, with the hard emission delayed by $\sim 10^3$ s during phases of rapid flux variability. The delays are primarily driven by the lowest-energy photons. Spectral modeling indicates a Comptonization-dominated flow comprising a cooler, extended outer region and a hotter, compact inner flow embedded in an optically thick wind. We interpret the delays as the combined effect of inward propagation of accretion-rate fluctuations and photon diffusion within the dense outflow. Fluctuations first enhance the soft-emitting outer regions and then propagate toward the hotter inner flow, where photons undergo stronger Comptonization before escaping with a kilosecond delay. The small inferred inner emitting radius disfavors an intermediate-mass black hole accretor. Conclusions. The sign, amplitude, and energy dependence of the delays disfavor standard reverberation. Propagation-driven variability coupled with radiative transfer in optically thick winds appears to play a major role in shaping the timing properties of super-Eddington accretion flows.

Extended Lya emission is routinely detected around high-redshift quasars, revealing large reservoirs of cool circumgalactic medium (CGM). Its resonant nature complicates interpretation of gas density, ionization state, and kinematics, making non-resonant tracers such as HeII and Ha essential. Extending previous analytical models, we use CLOUDY photo-ionization simulations to predict HeII/Ha in quasar-illuminated gas over a broad parameter range, including log-normal density distributions. The ratio constrains density fluctuations, commonly quantified by the clumping factor C. We compare the models with extended Lya, HeII, and Ha observations around quasars at z 2.1-4.5. At z 2.2, we observed 13 quasars with Keck/KCWI and targeted the systems with the most prominent extended Lya and HeII emission with Keck/MOSFIRE, providing the first statistical quasar-CGM sample with combined Lya, HeII, and Ha measurements. Within matched apertures out to  35 pkpc, stacked spectra give Lya/Ha=9.1, HeII/Ha=0.54, and HeII/Lya=0.06. Single-density models require very high CGM densities (n>10 cm^-3) or implausibly soft AGN spectra to reproduce the low HeII/Ha ratio. Broad log-normal density distributions instead reproduce it at lower median densities but require a substantial emissivity-weighted high-density tail, corresponding formally to C 10^3-10^4 in our parameterization. We also analyze 26 VLT/MUSE quasars at 3.1<z<4.5, where Ha is inaccessible from the ground, finding 14 systems with co-spatial extended Lya and HeII emission. The detected, emission-weighted HeII/Lya component shows no evidence for strong evolution between z 2.2 and z 3.7, though this does not imply an invariant underlying density PDF. These constraints provide a basis for comparison with theoretical models and hydrodynamical simulations of the physical processes shaping quasar CGM at high redshift.

Small-scale galaxy-galaxy weak lensing provides an independent way to probe the stellar initial mass function by constraining the matter distribution within galaxies. We forecast the potential of upcoming \textit{Euclid} observations using realistic mock catalogues designed for a DESI-like Bright Galaxy Survey, which is expected to cover approximately $9000\,\mathrm{deg}^2$ of the \textit{Euclid} wide survey area. We assess the impact of foreground lens light, which introduces significant scale-dependent biases in source detection, photometry, and shape measurements. Subtracting the lens light with \textsc{Galfit} reduces these biases by nearly an order of magnitude at scales down to four times the half-light radius. We model the predicted lensing signal around central galaxies with stellar masses between $9.5 \leq \log(M_*/h^{-2}M_\odot) \leq 11.5$ over projected separations of $10$ to $100\,h^{-1}\mathrm{kpc}$. The resulting signal-to-noise ratios reach $\sim 150$ for intermediate-mass galaxies. Assuming an NFW profile for the dark matter contribution, we constrain the stellar mismatch parameter $\alpha$ to a precision of approximately $8.5$ percent for the full sample and $8.6$ percent for massive galaxies. These results highlight the potential of small-scale galaxy–galaxy weak lensing as a robust probe of the IMF and the connection between stellar and dark matter in galaxies using upcoming \textit{Euclid} data.

Context. Protoclusters at reionization are thought to host a significant fraction of the cosmic star formation rate density, making them crucial for the timing and topology of reionization. The gas-phase metallicity, a key tracer of galaxy evolutionary stage, can now be measured directly in the early Universe with JWST. Aims. We measure the gas-phase metallicity of Lyman-$\alpha$ emitters (LAEs) in the LAGER-z7OD1 protocluster at $z\approx6.93$ via the direct ($T_e$-based) method using the [O III]$\lambda$4363 auroral line, and combine it with stellar masses to constrain the mass-metallicity relation (MZR) in dense environments. Methods. We use JWST/NIRSpec MSA G395H spectroscopy, derive metallicities with self-consistent analytic prescriptions, and propagate the dust-extinction uncertainty into an asymmetric error budget via Monte Carlo simulations based on the observed Balmer decrements. Stellar masses come from BEAGLE SED fitting of JWST/NIRCam and UltraVISTA photometry. Results. We obtain five secure [O III]$\lambda$4363 detections and one upper limit, with 12+log(O/H) $\approx$ 7.2-8.0. The weighted spectral stack yields 12+log(O/H) = $7.76^{+0.06}_{-0.05}$,  0.26 dex higher than stacks of LAEs at similar redshifts from JWST surveys. However, the MZR fit gives a slope $\gamma$ = 0.232 +/- 0.214 and normalization $Z_0$ = 7.888 +/- 0.199, placing our sources below the established MZR of normal galaxies and recent protocluster baselines at $z\sim5-7$. Conclusions. The higher metallicity relative to general LAEs suggests accelerated assembly driven by the overdensity, while the offset below the MZR points to a complex interplay between mass build-up and gas accretion. Since we target actively star-forming LAEs, we are likely capturing a phase of pristine gas inflow from the intergalactic medium that fuels star formation but dilutes the interstellar media of these protocluster members.

