arXiv subjects

Eric Ludwig

Publications and source records attributed to Eric Ludwig.

2 recordsLinked to original sources

arXiv2026

Variability in Supermassive Black-Hole Accretion Rates in Fuzzy Dark Matter Cores due to Black-Hole Wandering

Soliton cores in fuzzy dark matter (FDM) deepen nuclear potentials and have been proposed to strongly boost Bondi accretion, potentially aiding rapid black-hole growth at high redshift. We test this in live Schrodinger-Poisson FDM cores coupled to isothermal gas, evolving a moving black hole that grows via a strictly mass-conserving sink. We measure boosts relative to the initial mean-density Bondi rate. Low-mass seeds, with initial black-hole masses less than about 10^6 solar masses, do not sustain large boosts: black-hole wandering and soliton sloshing drive bursty accretion, with dense gas only intermittently present near the black hole. Intermediate seeds, with initial black-hole masses around 10^7 solar masses, produce the most durable enhancement, reaching boosts of order 100 for sound speed cs = 60 km/s, while hotter gas approaches near-background Bondi rates. High-mass seeds, with initial black-hole masses around 10^8 solar masses, quickly exhaust the sink-scale reservoir and become supply-limited, suppressing long-lived growth despite the deepened potential. In general, central-potential deepening, for example by a soliton halo, does not guarantee long-lived fueling: sustained boosts emerge only when the black hole remains dynamically confined within the dense nuclear gas region. Our results suggest that SMBH formation channels relying on soliton-enhanced accretion alone are unlikely to provide sufficient early growth.

astro-ph.CO↗

arXiv2024

Katachi: Decoding the Imprints of Past Star Formation on Present Day Morphology in Galaxies with Interpretable CNNs

The physical processes responsible for shaping how galaxies form and quench over time leave imprints on both the spatial (galaxy morphology) and temporal (star formation history; SFH) tracers that we use to study galaxies. While the morphology-SFR connection is well studied, the correlation with past star formation activity is not as well understood. To quantify this we present Katachi, an interpretable convolutional neural network (CNN) framework that learns the connection between the factors regulating star formation in galaxies on different spatial and temporal scales. Katachi is trained on 9904 galaxies at 0.02$<$z$<$0.1 in the SDSS-IV MaNGA DR17 sample to predict stellar mass (M$_*$; RMSE 0.22 dex), current star formation rate (SFR; RMSE 0.31 dex) and half-mass time (t$_{50}$; RMSE 0.23 dex). This information allows us to reconstruct non-parametric SFHs for each galaxy from \textit{gri} imaging alone. To quantify the morphological features informing the SFH predictions we use SHAP (SHapley Additive exPlanations). We recover the expected trends of M$_*$ governed by the growth of galaxy bulges, and SFR correlating with spiral arms and other star-forming regions. We also find the SHAP maps of D4000 are more complex than those of M$_*$ and SFR, and that morphology is correlated with t$_{50}$ even at fixed mass and SFR. Katachi serves as a scalable public framework to predict galaxy properties from large imaging surveys including Rubin, Roman, and Euclid, with large datasets of high SNR imaging across limited photometric bands.

astro-ph.GA↗