arXiv subjects

M. Parente

Publications and source records attributed to M. Parente.

3 recordsLinked to original sources

arXiv2025

The observed total star formation rate function up to z \sim 6: complementary UV and IR contributions and comparison with state-of-the-art galaxy formation models

We investigate how the obscured IR-derived and the dust-corrected UV star formation rate functions (SFRFs) compare with each other, and with predictions from state-of-the-art theoretical models of galaxy formation and evolution. We derive the IR-SFRF from the ALMA A$^3$COSMOS survey, by converting the IR luminosity functions (IR-LFs) into SFRF after correcting for AGN contribution. Similarly, we obtain the UV SFRFs from literature UV LFs, corrected for dust-extinction. First, we fit the two SFRFs independently via a MCMC approach, then we combine them to obtain the first estimate of the total SFRF out to $z \sim 6$. Finally, we compare this SFRF with the predictions of a set of theoretical models. We derived the UV (dust-extinction corrected, from literature UV-LFs) and IR SFRFs (from Herschel and ALMA IR-LFs) at $0.5 < z < 6$ , finding that they are mostly complementary, covering different ranges in star formation rate (SFR$ < 10-100$ M$_{\odot}$yr$^{-1}$ for the UV-corrected and SFR$ > 100$ M$_{\odot}$yr$^{-1}$ for the IR). From the comparison of the total SFRF with model predictions we find an overall good agreement at $z < 2.5$, with increasing difference at higher redshifts, with all models missing the galaxies that are forming stars with the highest SFRs. We finally obtained the UV (dust-corrected), IR and total star formation rate densities (SFRDs), finding that there are no redshift ranges where UV and IR alone are able to reproduce the whole total SFRD.

astro-ph.GA↗

arXiv2024

A$^3$COSMOS: the dust mass function and dust mass density at $0.5<z<6$

Context. Although dust in galaxies represents only a few percent of the total baryonic mass, it plays a crucial role in the physical processes occurring in galaxies. Studying the dust content of galaxies, particularly at high$-z$, is therefore crucial to understand the link between dust production, obscured star formation and the build-up of galaxy stellar mass. Aims. To study the dust properties (mass and temperature) of the largest Atacama Large Millimeter/submillimeter Array (ALMA)-selected sample of star-forming galaxies available from the archive (A$^3$COSMOS) and derive the dust mass function and dust mass density of galaxies from $z=0.5\,-\,6$. Methods. We performed spectral energy distribution (SED) fitting with the CIGALE code to constrain the dust mass and temperature of the A$^3$COSMOS galaxy sample, thanks to the UV-to-near-infrared photometric coverage of each galaxies combined with the ALMA (and Herschel when available) coverage of the Rayleigh-Jeans tail of their dust-continuum emission. We then computed and fitted the dust mass function by combining the A$^3$COSMOS and state-of-the-art {\it Herschel} samples, in order to obtain the best estimate of the integrated dust mass density up to $z \sim 6$. Results. Galaxies in \a3 have dust masses between $\sim 10^8$ and $\sim 10^{9.5}$ M$_{\odot}$. From the SED fitting, we were also able to derive a dust temperature, finding that the distribution of the dust temperature peaks at $\sim 30-35$K. The dust mass function at $z=0.5\,-\,6$ evolves with an increase of $M^*$ and decrease of the number density ($\Phi ^*$) and is in good agreement with literature estimates. The dust mass density shows a smooth decrease in its evolution from $z \sim 0.5$ to $z \sim 6$, which is steeper than what is found by models at $z \gtrsim 2$.

astro-ph.GA↗

arXiv2005

Various Solutions to the Firing Squad Synchronization Problems

We present different classes of solutions to the Firing Squad Synchronization Problem on networks of different shapes. The nodes are finite state processors that work at unison discrete steps. The networks considered are the line, the ring and the square. For all of these models we have considered one and two-way communication modes and also constrained the quantity of information that adjacent processors can exchange each step. We are given a particular time expressed as a function of the number of nodes of the network, $f(n)$ and present synchronization algorithms in time $n^2$, $n \log n$, $n\sqrt n$, $2^n$. The solutions are presented as {\em signals} that are used as building blocks to compose new solutions for all times expressed by polynomials with nonnegative coefficients.

cs.DS↗