We present the results from follow-up spectroscopy of three protocluster candidates at $z\sim3$, selected as overdense regions of $U$-dropout galaxies in the wide-field imaging of the Hyper SuprimeCam Subaru Strategic Programme. All three targets exhibit tight clustering in three-dimensional space, i.e. on the sky ($>4\sigma$ overdensity) and in redshift ($>98.4\%$ confidence), making for clear evidence of genuine protoclusters. Since these three protoclusters are identified by the same dataset and technique, they represent a good sample to study the diversity of protocluster properties with minimal observational biases. Although the average population across the three protoclusters is consistent with field galaxies, each protocluster individually exhibits distinguishing properties from each other or from field galaxies. In one protocluster, member galaxies stand out by a higher Ly$\alpha$ equivalent width ($EW_0$), and massive members that are still highly star-forming. In contrast, relatively more suppressed star formation appears in another protocluster where the Ly$\alpha$ $EW_0$ of member galaxies is systematically lower. These variations can be attributed to differences in the developmental phase of protoclusters. If the presence of quenching galaxies indicates a more mature system, galaxies with stronger Ly$\alpha$ emissions may be more prevalent in the earlier stages of cluster formation. The uniform approach to searching protoclusters on which this study builds enables us to link observed variations at the onset of cosmic noon to different pathways in the history of cluster formation.

Relativistic jets from AGN are expected to propagate through an inhomogeneous ISM, but the role of small-scale gas inhomogeneities in shaping their early evolution remains uncertain. We investigate this problem using 3D special-relativistic magnetohydrodynamic simulations with PLUTO, following a jet with a Lorentz factor of 10 propagating through a pc-scale medium. We compare a homogeneous ambient medium with two clumpy ambient-medium models, motivated by dense gas in the nuclear ISM, in which clouds occupy volume filling factors of $0.1$ and $1$ per cent. We compute synthetic synchrotron maps and spectra from Lagrangian macro-particles that have been accelerated by diffusive shock acceleration. Jet-cloud interactions deflect the flow, enhance shock formation, and produce a more asymmetric cocoon than in the homogeneous ISM case. Altogether, this results in a substantially stronger mass loading: the entrained mass increases from $0.43$ M$_{\odot}$ in the homogeneous run to $5.3$ and $8.8$ M$_{\odot}$ in the clumpy runs. The clumpy ISM also modifies the turbulence and the material mixing within the jet cocoon. The dynamical differences we find translate into brighter and more irregular synchrotron emission. For the same injected jet, the models with a clumpy medium produce stronger frequency-integrated synchrotron emission than the homogeneous run, with the largest differences in the SED occurring from the sub-mm to the infrared/optical bands. Our results demonstrate that including a small-scale ISM structure provides a more complete description of the early dynamical evolution of young AGN jets and their radiative properties.

Identifying the particle nature of dark matter remains one of the most significant challenges in modern physics. Direct detection experiments aim to observe rare scattering events between dark matter particles and terrestrial targets, a task that demands extreme background suppression and sensitivity to minute energy depositions. This review critically assesses the current experimental landscape, organizing detector technologies by the fundamental physical trade-offs that define their scientific reach. We contrast the multi-tonne scalability of noble-liquid Time Projection Chambers (TPCs), which currently define the sensitivity frontier for high-mass Weakly Interacting Massive Particles (WIMPs), with the precision of cryogenic semiconductors and Charge-Coupled Device (CCD)- based sensors, which dominate the search for low-mass and sub-GeV candidates. Special emphasis is placed on the role of advanced reconstruction pipelines and machine learning (ML) as integral components of detector performance. Finally, we discuss the strategic roadmap for the next decade as experiments approach the neutrino fog, where coherent elastic neutrino-nucleus scattering (CE{\nu}NS) produces an increasingly significant and ultimately irreducible background that can mimic DM-induced nuclear recoils. We argue that future progress will rely not on a single technology but on a complementary global program combining increased target mass, ultra-low energy thresholds, improved background discrimination, and distinct observables - such as directionality and temporal signatures - to maintain robust discovery capability in the presence of neutrino-induced backgrounds.

Recent observations have revealed a remarkably rapid buildup of cosmic dust in the interstellar medium (ISM) of high redshift galaxies, with complex dust compositions and large abundances already appearing at redshifts $z>6$. Here we present a comprehensive, joint analysis of observations taken with the {\em James Webb Space Telescope} (\jwst) and the Atacama Large Millimetre/submillimetre Array (ALMA) of the highly magnified ($\mu = 9.6$), dusty `normal' galaxy, A1689-zD1 at $z=7.13$. We perform detailed spectro-photometric modeling of the rest-frame UV to far-infrared spectral energy distribution (SED) based on archival photometry of the source and report new rest-frame optical strong-line measurements and metallicity estimates from recent \jwst/NIRSpec IFU data. We find that despite its substantial dust mass, $M_{\rm dust}\sim 1.5\times 10^{7}\,M_\odot$, A1689-zD1 has remarkably low dust-to-gas and dust-to-metal mass ratios, ${\rm DTG} = (5.5^{+3.5}_{-1.2})\times 10^{-4}$ and ${\rm DTM} = (6.2^{+4.2}_{-2.6})\times 10^{-2}$, respectively, due to its high metallicity $12+\log({\rm O/H}) = 8.36\pm 0.10$ and substantial gas mass, $M_{\rm gas} = (2.8^{+0.2}_{-1.7})\times 10^{10}\,M_\odot$ inferred from the [\cii] luminosity and bounded by its dynamics. The DTG and DTM mass ratios are an order of magnitude lower than expected for galaxies in the local universe with similar chemical enrichment. These low relative measurements are also consistent with the deficit observed in the $A_V/N_{\rm HI}$ ratio of A1689-zD1 in the line-of-sight. We find that this deviation in the DTG and DTM mass ratios appears to be ubiquitous in other metal-rich galaxies at similar redshifts, $z\gtrsim 6$. This suggests that the processes that form and destroy dust at later times, or the dust emissivity itself, are likely different for galaxies in the early Universe.

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.

We analyse black-hole scaling relations at the high-mass end, focusing in particular on the regime of ultra-massive black holes, $\mathrm{M}_\mathrm{BH} > 10^{10}\,\mathrm{M}_\odot$ (UMBHs). In a sample of 16 Brightest Cluster Galaxies (BCGs) without previous black-hole mass measurements we discover 8 UMBHs based on direct dynamical detections with triaxial Schwarzschild models. This first sample of triaxial black-hole mass determinations increases the number of known UMBHs by a factor of two and dramatically increases the constraints for BH mass scaling relations at the high-mass end. We find that BCGs are outliers in the canonical BH - $\sigma$ relation, while the size of their depleted cores - the central light-deficient region - is a much better unbiased predictor of the black hole mass and should be used as a proxy at the high-mass end. BCGs smoothly join the trend already established for massive core galaxies in previous studies. This also holds for tight correlations between core size and sphere-of-influence radius and core size and core density. All these relations strongly support the black-hole binary model for the formation of the centers of the most massive galaxies.

