arXiv subjects

Mario Gilberto Lattanzi

Publications and source records attributed to Mario Gilberto Lattanzi.

8 recordsLinked to original sources

arXiv2026

Combining astrometry with pulsar timing: the first joint analysis of very low frequency gravitational waves

The pHz to sub-nHz GW regime remains largely unexplored but is crucial for mapping the early inspiral stage of SMBHBs and probing early-Universe physics. Astrometry and pulsar timing offer orthogonal and deeply complementary secular observables to investigate this frequency band. We aim to present the first joint data analysis combining real astrometric proper motions with binary pulsar timing, to search for and constrain continuous gravitational waves (CWs) sourced by SMBHBs in the ultra-low-frequency regime ($10^{-12} \le f_{GW} \le10^{-9} Hz$). We employ a Bayesian model selection and upper limit estimation framework to combine apparent proper motion displacements of $\sim 1.5 \times 10^6$ quasars from the Gaia CRF3 catalog with the line-of-sight orbital period derivatives ($\dot{P}_b$) of 11 high-precision binary pulsars. To prevent spurious detections, we heavily model instrumental and astrophysical systematics: we propagate the Galactic potential uncertainty for pulsars via Monte Carlo simulations and perform a Vector Spherical Harmonics (VSH) decomposition up to the octupole order (l=3) for quasars. We find no statistically significant evidence for a CWs signal in the joint analysis ($\ln B_{joint} = -0.42 \pm 0.03$). In the absence of detection, we set the tightest constraints to date on CW strain in the pHz band, yielding a 95% upper limit of $h_0\le6.4x10^{-11}$ at a reference frequency of $f_{ref} = 4 \times 10^{-10}$ Hz. The combined dataset achieves full sky coverage and improves single-dataset upper limits by 20%-30%. Combining orthogonal observables successfully breaks spatial degeneracies intrinsic to isolated searches. Furthermore, forecasts from inj.-rec. indicate that with the extended temporal baseline and reduced uncertainties of the upcoming Gaia DR4, this joint framework is poised to break the $h_0 < 10^{-11}$ upper limit barrier for sub-nHz CWs.

astro-ph.IM↗

arXiv2025

The Problem of the Global Astrometric Sphere Reconstruction in Astrometry -- Issues and Approaches

In this contribution we give a brief account of the problem of the Global Astrometric Sphere Reconstruction in Astrometry, with particular reference to the Gaia and Gaia-like astrometric missions, namely those adopting a scanning strategy with observations in TDI mode. We sketch the design of the Gaia mission, the mathematical modelling that comes naturally from its observing strategy, and how the problem of the global sphere reconstruction translates into that of the solution of large, sparse, and overdetermined system of linearized equations. After a short description of the two approaches to this problem implemented in the Gaia data reduction pipelines, we list the main known problems of the current approaches, with specific reference to the calibration and the correlation issues. Finally, we suggest how an arc-based solution could help to alleviate some of these problems, how it would be possible to devise a mathematical model for such an observable despite the TDI observing mode, and the main difficulty that a parallel implementation of this model would have to solve.

astro-ph.IM↗

arXiv2025

The Gaia AVU-GSR solver: a CPU + GPU parallel code toward Exascale systems

The solver module of the Astrometric Verification Unit - Global Sphere Reconstruction (AVU-GSR) pipeline aims to find the astrometric parameters of $\sim$$10^8$ stars in the Milky Way, besides the attitude and instrumental settings of the Gaia satellite and the parametrized post Newtonian parameter $γ$ with a resolution of 10-100 micro-arcseconds. To perform this task, the code solves a system of linear equations with the iterative Least Squares (LSQR) algorithm, where the coefficient matrix is large (10-50 TB) and sparse and the iterations stop when convergence is reached in the least squares sense. The two matrix-by-vector products performed at each LSQR step were GPU-ported, firstly with OpenACC and then with CUDA, resulting in a $\sim$$1.5$x and $\sim$$14$x speedup, respectively, over an original code version entirely parallelized on the CPU with MPI + OpenMP. The CUDA code was further optimized and then ported with programming frameworks portable across different GPU architectures, obtaining a further $\sim$$2$x acceleration factor. One critical section of the code consists in the computation of covariances, whose total number is $N_{\rm unk} \times (N_{\rm unk} - 1)/2$ and occupy $\sim$1 EB, being $N_{\rm unk}$$\sim$$5 \times 10^8$ the total number of unknowns. This "Big Data" issue cannot be faced with standard approaches: we defined an I/O-based pipeline made of two concurrently launched jobs, where one job, i.e., the LSQR, writes the files and the second job reads them, iteratively computes the covariances and deletes them. The pipeline does not present significant bottlenecks until a number of covariances elements equal to $\sim$$8 \times 10^6$. The code currently runs in production on Leonardo CINECA infrastructure.

astro-ph.IM↗

arXiv2024

Exploring Milky Way rotation curves with Gaia DR3: a comparison between $Λ$CDM, MOND, and General Relativistic approaches

With the release of Gaia DR3, we extend the comparison between dynamical models for the Milky Way rotation curve initiated in the previous work. Utilising astrometric and spectro-photometric data for 719143 young disc stars within $|z|<1$ kpc and up to $R \simeq 19$ kpc, we investigate the accuracy of MOND and $Λ$CDM frameworks in addition to previously studied models, such as the classical one with a Navarro-Frenk-White dark matter halo and a general relativistic model. We find that all models, including MOND and $Λ$CDM, are statistically equivalent in representing the observed rotational velocities. However, $Λ$CDM, characterized by an Einasto density profile and cosmological constraints on its parameters, assigns more dark matter than the model featuring a Navarro-Frenk-White profile, with the virial mass estimated at $1.5\text{-}2.5 \times 10^{12} \, {\rm M}_{\odot}$ - a value significantly higher than recent literature estimates. Beyond $10\text{-}15$ kpc, non-Newtonian/non-baryonic contributions to the rotation curve are found to become dominant for all models consistently. Our results suggest the need for further exploration into the role of General Relativity, dark matter, and alternative theories of gravitational dynamics in shaping Milky Way's rotation curve.

