The Radio Spectral Energy Distribution and Star Formation Calibration in MIGHTEE-COSMOS Highly Star-forming Galaxies at 1.5 < z < 3.5

The Astrophysical Journal American Astronomical Society 989:1 (2025) 44

Authors:

Fatemeh Tabatabaei, Maryam Khademi, Matt J Jarvis, Russ Taylor, Imogen H Whittam, Fangxia An, Reihaneh Javadi, Eric J Murphy, Mattia Vaccari

Abstract:

Studying the radio spectral energy distribution (SED) of distant galaxies is essential for understanding their assembly and evolution over cosmic time. We present rest-frame radio SEDs of a sample of 160 star-forming galaxies at 1.5 < z < 3.5 in the Cosmic Evolution Survey field as part of the MeerKAT International GHz Tiered Extragalactic Exploration project. MeerKAT observations combined with archival Very Large Array and Giant Metrewave Radio Telescope data allow us to determine the integrated mid-radio (ν = 1–10 GHz) continuum (MRC) luminosity and magnetic field strength. A Bayesian method is used to model the SEDs and to separate the free–free and synchrotron emission. We also calibrate the star formation rate (SFR) in radio both directly through SED analysis and indirectly through the infrared–radio correlation (IRRC). With a mean value of αnt ≃ 0.7, the synchrotron spectral index flattens with both redshift and specific SFR, indicating that cosmic rays are more energetic in the early Universe due to higher star formation activity. The magnetic field strength increases with redshift, B ∝ (1 + z)(0.7±0.1), and SFR as B ∝ SFR0.3, suggesting a small-scale dynamo acting as its main amplification mechanism. Taking into account the evolution of the SEDs, the IRRC is redshift invariant, and it does not change with stellar mass at 1.5 < z < 3.5, although the correlation deviates from linearity. Similarly, we show that the SFR traced using the integrated MRC luminosity is redshift invariant.

Avoiding lensing bias in cosmic shear analysis

Monthly Notices of the Royal Astronomical Society 541:4 (2025) 3549-3560

Authors:

CAJ Duncan, ML Brown

Abstract:

We show, using the pseudo-Cl technique, how to estimate cosmic shear and galaxy–galaxy lensing power spectra that are insensitive to the effects of multiple sources of lensing bias including source-lens clustering, magnification bias, and obscuration effects. All of these effects are of significant concern for ongoing and near-future Stage-IV cosmic shear surveys. Their common attribute is that they all introduce a cosmological dependence into the selection of the galaxy shear sample. Here, we show how a simple adaptation of the pseudo-Cl method can help to suppress these biases to negligible levels in a model-independent way. Our approach is based on making pixelized maps of the shear field and then using a uniform weighting of those shear maps when extracting power spectra. To produce unbiased measurements, the weighting scheme must be independent of the cosmological signal, which makes the commonly used inverse-variance weighting scheme unsuitable for cosmic shear measurements. We demonstrate this explicitly. A frequently cited motivation for using inverse-variance weights is to minimize the errors on the resultant power spectra. We find that, for a Stage-IV-like survey configuration, this motivation is not compelling: the precision of power spectra recovered from uniform-weighted maps is only very slightly degraded compared to those recovered from an inverse-variance analysis, and we predict no degradation in cosmological parameter constraints. We suggest that other 2-point statistics, such as real-space correlation functions, can be rendered equally robust to these lensing biases by applying those estimators to pixelized shear maps using a uniform weighting scheme.

Euclid preparation

Astronomy & Astrophysics EDP Sciences 700 (2025) a78

Authors:

S de la Torre, F Marulli, E Keihänen, A Viitanen, M Viel, A Veropalumbo, E Branchini, D Tavagnacco, F Rizzo, J Valiviita, V Lindholm, V Allevato, G Parimbelli, E Sarpa, Z Ghaffari, A Amara, S Andreon, N Auricchio, C Baccigalupi, M Baldi, S Bardelli, A Basset, D Bonino, M Brescia, J Brinchmann, A Caillat, S Camera, V Capobianco, C Carbone, J Carretero, S Casas, FJ Castander, M Castellano, G Castignani, S Cavuoti, A Cimatti, C Colodro-Conde, G Congedo, CJ Conselice, L Conversi, Y Copin, F Courbin, HM Courtois, M Crocce, A Da Silva, H Degaudenzi, G De Lucia, AM Di Giorgio, J Dinis, F Dubath, CAJ Duncan, X Dupac, S Dusini, M Farina, S Farrens, F Faustini, S Ferriol, N Fourmanoit, M Frailis, E Franceschi, P Franzetti, M Fumana, S Galeotta, K George, W Gillard, B Gillis, C Giocoli, P Gómez-Alvarez, BR Granett, A Grazian, F Grupp, L Guzzo, SVH Haugan, W Holmes, F Hormuth, A Hornstrup, S Ilić, K Jahnke, M Jhabvala, B Joachimi, S Kermiche, A Kiessling, M Kilbinger, B Kubik, M Kunz, H Kurki-Suonio, S Ligori, PB Lilje, I Lloro, G Mainetti, D Maino, E Maiorano, O Mansutti, O Marggraf, K Markovic, M Martinelli, N Martinet, R Massey, S Maurogordato, E Medinaceli, S Mei, M Melchior, Y Mellier, M Meneghetti, E Merlin, G Meylan, M Moresco, B Morin, L Moscardini, E Munari, C Neissner, S-M Niemi, C Padilla, S Paltani, F Pasian, K Pedersen, WJ Percival, V Pettorino, S Pires, G Polenta, M Poncet, L Pozzetti, F Raison, A Renzi, J Rhodes, G Riccio, E Romelli, M Roncarelli, E Rossetti, R Saglia, Z Sakr, AG Sánchez, D Sapone, B Sartoris, P Schneider, T Schrabback, M Scodeggio, A Secroun, E Sefusatti, G Seidel, M Seiffert, S Serrano, C Sirignano, G Sirri, L Stanco, J Steinwagner, C Surace, P Tallada-Crespí, AN Taylor, I Tereno, R Toledo-Moreo, F Torradeflot, A Tsyganov, I Tutusaus, L Valenziano, T Vassallo, Y Wang, J Weller, A Zacchei, G Zamorani, E Zucca, A Biviano, M Bolzonella, E Bozzo, C Burigana, M Calabrese, D Di Ferdinando, JA Escartin Vigo, R Farinelli, F Finelli, L Gabarra, J Gracia-Carpio, S Matthew, N Mauri, A Mora, A Pezzotta, M Pöntinen, V Scottez, P Simon, A Spurio Mancini, M Tenti, M Wiesmann, Y Akrami, IT Andika, S Anselmi, M Archidiacono, F Atrio-Barandela, A Balaguera-Antolinez, D Bertacca, M Bethermin, A Blanchard, L Blot, H Böhringer, S Borgani, ML Brown, S Bruton, R Cabanac, A Calabro, B Camacho Quevedo, G Cañas-Herrera, A Cappi, F Caro, CS Carvalho, T Castro, KC Chambers, F Cogato, S Contarini, AR Cooray, O Cucciati, S Davini, F De Paolis, G Desprez, A Díaz-Sánchez, S Di Domizio, H Dole, S Escoffier, AG Ferrari, PG Ferreira, A Finoguenov, A Fontana, K Ganga, J García-Bellido, T Gasparetto, V Gautard, E Gaztanaga, F Giacomini, F Gianotti, G Gozaliasl, A Gregorio, M Guidi, CM Gutierrez, A Hall, S Hemmati, H Hildebrandt, J Hjorth, A Jimenez Muñoz, S Joudaki, JJE Kajava, Y Kang, V Kansal, D Karagiannis, CC Kirkpatrick, S Kruk, M Lattanzi, AMC Le Brun, S Lee, J Le Graet, L Legrand, M Lembo, J Lesgourgues, TI Liaudat, A Loureiro, J Macias-Perez, M Magliocchetti, F Mannucci, R Maoli, J Martín-Fleitas, CJAP Martins, L Maurin, RB Metcalf, M Miluzio, P Monaco, C Moretti, G Morgante, C Murray, S Nadathur, K Naidoo, A Navarro-Alsina, S Nesseris, K Paterson, L Patrizii, A Pisani, V Popa, D Potter, P Reimberg, I Risso, P-F Rocci, M Sahlén, A Schneider, M Schultheis, D Sciotti, E Sellentin, M Sereno, A Silvestri, LC Smith, K Tanidis, C Tao, N Tessore, G Testera, R Teyssier, S Toft, S Tosi, A Troja, M Tucci, C Valieri, D Vergani, G Verza, P Vielzeuf, NA Walton

Abstract:

The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of approximately 20–30 million H α -emitting galaxies up to a redshift of about 2. This ambitious project seeks to elucidate the nature of dark energy by mapping the three-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the three-dimensional two-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid dataset, which involves millions of galaxies. The key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including k -d tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the two-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission’s timeline, highlighting the software’s capability to handle large datasets efficiently.

