arXiv subjects

Cristiano G. Sabiu

Publications and source records attributed to Cristiano G. Sabiu.

At least 19 recordsLinked to original sources

arXiv2026

Intracluster Light as a Probe for Dark Matter: Exploring Self-interacting Dark Matter and Cold Dark Matter with C-EAGLE Sims

We assess whether intracluster light (ICL) can serve as an observational discriminator of dark matter physics. The self-interacting dark matter (SIDM) model has gained increasing attention as a possible resolution to small-scale discrepancies between collisionless cold dark matter (CDM) simulations and observations, predicting distinct tidal interaction histories within galaxy clusters. We analyze Cluster-EAGLE zoom-in galaxy clusters re-simulated from identical initial conditions in both CDM and SIDM frameworks. The morphological similarity between dark matter and multiple baryonic tracers -- gas, all stars, galaxies, and the combined brightest cluster galaxy plus ICL (BCG+ICL) -- is quantified using the Weighted Overlap Coefficient, a contour-overlap statistic. We find that dark matter is traced most accurately by BCG+ICL, followed by gas, all stars, and galaxies. The BCG+ICL component remains a robust tracer even at high redshift, while gas initially traces dark matter poorly but improves over time, eventually approaching the performance of BCG+ICL. Notably, in the SIDM case the gas distribution more closely resembles dark matter than in CDM. This reflects the underlying physics: in CDM, collisionless dark matter behaves similarly to the collisionless BCG+ICL, whereas in SIDM, self-interactions introduce an effective collisionality, making dark matter evolve more like the gas component. We also find that dwarf and satellite galaxies are more sensitive to the underlying dark matter model, despite their poorer overall tracing performance. Our results demonstrate the potential of ICL as a novel observational probe of dark matter physics and provide a first step toward using diffuse cluster light to constrain the nature of dark matter.

astro-ph.CO↗

arXiv2026

Climbing the $N$-point Ladder Part I: Information in the Higher-Order Configuration-Space Clustering of Dark Matter Halos

We quantify the information content of the configuration-space two-, three-, and connected four-point correlation functions of Quijote dark-matter haloes at $z=0$ and fixed number density. We build Fisher forecasts for $\{Ω_m, Ω_b, h, n_s, σ_8, M_ν\}$ in real and redshift space from ${\sim}38{,}000$ GPU-accelerated $N$-point measurements. Treating the statistics as a ladder, $\mathrm{2PCF} \rightarrow +\mathrm{3PCF} \rightarrow +ζ^{(4)}_{\mathrm{conn}}$, we report the information gained at each rung. The 3PCF supplies most of the accessible higher-order information: it tightens every parameter, most strongly $σ_8$ and $M_ν$, whose degeneracy it partially breaks, by factors of $1.6$--$6.3$ over the redshift-space $\{ξ_0,ξ_2\}$ baseline with per-parameter gains consistent with those of the Fourier-space halo bispectrum on the same simulations. The 3PCF gains persist under conservative, modelling-motivated scale cuts: restricted to the tree-level-validated regime with minimum triangle side $\ge40\,h^{-1}{\rm Mpc}$, it still improves $M_ν$ by $3.9\times$. The connected 4PCF adds a further $\sim1.2$--$1.5\times$, an increment insensitive to whether the quadrupole is included in the baseline but traceable to small-scale configurations with sides $\lesssim30\,h^{-1}{\rm Mpc}$. This rung-to-rung increment is stable against derivative-sample noise and compression regularization, whereas the absolute constraints remain limited by the finite simulation ensembles and are reported as preliminary. The configuration-space ladder thus offers an independent and complementary route to the higher-order information probed by the Fourier-space poly-spectra.

astro-ph.CO↗

arXiv2026

Exact topology of conservative multiplicative cascades: An ultrametric transfer-operator genus

