Linking simulations and observations of star-forming regions. I. Masses and temperatures of ALMAGAL-like cores

Dense cores and clumps in massive star-forming regions are commonly studied through (sub-)millimetre continuum observations, but inferred masses and temperatures can be biased by limited resolution, interferometric filtering, projection, and uncertain dust temperatures. By comparing numerical simulations with synthetic observations of massive star-forming clumps, we aim to quantify how reliably core masses and temperatures can be inferred from -like continuum data. ALMA We analysed radiation–hydrodynamic simulations of collapsing 1000 M_⊙ clumps post-processed with and to generate synthetic ALMAGAL-like images. Cores were defined around sink particles, allowing us to compare masses from the 3D simulations, idealised maps, and synthetic ALMA images. We quantified how resolution, projection, and viewing angle affect core masses, and tested three dust-temperature estimators (clump-scale L/M, a L/M+flux model, and a supervised machine learning-based estimate). RADMC-3D CASA RADMC-3D Projection effects cause line-of-sight integrated core masses within 1500 au to exceed the corresponding spherical masses by factors of two to three. The empirical L/M temperature prescription follows the global thermal evolution but misses the core-to-core scatter, producing individual core-mass errors of a factor of a few. Including local flux information improves temperature and mass estimates, and tests with a gradient-boosting machine learning model suggest further improvement. Synthetic ALMAGAL-like images recover the global core structure, but flux-reconstruction uncertainties introduce mass errors up to a factor of about three and limit reliable core-mass recovery to ≳ 0.3 M_⊙, comparable to the ALMAGAL completeness limit. We also derived an empirical relation between projected core mass and expected sink mass. Comparing synthetic ALMAGAL-like observations with known simulation properties quantifies the main biases in continuum-derived core masses. Individual core masses are typically uncertain by a factor of around three to five, mainly due to dust-temperature assumptions and flux reconstruction. Reducing these biases requires temperature estimates that include local core information rather than only a single clump-scale L/M-based prescription.