arXiv subjects

Marta González

Publications and source records attributed to Marta González.

7 recordsLinked to original sources

arXiv2026

S2D2: Small-scale Significant substructure DBSCAN Detection II. Tracing episodes and gradients of star formation activity

We provide the community with a homogeneous catalogue of small, significant substructures (henceforth NESTs) extracted from the spatial distribution of Young Stellar Objects (YSOs) in a large, consistent sample of star-forming regions. The catalog allows us to explore the relevance of small scale spatial substructure and discuss the interpretation of NESTs as tracers of star formation activity and remnants of the star formation process. We apply our procedure to consistent catalogues of YSOs to obtain NESTs in a sample of star-forming regions. We apply a photometric classification scheme to obtain the evolutionary stage of YSOs and statistically explore the distribution of class 0/I objects as a proxy of recent star formation activity. The region sample is diverse (in distance, size, structure, and global evolutionary stage), and we consequently find different structural properties and star formation histories. Most NESTs in regions with high recent star formation activity show even higher levels of activity. Moreover, the proportion of NESTs with higher activity than the region average increases with the global level of activity of the region. In approximately half of the regions we also find significant spans in the evolutionary stages of the NESTs, consistent with gradients and episodes of star formation. The combination of NESTs with a statistical exploration of the star formation history within each region provides robust and powerful insights into the star formation process. Our results support the role of NESTs as pristine remnants of star formation in highly active regions,stressing the role of fragmentation. The combination of small structures with large scale spatio-evolutionary patterns suggests hyerarchical, prolonged, dynamic, and complex star formation scenarios.

astro-ph.GA↗

arXiv2024

A stochastic and analytical model of hierarchical fragmentation: The fragmentation of gas structures into young stellar objects in the interstellar medium

Molecular clouds are the most important incubators of young stars clustered in various stellar structures whose spatial extension can vary from a few AU to several thousand AU. Although the reality of these stellar systems has been established, the physical origin of their multiplicity remains an open question. Our aim was to characterise these stellar groups at the onset of their formation by quantifying both the number of stars they contain and their mass using a hierarchical fragmentation model of the natal molecular cloud. We developed a stochastic and predictive model that reconciles the continuous multi-scale structure of a fragmenting molecular cloud with the discrete nature of the stars that are the products of this fragmentation. This model was implemented within a gravo-turbulent fragmentation framework to analytically follow the fragmentation properties along spatial scales using an isothermal and adiabatic equations of state (EOSs). Using an adiabatic EOS we determined a characteristic spatial scale where further fragmentation is prevented, around a few tens of AU. We show that fragmentation is a self-regulated process as fragments tend to become marginally unstable following a $M \propto R$ Bonnor-Ebert-like mass-size profile. Supersonic turbulent fragmentation structures the cloud down to $R \approx 0.1$ pc, and gradually turns into a less productive Jeans-type fragmentation under subsonic conditions so hierarchical fragmentation is a scale dependant process. Our work suggests that pre-stellar objects resulting from gas fragmentation, have to progressively increase their accretion rate in order to form stars. A hierarchical fragmentation scenario is compatible with both the multiplicity of stellar systems identified in Taurus and the multi-scale structure extracted within NGC 2264 molecular cloud.

astro-ph.GA↗

arXiv2022

Topography of the Young Galactic Disk: Spatial and Kinematic Patterns of the Clustered Star Formation in the Solar Neighborhood

The accuracy in determining the spatial-kinematical parameters of open clusters makes them ideal tracers of the Galactic structure. Young open clusters (YOCs) are the main representative of the clustered star formation mode, which identifies how most of the stars in the Galaxy form. We apply the Kriging technique to a sample of Gaia YOCs within a 3.5 kpc radius around the Sun and log(age) $\leq$ 7.5, age in years, to obtain the $Z(X,Y)$ and $V_Z(X,Y)$ maps. The previous work by Alfaro et al. (1991) showed that Kriging can provide reliable results even with small data samples ($N \sim 100$). We approach the 3D spatial and vertical velocity field structure of the Galactic disk defined by YOCs and analyze the hierarchy of the stellar cluster formation, which shows a rich hierarchical structure, displaying complexes embedded within each other. We discuss the fundamental characteristics of the methodology used to perform the mapping and point out the main results obtained in phenomenological terms. Both the 3D spatial distribution and the vertical velocity field reveal a complex disk structure with a high degree of substructures. Their analysis provides clues about the main physical mechanisms that shape the phase space of the clustered star formation in this Galactic area. Warp, corrugations, and high local deviations in $Z$ and $V_Z$, appear intimately connected in a single but intricate scenario.

astro-ph.GA↗

arXiv2022

Influence of protostellar jets and HII regions on the formation and evolution of stellar clusters