The multiplicative cascade is a well-known method for generating random fields that are both genuinely non-Gaussian and scale invariant. Its one-point and scaling statistics, namely the multifractal spectra $τ(q)$, $D_q$, and $f(α)$, are known exactly; however, its geometric and topological measures are not. In this work, we show that the topological structures of a conservative (microcanonical) random permutation cascade can be precisely predicted. We compute the digital (cubical) Euler characteristic, or genus, of the level-$j$ excursion set of the two-dimensional cascade in closed form, using a transfer operator on the cascade's $b$-ary tree closed by its ultrametric structure and a conservative without-replacement sibling split. The result requires no Monte Carlo and matches simulated realizations with a maximum residual of $\sim\!10^{-4}$ in the Euler density, a controlled discretization artifact of the atomic measure. We tie the genus scaling analytically to the multifractal spectrum, and show that for a geometric ladder of weights the genus is exactly self-similar under the multifractal-width dial. The construction uses the tree-sum cumulant machinery of Greiner et al. (Phys. Rev. E 58, 554, 1998), specialized to topological functionals; the conservative split carries the microcanonical fingerprint $\mathrm{Cov}(\ln w_a,\ln w_b)/\mathrm{Var}(\ln w)=-1/(n-1)$ that distinguishes it from canonical and lognormal cascades. The cascade is the multiplicative counterpart of the Rayleigh--Lévy flight and a controlled benchmark for the morphology of strongly non-Gaussian fields.

math-ph↗

arXiv2026

Fast Graph-based Higher-Order Clustering Statistics on the GPU

We present a significant update to GRAMSCI (GRAph Made Statistics for Cosmological Information; Sabiu et.al 2019), an algorithm for the fast computation of the general $N$-point spatial correlation function of any discrete point set embedded in $\mathbb{R}^n$. Utilizing the concepts of kd-trees and graph databases, we count all possible $N$-tuples in binned configurations within a given length scale. In this {\em Version 2 update} we describe several additions to the original code. We replace the binary-search inner loop, which cost $O(m\log m)$ per hub--spoke pair, where $m$ is the mean neighbor count, with a merge-walk algorithm that reduces the inner loop to $O(m)$. We implement a parity-decomposed 4pCF that separates the signal into even and odd channels, enabling direct tests of parity violation in the galaxy distribution. We estimate the disconnected 4pCF internally on the same graph to return the connected 4pCF. We provide a Python interface so the Fortran engine can be called directly from NumPy arrays. Finally, and principally, we present a GPU port of the full query engine (OpenACC): the 3pCF, 4pCF, and parity-decomposed 4pCF kernels run on a single consumer GPU with measured speedups of $2.6\times$ (3pCF) to $9\times$ (4pCF) over a 64-thread CPU node, and an out-of-core tiling scheme allows graphs far exceeding device memory. We measure a $9\times10^9$-edge BAO-scale 3pCF on a 24\,GB card with ${\sim}20\%$ overhead. We validate the code against its CPU reference, against analytic injection tests, and demonstrate BAO-scale applications on the DESI DR1 LRG sample compared against the EZmock ensemble.

astro-ph.IM↗

arXiv2026

Groups of Dwarf Galaxies in the Local Universe

We present a systematic search for dwarf-galaxy groups in the local Universe ($z<0.02$), identifying 28 systems containing at least four spectroscopically confirmed members selected from the SDSS and DESI surveys. Group membership is assigned based on projected separation -within 300\,kpc from the most massive galaxy (designated the ``central'') -and a relative line-of-sight velocity difference of less than 200\,km/s. The sample has a median redshift of $z=0.0131$ ($\sim55$\,Mpc) and a median central stellar mass of $1.7\times10^{9}\,M_\odot$, firmly placing these systems in the low-mass regime. In total, 28 groups contain 129 dwarf galaxy members, with a median stellar mass of $1.63\times10^{8}\,M_\odot$. The median $r$-band apparent magnitude of the member dwarfs is 17.38\,mag, slightly fainter than the spectroscopic observation limit of the SDSS main spectroscopic survey. Remarkably, several groups are centered on galaxies with stellar masses as low as $\sim10^{8}\,M_\odot$, comparable to the Fornax dwarf spheroidal, demonstrating that even very faint galaxies can host bound satellite systems. Most groups exhibit low velocity dispersions ($σ_{v}<50$\,km/s), consistent with being gravitationally bound. The inferred dynamical masses span $\sim10^{10}-10^{12}\,M_\odot$, while the corresponding three-dimensional velocity dispersions ($σ_{3D}$) fall between 50 and 100\,\kms, characteristic of dynamically cold, low-mass halos. Our results provide empirical constraints on small-scale structure formation and show strong consistency with predictions from cosmological volume simulations, supporting the picture that dwarf galaxies can serve as central hosts for their own satellite systems embedded within extended dark-matter halos.

