arXiv subjects

Giuseppe Murante

Publications and source records attributed to Giuseppe Murante.

At least 19 recordsLinked to original sources

arXiv2026

The OpenGadget3 Code for Cosmological Simulations

We present the public release of OpenGadget3 (OG3), a substantially extended and re-organised version of the widely used Gadget-2/3 family of cosmological simulation codes. Since G2 was made publicly available, the absence of continued official development led to the creation of numerous, mutually incompatible developer versions of G3 across the community. This made it effectively impossible to track bug fixes, reproduce published results, or consistently credit the many individual contributors. OG3 addresses this by consolidating these disparate developments into a single, documented, and continuously maintained code base, released under the GNU GPLv3 through a GitLab repository (with an accompanying wiki), regularly synchronised with the active developer branch, and supported by a dedicated continuous-integration (CI) pipeline. OG3 retains the core algorithmic backbone of its predecessors, a Barnes\&Hut oct-tree combined with a Particle-Mesh method for gravity, and a choice of Smoothed Particle Hydrodynamics or Meshless-Finite-Mass solvers for gas dynamics, within a hybrid MPI/OpenMP parallelisation framework, extended with GPU offloading via OpenACC and OpenMP. The code integrates an extensive suite of sub-resolution and physical modules, including primordial chemistry, radiative cooling, star formation, stellar feedback and chemical enrichment, dust formation and evolution, black hole growth and AGN feedback, MHD, thermal conduction, physical viscosity, SIDM, and massive neutrinos. OG3 introduces new features improving robustness, reproducibility, and usability: a flexible mixed-precision framework spanning 16- to 128-bit representations; expert-level tagged parameters with restart-time change log; extensive consistency checks against invalid configurations; and FAIR-compliant reporting of all settings, parameters, and specific publications. (shortened and abridged)

astro-ph.IM↗

arXiv2026

Interaction between vegetation and Snowball phases in the late Proterozoic Earth

Between 2.4 and 0.6 Gy ago, our planet underwent several episodes of global glaciations, including the Snowball Earth case that ended 635 My ago. Causes of this last Snowball event presumably included a decreased greenhouse gas concentration and high continental albedo, both associated with the passage of the super-continent Rodinia at equatorial latitudes. When large continental masses are in equatorial regions, silicate weathering is enhanced, leading to decreased atmospheric CO2 concentration, while the bare continental masses, which at the time hosted no vegetation, enhanced reflection of solar radiation. Since then, no other Snowball episodes were recorded. Here we numerically explore the climatic dynamics of a rocky planet for different values of solar output, continental configuration (current and Rodinia-like), CO2 concentration and continental albedo, simulating the effects of land vegetation. We found that for the solar input typical of 600-700 My ago (95% of the current value), the presence of bare continents with albedo 0.35 (granite) in the position estimated for Rodinia was sufficient to trigger a Snowball state for CO2 concentrations up to at least 1000 ppm. When bare continents are located in modern positions, Snowball could be triggered only for values of CO2 concentration below 400 ppm. At current solar input values, Snowball states appear only at or below 100 ppm. Thus, we found: a lower solar output is an essential component of the transition to Snowball; the presence of land vegetation is crucial and reduces the probability of entering a Snowball state; a low CO2 concentration was not needed for triggering a Snowball in bare Rodinia-like conditions and reduced solar output; current solar luminosity does not allow Snowball states, even for equatorial continents, unless continental albedo is that of granite and CO2 concentration is 100 ppm or less. [Abridged]

astro-ph.EP↗

arXiv2026

Assessing the Climate and Habitability of Tidally Locked Rocky Exoplanets

Tidally locked exoplanets orbiting M dwarf stars are prime targets in the search for habitable worlds, yet their complex climate dynamics challenge conventional models of habitability. We homogeneously estimated the liquid-water habitability of exoplanets with the highest up-to-date Earth-similarity index. We modified the climate model PLASIM to apply it to tidally locked exoplanets across a range of parameters. We systematically classified and compared potentially habitable exoplanets and selected among the ones featuring the highest Earth-similarity index in the conservative sample of the Habitable Wolds Catalog, both relative to each other and as a function of atmospheric pressure. Our analysis revealed three main climate regimes: Snowball, Hot, and Eyeball planets-the latter having a warm and habitable substellar region with T > 273 K and a localized hydrological cycle. Although surface temperature generally increases with pressure, Eyeball planet climates remain stable in a wide pressure range. Complex atmospheric dynamics govern the behavior of the climate, highlighting the need for detailed climate simulations to guide future observations.

