ArXiv TLDR

Short timescale variation in the submillimeter flux of Sagittarius A*

🐦 Tweet
2604.22144

Makoto Miyoshi, Yoshiaki Kato, Yoshiharu Asaki, Masato Tsuboi, Kenta Uehara + 6 more

astro-ph.GAastro-ph.HE

TLDR

Sgr A* exhibits short-timescale white-noise-like flux variability at 340 GHz, transitioning to red-noise, challenging prior models.

Key contributions

  • Monitored Sgr A* 340 GHz flux variability with ALMA using 10s snapshot imaging.
  • Employed careful self-calibration and relative measurements to ensure high data fidelity.
  • Identified a short-timescale (2.3-6.3 min) flat, white-noise-like variability regime.
  • Noted a transition to red-noise-like behavior at longer timescales, challenging prior models.

Why it matters

This study provides crucial empirical data on Sgr A*'s short-timescale variability, revealing a previously unobserved white-noise regime. This finding challenges current theoretical models of black hole accretion, offering new insights into the physical processes near the Galactic Center.

Original Abstract

We study short-timescale 340 GHz flux-density variability of Sgr A* using ALMA Cycle 3 observations. Careful self-calibration enabled 10 s snapshot imaging with very high effective image-domain SNR, allowing high-cadence monitoring of Galactic Center sources. To reduce atmospheric and instrumental effects, we measured Sgr A* relative to multiple non-variable sources in the same field and corrected apparent variability caused by time-dependent u-v coverage and PSF changes using simulations with a static input model. We then searched for characteristic timescales over 20 s < tau < Tobs/3 using structure functions, the Lomb--Scargle method, and state-space-model autoregressive spectral analysis. No dominant narrow periodicity is found. Instead, the data show a short-timescale flat, white-noise-like regime at tau below about 2.3--6.3 min, followed by red-noise-like behavior at longer timescales. This flat regime appears in both active and quiescent phases, suggesting statistically independent fluctuations on these timescales. We interpret its upper boundary as an empirical transition timescale between decorrelated short-timescale fluctuations and longer-timescale correlated variability. The physical origin of this flat component remains uncertain, since previous theoretical and numerical studies more commonly report red-noise-like or broken-power-law variability.

📬 Weekly AI Paper Digest

Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.