astro-ph.GA↗

arXiv2026

K-DRIFT Science Theme: Galaxies in the Faint Universe

Low-surface-brightness (LSB) structures serve as evidence of the intricate mass assembly of galaxies, and dedicatedly studying them promises to give us profound insights into the evolutionary history of galaxies. Furthermore, delving into the properties of star formation (SF) in the LSB regime can broaden our understanding of SF activity in regions characterized by low surface gas density, thereby shedding light on fundamental cosmic processes. However, systematic uncertainties may hamper the exploration of the LSB universe by limiting detectable SB levels. Indeed, despite dedicated advancements in telescope and observing techniques over decades, achieving ultra-deep photometric depths in optical wavelengths remains a formidable challenge. To overcome this challenge and explore the LSB universe that we have yet to see, we have been developing a novel telescope called K-DRIFT. This paper outlines the telescope's specification and describes various LSB features we aim for, explicitly focusing on nearby individual galaxies. To further advance the capabilities of the K-DRIFT survey, focused on LSB detection, we present several feasible research topics that utilize other survey data together and discuss the role of LSB observation in understanding the evolution of galaxies.

astro-ph.GA↗

arXiv2025

K-DRIFT Science Theme: Illuminating the Next Era of Galaxy Cluster Science

The KASI Deep Rolling Imaging Fast Telescope (K-DRIFT) is a pioneering instrument designed to explore low-surface-brightness (LSB) phenomena. This white paper presents a compelling array of science cases that showcase K-DRIFT's unique capabilities in unraveling the mysteries of intracluster light (ICL) and other LSB components within galaxy clusters. Exploring the origin of ICL in galaxy clusters and comparing the spatial distributions of ICL and dark matter will offer new insights into galaxy cluster dynamics. Moreover, investigating LSB objects in galaxy clusters, such as LSB structures in the brightest cluster galaxy, ultra-diffuse galaxies, and tidal features, will enhance our understanding of galaxy evolution within the cluster environment. We present our strategies for addressing scientific queries, encompassing LSB observation and analysis techniques, specialized simulations, and machine-learning approaches. Additionally, we examine the potential synergies between K-DRIFT and other ongoing or forthcoming multi-wavelength surveys. This white paper advocates for the recognition and support of K-DRIFT as a dedicated tool for advancing our understanding of the universe's subtlest phenomena.

astro-ph.GA↗

arXiv2025

Different Origins of Nucleated and Non-nucleated Dwarf Elliptical Galaxies: Identified by the Deep-learning

Dwarf elliptical galaxies (dEs) are the dominant population in galaxy clusters and serve as ideal probes for studying the environmental impact on galactic evolution. A substantial fraction of dEs are known to harbor central nuclei, which are among the densest stellar systems in the Universe. The large-scale distribution and the underlying origin of nucleated and non-nucleated dEs remain unresolved. Using a state-of-the-art machine learning framework, we systematically scan the Virgo cluster region ($15\arcdeg \times 20\arcdeg$ centered at $R.A. = 187.2\arcdeg$ and $Dec. = 9.6\arcdeg$) and construct the largest homogeneous sample of dEs (of total 2,123) with robust nucleus classifications. We find that nucleated dEs are more spatially clustered and exhibit a stronger association with massive galaxies than their non-nucleated counterparts. This suggests that most nucleated dEs likely formed alongside massive galaxies within the cluster (i.e, the in-situ formation). In contrast, non-nucleated dEs are more widely distributed across the cluster and align more closely with Virgo's global potential well, as traced by the cluster's hot gas. This indicates that most non-nucleated dEs originated outside the cluster (i.e, the ex-situ formation) and were later accreted and redistributed within it. Our findings shed new light on how dEs and their central nuclei form and evolve.

astro-ph.GA↗

arXiv2025

External Attention Transformer: A Robust AI Model for Identifying Initial Eccentricity Signatures in Binary Black Hole Events in Simulated Advanced LIGO Data

