An instability of feedback regulated star formation in galactic nuclei
Paul Torrey (1, 2), Philip F. Hopkins (2), Claude-Andr\'e, Faucher-Gigu\`ere (3), Mark Vogelsberger (1), Eliot Quataert (4), Du\v{s}an, Kere\v{s}(5), Norman Murray (6) ((1) MIT, (2) Caltech, (3) Northwestern, (4), UC Berkeley, (5) UC San Diego, (6) CITA)

TL;DR
This paper investigates the unstable, oscillatory nature of feedback-regulated star formation in galactic nuclei, revealing episodic bursts and quenching driven by short dynamical timescales and stellar feedback, contrasting with more stable large-scale star formation.
Contribution
It demonstrates through simulations that nuclear star formation is inherently unstable and episodic due to feedback dynamics, a novel insight into galactic nucleus behavior.
Findings
Nuclear star formation undergoes oscillatory cycles with bursts and quenching.
Star formation in nuclei does not reach steady state but varies dramatically.
The Kennicutt-Schmidt relation shows increased scatter at small scales.
Abstract
We examine the stability of feedback-regulated star formation (SF) in galactic nuclei and contrast it to SF in extended discs. In galactic nuclei the dynamical time becomes shorter than the time over which feedback from young stars evolves. We argue analytically that the balance between stellar feedback and gravity is unstable in this regime. We study this using numerical simulations with pc-scale resolution and explicit stellar feedback taken from stellar evolution models. The nuclear gas mass, young stellar mass, and SFR within the central ~100 pc (the short-timescale regime) never reach steady-state, but instead go through dramatic, oscillatory cycles. Stars form until a critical surface density of young stars is present (such that feedback overwhelms gravity), at which point they begin to expel gas from the nucleus. Since the dynamical times are shorter than the stellar evolution…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
