Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We investigate the role of baryonic physics in shaping the population, structure, and internal dynamics of galactic subhalos using the Mochima suite of cosmological zoom-in simulations. A refined method is developed to identify bound subhalo material by isolating the local gravitational potential and applying multi-criteria phase-space selection. This approach enables a robust characterisation of subhalo properties across five baryonic runs with varying prescriptions for star formation, and supernova and protostellar feedback, as well as a dark matter-only baseline. At the population level, we find that the concentration of the central massive host halo, modulated by baryonic physics in the central disc galaxy, is a key predictor of subhalo survival. Subhalos with more massive stellar components exhibit deeper internal potentials and enhanced resilience to tidal disruption. At the structural level, we identify a broad diversity in inner dark matter profiles, consistent with observations of dwarf galaxies. We show that this diversity correlates with both star formation history and environmental interaction. In particular, galaxies that form most of their stars early tend to retain steep cusps, while those with extended or recent star formation exhibit oscillating inner slopes shaped by bursty feedback and tidal perturbations. These findings suggest that the so-called “diversity problem” may reflect the complex interplay between feedback history and gravitational environment, rather than a breakdown of cold dark matter predictions.

Abstract:

We present an example cluster follow-up study with Euclid. Our target, a z ∼ 1.74 candidate cluster nicknamed the ‘Puddle’, was initially discovered by the Massive and Distant Clusters of WISE Survey 2 as a zphot ∼ 1.65 candidate cluster. It was also detected independently as a zphot ∼ 1.5 candidate with the two cluster-finding algorithms in Euclid Quick Release 1 (Q1). A Keck MOSFIRE spectrum shows the brightest nucleus is at z = 1.74 and is dominated by an active galactic nucleus. Our analysis focused on the galaxy population and the brightest cluster galaxy (BCG), and is based on Euclid and ancillary photometry. Compared to similar fields, we measured an overdensity of 110 ± 14 galaxies with HE ≤ 22.25 in a 2′ radius around the BCG. About 18 ± 4% of the completeness-corrected galaxy population is red, which is consistent with some clusters at z > 1.5 but lower than others. Euclid imaging revealed that six or seven galaxies appear to be assembling to form the future BCG. Spectral energy distribution fitting suggests that the merging BCG has a stellar mass of 5.7 ± 0.3 × 10¹¹ M⊙ and that it experienced a short burst of star formation ∼300 Myr ago. Its morphology and star-formation history suggest that the proto-BCG is a more evolved version of the merging core of SPT2349−56. These systems indicate that multiobject mergers might be a common BCG formation process. Assuming a similar density of mergers in the Euclid Wide Survey, we expect that Euclid will discover approximately 400 assembling BCGs by the end of its mission.

Abstract:

The Euclid mission of the European Space Agency seeks to understand the Universe’s expansion history and the nature of dark energy, through measurements of cosmic shear. This requires a very accurate estimate of the true redshift distribution of the galaxies, with the systematic error in the mean redshift satisfying σ⟨z⟩ < 0.002(1 + z) per tomographic bin. Achieving this accuracy relies on reference samples with spectroscopic redshifts, together with a procedure to match them to survey sources for which only photometric redshifts are available. One important source of systematic uncertainty is the mismatch in photometric properties between galaxies in the Euclid survey and the reference objects. We develop a method to degrade the photometry of objects with deep photometry to match the properties of any shallower survey in the multi-band photometric space, preserving all the correlations between the fluxes and their uncertainties. We compare our transfer method with more demanding image-based methods, such as Balrog from the Dark Energy Survey Collaboration. According to our metrics, our method outperforms Balrog. We implement our method in the redshift distribution reconstruction, based on the self-organising map approach, and test it using a realistic sample from the Euclid Flagship Mock Galaxy Simulation. We find that the key ingredient is to ensure that the reference objects are distributed in the colour space the same way as the wide-survey objects, which can be efficiently achieved with our transfer method. In our best implementation, the mean redshift biases are consistently reduced across the tomographic bins, bringing a significant fraction of them within the Euclid accuracy requirements in all tomographic bins. Equally importantly, the tests allow us to pinpoint which step in the calibration pipeline has the strongest impact on achieving the required accuracy. Our approach also reproduces the overall redshift distributions, which are crucial for applications such as angular clustering. The agreement between the reconstructed and true distributions demonstrates both the feasibility and robustness of the approach. This implementation is sufficient for Euclid Data Release 1 and provides a solid foundation for subsequent data releases.