We present the first results from the Manticore Project, dubbed Manticore-Local, a suite of Bayesian constrained simulations of the nearby Universe, generated by fitting a physical structure formation model to the 2M++ galaxy catalogue using the borg algorithm. This field-level inference yields physically consistent realizations of cosmic structure, leveraging a non-linear gravitational solver, a refined galaxy bias model, and physics-informed priors. The Manticore-Local posterior realizations evolve within a parent cosmological volume statistically consistent with Lambda-cold dark matter, demonstrated through extensive posterior predictive tests of power spectra, bispectra, initial condition Gaussianity, and the halo mass function. The inferred local supervolume (⁠R<200 Mpc, or z≲0.05⁠) shows no significant deviation from cosmological expectations; notably, we find no evidence for a large local underdensity, with the mean density suppressed by only ≈5per cent relative to the cosmic mean. Our model identifies high-significance counterparts for 14 prominent galaxy clusters – including Virgo, Coma, and Perseus – each within 1 deg of its observed sky position. Across the posterior ensemble, these counterparts are consistently detected with 2σ–4σ significance, and their reconstructed masses and redshifts agree closely with observational estimates, confirming the inference’s spatial and dynamical fidelity. The peculiar velocity field recovered by Manticore-Local achieves the highest Bayesian evidence across five independent data sets, surpassing state-of-the-art non-linear models, linear theory, Wiener filtering, and machine learning approaches. Unlike methods yielding only point estimates or using simplified dynamics, Manticore-Local provides a full Bayesian posterior over cosmic structure and evolution, enabling rigorous uncertainty quantification. These results establish Manticore-Local as the most advanced constrained realization suite of the local Universe to date, offering a robust statistical foundation for future studies of galaxy formation, velocity flows, and environmental dependencies in our cosmic neighbourhood.

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code SWIFT. The software package exploits hybrid shared- and distributed-memory task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. SWIFT also evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarize the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with ≈300 billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with SWIFT.

We introduce a new model for the accretion and feedback of supermassive black hole (SMBH) binaries to the ketjucode, which enables us to resolve the evolution of SMBH binaries down to separations of tens of Schwarzschild radii in gas-rich galaxy mergers. Our subgrid binary accretion model extends the widely used Bondi-Hoyle-Lyttleton accretion into the binary phase and incorporates preferential mass accretion on to the secondary SMBH, which is motivated by results from small-scale hydrodynamical circumbinary disc simulations. We perform idealized gas-rich disc galaxy merger simulations using pure thermal or pure kinetic active galactic nuclei (AGNs) feedback. Our binary accretion model provides more physically motivated SMBH mass ratios, which are one of the key parameters for computing gravitational wave (GW) induced recoil velocities. The merger time-scales of our simulated SMBH binaries are in the range t(merge) similar to 10-400 Myr. Prograde in-plane equal-mass galaxy mergers lead to the shortest merger time-scales, as they experience the strongest starbursts, with the ensuing high stellar density resulting in a rapid SMBH coalescence. Compared to the thermal AGN feedback, the kinetic AGN feedback predicts longer merger time-scales and results in more core-like stellar profiles, as it is more effective in removing gas from the galaxy centre and quenching star formation. This suggests that the AGN feedback implementation plays a critical role in modelling SMBH coalescences. Our model will be useful for improving the modelling of SMBH mergers in gas-rich galaxies, the prime targets for the upcoming LISA GW observatory.

The Milky Way is surrounded by 11 ‘classical’ satellite galaxies in a remarkable configuration: a thin plane that is possibly rotationally supported. Such a structure is thought to be highly unlikely to arise in the standard (ΛCDM) cosmological model (Λ cold dark matter model, where Λ is the cosmological constant). While other apparent discrepancies between predictions and observations of Milky Way satellite galaxies may be explained either through baryonic effects or by invoking alternative forms of dark matter particles, there is no known mechanism for making rotating satellite planes within the dispersion-supported dark matter haloes predicted to surround galaxies such as the Milky Way. This is the so-called ‘plane of satellites problem’, which challenges not only the ΛCDM model but the entire concept of dark matter. Here we show that the reportedly exceptional anisotropy of the Milky Way satellites is explained, in large part, by their lopsided radial distribution combined with the temporary conjunction of the two most distant satellites, Leo I and Leo II. Using Gaia proper motions, we show that the orbital pole alignment is much more common than previously reported, and reveal the plane of satellites to be transient rather than rotationally supported. Comparing with new simulations, where such short-lived planes are common, we find the Milky Way satellites to be compatible with standard model expectations.

We study structure formation in a set of cosmological simulations to uncover the scales in the initial density field that gave rise to the formation of present-day structures. Our simulations share a common primordial power spectrum (here Lambda cold dark matter, Lambda CDM), but the introduction of hierarchical variations of the phase information allows us to systematically study the scales that determine the formation of structure at later times. We consider the variance in z = 0 statistics such as the matter power spectrum and halo mass function. We also define a criterion for the existence of individual haloes across simulations, and determine what scales in the initial density field contain sufficient information for the non-linear formation of unique haloes. We study how the characteristics of individual haloes such as the mass and concentration, as well as the position and velocity, are affected by variations on different scales, and give scaling relations for haloes of different mass. Finally, we use the example of a cluster-mass halo to show how our hierarchical parametrization of the initial density field can be used to create variants of particular objects. With properties such as mass, concentration, kinematics, and substructure of haloes set on distinct and well-determined scales, and its unique ability to introduce variations localized in real space, our method is a powerful tool to study structure formation in cosmological simulations.