In the realm of astrophysics and energy research, a team of scientists from various institutions, including the Italian National Institute for Astrophysics (INAF), Stockholm University, and the University of Heidelberg, has been delving into the chemical evolution of the Milky Way’s Nuclear Stellar Disc (NSD). This dense, rotating stellar system, located within the central 200 parsecs of our galaxy, has been the focus of the LEGARE project, led by researchers such as E. Spitoni, M. Schultheis, F. Matteucci, and their colleagues.
The LEGARE project aims to understand the chemical evolution of the NSD, which is believed to be primarily fueled by gas inflows driven by the Milky Way’s central bar. The team constructed the first chemical evolution models for the NSD using a Bayesian approach, tailored to reproduce the observed metallicity distribution functions (MDFs) and compared with available abundance ratios for elements like Magnesium, Silicon, Calcium, and Iron. Their findings were published in the journal Astronomy & Astrophysics.
The researchers adopted a state-of-the-art chemical evolution model, assuming that the gas responsible for the NSD’s formation is driven by the Galactic bar-induced inflows. They posited that the chemical composition of the accreted material reflects that of the Galactic disc at a radius of 4 kiloparsecs. Using a Bayesian Markov Chain Monte Carlo (MCMC) framework, they fitted the MDFs of different samples of NSD stars.
Their initial analysis, taking the NSD data at face value without considering possible contamination from bulge stars, revealed an inconsistency. A formation scenario based solely on inner disc flowing gas could not account for the low metallicity tail of the observed MDF. This is because the inner disc metallicity, at the epoch of bar formation, was already near solar. However, models invoking dilution from additional metal-poor inflows successfully reproduced the observations. The best-fit model required inflow metallicity five times lower than the inner disc and a moderate star formation efficiency.
Interestingly, the same model successfully reproduced the observed alpha-to-Iron ratio versus Iron/Hydrogen ratio and predicted a star formation history consistent with recent estimates. However, if the MDF is contaminated by metal-poor bulge stars and restricted to Iron/Hydrogen > -0.3 dex, gas dilution is no longer required. In this scenario, the best-fit model has a very low star formation efficiency and a mild galactic wind.
For the energy sector, understanding the chemical evolution of the Milky Way’s NSD can provide insights into the processes that drive star formation and the distribution of elements crucial for energy production, such as Iron and Silicon. These elements are vital in various energy technologies, including steel production for infrastructure and Silicon for solar panels. Moreover, the Bayesian approach used in this study can be applied to optimize energy systems and predict their performance under different scenarios.
This article is based on research available at arXiv.