Initial orbital eccentricities of gravitational wave (GW) events associated with merging binary black holes (BBHs) should provide clues to their formation scenarios, mainly because various BBH formation channels predict distinct eccentricity distributions. However, searching for inspiral GWs from eccentric BBHs is computationally challenging due to sophisticated approaches to model such GW events. This ensures that Bayesian parameter estimation methods to characterize such events are computationally daunting. These considerations influenced us to propose a novel approach to identify and characterize eccentric BBH events in the LIGO-Virgo-KAGRA (LVK) collaboration data sets that leverages external attention transformer models. Employing simulated data that mimic LIGO O4 run, eccentric inspiral events modeled by an effective-one-body numerical-relativity waveform family, we show the effectiveness of our approach. By integrating this transformer-based framework with a convolutional neural network (CNN) architecture, we provide efficient way to identify eccentric BBH GW events and accurately characterize their source properties.

gr-qc↗

arXiv2025

An isolated early-type dwarf galaxy that ran away from the group environment

Understanding the quenching mechanisms in dwarf galaxies is crucial for constraining models of galaxy formation and evolution. In this vein, isolated dwarf galaxies offer valuable insight by helping disentangle the relative roles of internal and environmental processes in shutting down star formation. Here we report the discovery of a quiescent early-type dwarf galaxy (dE), SDSS J011754.86+095819.0 (hereafter dE01+09), located in a nearly isolated environment at a projected distance of approximately one megaparsec from its most likely host group, the NGC 524 group. dE01+09 has M_r = -15.72 and g-r = 0.67 mag and its light profile is well described by a Sérsic function with an index n = 1.1, consistent with typical dEs. Using optical spectroscopy from the DESI survey, we derive its simple stellar population properties, finding an intermediate luminosity-weighted age of 8.3$\pm$1.4 Gyr and a subsolar metallicity of -1.19$\pm$0.21 dex -- characteristics comparable to those of classical quiescent dEs. We propose that NGC 524 may represent an extreme example of group dynamics, in which a member galaxy, dE01+09, is ejected from its host group and subsequently evolves as an isolated system in the field.

astro-ph.GA↗

arXiv2025

Tracing Dark Matter in the Central Regions of Galaxy Clusters Using Galaxies, Gas, and Intracluster Light in TNG300: Connections to Cluster Dynamical State

Recent studies have highlighted the potential of intracluster light (ICL) as a dark matter tracer. Moreover, the ICL co-evolves with the brightest cluster galaxy (BCG) and the host cluster, making it a valuable tool for understanding cluster dynamics. In this study, we utilize 426 galaxy clusters (with total mass $M_{\rm tot}>10^{14} M_{\odot}$ at $z=0$) simulated in the cosmological hydrodynamical simulation Illustris TNG300 to compare the spatial distributions of dark matter, member galaxies, gas, and ICL and assess their effectiveness as dark matter tracers in the central regions of clusters at $R_{\rm vir}<0.3$. We apply the Weighted Overlap Coefficient (WOC), a methodology for quantifying the similarity of two-dimensional spatial distributions, to various components of the galaxy clusters at different dynamical stages. Our findings reveal that the spatial distributions of both ICL combined with the BCG and gas closely resemble the dark matter distribution, with higher fidelity observed in more relaxed galaxy clusters with earlier half-mass epochs. These results demonstrate that the BCG+ICL component serves as an effective tracer of dark matter, consistent with previous observational studies linking cluster light to mass. Moreover, the degree of spatial similarity between the BCG+ICL and dark matter distributions appears to reflect the dynamical state of the cluster.

astro-ph.GA↗

arXiv2024

Discovery of a Rare Group of Dwarf Galaxies in the Local Universe

We report the discovery of a rare isolated group of five dwarf galaxies located at z = 0.0086 ($D$ = 36 Mpc). All member galaxies are star-forming, blue, and gas-rich with $g-r$ indices ranging from 0.2 to 0.6 mag, and two of them show signs of ongoing mutual interaction. The most massive member of the group has a stellar mass that is half of the Small Magellanic Cloud stellar mass, and the median stellar mass of the group members is 7.87 $\times$ 10$^{7}$ M$_{\odot}$. The derived total dynamical mass of the group is $M_{\rm dyn}$ = 6.02$\times$10$^{10}$ M$_{\odot}$, whereas its total baryonic mass (stellar + HI) is 2.6$\times$10$^{9}$ M$_{\odot}$, which gives us the dynamical to baryonic mass ratio of 23. Interestingly, all galaxies found in the group are aligned along a straight line in the plane of the sky. The observed spatial extent of the member galaxies is 154 kpc, and their relative line-of-sight velocity span is within 75 km s$^{-1}$. Using the spatially resolved optical spectra provided by DESI EDR, we find that three group members share a common rotational direction. With these unique properties of the group and its member galaxies, we discuss the possible importance of such a system in the formation and evolution of dwarf galaxy groups and in testing the theory of large-scale structure formation.