MIGHTEE: A first look at MIGHTEE quasars

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2025) staf1187

Authors:

Sarah V White, Ivan Delvecchio, Nathan Adams, Ian Heywood, Imogen H Whittam, Catherine L Hale, Neo Namane, Rebecca AA Bowler, Jordan D Collier

Abstract:

Abstract In this work we study a robust, Ks-band complete, spectroscopically-confirmed sample of 104 unobscured (Type-1) quasars within the COSMOS and XMM-LSS fields of the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey, at 0.60 < zspec < 3.41. The quasars are selected via gJKs colour-space and, with 1.3-GHz flux-densities reaching rms ≈ 3.0 μ Jy beam−1, we find a radio-loudness fraction of 5percnt. Thanks to the deep, multiwavelength datasets that are available over these fields, the properties of radio-loud and radio-quiet quasars can be studied in a statistically-robust way, with the emphasis of this work being on the active-galactic-nuclei (AGN)-related and star-formation-related contributions to the total radio emission. We employ multiple star-formation-rate estimates for the analysis so that our results can be compared more-easily with others in the literature, and find that the fraction of sources that have their radio emission dominated by the AGN crucially depends on the SFR estimate that is derived from the radio luminosity. When redshift dependence is not taken into account, a larger fraction of sources is classed as having their radio emission dominated by the AGN. When redshift dependence is considered, a larger fraction of our sample is tentatively classed as ‘starbursts’. We also find that the fraction of (possible) starbursts increases with redshift, and provide multiple suggestions for this trend.

Euclid preparation

Astronomy & Astrophysics EDP Sciences 698 (2025) ARTN A233

Authors:

K Koyama, S Pamuk, S Casas, B Bose, P Carrilho, I Sáez-Casares, L Atayde, M Cataneo, B Fiorini, C Giocoli, Amc Le Brun, F Pace, A Pourtsidou, Y Rasera, Z Sakr, H-A Winther, E Altamura, J Adamek, M Baldi, M-A Breton, G Rácz, F Vernizzi, A Amara, S Andreon, N Auricchio, C Baccigalupi, S Bardelli, F Bernardeau, A Biviano, C Bodendorf, D Bonino, E Branchini, M Brescia, J Brinchmann, A Caillat, S Camera, G Cañas-Herrera, V Capobianco, C Carbone, J Carretero, M Castellano, G Castignani, S Cavuoti, Kc Chambers, A Cimatti, C Colodro-Conde, G Congedo, Cj Conselice, L Conversi, Y Copin

Abstract:

We study the constraint on f(R) gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu–Sawicki f(R) gravity model, we consider four different predictions for the ratio between the power spectrum in f(R) and that in Λ cold dark matter (ΛCDM): a fitting formula, the halo model reaction approach, ReACT, and two emulators based on dark matter only N-body simulations, FORGE and e-Mantis. These predictions are added to the MontePython implementation to predict the angular power spectra for weak lensing (WL), photometric galaxy clustering, and their cross-correlation. By running Markov chain Monte Carlo, we compare constraints on parameters and investigate the bias of the recovered f(R) parameter if the data are created by a different model. For the pessimistic setting of WL, one-dimensional bias for the f(R) parameter, log<inf>10</inf>| f<inf>R</inf><inf>0</inf>|, is found to be 0.5σ when FORGE is used to create the synthetic data with log<inf>10</inf>| f<inf>R</inf><inf>0</inf>| = −5.301 and fitted by e-Mantis. The impact of baryonic physics on WL is studied by using a baryonification emulator, BCemu. For the optimistic setting, the f(R) parameter and two main baryonic parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated for the adjustment of baryonic parameters, and the one-dimensional marginalised constraint on log<inf>10</inf>| f<inf>R</inf><inf>0</inf>| is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the ΛCDM synthetic data for WL, we obtain the prior-independent upper limit of log<inf>10</inf>| f<inf>R</inf><inf>0</inf>| < −5.6. Finally, we implement a method to include theoretical errors to avoid the bias due to inaccuracies in the nonlinear matter power spectrum prediction.