Star-forming galaxies spend most of their lifetimes on the star-forming main sequence, which establishes a tight empirical and statistical relation between stellar mass and star-formation rate. Occasional episodes of rapid star formation can push them temporarily above this sequence, turning them into starbursts. Yet some galaxies display starburst-like traits – rapid, dense, and compact star formation – while still remaining within the scatter of the main sequence. These "starbursts in the main sequence" (SBMSs) reveal the complexity and diversity of star formation modes, making them crucial for understanding how galaxies evolve and transition between different regimes. In this paper, we identify SBMSs in the cosmological simulation NewHorizon and follow their evolution across time to uncover their physical origins and the role of this special regime in shaping galaxy evolution. We explain the existence of SBMSs by a comparatively earlier assembly of their stellar mass, driven in particular by more frequent and repeated mergers as the other galaxies, as well as exceptionally productive starburst events triggered by these interactions. As a result, this regime appears preferentially – though not exclusively – in the most massive galaxies. The SBMS behavior is not continuous within individual galaxies but instead arises intermittently as a short-lived (  30 Myr) evolutionary mode. Nevertheless, such SBMS episodes exist throughout cosmic time across the galaxy population... [abridged]

We present a statistical census of the Na D-traced neutral interstellar medium (ISM) and outflows in 309 galaxies at $0.6<z<4$ using JWST/NIRSpec medium-resolution spectroscopy from the SMILES, JADES, Blue Jay, and Aurora surveys. After subtracting the stellar continuum, we model the Na D $\lambda\lambda 5890, 5896$ Åand identify 73 Na D ISM absorptions, including 63 robust (4 in broad-line AGNs) and 10 tentative detections. Of the robust detections, 88\% are found in massive galaxies ($\log(M_*/M_\odot)>10$), and 12\% in lower-mass systems. At high mass, ISM absorption is seen in both star-forming and quiescent galaxies, whereas in lower-mass systems it is observed only in star-forming galaxies. In massive quiescent galaxies, Na D detectability appears linked to star formation history: it is preferentially detected in older systems with larger 4000 Åbreaks, and younger, rapidly quenching galaxies with strong Balmer absorption H$\delta_A$. We identify Na D {\it outflows} in 25 galaxies, revealing a possible dichotomy in driving mechanisms between star-forming and quiescent galaxies. In star-forming galaxies, outflow properties correlate with star-formation properties, consistent with a star-formation-driven origin. In quiescent galaxies, however, outflows are not associated with residual star formation and often require more energy than such star formation can provide. Together with the high AGN fraction among outflow-detected quiescent galaxies, this suggests that AGN dominate Na D-traced neutral outflows in cosmic noon quiescent systems. We further identify four quiescent galaxies with possible AGN fossil outflows, suggesting that AGN-driven outflows can persist beyond the active accretion phase and may help maintain quiescence.

Observations with the JWST in lensed fields have revealed that galaxies at cosmic dawn may concentrate their star formation in highly dense, compact, star clusters. The high columns and low metallicities encountered in their birth environments suggest that Lyman-alpha (Ly$\alpha$) radiation pressure may be crucial to their formation and evolution. In this study, we address this question by post-processing snapshots from radiation hydrodynamic simulations of dense star cluster-forming clouds ($\Sigma_*\gtrsim10^3{M_\odot{pc}^{-2}}$) with a range of dust abundances ($Z_d=0-0.1Z_{d,\odot}$) using the COLT Monte Carlo code. We infer that Ly$\alpha$ is likely to have mild ( 10%) effects on the gas-to-star conversion efficiencies ($\epsilon_*\gtrsim60$%) for $Z_d\gtrsim0.01Z_{d,\odot}$, and even in dust-free environments, $\epsilon_*\gtrsim25$% - much higher than the <10% values typical of star-forming regions in the local Universe. This is because the densest filaments dominating stellar mass assembly ($n\gtrsim10^4{cm}^{-3}$) remain sub-Eddington ($f_{Edd}<1$). On the other hand, the bulk of the gas volume ($n\lesssim10^3{cm}^{-3}$) has $f_{Edd}>1$, with noticeable fractions having $f_{Edd}\gtrsim10$, implying that Ly$\alpha$ can launch dynamically significant winds from these systems rapidly ($\lesssim$4Myr), with possible implications for ionizing photon escape and galactic outflows. The Ly$\alpha$ force multiplier $M_F$ is highly sensitive to $Z_d$, with $M_F\lesssim3$ ($\lesssim 500$) for $0.1Z_{d,\odot}$ (dust-free) environments respectively. Nevertheless, Ly$\alpha$ dominates over UV and IR radiation pressure at all values of $Z_d\lesssim0.1Z_{d,\odot}$, by factors of  3-500. Our results suggest that Ly$\alpha$ radiation pressure reinforces the emerging picture of locally efficient, bursty star formation accompanied by rapid outflows in galaxies at cosmic dawn.

In this work, we focus our analysis of Fractional-Dimension Gravity (FDG) on our home galaxy, the Milky Way (MW), by using the latest Gaia DR3 data as well as previous rotation curve (RC) data for this galaxy. FDG is an alternative gravitational model (previously known as Newtonian Fractional-Dimension Gravity - NFDG) which does not require the dark matter (DM) paradigm. The MW is studied here with the methods of FDG and its observed rotation curves are successfully reproduced by using a variable fractional dimension $D\left (R\right)$, following previous studies of several other galaxies which were analyzed with the same methodology. An alternative dimension function $D_{m}\left(R \right)$, based on the mass-dimension field equation, was also used and yielded less accurate fits to the experimental data. In addition, we also considered possible implications of the FDG metric, based on the presence of additional weights, on the structure of Special Relativity (SR) for spacetimes with fractional dimension. One notable, but very speculative outcome of this analysis is the possibility of an effective superluminal motion in galactic regions where the space dimension is $D<3$.

