# AGN jet evolution simulation with GADGET4-OSAKA

## TL;DR

This study uses GADGET4-OSAKA to simulate AGN jet evolution, analyzing how numerical methods and parameters affect jet dynamics, energetics, and morphology, providing benchmarks for SPH modeling.

## Contribution

It systematically compares SPH and grid-based simulations of AGN jets, highlighting sensitivities to artificial viscosity and establishing benchmarks for SPH-based jet modeling.

## Key findings

- Jet lobe growth follows self-similar scaling relations.
- Jet size converges with resolution but is sensitive to artificial viscosity.
- Energy partitioning shows significant deviations from idealized models.

## Abstract

Active galactic nuclei (AGN) jets are powerful drivers of galaxy evolution, depositing energy and momentum into the circumgalactic and intracluster medium (CGM/ICM) and regulating gas cooling and star formation. We investigate the dynamics of jet evolution in the self-similar regime using the smoothed particle hydrodynamics (SPH) code GADGET4-Osaka, systematically vary jet-launching schemes, artificial-viscosity prescriptions, mass resolution, and jet lifetimes and compare the results with grid-based simulation. Our analysis combines quantitative diagnostics of jet size and energetics with detailed morphological and thermodynamic characterizations from slice maps and phase diagrams. We find that jet lobe growth follows analytic self-similar scaling relations and converges with resolution, but is highly sensitive to the choice of artificial viscosity. While the overall jet size tracks self-similar predictions, the partitioning of thermal and kinetic energy departs significantly from the idealized picture, reflecting enhanced dissipation and mixing, which is consistent with the jet propagation in grid-based simulations. These results establish robust benchmarks for SPH-based jet modeling, provide insight into the physical and numerical factors shaping jet--medium interactions, and lay the groundwork for future studies of AGN feedback in realistic galactic and cluster environments.