astro-ph.EP↗

arXiv2026

Dianoga simulations of galaxy clusters and groups: Properties of the baryonic components

We introduce the Dianoga set of cosmological simulations of galaxy clusters and groups, specifically aimed at studying the impact of the implementation of AGN feedback and star formation. Using the OpenGadget3 code, we carry out simulations of 28 regions centred on massive galaxy clusters, and of a cosmological box. This generates a sample of 293 halos with M_{200}> 1.5 x 10^{13} M_{\odot}. Parameters of AGN feedback in the reference implementation were minimally calibrated exclusively to match the local relation between SMBH masses and stellar masses of host galaxies. Simulations are compared to observed galaxy stellar mass function (GSMF), stellar mass fraction in clusters and groups, BCG masses, scaling relations between ICM/IGM properties and profiles of their thermodynamical properties. In the appendix, we show how results vary as we modify the reference feedback model in six alternative configurations. Our reference model predicts a GSMF in general agreement with observations, albeit overestimated in the high end. BCG stellar masses and mass fractions are higher than observed in massive clusters, while being closer to observations for groups. Predicted properties of the ICM/IGM are in general agreement with observations, with the core regions of simulated clusters having entropy and temperature profiles that are slightly less "cool-cored" than observed. A comparison with other implementations of AGN feedback highlights that models including thermal evaporation of the sub-resolution interstellar medium succeed to bring BCG masses and stellar mass fractions closer to observation, and to increase the cool-coreness of simulated clusters. Our results demonstrate that the details of the interface between AGN energy injection and the sub-resolution interstellar medium model are at least as critical as the total feedback efficiency itself.

astro-ph.CO↗

arXiv2026

Variability in Cosmological Hydrodynamical Simulations: how Stochastic Processes, Numerical Effects, and Reproducibility Limits impact Predictability

Cosmological hydrodynamical simulations are powerful tools for studying galaxy formation, yet their predictive precision is limited by stochastic variability and numerical uncertainty. We quantify this variability using four identical realizations of a zoom-in galaxy-cluster simulation evolved with \textsc{OpenGadget3} under tightly controlled compiler, library, and hardware settings. Variability is measured through the properties of matched galaxies across repeated runs, including a mixed linear model that separates run-to-run variation from within-run noise. Variations of approximately $10$-$25\%$ are found in galaxy dark matter and stellar masses for the baseline simulations. The variability trending above the shot-noise floor reflects the combined effects of stochastic star formation and feedback regulation, and is further amplified when black hole physics is included. Furthermore, our results indicate that feedback acts to regulate variability, reducing scatter in both stellar and black hole masses. Our inference from run-to-run variation indicates a noise-dominated regime that remains statistically reproducible, despite individual realization differences. These results establish baseline, noise-dominated variability estimates at low resolution, demonstrate how feedback modulates predictability, and provide a statistical framework for future studies of reproducibility in cosmological hydrodynamical simulations.

astro-ph.GA↗

arXiv2026

A Quantum Genetic Algorithm with application to Cosmological Parameters Estimation

An Amplitude-Encoded Quantum Genetic Algorithm (AEQGA) has been developed to minimize $χ^2$ functions of different cosmological probes (Supernovae Type Ia, Baryon Acoustic Oscillations, Cosmic Microwave Background Radiation), to find the best-fit value for two cosmological parameters, namely the Hubble Constant and the density matter content of the Universe today. Our main aim is to pave the way to testing the adoption of quantum optimization in the inference of the cosmological parameters that describe the universe evolution. AEQGA computes the merit function classically, and then uses a quantum circuit to entangle the population and perform crossover and mutation operations. The results show consistency with the isocontours of the objective functions. We then tested the general behavior of AEQGA as a function of its hyperparameters and compared it with a second quantum genetic algorithm found in the literature as well as with classical algorithms, finding consistent results.