The Nancy Grace Roman Space Telescope (Roman), NASA's next flagship mission, is currently scheduled to launch in August 2026. As part of its mission, Roman will conduct the Galactic Bulge Time Domain Survey (GBTDS), which will generate $\sim$50,000 epochs of high-precision photometric and astrometric data for $\sim 10^8$ sources across 1.7 deg$^2$ in the Galactic Bulge. Roman GBTDS astrometry is comparable to Gaia Data Release 4 in terms of number of stars, astrometric precision, and time baseline, and is highly complementary in terms of wavelength and sky location. In this paper, we investigate a synthetic population of GBTDS sources to characterize the detectability of unresolved astrometric binaries, in particular those with compact object companions. Assuming the occurrence rate of black holes (BHs) and neutron stars (NSs) in AU-scale orbits around stars is $10^{-7}$ and $10^{-6}$, respectively, and that Roman achieves an astrometric precision of $1\%$ of a pixel, $\mathcal{O}(10)$ BH+star and $\mathcal{O}(10)$ NS+star detached binaries will be detectable. The BHs will have median mass measurement uncertainties of $\sim 25\%$, increasing the existing sample of detached astrometric BH binaries by a factor of three. Together with the $\mathcal{O}(10^2)$ isolated BHs expected to be discovered by microlensing in the Roman GBTDS and an additional $\mathcal{O}(10)$ detached BH binaries in Gaia DR4, this will provide a representative view of the quiescent Galactic stellar-mass BH population.

Quasi-periodic eruptions (QPEs) are recurring bursts of X-ray radiation originating from supermassive black holes (SMBHs). They are an unprecedented type of structured, high-amplitude SMBH variability, but the physical origins of their regularity, timescales, energetics, and emission are uncertain. We present new XMM-Newton observations of the QPEs in ZTF19acnskyy/"Ansky", constituting the deepest observations of individual bursts in any source thus far. The X-ray spectra reveal time-evolving P Cygni profiles comprising blueshifted absorption and redshifted emission from L-shell transitions of Fe XIX-XXIV, with column densities $N_H\sim 10^{22-23}$ cm$^{-2}$ and bulk velocities of $|v_w/c|\sim 0.2$, indicating relativistic mass ejections during each eruption. We construct a time-dependent analytical model of a wind turning on to self-consistently compute its evolving luminosity and ionization properties, and find that the light curve and spectral lines can be simultaneously produced by a wide-angle outflow with $\dot{M}\sim 10^{-9}-10^{-8}\,M_\odot$ s$^{-1}$ kinetically powering the X-rays with an efficiency of $L_X/\dot{E}_K\sim 0.1$. For a covering fraction $f_\Omega\sim0.5$, each eruption ejects $\sim 10^{-3}\,M_\odot$ and $\gtrsim 10^{49}$ erg of kinetic energy, setting an upper bound on the QPE lifetime of $\lesssim1000$ bursts if the underlying mass reservoir is $\sim1 M_\odot$, and implying that the bursts may result in detectable multiwavelength signatures of reverberation and feedback. These measurements provide new quantitative constraints on QPE energetics, emission mechanisms, and the mass/energy they recycle into their circumnuclear environments, as well as an observational probe for direct comparison with physical models and hydrodynamical simulations of QPEs.

Offsets between cluster-scale dark matter halos and brightest cluster galaxies (BCGs) inferred from strong lensing (SL) models have been used to investigate cluster dynamics and dark matter physics. However, it is necessary to test whether these offsets are required by SL data themselves. We investigate whether allowing these offsets improves predictive accuracy and examine the effects on magnification, time-delay predictions, and critical curve positions. We evaluate lens models of Abell 370, RX J1347.5-1145, and MACS J0416.1-2403 using the jackknife method, which assesses predictions for source systems excluded from the lens reconstruction. Models are constructed with MrMARTIAN, which combines analytic mass profiles with a regularized grid that represents mass structure not captured by the profiles. We compare fixed and free halo position models across regularization weights. The root mean square values averaged over excluded systems agree within bootstrap uncertainties, while the median paired differences remain close to zero across all three clusters and tested regularization weights. These results indicate comparable predictive accuracy between the fixed and free models. The total mass distributions remain broadly similar, although the magnitudes of fitted halo offsets vary with regularization, showing that the mass decomposition is not unique. For these three clusters, offsets between BCGs and cluster-scale halos in the lens models are not required by the SL data to improve predictive accuracy within the MrMARTIAN framework. The mass decomposition between the regularized grid and cluster-scale halos is not uniquely determined. These findings limit physical interpretations based on fitted halo positions alone. The model dependence of magnification and time-delay estimation can also affect the inferred intrinsic properties of high-redshift sources or the Hubble constant.

We present a methodology for the reduction of archival spectral data together with the description of a newly developed Python-based software package featuring an interactive graphical interface. The work is primarily aimed at processing spectra obtained with electron-optical converters (EOCs), which are characterized by geometric distortions induced by the magnetic field of the registration system. Such data are preserved, in particular, in the archive of the Fesenkov Astrophysical Institute (FAI), which contains about 10,000 photographic plates. These distortions, along with the need to transform the optical density of the photographic material into relative intensity, cannot be corrected by standard astronomical packages such as IRAF and therefore require a dedicated approach. Historically, reductions at FAI were performed using a program written in the Microsoft QuickC language for computing platforms of the 1990s, rendering it incompatible with modern operating systems. The new package is implemented with the PyQt5 framework, retaining the logic of the original code while extending its functionality. The implemented algorithms include image rotation and cropping, geometric distortion correction, construction of the characteristic curve linking optical density and intensity, and direct conversion of pixel values in object spectra. The developed software ensures reproducible reduction of archival spectra and provides a cross-platform environment with potential for further extensions.

Accurate primary-beam models are essential for high-dynamic-range radio experiments, particularly searches for the redshifted 21-cm signal from the Epoch of Reionisation, where beam errors can couple bright foreground emission into the faint cosmological measurement. Using reprocessed satellite observations we infer the 137-MHz, zenith-pointed power beams of Murchison Widefield Array receiving elements. We develop two complementary Bayesian approaches for quantifying departures from nominal electromagnetic simulations: a physically motivated model of complex variations among individual dipoles and a hierarchical spline model for flexible direction-dependent structure. The measurements reveal shallower and displaced nulls together with coherent sidelobe deformations. The dipole model captures much of this broad structure, whereas the spline recovers additional localised features while remaining largely robust to isolated pass-shaped artefacts. Despite their sparse and distinct sampling patterns, four independent 20-day subsets, each containing approximately 20\% of the full dataset, recover consistent null and sidelobe morphology across the visible hemisphere. These results demonstrate that opportunistic satellite transmissions can support practical, repeatable beam reconstruction, while motivating future chromatic, phase-referenced measurements of the full Jones response.