Context. Understanding the conditions in which stars and stellar clusters form is of great importance. In particular the role that stellar feedback may have is still hampered by large uncertainties. Aims. We investigate the role played by ionising radiation and protostellar outflows during the formation and evolution of a stellar cluster. To self-consistently take into account gas accretion, we start with clumps of tens of parsecs in size. Methods. Using an adaptive mesh refinement code, we run magneto-hydrodynamical numerical simulations aiming at describing the collapse of massive clumps with either no stellar feedback or taking into account ionising radiation and/or protostellar jets. Results. Stellar feedback substantially modifies the protostellar cluster properties, in several ways. We confirm that protostellar outflows reduce the star formation rate by a factor of a few, although the outflows do not stop accretion and likely enough do not modify the final cluster mass. On the other hand, ionising radiation, once sufficiently massive stars have formed, efficiently expels the remaining gas and reduces the final cluster mass by a factor of several. We found that while HII radiation and jets barely change the distribution of high density gas, the latter increases, at a few places, the dense gas velocity dispersion again by a factor of several. As we are starting from a relatively large scale, we found that the clusters whose mass and size are respectively on the order of a few 1000 M and a fraction of parsec, present a significant level of rotation. Moreover we found that the sink particles which mimic the stars themselves, tend to have rotation axis aligned with the cluster large scale rotation. Finally, computing the classical Q parameter used to quantify stellar cluster structure, we infer that when jets are included in the calculation, [...]

astro-ph.GA↗

arXiv2021

The Spatial Evolution of Young Massive Clusters III. Effect of the Gaia Filter on 2D Spatial Distribution Studies

[Context.] Gaia is limited in the optical down to G~21 mag so it is essential to understand the biases introduced by a magnitude-limited sample on spatial distribution studies. [Aims.] We ascertain how sample incompleteness in Gaia observations of young clusters affects the local spatial analysis tool INDICATE and subsequently the perceived spatial properties of these clusters. [Methods.] We created a mock Gaia cluster catalogue from a synthetic dataset using the observation generating tool MYOSOTIS. The effect of cluster distance, uniform and variable extinction, binary fraction, population masking by the point spread function wings of high-mass members, and contrast sensitivity limits on the trends identified by INDICATE are explored. A comparison of the typical index values derived by INDICATE for members of the synthetic dataset and their corresponding mock Gaia catalogue observations is made to identify any significant changes. [Results.] We typically find only small variations in the pre- and post-observation index values of cluster populations, which can increase as a function of incompleteness percentage and binarity. No significant strengthening, or false signatures, of stellar concentrations are found but real signatures may be diluted. Conclusions drawn about the spatial behaviour of Gaia-observed cluster populations that are, and are not, associated with their natal nebulosity are reliable for most clusters but the perceived behaviours of individual members can change so INDICATE should be used as a measure of spatial behaviours between members as a function of their intrinsic properties (e.g. mass, age, object type), rather than to draw conclusions about any specific observed member. [Conclusions.] INDICATE is a robust spatial analysis tool to reliably study Gaia-observed young cluster populations within 1 kpc, up to a sample incompleteness of 83.3% and binarity of 50%.

astro-ph.GA↗

arXiv2020

S2D2: Small-scale Significant substructure DBSCAN Detection I. NESTs detection in 2D star-forming regions

The spatial and dynamical structure of star-forming regions can help provide insights on stellar formation patterns. The amount of data from current and upcoming surveys calls for robust and objective procedures to detect structure, so the results can be statistically analysed and different regions compared. We provide the community with a tool able to detect the small scale significant structure, above random expectation, in star-forming regions, which could be the imprint of the stellar formation process. The tool makes use of the one point correlation function and of nearest neighbour statistics to determine the parameters for the DBSCAN algorithm. The procedure successfully detects significant small scale substructures in heterogeneous regions, fulfilling the goals it was designed for, and providing very reliable structures. The analysis of regions close to complete spatial randomness ($Q \in [0.7,0.87]$) shows that, even when some structure is present and recovered, it is hardly distinguishable from spurious detection in homogeneous regions due to projection effects. Interpretation should thus be done with care. For concentrated regions, we detect a main structure surrounded by smaller ones, corresponding to the core plus some Poisson fluctuations around it. We argue that these structures do not correspond to the small compact regions we are looking for. In some realistic cases, a more complete hierarchical, multi-scale analysis would be needed to capture the complexity of the region. We have developed implementations of our procedure, and a catalogue of the NESTs (Nested Elementary STructures) detected by it in four star-forming regions (Taurus, IC 348, Upper Scorpius, and Carina), which are publicly available to the community. Implementations of the 3D, and up to 6D versions of the procedure including proper movements are in progress, and will be provided as future work.

astro-ph.GA↗

arXiv2015

Looking for phase-space structures in star-forming regions: An MST-based methodology

We present a method for analysing the phase space of star-forming regions. In particular we are searching for clumpy structures in the 3D subspace formed by two position coordinates and radial velocity. The aim of the method is the detection of kinematic segregated radial velocity groups, that is, radial velocity intervals whose associated stars are spatially concentrated. To this end we define a kinematic segregation index, $\tildeΛ$(RV), based on the Minimum Spanning Tree (MST) graph algorithm, which is estimated for a set of radial velocity intervals in the region. When $\tildeΛ$(RV) is significantly greater than 1 we consider that this bin represents a grouping in the phase space. We split a star-forming region into radial velocity bins and calculate the kinematic segregation index for each bin, and then we obtain the spectrum of kinematic groupings, which enables a quick visualization of the kinematic behaviour of the region under study. We carried out numerical models of different configurations in the subspace of the phase space formed by the coordinates and the radial velocity that various case studies illustrate. The analysis of the test cases demonstrates the potential of the new methodology for detecting different kind of groupings in phase space.

astro-ph.IM↗