LL
L. Leuzzi
astro-ph.COastro-ph.GAastro-ph.IMcs.CV
On Valency
published · living versionsW_3sjxn36v·v1 · currentpublished
Euclid Quick Data Release (Q1). The metallicity of the intracluster light
with Euclid Collaboration, J. B. Golden-Marx, N. A. Hatch, S. P. Bamford +318
1 version
Preprints & journals
29 papers in the corpus · 2023–2026Observation-driven simulations of strong lensing galaxy clusters2609.07840v1 · L. Leuzzi, M. Meneghetti, A. Adam et al.2026 · 0 citationsarXiv
Deep Learning galaxy cluster's structural parameters from Weak Lensing observations2605.00105v2 · M. Fogliardi, M. Meneghetti, C. Giocoli et al.2026 · 0 citationsarXiv
Euclid preparation. XCV. Cosmology Likelihood for Observables in Euclid (CLOE). 2. Code implementation2603.22475v2 · S. Joudaki, V. Pettorino, L. Blot et al.2026 · 5 citationsarXiv
Euclid preparation. 3D reconstruction of the cosmic web with simulated Euclid Deep spectroscopic samples2601.10709v1 · K. Kraljic, C. Laigle, M. Balogh et al.2026 · 0 citationsarXiv
Euclid preparation. XCII. Controlling angular systematics in the Euclid spectroscopic galaxy sample2511.20856v2 · P. Monaco, M. Y. Elkhashab, B. R. Granett et al.2025 · 0 citationsarXiv
Euclid preparation: LXXXVII. Non-Gaussianity of 2-point statistics likelihood: Precise analysis of the matter power spectrum distribution2511.08266v3 · J. Bel, S. Gouyou Beauchamps, P. Baratta et al.2025 · 0 citationsarXiv
Euclid Quick Data Release (Q1). Quenching precedes bulge formation in dense environments but follows it in the field2511.02964v2 · F. Gentile, E. Daddi, D. Elbaz et al.2025 · 0 citationsarXiv
Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks2511.03064v2 · L. Bazzanini, G. Angora, P. Bergamini et al.2025 · 1 citationarXiv
Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 6: Impact of systematic uncertainties on the cosmological analysis2510.10021v1 · L. Blot, K. Tanidis, G. Canas-Herrera et al.2025 · 0 citationsarXiv
Euclid preparation XCVII. Cosmology Likelihood for Observables in Euclid (CLOE). 4: Validation and performance2510.09141v2 · M. Martinelli, A. Pezzotta, D. Sciotti et al.2025 · 2 citationsarXiv
Euclid preparation. XCVIII. Cosmology Likelihood for Observables in Euclid (CLOE). 5: Extensions beyond the standard modelling of theoretical probes and systematic effects2510.09147v2 · L. W. K. Goh, A. Nouri-Zonoz, S. Pamuk et al.2025 · 0 citationsarXiv
Euclid preparation. XCVI. Cosmology Likelihood for Observables in Euclid (CLOE). 3. Inference and Forecasts2510.09153v2 · G. Canas-Herrera, L. W. K. Goh, L. Blot et al.2025 · 0 citationsarXiv
Euclid preparation LXXIX. Using mock low surface brightness dwarf galaxies to probe Euclid Wide Survey detection capabilities2509.13163v2 · M. Urbano, P.-A. Duc, M. Poulain et al.2025 · 0 citationsarXiv
Euclid preparation. Simulating thousands of Euclid spectroscopic skies2507.12116v3 · P. Monaco, G. Parimbelli, M. Y. Elkhashab et al.2025 · 7 citationsA&A 704, A306 (2025)
Euclid preparation. LXXXIX. Accurate and precise data-driven angular power spectrum covariances2506.09118v2 · K. Naidoo, J. Ruiz-Zapatero, N. Tessore et al.2025 · 1 citationA&A 708, A167 (2026)
Euclid preparation. The impact of redshift interlopers on the two-point correlation function analysis2505.04688v2 · I. Risso, A. Veropalumbo, E. Branchini et al.2025 · 0 citationsA&A 707, A233 (2026)
Euclid Quick Data Release (Q1): The evolution of the passive-density and morphology-density relations between and 2503.15313v2 · C. Cleland, S. Mei, G. De Lucia et al.2025 · 4 citationsarXiv
Euclid Quick Data Release (Q1). A first view of the star-forming main sequence in the Euclid Deep Fields2503.15314v3 · A. Enia, L. Pozzetti, M. Bolzonella et al.2025 · 0 citationsarXiv
Euclid Quick Data Release (Q1). A probabilistic classification of quenched galaxies2503.15315v3 · P. Corcho-Caballero, Y. Ascasibar, G. Verdoes Kleijn et al.2025 · 4 citationsarXiv
Euclid Quick Data Release (Q1). First Euclid statistical study of galaxy mergers and their connection to active galactic nuclei2503.15317v2 · A. La Marca, L. Wang, B. Margalef-Bentabol et al.2025 · 8 citationsarXiv
Euclid Quick Data Release (Q1). Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images2503.15321v3 · G. Stevens, S. Fotopoulou, M. N. Bremer et al.2025 · 1 citationarXiv
Euclid Quick Data Release (Q1). An investigation of optically faint, red objects in the Euclid Deep Fields2503.15322v1 · G. Girardi, G. Rodighiero, L. Bisigello et al.2025 · 0 citationsarXiv
Euclid Quick Data Release (Q1). Extending the quest for little red dots to z<42503.15323v2 · L. Bisigello, G. Rodighiero, S. Fotopoulou et al.2025 · 11 citationsarXiv
Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine C: Finding lenses with machine learning2503.15326v2 · N. E. P. Lines, T. E. Collett, M. Walmsley et al.2025 · 14 citationsarXiv
Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E -- Ensemble classification of strong gravitational lenses: lessons for Data Release 12503.15328v1 · P. Holloway, A. Verma, M. Walmsley et al.2025 · 2 citationsarXiv
Euclid Quick Data Release (Q1). LEMON -- Lens Modelling with Neural networks. Automated and fast modelling of Euclid gravitational lenses with a singular isothermal ellipsoid mass profile2503.15329v2 · V. Busillo, C. Tortora, R. B. Metcalf et al.2025 · 1 citationarXiv
Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters2503.15330v1 · P. Bergamini, M. Meneghetti, A. Acebron et al.2025 · 2 citationsarXiv
Euclid Quick Data Release (Q1). The role of cosmic connectivity in shaping galaxy clusters2503.15332v2 · C. Gouin, C. Laigle, F. Sarron et al.2025 · 1 citationarXiv
Euclid Preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events2307.08736v2 · L. Leuzzi, M. Meneghetti, G. Angora et al.2023 · 0 citationsAstronomy & Astrophysics,2024, 681, A68
Career total: 99 works. 29 are in this corpus.
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