arXiv subjects

Martina Torsello

Publications and source records attributed to Martina Torsello.

5 recordsLinked to original sources

arXiv2026

The ViSta method for optimized stacking of broadband interferometric data in the Fourier domain

We present the optimized version of ViSta, a visibility-domain stacking method that combines interferometric observations in the Fourier domain from radio to sub-millimeter wavelengths. By stacking visibilities directly and transforming them into the rest frame, ViSta enhances the signal, suppresses noise, and improves image reconstruction through extended uv-coverage. ViSta outperforms image stacking when individual sources are too faint to detect, achieving higher SNR in the low-signal and extended regime. This new optimized version features a C++/OpenMP kernel which replaces CASA demanding functions, enabling GPU acceleration while minimising memory usage and intermediate data products. The method is highly flexible, allowing stacking regardless of array configuration, spectral setup, or telescope. In the SKA era, where visibilities will not be routinely preserved, ViSta helps in assessing the information lost in the image-plane transition and in exploiting the vast amount of data still stored in interferometric archives.

astro-ph.IM↗

arXiv2026

Cosmography with DESI-DR1 Cosmic Chronometers: Direct H(z) measurements from Luminous Red Galaxy ages

Providing robust redshift estimates for almost 3 million luminous red galaxies (LRGs), the Dark Energy Spectroscopic Instrument (DESI) offers a unique opportunity to test the expansion rate of the Universe with independent approaches. We apply the cosmic chronometer method to derive new, independent constraints on the Hubble parameter at 0.3<z<1.2 from the differential age evolution of DESI LRGs. We select spectra applying spectroscopic cuts to ensure sample purity and remove contamination by star-forming objects, then build a robust sample of cosmic chronometers (CCs) by stacking to obtain stable, high signal-to-noise (S/N) spectra, which also serves as a democratic binning choice for the $t-z$ plane. Ages are estimated by measuring Lick indices on the stacked spectra and fitting them with a theoretical stellar population model. We obtain $t-z$ relations from which we derive $H(z)$ constraints via two independent approaches: a fit with a pivotal-redshift cosmography, and a direct estimate from the original CC method. The cosmographic fit yields posteriors for the kinematic parameters $\{H_{z_0}, q_{z_0}, j_{z_0}\}$ compatible with currently considered cosmologies, giving a precision-level estimate of $H(z)$. We provide the maximum-a-posteriori (MAP) $H(z)$ estimate, an array of the median confidence region in the $H-z$ plane, and its covariance matrix. We also leverage the redshift distributions of the $t-z$ relation for different velocity dispersion groups to obtain two independent local measurements using the discrete approximation $H(z) \approx -Δz/[Δt (1+z)]$; the one from the reddest envelope of CCs gives $H(z \approx 0.61) = 88.5^{+6.7}_{-12.6}$ (stat.) $\pm 8.1$ (syst.) km s$^{-1}$ Mpc$^{-1}$. Systematic uncertainties for both the cosmographic and discrete $H(z)$ measurements come from a comprehensive analysis of all methodological choices in the data treatment.

astro-ph.CO↗

arXiv2025

The ViSta method for stacking in the Fourier domain and its application to the dusty star-forming galaxies in the ALMA Science Archive

We present ViSta, a Visibility Stacking method to combine interferometric observations in the Fourier domain at radio to sub-millimeter wavelengths for galaxies. The goal of our method is to maximize the exploitation of available archival interferometric data. By stacking visibilities of galaxies with secure spectroscopic redshifts directly in the Fourier domain and transforming them into the rest-frame, we can enhance the stacked signal, suppress noise, and improve image reconstruction thanks to an extended coverage of the visibility domain. The ViSta method is highly flexible, allowing stacking of visibilities regardless of the array configuration or spectral setup. It is effective for both targeted sources and spurious detections offset from the phase center, whether unresolved or extended, within the field of view of the telescope. We validated the method using simulated interferometric datasets. For point-like sources, we can reconstruct the true emission with approximately 90% accuracy, obtaining similar results to classical image-plane stacking. In contrast, for faint and extended sources below the noise level, our method can provide a more accurate estimate of the signal compared to traditional image-based approaches. Finally, we applied ViSta to a sample of dusty star-forming galaxies (DSFGs) observed with the Atacama Large Millimeter/sub-millimeter Array (ALMA) to detect the CO(3-2) emission line. As for the simulated case, we demonstrated that our tool performs better than image-plane stacking when the signal from individual sources is no longer easily detectable, achieving higher SNR. Finally, we outline potential future applications of this stacking approach.

astro-ph.GA↗

arXiv2024

Astrochemistry of the molecular gas in Dusty Star-Forming Galaxies at the Cosmic Noon

FIR and submm observations have established the fundamental role of dust-obscured star formation in the assembly of stellar mass over the past 12 billion years. At z between 2 and 4, the bulk of star formation is enshrouded in dust, and dusty star forming galaxies (DSFGs) contain about half of the total stellar mass density. Star formation develops in dense molecular clouds, and is regulated by a complex interplay between all the ISM components that contribute to the energy budget of a galaxy: gas, dust, cosmic rays, interstellar electromagnetic fields, gravitational field, dark matter. Molecular gas is the actual link between star forming gas and its complex environment, providing by far the richest amount of information about the star formation process. However, molecular lines interpretation requires complex modeling of astrochemical networks, which regulate the molecular formation and establishes molecular abundances in a cloud, and a modeling of the physical conditions of the gas in which molecular energy levels become populated. This paper critically reviews the main astrochemical parameters needed to get predictions about molecular signals in DSFGs. We review the current knowledge and the open questions about the interstellar medium of DSFGs, outlying the key role of molecular gas as a tracer and shaper of the star formation process.

astro-ph.GA↗

arXiv2024

GalaPy, the highly optimised C++/Python spectral modelling tool for galaxies -- I. Library presentation and photometric fitting

Fostered by upcoming data from new generation observational campaigns, we are about to enter a new era for the study of how galaxies form and evolve. The unprecedented quantity of data that will be collected, from distances only marginally grasped up to now, will require analysis tools designed to target the specific physical peculiarities of the observed sources and handle extremely large datasets. One powerful method to investigate the complex astrophysical processes that govern the properties of galaxies is to model their observed spectral energy distribution (SED) at different stages of evolution and times throughout the history of the Universe. To address these challenges, we have developed GalaPy, a new library for modelling and fitting SEDs of galaxies from the X-ray to the radio band, as well as the evolution of their components and dust attenuation/reradiation. GalaPy incorporates both empirical and physically-motivated star formation histories, state-of-the-art single stellar population synthesis libraries, a two-component dust model for attenuation, an age-dependent energy conservation algorithm to compute dust reradiation, and additional sources of stellar continuum such as synchrotron, nebular/free-free emission and X-ray radiation from low and high mass binary stars. GalaPy has a hybrid implementation that combines the high performance of compiled C++ with the flexibility of Python, and exploits an object-oriented design. It generates models on the fly without relying on templates, and exploits fully Bayesian parameter space sampling. In this first work, we introduce the project and showcase the photometric SED fitting tools already available to users. The library is available on the Python Package Index (PyPI) and comes with extensive online documentation and tutorials.

astro-ph.GA↗