Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Abstract The galaxy luminosity and stellar mass function (LF, SMF), and halo mass function (HMF), are fundamental quantities in astrophysics and crucial inputs to a range of astrophysical and cosmological analyses. They are typically parametrised by fitting functions that have been chosen ‘by eye’ to match observed or simulated data. We apply symbolic regression—specifically the Exhaustive Symbolic Regression (ESR) algorithm—to automate the search for optimal LF, SMF and HMF functional forms. ESR scores all functions up to a maximum complexity composed of a user-defined basis set of operators using the description length, an approximation to the Bayesian evidence that balances accuracy with complexity. We find many functions that outperform the Schechter and double Schechter functions for the LF and SMF, and that outperform all investigated literature functions (that outperform the Press–Schechter, Warren, Tinker, Sheth–Tormen and Jenkins) for the HMF. By additionally imposing ‘physicality checks’ on functions’ extrapolation and integration properties, we identify the optimal, low-complexity functional forms in terms of accuracy, simplicity and behaviour beyond the data range. As well as providing drop-in replacements for literature LF, SMF and HMF fitting functions, and identifying robust behaviour across well-fitting functions, we present a framework with which symbolic regression may be used to automate the discovery of optimal functions for any astrophysical dataset.

Abstract:

We present constraints on the amplitude of matter fluctuations from the clustering of galaxies and their cross-correlation with the gravitational lensing convergence of the cosmic microwave background (CMB), focusing on low redshifts (z ≲ 0.3), where potential deviations from a perfect cosmological constant dominating the growth of structure could be more prominent. Specifically, we make use of data from the 2MASS photometric survey (2MPZ) and the WISE×SuperCOSMOS galaxy survey, in combination with CMB lensing data from Planck. Using a hybrid effective field theory (HEFT) approach to model galaxy bias we obtain constraints on the combination S 8 = σ 8 √(Ω m /0.3), where σ 8 is the amplitude of matter fluctuations, and Ω m is the non-relativistic matter fraction. Using a prior on Ω m based on the baryon acoustic oscillation measurements of DESI, we find S 8 = 0.79 ± 0.06, in reasonable agreement with CMB constraints. We also find that, in the absence of this prior, the data favours a value of Ω m = 0.245 ± 0.024, that is 2.8σ lower than Planck. This result is driven by the broadband shape of the galaxy auto-correlation, and may be affected by theoretical uncertainties in the HEFT power spectrum templates. We further reconstruct the low-redshift growth history, finding it to be compatible with the Planck predictions, as well as existing constraints from lensing tomography. Finally, we study our constraints on the HEFT bias parameters of the galaxy samples studied, finding them to be in reasonable agreement with coevolution predictions.

Abstract:

A primary target of the Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of primordial non-Gaussianity would rule out the simplest models of cosmic inflation and transform our understanding of the origin of the Universe. This paper forecasts how well field-level inference of galaxy redshift surveys can constrain the amplitude of local primordial non-Gaussianity, f NL^local, within a Bayesian hierarchical framework, in the upcoming Euclid data. We designed and simulated mock datasets and performed Markov chain Monte Carlo analyses using a full-field forward modelling approach. By including the formation history of the cosmic matter field in the analysis, the method takes into account all available probes of primordial non-Gaussianity, and goes beyond statistical summary estimators of f NL^local. Probes include, for example, two-point and higher-order statistics, peculiar velocity fields, and scale-dependent galaxy biases. Furthermore, the method simultaneously handles systematic survey effects, such as selection effects, survey geometries, and galaxy biases. The forecast shows that, using simulated Euclid data, the method can achieve a precision of σ(f NL^local) = 2.6 (68.3% confidence level), assuming a grid resolution of ΔL = 31.25 h ⁻¹ Mpc and a cut-off scale of k NF = 0.1 h Mpc⁻¹. We also provide data products, including realistic simulations with non-zero values of f NL^local and maps of adiabatic curvature fluctuations. The results underscore the feasibility and advantages of field-level inference to constrain f NL^local in galaxy redshift surveys. Our approach consistently captures all the information available in the large-scale structure to constrain f NL^local, and resolves the degeneracy between early-universe physics and late-time gravitational effects, while mitigating the impact of systematic and observational effects.

