<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Euclid |</title><link>https://tommasoronconi.github.io/tags/euclid/</link><atom:link href="https://tommasoronconi.github.io/tags/euclid/index.xml" rel="self" type="application/rss+xml"/><description>Euclid</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 29 Jul 2026 00:00:00 +0000</lastBuildDate><image><url>https://tommasoronconi.github.io/media/icon.svg</url><title>Euclid</title><link>https://tommasoronconi.github.io/tags/euclid/</link></image><item><title>The galaxy–halo connection</title><link>https://tommasoronconi.github.io/research/galaxy-halo-connection/</link><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><guid>https://tommasoronconi.github.io/research/galaxy-halo-connection/</guid><description>&lt;p&gt;A central axis of my work is the development of empirical models linking dark matter
haloes to galaxies, in order to generate realistic mock galaxy catalogues for &lt;strong&gt;SKAO&lt;/strong&gt;
and &lt;strong&gt;Euclid&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;As a major outcome of my Ph.D. thesis I created &lt;strong&gt;SCAMPy&lt;/strong&gt;, a hybrid C++/Python library
for &lt;em&gt;painting&lt;/em&gt; observed galaxy populations on top of the dark matter halo/sub-halo
hierarchy of N-body simulations. It implements the Sub-halo Clustering and Abundance
Matching scheme: a Halo Occupation Distribution prescription first selects which
sub-haloes host galaxies, then sub-halo abundance matching assigns observable properties
to each object. The method requires only the observed distribution of the target property
— a luminosity function, say — and the clustering statistics of the target population.
The result is a computationally efficient, fully data-driven way to produce mocks that
reproduce both the 1- and 2-point statistics of any observed sample, from high-redshift
Lyman-break galaxies to low-redshift radio sources. SCAMPy has since become a core
ingredient in the simulation pipelines used for SKAO preparatory science.&lt;/p&gt;
&lt;p&gt;During a research stay at SKAO Headquarters I also contributed to &lt;strong&gt;T-RECS&lt;/strong&gt;, a tool for
simulating radio sources in continuum and HI line, now widely used in the radio-cosmology
community for survey design and theoretical modelling.&lt;/p&gt;
&lt;p&gt;This line of work recently culminated in a comprehensive framework for constructing
full-sky empirical mock catalogues of the radio sky: a modular pipeline combining a
simulated dark-matter light-cone, built from the high-resolution DEMNUni N-body
simulations, with empirically sampled galaxy populations generated by T-RECS and assigned
to haloes via an extended version of SCAMPy. The resulting catalogues cover the full 4π
steradians down to redshift &lt;em&gt;z&lt;/em&gt; = 5 and place multiple radio populations on a common
light-cone: continuum-emitting AGN and star-forming galaxies alongside HI line-emitting
sources. No single existing approach had previously combined full-sky coverage, multiple
radio populations, empirical flexibility and modularity.&lt;/p&gt;
&lt;p&gt;I currently lead a European collaboration integrating these pipelines to enable joint
radio continuum and line studies. In this context I coordinated the &lt;strong&gt;HI Simulations
chapter&lt;/strong&gt; for the next edition of &lt;em&gt;Advancing Astrophysics with the SKA&lt;/em&gt; (AASKA II),
bringing together researchers from four continents to compile a comprehensive description
and comparison of the simulations available for studying post-reionization HI.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Currently:&lt;/strong&gt; extending the framework to incorporate multi-wavelength counterparts,
connecting radio populations to their optical, infrared and sub-mm emission for
cross-survey analyses combining SKAO with Euclid and other facilities. I am also
exploring reinforcement-learning approaches to extend the empirical models underlying the
galaxy–halo connection.&lt;/p&gt;
&lt;hr&gt;
&lt;p&gt;&lt;em&gt;Key papers:&lt;/em&gt;
·
·
&lt;/p&gt;
&lt;p&gt;&lt;em&gt;Software:&lt;/em&gt;
·
&lt;/p&gt;</description></item><item><title>Cosmic voids</title><link>https://tommasoronconi.github.io/research/cosmic-voids/</link><pubDate>Wed, 29 Jul 2026 00:00:00 +0000</pubDate><guid>https://tommasoronconi.github.io/research/cosmic-voids/</guid><description>&lt;p&gt;A major research theme has been the study of &lt;strong&gt;cosmic voids&lt;/strong&gt; — vast, under-dense regions
occupying most of the volume of the Universe. When I began working on my Master&amp;rsquo;s thesis,
the community had theoretically demonstrated that the statistical properties of these
structures could be exploited to constrain dark energy and test theories of gravity, but
the theoretical models describing the void size distribution consistently failed to
predict both simulated and observed data.&lt;/p&gt;
&lt;p&gt;My work has paved the way for the cosmological exploitation of the &lt;strong&gt;void size function&lt;/strong&gt;
when voids are identified in any distribution of tracers, including real data catalogues.
In Ronconi &amp;amp; Marulli (2017) we presented an algorithm that redefines void ridges and,
consequently, their radii; I implemented it inside &lt;strong&gt;CosmoBolognaLib&lt;/strong&gt;, a large set of
open-source numerical libraries for cosmological calculations.&lt;/p&gt;
&lt;p&gt;With this tool we then demonstrated that, as long as our specifications are accounted
for, the size function is a viable approach for studying cosmology with cosmic voids. The
result was further validated by its adoption as a fundamental tool in Key Projects within
the Euclid Collaboration, used to forecast the cosmological constraining power of void
statistics.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Currently:&lt;/strong&gt; I am working with members of the Euclid Collaboration on void statistics
in mock galaxy catalogues, and investigating a new theoretical model of the void
distribution based on stochastic differential equations, together with Andrea Lapi at
SISSA. A Ph.D. student has recently been selected to pursue this direction over the next
three years under our supervision.&lt;/p&gt;
&lt;hr&gt;
&lt;p&gt;&lt;em&gt;Key papers:&lt;/em&gt;
·
·
·
&lt;/p&gt;
&lt;p&gt;&lt;em&gt;Software:&lt;/em&gt; CosmoBolognaLib
&lt;/p&gt;</description></item></channel></rss>