Semi-analytic models (SAMs) have been treating galaxy populations as dynamical systems for $\gtrsim50$ years, but their evolution equations remain poorly constrained. We introduce sapphire, a modular, automatically differentiable, GPU-accelerated SAM written from scratch in JAX. For the first time, we compute exact Jacobian matrices of our nonlinear differential equations and show that they have interpretable, non-random structures, using the Pandya et al. (2023) physical model as an initial example. Both local and global sensitivity analyses reveal that supernova energy loading is a key astrophysical parameter for galaxy evolution. We use gradient descent and Hamiltonian Monte Carlo (HMC) to perform comprehensive mock parameter recovery tests. These indicate that the z=0 stellar-to-halo-mass relation alone does not contain enough information to infer many astrophysical parameters. Using observations of star-forming galaxies from the MaNGA survey and the Behroozi et al. (2019) empirical model as one baseline, we derive multiple posteriors assuming different combinations of data, including z=0 interstellar medium gas fractions and metallicities. The inferred physical parameters suggest that galaxies self-regulate their star formation primarily through preventative rather than ejective feedback. Both Fisher and HMC forecasts demonstrate the potential of sapphire to enable precision inference for galaxy formation, but more work is needed to expand its library of models. We discuss how our unique blend of differentiability, massive GPU parallelization, numerical robustness and principled Bayesian methods sets the stage for hybrid physics-informed, data-driven discovery of galaxy formation astrophysics and cosmology. We make sapphire publicly available at this https URL.
The structures and dynamics of the interstellar medium are governed by a combination of self-gravity, external gravity, and various sources of ordered and random motions on different spatial scales. This paper uses ALMA CO (3-2) observations at 0.1" $\approx$ 5 pc resolution to examine the scale dependence of molecular gas structure and dynamics in the central molecular zone (CMZ) of a nearby galaxy, NGC 3351. We use the dendrogram technique to characterize hierarchical molecular gas structures spanning two decades in spatial scales and measure their size, gas mass, and velocity dispersion. Their size-linewidth relation shows a power-law slope of 0.58, comparable to measurements for CMZs in other galaxies and suggestive of significant contribution from ordered motion on large scales. We further decompose the observed velocity dispersion in each gas structure into ordered versus random motions. The former appears stronger in gas structures at $\gtrsim$ 30 pc while the latter becomes more dominant at $\lesssim$ 30 pc. Modulo uncertainties with the CO-to-H$_2$ conversion factor, the estimated gravitational free-fall time is comparable to the crossing time of ordered motions for structures on all spatial scales, and both becomes longer than the crossing time of random motions at small, $\lesssim$ 10 pc scales. Our results highlight the varying sources and drivers of gas motions on different spatial scales in the CMZ of a Milky Way-like galaxy.
Improving predictions of the geomagnetic impact of coronal mass ejections (CMEs) requires understanding how solar source properties relate to in-situ measurements at Earth. However, major geomagnetic storms frequently arise from interacting CMEs, complicating the link back to their solar origins. We analyze a CME interaction event that caused a major geomagnetic storm in 2024 October 10-11 (D$_{st}$ $\sim$-333 nT). Multiviewpoint observations reveal that the storm was related to a sympathetic eruption involving a quiescent filament and an active-region CME. The coronagraph on board the Advanced Space-based Solar Observatory clearly shows that this sympathetic eruption resulted in two distinct CMEs. Due to the overlap of the CMEs in the coronagraph field of view (FOV), a spheroid shock model was used to fit the observed shock. Kinematic analysis indicates that the interacting CMEs had completed their impulsive acceleration phase before entering the coronagraph FOV, with a slow deceleration continuing beyond 100 R$_\odot$. In-situ measurements indicate that the enhanced southward magnetic fields, arising from compression during CME interactions, were the primary driver of the storm. Compared to photospheric fields, the in-situ magnetic fields suggest that the trailing CME maintained flux-rope-like signatures consistent with the source region. In contrast, the compressed leading CME displayed varying magnetic configurations between Wind and STEREO-A, featuring distorted flux-rope signatures and inconsistent inferred axis orientations. Our study bridges solar source dynamics to in-situ multipoint measurements, providing key insights for space weather prediction. Nevertheless, the direct linkage between source-region magnetic field configurations and these measurements remains tentative and requires further investigation.
The chemical abundance of host stars plays a pivotal role in shaping the formation history of planetary systems, yet the influence of elements beyond iron remains poorly understood. Here, we investigate the relationship between the carbon-to-oxygen (C/O) ratio of host stars and the orbital periods of giant planets. By analyzing high-resolution spectroscopic data from 598 planet-hosting stars (hosting 929 planets) across SDSS, Keck, and HARPS surveys, we identify a correlation: stars with higher C/O ratios are more likely to host longer-period giant planets. Theoretical models of pebble-driven planet formation and migration further support this observation, demonstrating that elevated C/O ratios enhance solid material availability at outer disk regions, promoting giant planet formation at larger distances and subsequent moderate inward migration. Our findings establish stellar C/O as a critical factor in shaping the orbital architecture of giant planets, bridging disk chemistry to planetary system evolution.
We incorporate an arbitrarily high-order method for the Laplacian operator into the Spectral Difference method (SD). The resulting method is capable of capturing shocks thanks to its a-posteriori limiting methodology, and therefore it is able to survive scenarios in which the dissipative scales (viscous and diffusive) are not properly described. Moreover, it is capable of capturing these scales at lower resolution compared to lower-order methods and therefore attains convergence at lower resolution. We show that the method at hand has exponential convergence when describing smooth solutions and is able to recover a high-order solution when solving the dissipative scales.