Chandra established that soft X-ray spectral imaging with approximately 1 arcsec angular resolution is an essential tool for almost every area of astrophysics, from the early Universe to ice chemistry in protoplanetary disks. While Chandra continues to deliver groundbreaking science, it lacks the sensitivity to be the counterpart to JWST, Roman, Rubin, LISA, ngVLA, ALMA, IceCube, NewAthena, ELT, and other upcoming large facilities. Here we highlight the scientific potential of a Chandra successor with >10x higher sensitivity and >50x survey speed. While the scientific reach of such a mission is very broad, we showcase four high-priority science questions that require these capabilities – How did supermassive black holes form?, How does stellar and AGN feedback work in galaxies?, How does high-energy stellar activity affect exoplanet atmospheres? and, How do black holes merge? A Chandra successor in the 2030s would also demonstrate the X-ray mirror technology for a future flagship and sustain the US high energy astrophysics workforce until that flagship launches. We outline the science-instrument trade space by sketching three missions based on the NASA Probe concept study report for the Advanced X-ray Imaging Satellite (AXIS): AXIS-Deep, AXIS-Classic, and AXIS-Fast, highlighting a breakthrough science case for each and listing others that drive the design.

Future spectroscopic survey facilities such as Spec-S5 and the Wide-Field Spectroscopic Telescope (WST) will contain more than 25,000 optical fibers. Characterizing the focal ratio degradation (FRD) and throughput of these fibers is essential for spectroscopic calibration, sky subtraction, and overall instrument performance, but manual testing of such large fiber populations is prohibitively time-consuming. In this work, we present an automated multi-stressor optical fiber characterization platform capable of measuring both FRD and relative throughput while systematically varying optical and mechanical stress conditions. The system enables characterization as a function of input angle, wavelength, bend radius, twist angle, and externally applied load, while also allowing combinations of stressors to be investigated simultaneously. A custom software framework automates hardware control, data acquisition, and data analysis, enabling large characterization campaigns to be performed with minimal user intervention. Validation measurements performed on a multimode optical fiber demonstrate the ability of the platform to resolve both pronounced and subtle stress-dependent variations in FRD and relative throughput. The results show the expected dependence of FRD on input angle and bend radius, reveal comparatively weak sensitivity to externally applied compressive loading under the investigated conditions, and identify a reproducible periodic dependence on fiber twist angle. In addition, relative throughput measurements indicate that the reduction in relative throughput with increasing input angle cannot be explained solely by a simple projected-area model. The automated workflow and scalability of the system provide a versatile framework for the large-scale characterization of optical fibers required by next-generation spectroscopic survey facilities.

Abandoning the traditional approaches to multi-object spectrographs, the Digital Micro-mirror Device-based Multi-Object Spectrograph (DMD-MOS) leverages a robust, elegant method for creating multi-object spectroscopy slit masks through use of a DMD, which is an array of microscopic flat mirrors where each micro-mirror can be addressed to physically flip between two discrete angles. We have designed two optical channels for DMD-MOS - one for each of these two positions: 1) an imaging channel that can be used for multi-object target selection and 2) a spectrograph channel. Using this two-channel approach, DMD-MOS can simultaneously image the telescope field of view (FOV) with the imaging channel and actuate the specific DMD micro-mirrors to send light from chosen targets into the spectrograph channel. In this work, we present the results of our laboratory testing of DMD-MOS including spectral resolution, line spread function, wavelength coverage, and the mapping between the DMD and imaging channel planes, the latter of which enables DMD-MOS and our control software to instantaneously configure the DMD to observe chosen target(s) in the acquisition field.

The OrcaQuest CMOS sensor by Hamamatsu Photonics has been found to exhibit a non-linear gain curve at low exposure times. This effect is characterized through the various exposure tests and data reduction pipelines detailed in this report, and a more accurate gain characterization curve is provided. Such data can be used to provide more consistent measures of pixel gain, linearity, and high framerate images.

Accurately extracting information from galaxy surveys, particularly at non-linear scales, requires increasingly complex and flexible forward models of the observed galaxy distribution. A key component is the galaxy bias relation, which connects the underlying matter distribution to observed galaxies and requires more expressive representations than those currently incorporated into Bayesian field-level inference. Certain parameterized models for this mapping can be overparameterized, with individual parameters carrying no direct physical interpretation, making them challenging to constrain. Our objective is to guide the inference of flexible model parameters towards physically plausible regions of parameter space through physics-informed priors. These priors are derived from high-fidelity simulations, thereby enabling the indirect use of simulations that cannot be integrated directly into gradient-based field-level inference. To this end, we introduce the ROBIN-PIP (RObust Bayesian INference with Physics-Informed Priors) framework. As a proof of concept, we jointly infer the cosmic initial conditions and the parameters of a truncated power-law galaxy bias model for a simulated universe. We integrate ROBIN-PIP into the Bayesian Origin Reconstruction from Galaxies algorithm and benchmark against inference without the simulation-based prior. With the additional prior, posterior standard deviations of the bias model parameters are reduced by up to $20\%$ and autocorrelation lengths are reduced from $730$-$870$ to $440$-$550$, increasing the effective sample sizes. We find no bias in the recovered initial conditions, demonstrating that ROBIN-PIP guides inference towards physically consistent solutions without compromising the data likelihood and highlighting its potential to incorporate overparameterized models in field-level inference.

Sensor noise is a fundamental barrier to low-flux astronomical imaging and spectroscopy, where the ideal sensor would unambiguously distinguish individual photon arrivals. While optical semiconductor arrays can reach single-photon sensitivity, comparable performance in the infrared has largely required superconducting detectors. These must be operated at temperatures near absolute zero and require substantially more power, introducing major system-level challenges. HgCdTe avalanche photodiodes offer a semiconductor alternative by amplifying charge before readout, but dark current and tunneling effects have limited their use in the faintest regimes. Here we demonstrate single-photon-resolving operation in a megapixel-format HgCdTe linear-mode avalanche photodiode array operated at conventional cryogenic temperature. Avalanche gain raises photon-induced steps in non-destructive up-the-ramp data above the readout-noise floor while leaving the dark signal largely unamplified, with a false positive rate of approximately 2 false counts per thousand reads per pixel. These results establish LmAPDs as a promising route toward infrared photon-counting focal planes for future low-background astronomical observatories.