astro-ph.GA↗

arXiv2023

The MPI + CUDA Gaia AVU-GSR Parallel Solver Toward Next-generation Exascale Infrastructures

We ported to the GPU with CUDA the Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver developed for the ESA Gaia mission, by optimizing a previous OpenACC porting of this application. The code aims to find, with a [10,100]$μ$as precision, the astrometric parameters of $\sim$$10^8$ stars, the attitude and instrumental settings of the Gaia satellite, and the global parameter $γ$ of the parametrized Post-Newtonian formalism, by solving a system of linear equations, $A\times x=b$, with the LSQR iterative algorithm. The coefficient matrix $A$ of the final Gaia dataset is large, with $\sim$$10^{11} \times 10^8$ elements, and sparse, reaching a size of $\sim$10-100 TB, typical for the Big Data analysis, which requires an efficient parallelization to obtain scientific results in reasonable timescales. The speedup of the CUDA code over the original AVU-GSR solver, parallelized on the CPU with MPI+OpenMP, increases with the system size and the number of resources, reaching a maximum of $\sim$14x, >9x over the OpenACC application. This result is obtained by comparing the two codes on the CINECA cluster Marconi100, with 4 V100 GPUs per node. After verifying the agreement between the solutions of a set of systems with different sizes computed with the CUDA and the OpenMP codes and that the solutions showed the required precision, the CUDA code was put in production on Marconi100, essential for an optimal AVU-GSR pipeline and the successive Gaia Data Releases. This analysis represents a first step to understand the (pre-)Exascale behavior of a class of applications that follow the same structure of this code. In the next months, we plan to run this code on the pre-Exascale platform Leonardo of CINECA, with 4 next-generation A200 GPUs per node, toward a porting on this infrastructure, where we expect to obtain even higher performances.

astro-ph.IM↗

arXiv2022

The Gaia AVU-GSR parallel solver: preliminary studies of a LSQR-based application in perspective of exascale systems

The Gaia Astrometric Verification Unit-Global Sphere Reconstruction (AVU-GSR) Parallel Solver aims to find the astrometric parameters for $\sim$10$^8$ stars in the Milky Way, the attitude and the instrumental specifications of the Gaia satellite, and the global parameter $γ$ of the post Newtonian formalism. The code iteratively solves a system of linear equations, $\mathbf{A} \times \vec{x} = \vec{b}$, where the coefficient matrix $\mathbf{A}$ is large ($\sim$$10^{11} \times 10^8$ elements) and sparse. To solve this system of equations, the code exploits a hybrid implementation of the iterative PC-LSQR algorithm, where the computation related to different horizontal portions of the coefficient matrix is assigned to separate MPI processes. In the original code, each matrix portion is further parallelized over the OpenMP threads. To further improve the code performance, we ported the application to the GPU, replacing the OpenMP parallelization language with OpenACC. In this port, $\sim$95% of the data is copied from the host to the device at the beginning of the entire cycle of iterations, making the code $compute$ $bound$ rather than $data$$-$$transfer$ $bound$. The OpenACC code presents a speedup of $\sim$1.5 over the OpenMP version but further optimizations are in progress to obtain higher gains. The code runs on multiple GPUs and it was tested on the CINECA supercomputer Marconi100, in anticipation of a port to the pre-exascale system Leonardo, that will be installed at CINECA in 2022.

astro-ph.IM↗

arXiv2021

Progress on the Astrometric Gravitation Probe design

The Astrometric Gravitation Probe mission is a modern version of the 1919 Dyson-Eddington-Davidson experiment, based on a space-borne telescope with a permanent built-in eclipse, provided by a coronagraphic system. The expected improvement on experimental bounds to General Relativity and competing gravitation theories is by at least two orders of magnitude. The measurement principle is reviewed, in particular the principle of Fizeau-like combination of a set of individual inverted coronagraphs simultaneously feeding a common high resolution telescope. Also, the payload has a dual field of view property, in order to support simultaneous observations of stellar fields either very close, or far away, from the Sun, i.e. fields affected by either high or low light bending. We discuss a set of solutions introduced in the optical design to improve on technical feasibility and robustness of the optical performance against perturbations, in particular induced by manufacturing and alignment tolerances, and launch stresses.

astro-ph.IM↗

arXiv2015

The Ray Tracing Analytical Solution within the RAMOD framework. The case of a Gaia-like observer

This paper presents the analytical solution of the inverse ray tracing problem for photons emitted by a star and collected by an observer located in the gravitational field of the Solar System. This solution has been conceived to suit the accuracy achievable by the ESA Gaia satellite (launched on December 19, 2013) consistently with the measurement protocol in General relativity adopted within the RAMOD framework. Aim of this study is to provide a general relativistic tool for the science exploitation of such a revolutionary mission, whose main goal is to trace back star directions from within our local curved space-time, therefore providing a three-dimensional map of our Galaxy. The results are useful for a thorough comparison and cross-checking validation of what already exists in the field of Relativistic Astrometry. Moreover, the analytical solutions presented here can be extended to model other measurements that require the same order of accuracy expected for Gaia.

gr-qc↗