astro-ph.GA↗

arXiv2024

Constructing a Galaxy Cluster Catalog in IllustrisTNG-300 using the Mulguisin Algorithm

We present a new simulated galaxy cluster catalog based on the IllustrisTNG simulation. We use the Mulguisin (MGS) algorithm to identify galaxy overdensities. Our cluster identification differs from the previous FoF cluster identification in two aspects; 1) we identify cluster halos based on the galaxy subhalos instead of unobservable dark matter particles, and 2) we use the MGS algorithm that separates galaxy overdensities hosted by massive galaxies. Our approach provides a cluster catalog constructed similar to the observed cluster catalogs using spectroscopic surveys. The MGS cluster catalog lists 303 halos with M$_{200} > 10^{14}$ M$_{\odot}$, including $\sim 10\%$ more than the FoF. The MGS catalog includes more systems because we separate some independent massive MGS cluster halos that are bundled into a single FoF algorithm. These independent MGS halos are apparently distinguishable in galaxy spatial distribution and the phase-space diagram. Because we constructed a refined cluster catalog that identifies local galaxy overdensities, we evaluate the effect of MGS clusters on the evolution of galaxies better than using the FoF cluster catalog. The MGS halo identification also enables effective identifications of merging clusters by selecting systems with neighboring galaxy overdensities. We thus highlight that the MGS cluster catalog is a useful tool for studying clusters in cosmological simulations and for comparing with the observed cluster samples.

astro-ph.GA↗

arXiv2024

Spatial Distribution of Intracluster Light versus Dark Matter in Horizon Run 5

One intriguing approach for studying the dynamical evolution of galaxy clusters is to compare the spatial distributions among various components, such as dark matter, member galaxies, gas, and intracluster light (ICL). Utilizing the recently introduced Weighted Overlap Coefficient (WOC) \citep{2022ApJS..261...28Y}, we analyze the spatial distributions of components within 174 galaxy clusters ($M_{\rm tot}> 5 \times 10^{13} M_{\odot}$, $z=0.625$) at varying dynamical states in the cosmological hydrodynamical simulation Horizon Run 5. We observe that the distributions of gas and the combination of ICL with the brightest cluster galaxy (BCG) closely resembles the dark matter distribution, particularly in more relaxed clusters, characterized by the half-mass epoch. The similarity in spatial distribution between dark matter and BCG+ICL mimics the changes in the dynamical state of clusters during a major merger. Notably, at redshifts $>$ 1, BCG+ICL traced dark matter more accurately than the gas. Additionally, we examined the one-dimensional radial profiles of each component, which show that the BCG+ICL is a sensitive component revealing the dynamical state of clusters. We propose a new method that can approximately recover the dark matter profile by scaling the BCG+ICL radial profile. Furthermore, we find a recipe for tracing dark matter in unrelaxed clusters by including the most massive satellite galaxies together with BCG+ICL distribution. Combining the BCG+ICL and the gas distribution enhances the dark matter tracing ability. Our results imply that the BCG+ICL distribution is an effective tracer for the dark matter distribution, and the similarity of spatial distribution may be a useful probe of the dynamical state of a cluster.

astro-ph.CO↗

arXiv2024

MulGuisin, a Topological Network Finder and its Performance on Galaxy Clustering

We introduce a new clustering algorithm, MulGuisin (MGS), that can identify distinct galaxy over-densities using topological information from the galaxy distribution. This algorithm was first introduced in an LHC experiment as a Jet Finder software, which looks for particles that clump together in close proximity. The algorithm preferentially considers particles with high energies and merges them only when they are closer than a certain distance to create a jet. MGS shares some similarities with the minimum spanning tree (MST) since it provides both clustering and network-based topology information. Also, similar to the density-based spatial clustering of applications with noise (DBSCAN), MGS uses the ranking or the local density of each particle to construct clustering. In this paper, we compare the performances of clustering algorithms using controlled data and some realistic simulation data as well as the SDSS observation data, and we demonstrate that our new algorithm finds networks most efficiently and defines galaxy networks in a way that most closely resembles human vision.

