The spatially-resolved effect of mergers on the stellar mass assembly of MaNGA galaxies

Abstract

Understanding the origin of stars within a galaxy - whether formed in-situ or accreted from other galaxies (ex-situ) - is key to constraining its evolution. Spatially resolving these components provides crucial insights into a galaxy's mass assembly history. We aim to predict the spatial distribution of ex-situ stellar mass fraction in MaNGA galaxies, and to identify distinct assembly histories based on the radial gradients of these predictions in the central regions. We employ a diffusion model trained on mock MaNGA analogs (MaNGIA), derived from the TNG50 cosmological simulation. The model learns to predict the posterior distribution of resolved ex-situ stellar mass fraction maps, conditioned on stellar mass density, velocity, and velocity dispersion gradient maps. After validating the model on an unseen test set from MaNGIA, we apply it to MaNGA galaxies to infer the spatially-resolved distribution of their ex-situ stellar mass fractions - i.e. the fraction of stellar mass in each spaxel originating from mergers. We identify four broad categories of ex-situ mass distributions: flat gradient, in-situ dominated; flat gradient, ex-situ dominated; positive gradient; and negative gradient. The vast majority of MaNGA galaxies fall in the first category - flat gradients with low ex-situ fractions - confirming that in-situ star formation is the main assembly driver for low- to intermediate-mass galaxies. At high stellar masses, the ex-situ maps are more diverse, highlighting the key role of mergers in building the most massive systems. Ex-situ mass distributions correlate with morphology, star-formation activity, stellar kinematics, and environment, indicating that accretion history is a primary factor shaping massive galaxies. Finally, by tracing their assembly histories in TNG50, we link each class to distinct merger scenarios, ranging from secular evolution to merger-dominated growth.

15 pages, 12 figures, Accepted for publication in A&A

References in corpus (46)

• Overview of the SDSS-IV MaNGA Survey: Mapping Nearby Galaxies at Apache Point Observatory
• 3D-HST+CANDELS: The Evolution of the Galaxy Size-Mass Distribution since $z=3$
• Compaction and Quenching of High-z Galaxies in Cosmological Simulations: Blue and Red Nuggets
• Galaxy Pairs in the Sloan Digital Sky Survey I: Star Formation, AGN Fraction, and the Luminosity/Mass-Metallicity Relation
• Streams, substructures and the early history of the Milky Way
• The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations
• The role of mergers and halo spin in shaping galaxy morphology
• Morphology and star formation in IllustrisTNG: the build-up of spheroids and discs
• Observational constraints on the merger history of galaxies since $z\approx 6$: Probabilistic galaxy pair counts in the CANDELS fields
• SDSS-IV MaNGA: pyPipe3D analysis release for 10,000 galaxies
• Diverse Stellar Haloes in Nearby Milky Way-Mass Disc Galaxies
• A consistent measure of the merger histories of massive galaxies using close-pair statistics I: Major mergers at $z<3.5$
• SDSS-IV DR17: Final Release of MaNGA PyMorph Photometric and Deep Learning Morphological Catalogs
• Galaxy Merger Rates up to z $\sim$ 3 using a Bayesian Deep Learning Model $-$ A Major-Merger classifier using IllustrisTNG Simulation data
• Major Merging History in CANDELS. I. Evolution of the Incidence of Massive Galaxy-Galaxy Pairs from z=3 to z~0
• Galaxy And Mass Assembly (GAMA): The mechanisms for quiescent galaxy formation at $z<1$
• Convolutional neural network identification of galaxy post-mergers in UNIONS using IllustrisTNG
• pyFIT3D and pyPipe3D -- The new version of the Integral Field Spectroscopy data analysis pipeline
• An EAGLE's View of Ex-situ Galaxy Growth
• Wet Compaction to a Blue Nugget: a Critical Phase in Galaxy Evolution
• AstroCLIP: A Cross-Modal Foundation Model for Galaxies
• The stellar halos of ETGs in the IllustrisTNG simulations: II. Accretion, merger history, and dark halo connection
• A Self-Calibrating Halo-Based Group Finder: Application to SDSS
• A direct measurement of galaxy major and minor merger rates and stellar mass accretion histories at $z<3$ using galaxy pairs in the REFINE survey
• The ALHAMBRA survey: Accurate merger fractions by PDF analysis of photometric close pairs
• ERGO-ML I: Inferring the assembly histories of IllustrisTNG galaxies from integral observable properties via invertible neural networks
• Mass of the dynamically hot inner stellar halo predicts the ancient accreted stellar mass
• Probabilistic Mass Mapping with Neural Score Estimation
• The origin of bulges and discs in the CALIFA survey: I. Morphological evolution
• Accreted or Not Accreted? The Fraction of Accreted Mass in Galaxies from Simulations and Observations
• The Contribution of In-situ and Ex-situ Star Formation in Early-Type Galaxies: MaNGA versus IllustrisTNG
• The Fornax3D project: discovery of ancient massive merger events in the Fornax cluster galaxies NGC 1380 and NGC 1427
• Relating the Diverse Merger Histories and Satellite Populations of Nearby Galaxies
• MaNGIA: 10,000 mock galaxies for stellar population analysis
• Beyond Gaussian Noise: A Generalized Approach to Likelihood Analysis with non-Gaussian Noise
• Mapping Accreted Stars in Early-Type Galaxies Across the Mass-Size Plane
• Galaxy merger challenge: A comparison study between machine learning-based detection methods
• Baryonic properties of nearby galaxies across the stellar-to-total dynamical mass relation
• The Origin of Stars in the Inner 500 Parsecs in TNG50 Galaxies
• ERGO-ML: Towards a robust machine learning model for inferring the fraction of accreted stars in galaxies from integral-field spectroscopic maps
• Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
• Galaxy assembly bias in the stellar-to-halo mass relation for red central galaxies from SDSS
• The diverse physical origins of stars in the dynamically hot bulge: CALIFA vs. IllustrisTNG
• Radio-astronomical Image Reconstruction with Conditional Denoising Diffusion Model
• Determining the time before or after a galaxy merger event
• Robust machine learning model of inferring the ex-situ stellar fraction of galaxies from photometric data

Cited by in corpus (1)

• COSMOS-Web: Galaxy Size and Surface Brightness Evolution at Rest-Frame 1.22 $\mu$m Since $z=3$