astro-ph.CO↗

arXiv2026

Quantum Algorithm for the Fixed-Radius Neighbor Search

Neighbor search is a computationally demanding problem, usually both time- and memory-consuming. The main problem of this kind of algorithms is the long execution time due to cache misses. In this work, we propose a quantum algorithm for the Fixed RAdius Neighbor Search problem (FRANS) based on the fixed-point version of Grover's algorithm. We propose an efficient circuit for solving the FRANS with linear query complexity with the number of particles $N$. The quantum circuit returns the list of all the neighbors' pairs within the fixed radius, together with their distance, avoiding the slow down given by cache miss. We analyzed the gate and the query complexity of the circuit. Our FRANS algorithm presents a query complexity of $\mathcal{O}(N/\sqrt{M})$, where $M$ is the number of solutions, reaching the optimal lower bound of the Grover's algorithm. We propose different implementations of the oracle, which must be chosen depending on the precise structure of the database. Among these, we present an implementation using the Chebyshev distance with depth $\mathcal{O}(q_1)$, where $2^{q_1}$ is the number of grid points used to discretize a spatial dimension. State-of-the-art algorithms for state preparation allow for a trade-off between depth and width of the circuit, with a volume (depth$\times$ width) of $\mathcal{O}(N\log(N))$. This unfavorable scaling can be brought down to $\mathcal{O}(\text{poly}(\log N))$ in case of structured datasets. We proposed a stopping criterion based on Bayes interference and tested its validity on $1D$ simulations. Finally, we accounted for the readout complexity and assessed the resilience of the model to the readout error, suggesting an error correction-free strategy to check the accuracy of the results.

quant-ph↗

arXiv2025

Quantum Markov Chain Monte Carlo for Cosmological Functions

We present an implementation of Quantum Computing for a Markov Chain Monte Carlo method with an application to cosmological functions, to derive posterior distributions from cosmological probes. The algorithm proposes new steps in the parameter space via a quantum circuit whose resulting statevector provides the components of the shift vector. The proposed point is accepted or rejected via the classical Metropolis-Hastings acceptance method. The advantage of this hybrid quantum approach is that the step size and direction change in a way independent of the evolution of the chain, thus ideally avoiding the presence of local minima. The results are consistent with analyses performed with classical methods, both for a test function and real cosmological data. The final goal is to generalize this algorithm to test its application to complex cosmological computations.

astro-ph.CO↗

arXiv2025

Dynamical friction and massive black hole orbits: analytical predictions and numerical solutions

We investigate the orbital decay of a massive BH embedded in a dark matter halo and a stellar bulge, using both analytical and numerical simulations with the aim of developing and validating a reliable dynamical friction (DF) correction across simulation resolutions. We develop a Python-based library to solve the equations of motion of the BH and provide an analytical framework for the numerical results. Then, we carry out simulations at different resolutions and for different softening choices using the Tree-PM code OpenGADGET3, where we implement an improved DF correction based on a kernel-weighted local density estimation. Our results demonstrate that the DF correction significantly accelerates BH sinking and ensures convergence with increasing resolution, closely matching analytical predictions. We find that in low-resolution regimes - particularly when the BH mass is smaller than that of the background particles - our DF model still effectively controls BH dynamics. Contrary to expectations, the inclusion of a stellar bulge can delay sinking due to numerical heating, an effect partially mitigated by the DF correction. We conclude that our refined DF implementation provides a robust framework for modeling BH dynamics both in controlled simulation setups of galaxies and in large-scale cosmological simulations. This will be crucial for future simulation campaigns, to enable more accurate predictions of AGN accretion and feedback, and to estimate gravitational-wave event rates.

astro-ph.GA↗

arXiv2025

The Application of Quantum Fourier Transform in Cosmic Microwave Background Data Analysis

The Cosmic Microwave Background (CMB) data analysis and the map-making process rely heavily on the use of spherical harmonics. For suitable pixelizations of the sphere, the (forward and inverse) Fourier transform plays a crucial role in computing all-sky map from spherical harmonic expansion coefficients -- or from angular power spectrum -- and vice versa. While the Fast Fourier Transform (FFT) is traditionally employed in these computations, the Quantum Fourier Transform (QFT) offers a theoretical advantage in terms of computational efficiency and potential speedup. In this work, we study the potential advantage of using the QFT in this context by exploring the substitution of the FFT with the QFT within the \textit{healpy} package. Performance evaluations are conducted using the Aer simulator. Our results indicate that QFT exhibits potential advantages over FFT that are particularly relevant at high-resolution. However, classical-to-quantum data encoding overhead represents a limitation to current efficiency. In this work, we adopted amplitude encoding, due to its efficiency on encoding maximum data to minimum number of qubits. We identify data encoding as a potential significant bottleneck and discuss its impact on quantum speedup. Future improvements in quantum encoding strategies and algorithmic optimizations could further enhance the feasibility of QFT in CMB data analysis.

