We present the most precise and lowest-mass weak lensing measurements of dwarf galaxies to date, enabled by spectroscopic lenses from the Dark Energy Spectroscopic Instrument (DESI) and photometric lenses from the Dark Energy Survey (DES) calibrated with DESI redshifts. Using DESI spectroscopy from the first data release, we construct clean samples of galaxies with median stellar masses $\log_{10}(M_*/M_{\odot})=8.3-10.1$ and measure their weak lensing signals with sources from DES, KiDS, and SDSS, achieving detections with $S/N$ up to 14 for dwarf galaxies ($\log_{10}(M_*/M_{\odot})<$9.25) -- opening up a new regime for lensing measurements of low-mass systems. Leveraging DES photometry calibrated with DESI, we extend to a photometric dwarf sample of over 700,000 galaxies, enabling robust lensing detections of dwarf galaxies with combined $S/N=38$ and a significant measurement down to $\log_{10}(M_*/M_{\odot})=8.0$. We show that the one-halo regime (scales $\lesssim 0.15h^{-1}\rm Mpc$) is insensitive to various systematic and sample selection effects, providing robust halo mass estimates, while the signal in the two-halo regime depends on galaxy color and environment. These results demonstrate that DESI already enables precise dwarf lensing measurements, and that calibrated photometric samples extend this capability. Together, they pave the way for novel constraints on dwarf galaxy formation and dark matter physics with upcoming surveys like the Vera C. Rubin Observatory's LSST.
Accretion disks are ubiquitous in astrophysics, appearing in diverse environments from planet-forming systems to X-ray binaries and active galactic nuclei. Traditionally, modeling their dynamics requires computationally intensive (magneto)hydrodynamic simulations. Recently, Physics-Informed Neural Networks (PINNs) have emerged as a promising alternative. This approach trains neural networks directly on physical laws without requiring data. We for the first time demonstrate PINNs for solving the two-dimensional, time-dependent hydrodynamics of non-self-gravitating accretion disks. Our models provide solutions at arbitrary times and locations within the training domain, and successfully reproduce key physical phenomena, including the excitation and propagation of spiral density waves and gap formation from disk-companion interactions. Notably, the boundary-free approach enabled by PINNs naturally eliminates the spurious wave reflections at disk edges, which are challenging to suppress in numerical simulations. These results highlight how advanced machine learning techniques can enable physics-driven, data-free modeling of complex astrophysical systems, potentially offering an alternative to traditional numerical simulations in the future.
JWST has revealed an abundance of supermassive black holes (BHs) in the early Universe, and yet the lowest mass seed black holes that gave rise to these populations remain elusive. Here we present a systematic search for broad-line Active Galactic Nuclei (AGNs) in some of the faintest high-$z$ galaxies surveyed yet by combining ultra-deep JWST/NIRSpec G395M spectroscopy with the strong lensing aid in Abell S1063. By employing the profile of the [OIII]$\lambda 5007$ emission lines as a template for narrow-line components and carefully cross-validating with mock observations, we identify a sample of ten broad-line AGNs at $4.5<z<7.0$ (eight secure, two tentative). The inferred BH masses from the broad H$\alpha$ line explore the intermediate BH mass regime down to $\sim 10^{5.5}\,M_\odot$. The stellar mass ($M_*$) is estimated with a galaxy+AGN composite model, and we find the BH to stellar mass ratio spans down to $M_{\rm BH}/M_*\lesssim 0.1\%$, unveiling populations on the empirical $M_{\rm BH}-M*$ relation observed in the local universe. We also derive the black hole mass function and investigate its low-mass end at this epoch. While we confirm the agreement of our results with previous studies at $M_{\rm BH}\gtrsim10^{6.5}M_{\odot}$, we find the mass range of $\sim 10^{5.5}\,M_\odot$ features an enhanced abundance with respect to the extrapolated best-fit Schechter function. Comparison with theoretical models suggests that a possible origin for this enhanced abundance is the direct-collapse BH formation, supporting the scenario that the direct collapse of massive gas clouds is a significant pathway for the earliest supermassive BHs.
