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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2602.23077 |
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- We present a computational framework for galactic evolution based on a coupled stochastic nonlinear oscillator, implemented with the \textbf{Stochastic Hopf Engine}. Gas density ($G$) and star formation rate ($S$) co-evolve through a supercritical Hopf bifurcation, capturing the transition from quiescent stability to merger-driven starbursts. Scatter in dark matter halo properties, modeled as multiplicative noise via the \textbf{Euler--Maruyama method}, broadens the bifurcation into a regime where noise-induced bursts occur below the deterministic threshold. Simulations reveal a periodic signature, the \textbf{Galactic Heartbeat}, emerging as a deterministic limit cycle validated by the \textbf{data3} resonance peak in the star-formation spectrum. A radial reduction yields an effective \textbf{Fokker--Planck equation} for burst amplitude; its stationary solution matches numerical PDFs, providing statistical closure. Including differential shear $Ω(r)$ and spatially varying bifurcation fields reproduces spiral morphologies and AGN-driven quenching. Driving the growth parameter sub-critical ($r_{agn} < 0$) yields ``Red and Dead'' cores via attractor collapse. Dark matter halo scatter suppresses mean star formation while enhancing intermittency, offering a minimal yet interpretable framework linking local feedback and global potentials to macroscopic galactic evolution.