Pulsar timing array (PTA) experiments have seen evidence for a nanohertz-frequency gravitational wave background (GWB) through coordinated radio timing observations of millisecond pulsars. The significance of this evidence is expected to grow and the GWB's progenitor(s) uncovered with continued observations, especially as the next generation of radio telescopes comes online. We present a framework for simulating timing observations of a set of pulsars with a set of telescopes to predict the per-pulsar optimal instrument, observing frequency, and integration time. We apply this methodology to the NANOGrav source list of 85 pulsars observed with the Green Bank Telescope, Very Large Array, Canadian Hydrogen Intensity Mapping Experiment (CHIME), and the Deep Synoptic Array (DSA), a radio dish array under construction in Nevada. We discuss the dominant noise contributions to the timing precision of these pulsars and show that most are not dominated by intrinsic pulse phase jitter noise. We also determine which pulsars should be timed with DSA and CHIME or only DSA and show that an ab initio DSA PTA is more sensitive than one which uses current instruments. Finally, we solve for the optimal integration time per pulsar, subject to a fixed time budget, that maximizes the GWB signal-to-noise. We show that there is little benefit to optimizing over integration time for these pulsars observed with DSA. Through Monte Carlo realizations of the PTA, we show that the GWB sensitivity improves by $\sim 5\%$ for time-optimized observations compared to the equal-time-per-source scenario with an early-science, fixed source list.

Binary pulsars provide valuable laboratories for testing theories of gravity, but orbital Doppler shifts complicate their detection. Fourier-domain acceleration and jerk searches address this challenge via matched filtering, but at substantial computational cost. We present LeoNet, a convolutional neural network that uses ten learnable filters to extract features of signals affected by Doppler shifts. The resulting ten-channel feature map provides a compact, lower-dimensional alternative to an explicitly sampled acceleration-jerk response grid and is analysed by a convolutional classifier to identify candidate signals. For simulated observations lasting 500 s, LeoNet achieves a mean relative reduction in false negative rate of 55.5% across five sampling intervals compared with the evaluated PRESTO acceleration-search configuration. TensorRT-optimised LeoNet processes each 500 s observation in 3.44-4.37 ms in FP32 on an NVIDIA H100 PCIe GPU across eight sampling intervals, including preprocessing, inference, and postprocessing. At a sampling interval of 128 microseconds, its mean processing time is 3.54 ms, compared with 1.767 s for PRESTO FDAS on an AMD EPYC 9825 CPU with search-frequency limits of 96-1000 Hz, corresponding to an approximately 499-fold speedup in the measured processing time. These results suggest that LeoNet has the potential to improve detection performance, while its millisecond-scale processing time supports its use as a candidate-identification stage in real-time binary pulsar search pipelines.

The correction of systematic errors in TESS light curves is crucial for all astrophysical analyses employing these observations. Here we present a data analysis and a software package, SysCoCoPy, to investigate and directly compare the performance of the Presearch Data Conditioning (PDC) correcting method from the Science Processing Operations Center (SPOC) pipeline and three correctors developed by the community. We incorporate these three correctors based on their implementations in Lightkurve and are particularly interested in the ability of the four correctors to remove scattered light contamination from the Earth and the Moon, which is a key systematic for TESS. We implemented these correctors in SysCoCoPy with a framework that allows an automatic optimization of their parameters to scale the analysis towards increasingly larger samples. SysCoCoPy provides qualitative and quantitative products for the comparison of individual cases as well as statistical results for selected samples. We currently find that while our automatic parameter optimization provides a significant number of successful scattered-light corrections for two of the correctors with a design that favors this purpose, an statistical analysis of our largest sample indicates that PDC is presently more robust, with a larger overall success level of the metrics used.

I present a greatly improved version of SOLARPROP, an open source framework for building models of charge-sign dependent solar modulation of cosmic rays in the heliosphere. The transport equation of charged particles is solved by converting it to a set of stochastic differential equations (SDEs). The code now includes the full set of SDEs in two spatial dimensions, allowing for magnetic fields with latitudinal components, and it has been generalized to accommodate models in three spatial dimensions. Due to code parallelization and optimization, a speedup of up to three orders of magnitude with respect to the original version is achieved. Python bindings have been added for ease of use. The code has been validated against the results of several model calculations found in the literature. While excellent agreement is found in many cases, important differences are observed for two model implementations. Possible root causes for the differences have been investigated.

Mechanical properties of rubble-pile asteroid regolith remain poorly constrained because contact responses depend on both material properties and local particle configuration. This study examines whether early-time high-speed penetrator dynamics can constrain particle stiffness, represented by the particle Young's modulus E, within a controlled discrete-element model. A bidirectionally coupled EDEM-Adams discrete-element-multibody model is used to screen six parameters: Young's modulus, Poisson's ratio, coefficient of restitution, static friction coefficient, rolling friction coefficient, and adhesion strength. Five Young's-modulus levels are then tested at the same 17 spatial locations in one settled granular bed, giving 85 simulations with location-matched comparisons across modulus levels. Within the 75-90 m s^-1 speed range, varying Young's modulus yields the clearest and most systematic differences in probe deceleration, whereas the other parameters have weaker effects over the tested ranges. Validation by withholding all modulus cases at one location in turn indicates that the early response is more informative for distinguishing broad modulus ranges than adjacent modulus levels. Mesoscale analysis links the response differences to concentrated interface load sharing and spatially extended three-dimensional high-capacity contact paths as Young's modulus increases. The results provide a numerical basis for narrowing the particle Young's-modulus range from high-speed penetration responses despite local granular variability. Quantitative application to real asteroid regolith requires further experimental validation.

hyprfine is an analytic simulation of the sky-averaged 21-cm signal from $z=1100 - 6$ written using JAX and Python for native GPU capabilities. It models the average temperature of the 21-cm signal over cosmic time as a function of the $\Lambda$-CDM cosmology parameters and the astrophysics of the first stars and galaxies. As far as we are aware, the code is the first analytic GPU native simulation of the 21-cm signal. It runs in a fraction of a second, parallelises efficiently across a GPU and is differentiable through the Dark Ages ($z \geq 35$).

