A Physics Informed Neural Network Approach to Decipher Environmental Confinement of Molecular Clouds in the Third Galactic Quadrant
Abstract
Recent high-sensitivity and high-resolution surveys of the Third Galactic Quadrant [219.75 ≤ l ≤ 229.75 and −5.25 ≤ b ≤ 5.25], such as the Milky Way Imaging Scroll Painting ( MWISP) survey, have revealed a significant population of molecular clouds (MCs) that appear virially unbound (αvir > 2) according to traditional isolated MC models. However, these apparently unstable cloud structures are actually found long-lived and actively undertaking star formation. This inconsistency presents a Virial Paradox. In the present work, we employ a Physics-Informed Neural Network (PINN) to address this discrepancy by re-evaluating the stability of 2,091 MCs . Unlike traditional machine learning, our PINN model embeds the complete Eulerian Virial Theorem including external surface pressure support (Pext) directly into the network's loss function. This model autonomously discovers a global Galactic pressure field that scales inversely with vertical height (|z|) and Galactocentric radius (RGC), consistent with the properties of the Galactic Flare. By incorporating this AI-derived pressure support, we demonstrate a dramatic shift in the stability census: 99.9\% of previously thought unbound clouds are found to be in a state of pressure confined equilibrium (αAI ≤ 2). Furthermore, we find a robust log-log correlation (R = 0.64) between our corrected stability parameter and the star formation rate (SFR). This correlation provides independent physical validation that environmental confinement is a primary regulator of star forming efficiency in the outer Galaxy.
Related
- Environmental Modulation of Small-scale Galactic Conformity in the Virgo Filaments
- Examining Turbulence in Galactic Molecular Clouds. II. Turbulence Cascade Beyond the Scale of Giant Molecular Clouds
- Environmental dependence in the halo model informed by the FLAMINGO simulations
- Hierarchical Dynamics within Molecular Clouds: Type 4 Scaling Relations of Molecular Clouds in the Second Galactic Quadrant
- Hierarchical Dynamics within Molecular Clouds: Type 4 Scaling Relations of Molecular Clouds in the Second Galactic Quadrant
BibTeX
@misc{mondal2026physics,
title = {{A Physics Informed Neural Network Approach to Decipher Environmental Confinement of Molecular Clouds in the Third Galactic Quadrant}},
author = {Ashok Mondal},
howpublished = {arXiv},
year = {2026},
month = nov,
doi = {10.48550/arxiv.2611.03450},
eprint = {2611.03450},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2611.03450},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - A Physics Informed Neural Network Approach to Decipher Environmental Confinement of Molecular Clouds in the Third Galactic Quadrant
AU - Ashok Mondal
PY - 2026
DA - 2026/11/02
PB - arXiv
DO - 10.48550/arxiv.2611.03450
UR - https://arxiv.org/abs/2611.03450
AB - Recent high-sensitivity and high-resolution surveys of the Third Galactic Quadrant [219.75 ≤ l ≤ 229.75 and −5.25 ≤ b ≤ 5.25], such as the Milky Way Imaging Scroll Painting ( MWISP) survey, have revealed a significant population of molecular clouds (MCs) that appear virially unbound (α_vir > 2) according to traditional isolated MC models. However, these apparently unstable cloud structures are actually found long-lived and actively undertaking star formation. This inconsistency presents a Virial Paradox. In the present work, we employ a Physics-Informed Neural Network (PINN) to address this discrepancy by re-evaluating the stability of 2,091 MCs . Unlike traditional machine learning, our PINN model embeds the complete Eulerian Virial Theorem including external surface pressure support (P_ext) directly into the network's loss function. This model autonomously discovers a global Galactic pressure field that scales inversely with vertical height (|z|) and Galactocentric radius (R_GC), consistent with the properties of the Galactic Flare. By incorporating this AI-derived pressure support, we demonstrate a dramatic shift in the stability census: 99.9\% of previously thought unbound clouds are found to be in a state of pressure confined equilibrium (α_AI ≤ 2). Furthermore, we find a robust log-log correlation (R = 0.64) between our corrected stability parameter and the star formation rate (SFR). This correlation provides independent physical validation that environmental confinement is a primary regulator of star forming efficiency in the outer Galaxy.
ER -