We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5\sigma$ lower than $\Lambda$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $\Lambda$CDM predictions.
Axion-like particles (ALPs), hypothetical pseudoscalar particles that couple to photons, are among the most actively investigated candidates for new physics beyond the Standard Model. Their interaction with gamma rays in the presence of astrophysical magnetic fields can leave characteristic, energy-dependent modulations in observed spectra. Capturing such subtle features requires precise statistical inference, but standard likelihood-based methods often fall short when faced with complex models, large number of nuisance parameters and limited analytical tractability. In this work, we investigate the application of simulation-based inference (SBI), specifically Truncated Marginal Neural Ratio Estimation (TMNRE), to constrain ALP parameters using simulated observations from the upcoming Cherenkov Telescope Array Observatory (CTAO). We model the gamma-ray emission from the active galactic nucleus NGC 1275, accounting for photon-ALP mixing, extragalactic background light (EBL) absorption, and the full CTAO instrument response. Leveraging the Swyft framework, we infer posteriors for the ALP mass and coupling strength and demonstrate its potential to extract meaningful constraints on ALPs from future real gamma-ray data with CTAO.
The T Tauri star T Cha is known to have a protoplanetary disk with a dust gap separating the inner and outer disk regions. The mid-IR JWST spectrum of T Cha show multiple prominent aromatic infrared bands (AIBs) around 6.2, 8.1, and 11.3 $\mu$m. AIBs are commonly accepted as the emission stemming from PAH molecules. We aim to characterize the PAHs giving rise to the AIBs observed in the JWST spectrum of T Cha. Our objective is to estimate the PAH abundances, in terms of their sizes, ionization fraction, and mass, in the disk of T Cha. We perform spectral fitting of the observed AIBs to identify the possible underlying PAH emission components. We transfer the stellar radiation through a parametric disk model of T Cha in order to reproduce the mid-IR spectrum, optical photometric fluxes, and mm continuum band fluxes of T Cha. We include stochastically heated PAH dust grains in our model to simulate the AIBs, and hence estimate the PAH abundances from the modelling. We use the results from previous observations and modelling efforts to reduce our model degeneracies. We estimate the PAH abundances in T Cha self-consistently, with other important disk parameters. The overall disk morphology - an inner and an outer disk separated by a dust gap - derived in this work is consistent with the previous results from Spitzer, VLT, and ALMA observations. PAHs are located only in the outer disk in our model. We estimate a population of small PAHs of <30 C atoms, with an ionized PAH fraction of ~0.15. We also obtain a PAH-to-dust mass ratio of ~6.5$\times$10$^{-3}$, which amounts to ~16% of the ISM value. We predict that the outer disk should have a frontal wall with smaller dust grains limited up to $\mu$m-order to fit the slope of the continuum within 14-15 $\mu$m. We propose a possibility of sub-micron dust grains within the gap to justify an observed plateau around ~10 $\mu$m in the JWST spectrum.
The Giant Radio Array for Neutrino Detection (GRAND) is a proposed multi-messenger observatory of ultra-high-energy (UHE) particles of cosmic origin. Its main goal is to find the long-sought origin of UHE cosmic rays by detecting large numbers of them and the secondary particles created by their interaction -- gamma rays, and, especially, neutrinos. GRAND will do so using large arrays of radio antennas that look for the radio signals emitted by the air showers initiated by the interactions of the UHE particles in the atmosphere. Since 2023, three small-scale prototype GRAND arrays have been in operation: GRAND@Nançay in France, GRAND@Auger in Argentina, and GRANDProto300 in China. Together, their goal is to validate the detection principle of GRAND under prolonged field conditions, achieving efficient, autonomous radio-detection of air showers. We describe the hardware, software, layout, and operation of the GRAND prototypes and show the first radio spectra measured by them. Despite challenges, the successful operation of the prototypes confirms that the GRAND instrumentation is apt to address the goals of the experiment and lays the groundwork for its ensuing stages.