Abstract:

Massive early-type galaxies (ETGs; M > 10¹¹ M⊙) are believed to form primarily through mergers of less massive progenitors, which leave behind numerous traces of violent formation histories, such as stellar streams and shells. A particularly striking signature of these mergers is the formation of supermassive black hole (SMBH) binaries, which can create depleted stellar cores through interactions with stars on radial orbits – a process known as core scouring. The secondary SMBH in such systems may still carry a dense stellar envelope and thereby remain observable for some time as a secondary nucleus while it sinks towards the shared gravitational potential of the merged galaxy. Direct observations of secondary nuclei on sub-kiloparsec scales remain rare, with only a few notable cases, such as NGC 5419. Investigating such features and building up statistics requires both high spatial resolution and wide-field coverage, a capability uniquely provided by Euclid. In this study, we leverage Euclid’s Q1 Early Release data to systematically search for secondary nuclei in ETGs. We present a preliminary sample of 666 candidate systems distributed over 504 hosts (some of which contain multiple secondary nuclei). The vast majority of these fall at separations of 3 kpc to 15 kpc, indicative of normal mergers. However, 44 fall at projected separations of less than 2 kpc. We argue that this most interesting subset of secondary nucleus candidates – those at very close angular separations – are unlikely to be a consequence of chance alignments. We show that their stellar masses are mostly too large for them to be globular clusters and that a significant subset are unresolved even at Euclid’s spatial resolution, rendering them too small to be dwarf galaxies. These objects may represent the highest-density nuclei of a previously merged galaxy currently sinking into the centre of the new common gravitational potential, and thus they likely host a secondary SMBH. We also demonstrate that convolutional neural networks offer a viable avenue to detect multiple nuclei in the 30 times larger sky coverage of the future Euclid DR1. Finally, we argue that our method can detect the remnants of a recoil event from two merged SMBHs, as two of our secondary nuclei candidates are unresolved at the Euclid spatial resolution, appear at projected physical separations of less than 2 kpc, and appear in hosts of M > 10¹¹ M⊙, which makes them viable candidates.

Abstract:

Using the vast statistics provided by both Euclid and the LOFAR surveys, we present the first large-scale study of the connection among radio emission, its morphology, and the merging properties of the hosts of radio sources up to z ∼ 2. By dividing the radio sample into active galactic nuclei (AGNs) and star-forming galaxies, we find that radio-emitting AGNs show a clear preference for residing within galaxies undergoing a merging event. This is more significant for AGNs that present complex or extended radio emission; indeed, about half of them are associated with merging systems, while only ∼15% are hosted by a non-interacting galaxy. The observed trend is primarily driven by AGNs residing at z < 1, especially in the case of high – P144 MHz > 10²⁴ W Hz⁻¹ sr⁻¹ – radio luminosities (∼56% in mergers versus ∼10% in non-mergers regardless of radio appearance). On the other hand, this preference seems to disappear at higher redshifts, where only bright AGNs with extended radio emission still prefer galaxies undergoing a merging event. The situation is reversed in the case of radio-emitting star-forming galaxies, which are preferentially associated with non-interacting systems. This is more significant as we move towards low-radio-luminosity/star-formation objects (P144 MHz < 10²³ W Hz⁻¹ sr⁻¹) for which we find ∼40% in non-mergers versus ∼20% in mergers. These values hold regardless of redshift. We interpreted the above result for AGNs with their need to accrete outer gas from local encounters in order to trigger (radio) activity, especially in the case of extended radio emission such as hot spots and lobes. This is mostly observed at z < 1, since galaxies in the local Universe are more gas deprived than their higher redshift counterparts. Internal gas reservoirs instead seem sufficient to trigger star formation within the majority of galaxies, which indeed mostly appear as non-interacting systems at all redshifts probed.