Almannaei, Aisha Sultan Y. A.; (2025) Unveiling the Dynamics and Stellar Populations of the Milky Way Disc in the Gaia Era. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Understanding the formation and evolution of our Galaxy, the Milky Way, is a fundamental challenge in Galactic astronomy. A key question is how the structure, dynamics, and populations of the Galactic stellar disc, particularly the influence of spiral arms and the distribution of stellar ages, inform our understanding of the history of stellar disc formation. This thesis addresses the impact of spiral arms on the local circular velocity and constructs a map of the stellar age distribution in the Galactic disc by leveraging the unprecedented astrometric and spectroscopic data from Gaia DR3. In the first part of this work, we investigate the kinematics of young OB stars in the solar neighbourhood to constrain the local circular velocity, Vc(R0), a critical parameter for modeling the Milky Way’s total mass distribution. Using a one-dimensional axisymmetric disc model, we find that Vc(R0) varies with spatial sampling, with values ranging from 234±2 kms−1 (for stars within 2 kpc) to 238±2 kms−1 (within 0.5 kpc). These variations are linked to the influence of the Local spiral arm, which induces measurable perturbations in stellar motions. By comparing to N-body simulations including spiral arms, the rotational velocity gap between the Coma Berenices and Hyades–Pleiades moving groups is interpreted as a signature of the Local arm’s co-rotation resonance, suggesting that this feature can be used to infer the azimuthally averaged circular velocity of the Milky Way. To further unveil the holistic view of the structure of the different populations of the Milky Way disc stars, the second part of the thesis focuses on the challenge of determining stellar ages. Precisely measuring the stellar age is essential for Galactic archaeology, using the stars with various ages as the fossil records to reconstruct the formation history of the Galaxy. We develop two machine learning models, Stellar age Inference Derived from Gaia spectRA using RVS spectra (SIDRA-RVS) and Stellar age Inference Derived from Gaia spectRA using XP parameters (SIDRA-XP), to infer the ages of red giant branch and high-mass red clump stars from Gaia’s RVS spectra and BP/RP spectrophotometric data, respectively. Trained on asteroseismically calibrated age data from the APOGEE stellar spectra, these models achieve high precision, with SIDRA-XP outperforming SIDRA-RVS. Applying SIDRA-XP to over 2.2 million stars reveals key features of the Milky Way’s evolutionary history, including the Gaia–Sausage–Enceladus merger and a possible gas-rich interaction with the Sagittarius dwarf galaxy. Together, these studies demonstrate Gaia’s transformative role in Galactic archaeology and highlight the importance of combining stellar kinematics and age distributions to unravel the Milky Way’s past.

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