arXiv subjects

Lucas Valenzuela

Publications and source records attributed to Lucas Valenzuela.

5 recordsLinked to original sources

arXiv2026

Extragalactic Planetary Nebulae (xPNe). Determining Distances out to 100 Mpc and the Renaissance of the PN Luminosity Function Method

The discrepancy of the Hubble parameter H0 as measured from the cosmic microwave background versus that found from traditional distance ladder measurements has produced considerable discussion about the need for another force in cosmology. However the significance of the discrepancy depends on understanding the systematic associated with crowding, metallicity effects, and extinction of the stellar tracers. Thus additional precision distance indicators in the local universe are desperately needed for investigating the H0 tension. The analysis of MUSE archival data makes the case that the Planetary Nebula Luminosity Function (PNLF) has become such an indicator, as the method can reach distances comparable to HST distances of Cepheid at a fraction of a cost, in terms of telescope time and ground-based. With new wide-field spectroscopic facilities it becomes possible to measure distances to early-type galaxies (ETGs) using the PNLF out to 100 Mpc distance, achieving a precise estimate for the H0 value which is independent of the Type Ia supernova calibration, with only single-epoch measurements.

astro-ph.GA↗

arXiv2026

Extragalactic Planetary Nebulae (xPNe). Chemical evolution and assembly histories of nearby galaxies using Oxygen and Argon abundances. From the local universe to cosmic dawn

How galaxies formed and evolved in the expanding Universe is the main science goal of Near-Field Cosmology research. Studies of the properties of galaxies' resolved stars open a widow on their ancient galactic components, probing star formation during epochs more than 10 billion years ago. Extragalactic Planetary Nebulae (xPNe) can help decipher the signatures of mergers and interactions persisting over many dynamical times by tracing elemental abundances coupled with their kinematics and spatial distributions. With new facilities, reaching higher angular resolution, area coverage and sensitivity, one can use xPNe to map Oxygen and Argon element abundances, in addition to their kinematics, to extend the Galactic Archeology investigation to the oldest stellar aggregates in our Local Universe.

astro-ph.IM↗

arXiv2026

Extragalactic planetary nebulae -- tracers of kinematics and stellar populations out to 100 Mpc

Extragalactic planetary nebulae (xPNe) in galaxies beyond the Local Universe serve as discrete tracers for studying the element abundances and kinematics of galaxies covering a wide range of morphologies and masses at a variety of angular distances, from the centre well out into their haloes. They are direct stellar probes to identify the galaxy progenitors of haloes and the intracluster light. Even with new facilities, reaching higher angular resolution and sensitivity, xPNe are the only stellar tracers that can be directly and singularly detected and characterised out to 100 Mpc distance, making them crucial for tracing halo and intracluster light assembly. New wide-field spectroscopic instruments at 10+meter-class telescopes will allow the unprecedented characterisation of xPN populations from galaxy centres to their diffuse outskirts. Panoramic integral-field spectroscopy will enable the simultaneous study of xPN and stellar population properties, establishing their use as age- and metallicity-tracers while also improving post-AGB stellar evolution models.

astro-ph.GA↗

arXiv2025

B-Call: Integrating Ideological Position and Political Cohesion in Legislative Voting Models

This paper combines two significant areas of political science research: measuring individual ideological position and cohesion. Although both approaches help analyze legislative behaviors, no unified model currently integrates these dimensions. To fill this gap, the paper proposes a methodology called B-Call that combines ideological positioning with voting cohesion, treating votes as random variables. The model is empirically validated using roll-call data from the United States, Brazil, and Chile legislatures, which represent diverse legislative dynamics. The analysis aims to capture the complexities of voting and legislative behaviors, resulting in a two-dimensional indicator. This study addresses gaps in current legislative voting models, particularly in contexts with limited party control.

cs.SI↗

arXiv2018

Unsupervised Classification of Variable Stars

During the last ten years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric datasets where objects are represented as light curves. Classifiers require training sets to learn the underlying patterns that allow the separation among classes. Unfortunately, building training sets is an expensive process that demands a lot of human efforts. Every time data comes from new surveys; the only available training instances are the ones that have a cross-match with previously labelled objects, consequently generating insufficient training sets compared with the large amounts of unlabelled sources. In this work, we present an algorithm that performs unsupervised classification of variable stars, relying only on the similarity among light curves. We tackle the unsupervised classification problem by proposing an untraditional approach. Instead of trying to match classes of stars with clusters found by a clustering algorithm, we propose a query based method where astronomers can find groups of variable stars ranked by similarity. We also develop a fast similarity function specific for light curves, based on a novel data structure that allows scaling the search over the entire dataset of unlabelled objects. Experiments show that our unsupervised model achieves high accuracy in the classification of different types of variable stars and that the proposed algorithm scales up to massive amounts of light curves.

astro-ph.IM↗