MAGNUS I: A MUSE-DEEP sample of early-type galaxies at intermediate redshift
(2025)
MAGNUS II: Rotational 91̽»¨ of massive early-type galaxies decreased over the past 7 billion years
(2025)
PowerBin: fast adaptive data binning with Centroidal Power Diagrams
Monthly Notices of the Royal Astronomical Society 91̽»¨ University Press 544:2 (2025) staf1726
Abstract:
Adaptive binning is a crucial step in the analysis of large astronomical data sets, such as those from integral-field spectroscopy, to ensure a sufficient signal-to-noise ratio () for reliable model fitting. However, the widely used Voronoi-binning method and its variants suffer from two key limitations: they scale poorly with data size, often as , creating a computational bottleneck for modern surveys, and they can produce undesirable non-convex or disconnected bins. I introduce PowerBin, a new algorithm that overcomes these issues. I frame the binning problem within the theory of optimal transport, for which the solution is a Centroidal Power Diagram (CPD), guaranteeing convex bins. Instead of formal CPD solvers, which are unstable with real data, I develop a fast and robust heuristic based on a physical analogy of packed soap bubbles. This method reliably enforces capacity constraints even for non-additive measures like with correlated noise. I also present a new bin-accretion algorithm with complexity, removing the previous bottleneck. The combined PowerBin algorithm scales as , making it about two orders of magnitude faster than previous methods on million-pixel data sets. I demonstrate its performance on a range of simulated and real data, showing it produces high-quality, convex tessellations with excellent uniformity. The public python implementation provides a fast, robust, and scalable tool for the analysis of modern astronomical data.High-order stellar kinematics in MaNGA integral-field spectroscopy survey: classification, stellar population, and the impact of galaxy bars and mergers
Monthly Notices of the Royal Astronomical Society 91̽»¨ University Press 544:1 (2025) 1038-1055
Abstract:
We extract with ppxf and analyse the high-order stellar kinematic moments (related to skewness) and (related to kurtosis) in a complete subsample of 2230 galaxies with well-sampled line-of-sight velocity distributions () from the final data release of 10 010 unique galaxies of the MaNGA survey. To reduce template mismatch, we created a stellar library based on MaStar. We used proxies for the specific angular momentum parameter () and ellipticity () to distinguish between fast and slow rotators. Using the Pearson correlation coefficient between spatially resolved and within the isophotes of 2.5 half-light radii (), we classified 1599 fast rotators into (i) 1073 galaxies showing a strong versus anticorrelation, indicative of normal rotating stellar discs as observed in earlier studies, and (ii) 526 galaxies exhibiting weak or no correlation between and . These galaxies are likely disturbed, showing signs of bars or merging. Further inspection revealed that 85 galaxies from the latter group contain an anticorrelated inner disc, with half of these inner discs composed of younger stellar populations, indicative of recent gas accretion and nuclear star formation. This catalogue presents measurements of high-order stellar kinematic moments, providing a basis for exploring their potential links with the kinematic structures of galaxies. We have made the newly extracted high-order kinematics publicly available for further studies on stellar dynamics and galaxy formation.An accurate measurement of the spectral resolution of the JWST Near Infrared Spectrograph
Astronomy & Astrophysics EDP Sciences 702 (2025) l12