astro-ph.IM↗

arXiv2025

Numerical limits in the integration of Vlasov-Poisson equation for Cold Dark Matter

The Vlasov-Poisson systems of equations (VP) describes the evolution of a distribution of collisionless particles under the effect of a collective-field potential. VP is at the basis of the study of the gravitational instability of cosmological density perturbations in Dark-Matter (DM), but its range of application extends to other fields, such as plasma physics. In the case of Cold Dark Matter, a single velocity is associated with each fluid-element (or particle) , the initial condition presents a stiff discontinuity. This creates problems such as diffusion or negative distribution function when a grid based method is used to solve VP. In this work we want to highlight this problem, focusing on the technical aspects of this phenomenon. By comparing different finite volume methods and a spectral method we observe that, while all integration schemes preserve the invariants of the system (e.g, energy), the physical observable of interest, i.e., the density, is not correctly reproduced. We thus compare the density obtained with the different Eulerian integration schemes with the result obtained from a reference N-body method. We point out that the most suitable method to solve the VP system for a self-gravitating system is a spectral method.

physics.comp-ph↗

arXiv2025

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection

This study evaluates the use of Quantum Convolutional Neural Networks (QCNNs) for identifying signals resembling Gamma-Ray Bursts (GRBs) within simulated astrophysical datasets in the form of light curves. The task addressed here focuses on distinguishing GRB-like signals from background noise in simulated Cherenkov Telescope Array Observatory (CTAO) data, the next-generation astrophysical observatory for very high-energy gamma-ray science. QCNNs, a quantum counterpart of classical Convolutional Neural Networks (CNNs), leverage quantum principles to process and analyze high-dimensional data efficiently. We implemented a hybrid quantum-classical machine learning technique using the Qiskit framework, with the QCNNs trained on a quantum simulator. Several QCNN architectures were tested, employing different encoding methods such as Data Reuploading and Amplitude encoding. Key findings include that QCNNs achieved accuracy comparable to classical CNNs, often surpassing 90\%, while using fewer parameters, potentially leading to more efficient models in terms of computational resources. A benchmark study further examined how hyperparameters like the number of qubits and encoding methods affected performance, with more qubits and advanced encoding methods generally enhancing accuracy but increasing complexity. QCNNs showed robust performance on time-series datasets, successfully detecting GRB signals with high precision. The research is a pioneering effort in applying QCNNs to astrophysics, offering insights into their potential and limitations. This work sets the stage for future investigations to fully realize the advantages of QCNNs in astrophysical data analysis.

astro-ph.HE↗

arXiv2024

Dynamical friction and evolution of black holes in cosmological simulations: a new implementation in OpenGadget3

We implement a sub-resolution prescription for the unresolved dynamical friction onto black holes (BHs) in the OpenGadget3 code. We carry out cosmological simulations of a volume of 16 cMpc3 and zoom-ins of a galaxy group and of a galaxy cluster. The advantages of our new technique are assessed in comparison to commonly adopted methods to hamper spurious BH displacements, i.e. repositioning onto a local minimum of the gravitational potential and ad-hoc boosting of the BH particle dynamical mass. The newly-introduced dynamical friction correction provides centering of BHs on host halos which is at least comparable with the other techniques. It predicts half as many merger events with respect to the repositioning prescription, with the advantage of being less prone to leave sub-structures without any central BH. Simulations featuring our dynamical friction prescription produce a smaller (by up to 50% with respect to repositioning) population of wandering BHs and final BH masses in good agreement with observations. As for individual BH-BH interactions, our dynamical friction model captures the gradual inspiraling of orbits before the merger occurs. By contrast, the repositioning scheme, in its most classical renditions considered, describes extremely fast mergers, while the dynamical mass misrepresents the BHs' dynamics, introducing numerical scattering between the orbiting BHs. Given its performances in describing the centering of BHs within host galaxies and the orbiting of BH pair before their merging, our dynamical friction correction opens interesting applications for an accurate description of the evolution of BH demography within cosmological simulations of galaxy formation at different cosmic epochs and within different environments.

