The LEGARE Project - I. Chemical evolution model of the Nuclear Stellar Disc in a Bayesian framework

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Volume 707 (March 2026)

A&A, 707 (2026) A202

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Table 1

Main properties of our best-fit models for the NSD varying the chemical enrichment of the gas flow.

NSD Models
	PRIM	ENR_D10	ENR_D05	ENR_D03	ENR
X_ℱ,NSD(t)	Primordial	X_4D(t)/10	X_4D(t)/5	X_4D(t)/3	X_4D(t)
MCMC results

τ [Gyr]	${3.812}_{- 0.253}^{+ 0.204}$ $Mathematical equation: $\[3.812_{-0.253}^{+0.204}\]$$	${4.624}_{- 0.447}^{+ 0.502}$ $Mathematical equation: $\[4.624_{-0.447}^{+0.502}\]$$	${5.324}_{- 0.655}^{+ 0.872}$ $Mathematical equation: $\[5.324_{-0.655}^{+0.872}\]$$	${4.732}_{- 0.620}^{+ 0.920}$ $Mathematical equation: $\[4.732_{-0.620}^{+0.920}\]$$	${3.358}_{- 1.048}^{+ 1.408}$ $Mathematical equation: $\[3.358_{-1.048}^{+1.408}\]$$
ω	${0.001}_{- 0.001}^{+ 0.002}$ $Mathematical equation: $\[0.001_{-0.001}^{+0.002}\]$$	${0.003}_{- 0.002}^{+ 0.005}$ $Mathematical equation: $\[0.003_{-0.002}^{+0.005}\]$$	${0.008}_{- 0.006}^{+ 0.013}$ $Mathematical equation: $\[0.008_{-0.006}^{+0.013}\]$$	${0.030}_{- 0.022}^{+ 0.036}$ $Mathematical equation: $\[0.030_{-0.022}^{+0.036}\]$$	${1.959}_{- 1.222}^{+ 2.492}$ $Mathematical equation: $\[1.959_{-1.222}^{+2.492}\]$$
ν [Gyr⁻¹]	${31.205}_{- 6.613}^{+ 10.343}$ $Mathematical equation: $\[31.205_{-6.613}^{+10.343}\]$$	${10.673}_{- 1.899}^{+ 2.354}$ $Mathematical equation: $\[10.673_{-1.899}^{+2.354}\]$$	${4.041}_{- 0.473}^{+ 0.733}$ $Mathematical equation: $\[4.041_{-0.473}^{+0.733}\]$$	${1.710}_{- 0.184}^{+ 0.284}$ $Mathematical equation: $\[1.710_{-0.184}^{+0.284}\]$$	${0.260}_{- 0.046}^{+ 0.185}$ $Mathematical equation: $\[0.260_{-0.046}^{+0.185}\]$$

NSD DATA	Sample A				Sample B

Notes. In the upper part of the table, we show the chemical composition of the gas flow into the NSD. In the lower one, we indicate the accretion timescale, τ, loading factor, ω, and star formation efficiency, ν from our MCMC estimates for the four considered models. In the last row, we report the observed samples adopted as constraints in the MCMC analysis.

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