astro-ph.IM↗

arXiv2023

The Universe is worth $64^3$ pixels: Convolution Neural Network and Vision Transformers for Cosmology

We present a novel approach for estimating cosmological parameters, $Ω_m$, $σ_8$, $w_0$, and one derived parameter, $S_8$, from 3D lightcone data of dark matter halos in redshift space covering a sky area of $40^\circ \times 40^\circ$ and redshift range of $0.3 < z < 0.8$, binned to $64^3$ voxels. Using two deep learning algorithms, Convolutional Neural Network (CNN) and Vision Transformer (ViT), we compare their performance with the standard two-point correlation (2pcf) function. Our results indicate that CNN yields the best performance, while ViT also demonstrates significant potential in predicting cosmological parameters. By combining the outcomes of Vision Transformer, Convolution Neural Network, and 2pcf, we achieved a substantial reduction in error compared to the 2pcf alone. To better understand the inner workings of the machine learning algorithms, we employed the Grad-CAM method to investigate the sources of essential information in activation maps of the CNN and ViT. Our findings suggest that the algorithms focus on different parts of the density field and redshift depending on which parameter they are predicting. This proof-of-concept work paves the way for incorporating deep learning methods to estimate cosmological parameters from large-scale structures, potentially leading to tighter constraints and improved understanding of the Universe.

astro-ph.CO↗

arXiv2023

Reconstructing the cosmological density and velocity fields from redshifted galaxy distributions using V-net

The distribution of matter that is measured through galaxy redshift and peculiar velocity surveys can be harnessed to learn about the physics of dark matter, dark energy, and the nature of gravity. To improve our understanding of the matter of the Universe, we can reconstruct the full density and velocity fields from the galaxies that act as tracer particles. In this paper, we use the simulated halos as proxies for the galaxies. We use a convolutional neural network, a V-net, trained on numerical simulations of structure formation to reconstruct the density and velocity fields. We find that, with detailed tuning of the loss function, the V-net could produce better fits to the density field in the high-density and low-density regions, and improved predictions for the probability distribution of the amplitudes of the velocities. However, the weights will reduce the precision of the estimated $β$ parameter. We also find that the redshift-space distortions of the halo catalogue do not significantly contaminate the reconstructed real-space density and velocity field. We estimate the velocity field $β$ parameter by comparing the peculiar velocities of halo catalogues to the reconstructed velocity fields, and find the estimated $β$ values agree with the fiducial value at the 68\% confidence level.

astro-ph.CO↗

arXiv2022

Comparison of spatial distributions of Intracluster light and Dark Matter

In a galaxy cluster, the relative spatial distributions of dark matter, member galaxies, gas, and intracluster light (ICL) may connote their mutual interactions over the cluster evolution. However, it is a challenging problem to provide a quantitative measure for the shape matching between two multi-dimensional scalar distributions. We present a novel methodology, named the {\em Weighted Overlap Coefficient (WOC)}, to quantify the similarity of 2-dimensional spatial distributions. We compare the WOC with a standard method known as the Modified Hausdorff Distance (MHD). We find that our method is robust, and performs well even with the existence of multiple sub-structures. We apply our methodology to search for a visible component whose spatial distribution resembled with that of dark matter. If such a component could be found to trace the dark matter distribution with high fidelity for more relaxed galaxy clusters, then the similarity of the distributions could also be used as a dynamical stage estimator of the cluster. We apply the method to six galaxy clusters at different dynamical stages simulated within the GRT simulation, which is an N-body simulation using the galaxy replacement technique. Among the various components (stellar particles, galaxies, ICL), the ICL+ brightest cluster galaxy (BCG) component most faithfully trace the dark matter distribution. Among the sample galaxy clusters, the relaxed clusters show stronger similarity in the spatial distribution of the dark matter and ICL+BCG than the dynamically young clusters. While the MHD results show weaker trend with the dynamical stages.

astro-ph.GA↗