Cosmology

Abstract:

Radio observations offer a dust-independent probe of star formation and active galactic nucleus (AGN) activity, but sufficiently deep data are required to access the cross-over luminosity between these processes at high redshift (). We present three spectroscopically confirmed high-redshift radio sources (HzRSs) detected at 1.3 GHz at –5.6, with radio luminosities spanning –. These sources were first identified as high-redshift candidates through spectral energy distribution (SED) fitting of archival Hubble, James Webb Space Telescope (JWST) NIRCam + MIRI, and ground-based photometry, and then spectroscopically confirmed via the emission line using wide-field slitless spectroscopy from JWST COSMOS-3D. The star formation rates (SFRs) measured from SED fitting, the flux, and the 1.3 GHz luminosity, span –, demonstrating broad agreement between these SFR tracers. We find that these three sources lie either on or 0.5–1.0 dex above the star-forming main sequence at –6 and have undergone a recent burst of star formation. The sources have extended rest-ultraviolet (UV)/optical morphologies with no evidence for a dominant point source component, indicating that an AGN is unlikely to dominate their rest-UV and optical emission. Two of the sources have complex, multicomponent rest-frame UV/optical morphologies, suggesting that their starbursts may be triggered by merging activity. These HzRSs open up a new window towards probing radio emission powered by star formation alone at , representing a remarkable opportunity to begin tracing star formation, independent of dust, in the early Universe.

Abstract:

Radio-AGNs (active galactic nuclei) are observed to be more strongly clustered than non-active galaxies, though it is unclear whether this is simply due to their preference for massive host galaxies, or if they reside in distinct environments beyond this mass dependence. Using data from three fields covered by the MIGHTEE survey, we measure the angular two-point cross-correlation functions with a large, stellar mass-limited population of near-infrared selected galaxies, overcoming limitations of previous single-deep-field studies. By fitting halo occupation distribution models, we infer the galaxy bias parameters, b, for radio-AGN in three redshift ranges with median redshifts of , , and , finding , , and , respectively. The typical dark matter halo mass decreases with increasing redshift: , , and , which we attribute to the increased abundance of cold gas required to fuel AGN activity at earlier times. The AGN duty cycle is determined to be per cent, and we estimate that the total energy radiated by radio-jets over is per halo, which is sufficient to account for the observed excess heating of gas beyond that of gravitational collapse. Comparing the typical dark matter halo masses to the values obtained for the control sample, we find that the halo masses of radio-AGN are , , and times greater than those of the stellar mass- and redshift-matched galaxies. This difference could arise because AGN feedback suppresses stellar mass growth while leaving halo mass unchanged, or because radio-AGN preferentially reside in earlier forming haloes which are more strongly clustered.

Abstract:

Abstract Symbolic regression (SR) has emerged as a powerful method for uncovering interpretable mathematical relationships from data, offering a novel route to both scientific discovery and efficient empirical modelling. This article introduces the Special issue on symbolic regression for the physical sciences, motivated by the Royal Society discussion meeting held in April 2025. The contributions collected here span applications from automated equation discovery and emergent-phenomena modelling to the construction of compact emulators for computationally expensive simulations. The introductory review outlines the conceptual foundations of SR, contrasts it with conventional regression approaches and surveys its main use cases in the physical sciences, including the derivation of effective theories, empirical functional forms and surrogate models. We summarize methodological considerations such as search-space design, operator selection, complexity control, feature selection and integration with modern AI approaches. We also highlight ongoing challenges, including scalability, robustness to noise, overfitting and computational complexity. Finally, we emphasize emerging directions, particularly the incorporation of symmetry constraints, asymptotic behaviour and other theoretical information. Taken together, the papers in this Special issue illustrate the accelerating progress of SR and its growing relevance across the physical sciences. This article is part of the discussion meeting issue ‘Symbolic regression in the physical sciences’.

Abstract:

We present a measurement of the Lyα intensity mapping power spectrum from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). We measure the cross-power spectrum of the Lyα intensity and Lyα-emitting galaxies (LAEs) in a redshift range of 1.9 ≤ z ≤ 3.5. We calculate the intensity from HETDEX spectra that do not contain any detected LAEs above a signal-to-noise ratio of 5.5. To produce a power spectrum model and its covariance matrix, we simulate the data using lognormal mocks for the LAE catalog and Lyα intensity in redshift space. The simulations include the HETDEX sensitivity, selection function, and mask. The measurements yield the product of the LAE bias, the intensity bias, the mean intensity of undetected sources, and the ratio of the actual and fiducial redshift-space distortion parameters, bgbI〈I〉F¯RSD/F¯RSDfid= (6.7 ± 3.1), (11.7 ± 1.4), and (8.3 ± 1.5) × 10−22 erg s−1 cm−2 arcsec−2 Å−1 in three redshift bins centered at z¯=2.1 , 2.6, and 3.2, respectively. The results are reasonably consistent with cosmological hydrodynamical simulations that include Lyα radiative transfer. They are, however, significantly smaller than previous results from cross-correlations of quasars with Lyα intensity. These results demonstrate the statistical power of HETDEX for Lyα intensity mapping and pave the way for a more comprehensive analysis. They will also be useful for constraining models of Lyα emission from galaxies used in modern cosmological simulations of galaxy formation and evolution.

Abstract:

We present a search for z ≃ 7 Lyman-break galaxies using the 1.72 deg 2 near-infrared (NIR) UltraVISTA survey in the COSMOS field, reaching 5 σ depths in Y of 26.2. We incorporated deep Euclid optical and Euclid + Spitzer NIR imaging for a full spectral energy distribution (SED) fitting analysis. We found 289 candidate galaxies at 6.5 ≤ z ≤ 7.5 covering −22.6 ≤ M UV ≤ −20.2, faint enough to overlap with Hubble Space Telescope studies. We conducted a separate selection by including complementary Euclid performance verification imaging (reaching 5 σ depths of 26.3), yielding 140 galaxies in 0.65 deg 2 , with 38 sources unique to this sample. We computed the rest-frame UV luminosity function (UV LF) from our samples, extending below the knee ( M ∗ = 21.14 +0.28 −0.25 ). We find that the shape of the UV LF is consistent with both a Schechter function and a double power law (DPL) at the magnitudes probed by this sample, with a DPL preferred at M UV < −22.5 when bright-end results are included. The UltraVISTA + Euclid sample provides a clean measurement of the LF due to the overlapping NIR filters identifying molecular absorption features in the SEDs of ultra-cool dwarf interlopers, and additional faint galaxies were recovered. A comparison with JWST LFs at z > 7 suggests a gentle evolution in the bright-end slope, although this is limited by a lack of robust bright-end measurements at z > 9. We forecast that in the Euclid Deep Fields, the removal of contaminant ultra-cool dwarfs as point sources will be possible at J E < 24.5. Finally, we present a high-equivalent-width Lyman- α emitter candidate identified by combining HSC, VISTA, and Euclid broadband photometry, highlighting the synergistic power these instruments will have in the Euclid Auxiliary Fields for identifying extreme sources in the epoch of reionisation.