271 citations · 717 across the 19 of their papers we have counts for
25 papers · 1 filter
The 3D morphology of open clusters in the solar neighborhood III: Fractal dimension
Chang Qin, Xiaoying Pang, Mario Pasquato +2
We analyze the fractal dimension of open clusters using 3D spatial data from Gaia DR3 for 93 open clusters from Pang et al. (2024) and 127 open clusters from Hunt & Reffert (2024)…
A machine learning framework to generate star cluster realisations
George P. Prodan, Mario Pasquato, Giuliano Iorio +4
Context. Computational astronomy has reached the stage where running a gravitational N-body simulation of a stellar system, such as a Milky Way star cluster, is computationally fea…
Reconstructing Robust Background IFU spectra using Machine Learning
Carter Lee Rhea, Julie Hlavacek-Larrondo, Justine Giroux +6
In astronomy, spectroscopy consists of observing an astrophysical source and extracting its spectrum of electromagnetic radiation. Once extracted, a model is fit to the spectra to…
Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
L. Cavallo, L. Spina, G. Carraro +7
With the unprecedented increase of known star clusters, quick and modern tools are needed for their analysis. In this work, we develop an artificial neural network trained on synth…
Interpretable machine learning for finding intermediate-mass black holes
Mario Pasquato, Piero Trevisan, Abbas Askar +4
Definitive evidence that globular clusters (GCs) host intermediate-mass black holes (IMBHs) is elusive. Machine learning (ML) models trained on GC simulations can in principle pred…
Dynamics of intermediate mass black holes in globular clusters. Wander radius and anisotropy profiles
Pierfrancesco Di Cintio, Mario Pasquato, Luca Barbieri +2
We recently introduced a new method for simulating collisional gravitational N-body systems with approximately linear time scaling with , based on the Multi-Particle Collision (…