Euclid: Quick Data Release (Q1) -- Secondary nuclei in early-type galaxies

TL;DR

This paper uses Euclid data to identify potential secondary nuclei in early-type galaxies, which may indicate past mergers and SMBH activity, and explores neural networks for future detection in larger surveys.

Contribution

It presents a systematic search for secondary nuclei in ETGs using Euclid's early data, introduces a candidate catalog, and demonstrates neural network methods for future large-scale detection.

Findings

Identified 666 candidate systems with secondary nuclei.

Most candidates are at separations of 3-15 kpc, typical of mergers.

Some candidates are unresolved or too small for globular clusters.

Abstract

Massive early-type galaxies (ETGs) are believed to form primarily through mergers of less massive progenitors, leaving 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 is sinking towards the shared gravitational potential of the merged galaxy. 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. 44 fall at projected separations of less than 2 kpc. We argue those candidates 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 may represent the highest-density nuclei of a previously merged galaxy, currently sinking into the centre of the new, common gravitational potential and thus likely to host a secondary SMBH. We then demonstrate that convolutional neural networks offer a viable avenue to detect multiple nuclei in the thirty-times larger sky coverage of the future Euclid DR1. Finally, we argue that our method could detect the remnants of a recoil event from two merged SMBHs.