The antenna-elements that make up a radio interferometer form a spatial filter that samples components of the Fourier transform of a target radio astronomical source brightness. Along the signal path, there are multiplicative and additive perturbation effects that alter the signal and that should be corrected. The process of mitigating these perturbation effects is called calibration. In this work, we develop a new and fast Maximum Likelihood based estimator of these perturbation effects using the Exponential Map and Lie groups. To evaluate its performance, we compare it to the Cramér-Rao Lower Bound and, to test the estimation time, we compare it with the Expectation Maximization algorithm, another fast Maximum Likelihood estimator. Finally, we apply our estimator to a real observation of the protoplanetary disk AS 209 made with the Submillimeter Array. We found that our proposed estimator meets the Cramér-Rao Lower Bound and it was approximately 40 times faster than the Expectation Maximization algorithm.

We present an analysis of pulsar spin noise based on physically-motivated two-component models of spin wandering. We focus on two models, distinguished by their total angular momentum dynamics: a singular, nonstationary model with a diffusive total angular momentum, and a minimal, stationary model anchored on a conserved total angular momentum. We develop scalable Gaussian process methods and, using mock data, show that the two models are fully testable and distinguishable with full-state observations, i.e., simultaneous independent data on the crust and the superfluid rotational states. This paves a path to testing stationarity in pulsar spin noise, potentially achievable with joint continuous gravitational wave observations and radio timing of pulsars. However, robust inferences and predictions are harder to achieve, and depend on the priors and data quality, when only one component is observationally accessible.

Whether spin noise of a neutron star is stationary is, in two-component models, a question of whether stellar angular momentum is conserved internally or exchanged externally through independent stochastic torques on the crust and superfluid. The question is posed in the two components' angular velocities, but radio pulsar timing observes only the crust, through its rotational phase after a deterministic timing model is fitted. We develop a Gaussian process method for testing spin noise stationarity directly with such phase data. Starting from the exact analytical phase means and covariances of a singular, nonstationary and a minimal, stationary two-component model, we show that the crust phase covariances are semiseparable and construct a likelihood that scales linearly with the number of observations, with the timing model marginalized analytically. We analyze simulated phase data from both models using full-state and crust-only observations, and after differentiation into local spin frequencies. Integration, timing model removal and differentiation neither create nor destroy the distinction between stationary and nonstationary spin noise, but determine how much survives in a finite, noisy data set. With both components observed, the models are distinguished decisively and the generating parameters are recovered. With the crust alone, both models describe the observed phase equally well over much of parameter space, and the Bayes factors are of order unity and prior-limited. The minimal model nonetheless ties the hidden superfluid phase to the observed crust phase through a single factor set by the superfluid inertia fraction, so an independent estimate of this fraction, as from glitches, turns it into a falsifiable prediction that a continuous gravitational wave observation of the interior could test.

Blind extragalactic radio continuum surveys are increasingly conducted at sub-arcsecond angular resolutions. However, these surveys contain substantially more spurious sources than expected from purely Gaussian noise statistics. We investigate the origin of these false detections using the 10GHz GOODS-N mosaic obtained with the Karl G. Jansky Very Large Array (VLA), which reaches a native angular resolution of 0.22arcsec and exhibits a nearly Gaussian pixel-noise distribution. We show that part of the increase in the spurious-source fraction at high angular resolution arises naturally from the larger number of independent resolution elements, while residual wide-field imaging effects associated with the primary-beam response make only a modest contribution. Nevertheless, even after accounting for these effects, the observed fraction of false detections remains several times higher than predicted for Gaussian noise. An analysis of the noise autocorrelation function reveals that images with relatively sparse uv coverage retain significant dirty-beam sidelobes that introduce correlated noise fluctuations, substantially increasing the probability of false detections. We conclude that the excess of spurious sources is an intrinsic consequence of incomplete uv sampling rather than the imaging methodology itself, highlighting that future deep radio continuum surveys require not only high angular resolution but also sufficiently dense uv coverage to minimize spurious detections.

X-ray observatories introduce unwanted instrumental effects into photon count data that must be accurately accounted for. In particular, the spatially variant point spread function (PSF) and shot noise pose a non-trivial inverse problem. We apply Bayesian inference grounded in information field theory (IFT) combined with a fast spatially variant PSF representation to infer the posterior mean and uncertainty of the X-ray flux under a minimal set of physically motivated prior assumptions, thereby removing or reducing these instrumental effects. First, ignoring spatial PSF variability, the IFT-based deconvolution is benchmarked on a synthetic example against three variants of the Richardson-Lucy (RL) algorithm using SSIM, RMSE, and NLL as evaluation metrics. Second, the ability of an interpolated patch-based convolution scheme to accurately represent the complex, spatially variant Chandra PSF is assessed on simulated PSF data. Finally, deblurring and spatially variant PSF representation are combined and applied to real Chandra observations of the supernova remnant Cassiopeia A. The IFT-based deconvolution outperforms all tested RL variants on the synthetic benchmark. The patch-based convolution scheme accurately recovers the complex structure of the Chandra PSF. Applied to Cassiopeia A, the reconstructed image appears visually sharper than the exposure-corrected data, and the data residuals are consistent with pure noise, indicating an accurate model of both the instrument and the sky. A comparison with a highly resolved reference dataset confirms this impression. The presented framework enables the removal of spatially variant PSFs from noisy data and opens avenues for future work on cross-calibration between multiple observations or different X-ray instruments, building on the principled uncertainty quantification inherent to the Bayesian framework.

Current all-sky surveys such as Vera Rubin's Legacy Survey of Space and Time and the Zwicky Transient Facility (ZTF) promise a wealth of scientific gains that are contained in the millions of astrophysical transient candidates produced each night. Kilonovae, one such transient of interest, will be challenging to identify in the alert stream and will require efficient artificial intelligence models to parse the large, real-time influx of data. In order to build these large models, comprehensive multimodal datasets are necessary for training. Due to a lack of numerous kilonova observations, we propose $\texttt{kilonova-multimodal-emulator}$ – a simulation pipeline for realistic, multimodal kilonova observations comprised of photometry, spectra, and images. We demonstrate this pipeline for ZTF-type observations, based on historical cadence and limiting magnitude information from the Bright Transient Survey (BTS) and using the latest radiative transfer kilonova models to produce a comprehensive dataset meant for the training of large artificial intelligence model.