astro-ph.CO↗

arXiv2024

Intertwined Formation of $\rm{H_2}$, Dust, and Stars in Cosmological Simulations

Context: Molecular hydrogen ($\rm{H_2}$) is crucial in galaxy formation and evolution, serving as the main fuel for star formation (SF). In metal-enriched environments, $\rm{H_2}$ primarily forms on interstellar dust grain surfaces. However, due to the complexities of modelling this process, SF in cosmological simulations often relies on empirical or theoretical frameworks validated only in the Local Universe to estimate the abundance of $\rm{H_2}$. Aims: This study aims to model the connection between star, dust, and $\rm{H_2}$ formation processes in cosmological simulations. Methods: We include $\rm{H_2}$ formation on dust grain surfaces and account for molecule destruction and radiation shielding into the SF and feedback model MUPPI. Results: The model reproduces key properties of observed galaxies for stellar, dust, and $\rm{H_2}$ components. The cosmic density of $\rm{H_2}$ ($ρ_{\rm{H2}}$) peaks around $z=1.5$, then decreases by half towards $z=0$, showing milder evolution than observed. The $\rm{H_2}$ mass function since $z=2$ also shows gentler evolution. Our model successfully recovers the integrated molecular Kennicutt-Schmidt (mKS) law between surface star formation rate ($Σ_{\rm SFR}$) and surface $\rm{H_2}$ density ($Σ_{\rm H2}$) at $z=0$, already evident at $z=2$ with a higher normalization. We find hints of a broken power law with a steeper slope at higher $Σ_{\rm H2}$, aligning with some observational findings. Additionally, the $\rm{H_2}$-to-dust mass ratio in galaxies shows a decreasing trend with gas metallicity and stellar mass. The $\rm{H_2}$-to-dust mass fraction for the global galaxy population is higher at higher redshifts. The analysis of the atomic-to-molecular transition on a particle-by-particle basis suggests that gas metallicity cannot reliably substitute the dust-to-gas ratio in models simulating dust-promoted $\rm{H_2}$.

astro-ph.GA↗

arXiv2024

Impact of vegetation albedo on the habitability of Earth-like exoplanets

Vegetation can modify the planetary surface albedo via the Charney mechanism, as plants are usually darker than the bare surface of the continents. We updated ESTM (Earth-like Surface Temperature Model) to incorporate the presence, distribution and evolution of two dynamically competing vegetation types that resemble grasslands and trees (the latter in the double stages of life: adults and seedlings). The newly developed model was applied to estimate how the climate-vegetation system reaches equilibrium across different rocky planetary configurations, and to assess its impact on temperature and habitability. With respect to a world with bare granite continents, the effect of vegetation-albedo feedback is to increase the average surface temperature. Since grasses and trees exhibit different albedos, they affect temperature to different degrees. The ultimate impact on climate depends on the outcome of the competition between these vegetation types. The change in albedo due to vegetation extends the habitable zone and enhances the overall planetary habitability beyond its traditional outer edge. This effect is especially relevant for planets that have a larger extension of continents than Earth. For Earth, the semi-major axis d = 1.04 UA represents the turning point where vegetation enhances habitability from h = 0.0 to h = 0.485 (in the grass-dominance case), to h = 0.584 (in the case of coexistence between grasses and trees), and to h = 0.612 (in the tree-dominance case). This illustrates the transition from a snowball state to a planet with intermediate habitability at the outer edge of the circumstellar habitability zone.

astro-ph.EP↗

arXiv2024

SubDLe: identification of substructures in cosmological simulations with deep learning