Efficient and accurate estimation of the detection probability of a gravitational wave event given its source parameters remains a challenging problem because it conventionally requires expensive Monte Carlo injection campaigns. We present a machine learning-based approach using Normalizing Flows (NFs) to estimate the detection probability of gravitational wave events for a LIGO/Virgo/KAGRA O4-like detector network configuration. We utilize the publicly available injection dataset as training and test data. We test our method and implementation by evaluating the raw NF performance as a generative model based on its ability to recover the correct parameter distributions of detected events. In addition, we compare the detection efficiencies predicted by the NF emulator with those from Monte Carlo importance sampling and find good agreement. Furthermore, estimating the detection efficiency for a wide variety of population models, including those with sharp features, can be more precise than estimates obtained via Monte Carlo importance sampling. We show that the NF emulator can be used in population analysis of gravitational wave sources, similar to previous neural network approaches. The training code and trained models from this work are publicly available.

Software is both a foundational tool and a primary output of modern computational research, yet citation practices for software remain inconsistent, incomplete, and rarely machine-actionable. Existing infrastructure designed for paper and data citation does not adequately serve the distinct needs of software citation, leaving a gap that impedes reproducibility, misattributes scholarly credit, and obscures the labor embedded in research pipelines. Drawing on a NASA-funded community workshop held in April 2026, we present an analysis of four interconnected themes: (I) the cultural barriers to consistent citation practice; (II) the need for clearer community norms and conventions; (III) gaps in existing technical infrastructure and workflow; and (IV) the emerging challenges posed by AI-assisted research. For each theme we identify targeted interventions and assign responsibility across stakeholder groups. We conclude that meaningful progress requires simultaneous action on technical and cultural fronts. Journal editors and publishers represent the single highest-leverage point for accelerating this change, and correct citation must become the path of least resistance within researchers' existing workflows.

We apply Markov Chain Monte Carlo (MCMC) to the problem of parametric galaxy modeling, estimating posterior distributions of galaxy properties such as ellipticity and brightness for more than 100,000 coadded images of galaxies taken from DC2, a simulated telescope survey resembling the ongoing Rubin Observatory Legacy Survey of Space and Time (LSST). This analysis focuses only on truly unblended galaxies detected as single objects. We use a physically informed prior, apply selection corrections to the likelihood, and systematically study the bias and calibration of our posteriors. The resulting posterior samples support rigorous probabilistic inference of galaxy model parameters and their uncertainties, even for low signal-to-noise galaxies that are often excluded from cosmological analyses. We implement the probabilistic modeling and MCMC inference using the JIF (Joint Image Framework) package, which we make freely available.

The shape of the submillimeter galaxy number counts below the confusion limit is a key record of cosmic star formation but is accessible only statistically, through the one-point distribution of map surface brightness, $P(D)$. Classical $P(D)$ analysis compresses the counts into flux-integrated constraints and requires a full instrument forward model. We introduce an extreme-value-theory analysis of the confusion $P(D)$ tail: the peaks-over-threshold formalism, in which exceedances above a threshold $u$ follow a generalized Pareto distribution (GPD). The GPD shape parameter $\xi(u)$ is a flux-resolved, normalization-free readout of the local logarithmic slope of the counts, and its gravitational-lensing modulation $\Delta\xi(u)$ probes their local curvature. We derive analytic relations for both, validate them with end-to-end simulations, and apply the method to Planck 857 GHz maps and the Herschel/SPIRE 350 $\mu$m map of GAMA-09. At Planck's 5' resolution the tail reflects the bright, clustered sky rather than the faint counts, though the background alone excludes the single power-law count model. At SPIRE resolution $\xi$ rises markedly with threshold, consistent with the strongly lensed bright population (a first detection of lensing in a $P(D)$ tail), and the bright-masked map favors the Schechter model. Behind galaxy clusters we set the first calibrated upper limits on $\Delta\xi(u)$. CCAT/FYST should separate the count models directly, but a cluster-lensing detection needs more $10^{15}\,M_\odot$ clusters than the sky contains. The GPD tail statistic thus discriminates the functional form of the counts at fluxes of order the threshold, below the detection limit, invariant to map mean, gain and count normalization, and robust to clustering; lensing supplies a calibrated ruler for count features, whose detection awaits deep, high-resolution surveys of massive clusters.

Microwave Kinetic Inductance Detectors (MKIDs) are superconducting photon counting detectors that simultaneously measure the energy and arrival time of individual photons and are suitable for large-format arrays. The energy resolving power R = E/$\Delta$E is the primary figure of merit for spectrophotometric applications. It is limited in practice by the assumptions underlying the Wiener optimal filter used to estimate photon energy: stationary noise, linear response, and energy independent pulse shapes, all of which MKIDs structurally violate. We present Venom (Very Efficient Neural Optimal-filter for MKIDs), a selective state space model based on the Mamba architecture that replaces the coordinate transform and optimal filter, operating directly on raw in-phase/quadrature timestream data, carrying 3,314 trainable parameters, and targeting deployment on the MKIDGen3 and future system-on-chip readout platforms. To deal with the small calibration datasets typical of MKID experiments, we train on synthetic pulses drawn from a streaming principal component analysis that samples photon energy continuously between calibration wavelengths. All numbers are reported on a stratified 15% held-out validation set, with R measured from a kernel density estimate. On an InHf bilayer resonator (ten wavelengths, 254-1310nm), Venom reaches a mean R of 26.4 versus 24.2 for the published per-wavelength optimal filter baseline, a 9% improvement from one model in place of ten per-laser filter templates. The R of 38.6 at 254 nm is the highest ever recorded for an ultraviolet-to-near-infrared MKID suitable for use in a dense array. On a PtSi resonator (five wavelengths, 808-1310nm), where the published analysis used one shared 920nm template, Venom matches the optimal filter, with a mean R of 9.1 versus 8.8 at the three interior wavelengths.