The identification of substructures within halos in cosmological hydrodynamical simulations is a fundamental step to identify the simulated counterparts of real objects, namely galaxies. For this reason, substructure finders play a crucial role in extracting relevant information from the simulation outputs. They are based on physically-motivated definitions of substructures, performing multiple steps of particle-by-particle operations, thus computationally expensive. The purpose of this work is to develop a fast algorithm to identify substructures in simulations. The final aim, besides a faster production of subhalo catalogues, is to provide an algorithm fast enough to be applied with a fine time-cadence during the evolution of the simulations. We chose to apply the architecture of a well known Fully Convolutional Network, U-Net, to the identification of substructures within the mass density field of the simulation. We have developed SubDLe (Substructure identification with Deep Learning), an algorithm which combines a 3D generalization of U-Net and a Friends-of-Friends algorithm, and trained it to reproduce the identification of substructures performed by the SubFind algorithm in a set of zoom-in cosmological hydrodynamical simulations of galaxy clusters. For the feasibility study presented in this work, we have trained and tested SubDLe on galaxy clusters at $z=0$, using a NVIDIA P100 GPU. We focused our tests on the version of the algorithm working on the identification of purely stellar substructures, stellar SubDLe. Our stellar SubDLe is capable of identifying the majority of galaxies in the challenging high-density environment of galaxy clusters in short computing times. This result has interesting implications in view of the possibility of integrating fast subhalo finders within simulation codes, that can take advantage of accelerators available on state-of-art computing nodes.

astro-ph.CO↗

arXiv2024

From Vlasov-Poisson to Schrödinger-Poisson: dark matter simulation with a quantum variational time evolution algorithm

Cosmological simulations describing the evolution of density perturbations of a self-gravitating collisionless Dark Matter (DM) fluid in an expanding background, provide a powerful tool to follow the formation of cosmic structures over wide dynamic ranges. The most widely adopted approach, based on the N-body discretization of the collisionless Vlasov-Poisson (VP) equations, is hampered by an unfavorable scaling when simulating the wide range of scales needed to cover at the same time the formation of single galaxies and of the largest cosmic structures. The dynamics described by the VP equations is limited by the rapid increase of the number of resolution elements which is required to simulate an ever growing range of scales. Recent studies showed an interesting mapping of the 6-dimensional+1 (6D+1) VP problem into a more amenable 3D+1 non-linear Schrödinger-Poisson (SP) problem for simulating the evolution of DM perturbations. This opens up the possibility of improving the scaling of time propagation simulations using quantum computing. In this paper, we introduce a quantum algorithm for simulating the (SP) equation by adapting a variational real-time evolution approach to a self-consistent, non-linear, problem. To achieve this, we designed a novel set of quantum circuits that establish connections between the solution of the original Poisson equation and the solution of the corresponding time-dependent Schrödinger equation. We also analyzed how nonlinearity impacts the variance of observables. Furthermore, we explored how the spatial resolution behaves as the SP dynamics approaches the classical limit and discovered an empirical logarithmic relationship between the required number of qubits and the scale of the SP equation. This entire approach holds the potential to serve as an efficient alternative for solving the Vlasov-Poisson (VP) equation by means of classical algorithms.

quant-ph↗

arXiv2023

Seasonal thaws under mid-to-low pressure atmospheres on Early Mars

Despite decades of scientific research on the subject, the climate of the first 1.5 Gyr of Mars history has not been fully understood yet. Especially challenging is the need to reconcile the presence of liquid water for extended periods of time on the martian surface with the comparatively low insolation received by the planet, a problem which is known as the Faint Young Sun (FYS) Paradox. In this paper we use ESTM, a latitudinal energy balance model with enhanced prescriptions for meridional heat diffusion, and the radiative transfer code EOS to investigate how seasonal variations of temperature can give rise to local conditions which are conductive to liquid water runoffs. We include the effects of the martian dichotomy, a northern ocean with either 150 or 550 m of Global Equivalent Layer (GEL) and simplified CO$_2$ or H$_2$O clouds. We find that 1.3-to-2.0 bar CO$_2$-dominated atmospheres can produce seasonal thaws due to inefficient heat redistribution, provided that the eccentricity and the obliquity of the planet are sufficiently different from zero. We also studied the impact of different values for the argument of perihelion. When local favorable conditions exist, they nearly always persist for $>15\%$ of the martian year. These results are obtained without the need for additional greenhouse gases (e.g. H$_2$, CH$_4$) or transient heat-injecting phenomena (e.g. asteroid impacts, volcanic eruptions). Moderate amounts (0.1 to 1\%) of CH$_4$ significantly widens the parameter space region in which seasonal thaws are possible.

astro-ph.EP↗