Current test-time scaling (TTS) techniques enhance large language model (LLM) performance by allocating additional computation at inference time, yet they remain insufficient for agentic settings, where actions directly interact with external environments and their effects can be irreversible and costly. We propose ARTIS, Agentic Risk-Aware Test-Time Scaling via Iterative Simulation, a framework that decouples exploration from commitment by enabling test-time exploration through simulated interactions prior to real-world execution. This design allows extending inference-time computation to improve action-level reliability and robustness without incurring environmental risk. We further show that naive LLM-based simulators struggle to capture rare but high-impact failure modes, substantially limiting their effectiveness for agentic decision making. To address this limitation, we introduce a risk-aware tool simulator that emphasizes fidelity on failure-inducing actions via targeted data generation and rebalanced training. Experiments on multi-turn and multi-step agentic benchmarks demonstrate that iterative simulation substantially improves agent reliability, and that risk-aware simul
The unprecedented statistical power of galaxy cluster catalogs from the SRG (Spectrum Roentgen Gamma)/eROSITA All-Sky Survey provides a unique opportunity to place stringent constraints on cosmological models through measurements of structure growth. Fully exploiting the potential of these large X-ray-selected cluster samples, however, requires robust statistical frameworks that accurately connect observable quantities to the underlying cosmological parameters. We develop and implement a simulation-based inference (SBI) framework for cosmological parameter estimation using a realistic mock-generation pipeline calibrated on eRASS1 simulations. Synthetic galaxy cluster catalogs are propagated through the survey selection function to produce mock eRASS1 observations that reproduce the data's statistical properties. At the core of the method lies a set-based neural network (GNN on sets) that encodes information from individual clusters and is coupled to a masked autoregressive flow for flexible posterior density estimation. This approach enables the use of the full cluster-level information content without compressing the observables into binned summary statistics. Our framework recove
The world is full of systems of distributed agents, collaborating and competing in complex ways: firms and workers specialise within economies, neurons adapt their tuning across brain circuits, and species compete and coexist within ecosystems. In that context, individual research fields built theories explaining how comparative advantage drives trade specialisation, how balanced neural representations emerge from sensory coding, and how biodiversity sustains ecological productivity. Here we propose that many of these well-understood findings across fields can be captured in one simple joint cross-disciplinary model, which we call the Distributed Production System. It captures how agent heterogeneity, resource constraints, communication topology, and task structure jointly determine the productivity, efficiency, and robustness of distributed systems across biology, economics, neuroscience, and computing. This model reveals that a small set of underlying laws generates the complex dynamics observed across fields. These can be summarised in our Principle of Maximum Heterogeneity: any distributed production system optimising for performance will converge on an increasingly heterogeneo
The detection of the extended X-ray-emission of the intracluster medium by the first SRG/eROSITA All-Sky Survey (eRASS1), combined with optical and near-infrared follow-up, resulted in the identification of more than 12000 galaxy clusters, yielding precise constraints on cosmological parameters. However, some clusters of galaxies can be misclassified as point sources by eROSITA's source detection algorithm due to the interplay between the point-spread function, the shallow depth of the survey, compact (cool core) X-ray emission, and bright active galactic nuclei hosted in their centers or their vicinity. To identify such misclassified galaxy clusters and groups, we apply optical follow-up to the eRASS1 X-ray point sources analogously to the treatment of the extent-selected catalog. After rigorous filtering to ensure purity, we find a total of 8347 clusters of galaxies, of which 5819 are novel detections, in a redshift range $0.05 < z \lesssim 1.1$. This corresponds to a 70 % discovery rate, a fraction similar to that of the extent-selected sample. To facilitate finding new exceptional clusters such as the Phoenix cluster (which is recovered in our sample), we divide the clusters
The soft X-ray telescope on board the Spectrum-Roentgen-Gamma (SRG) mission, eROSITA (extended ROentgen Survey with an Imaging Telescope Array), has produced the largest sample to date of galaxy groups and clusters detected via their intracluster/intragroup medium (ICM/IGrM) emission. Scaling relations between the intrinsic properties of these systems provide valuable insight into their formation and evolution. In this work, we investigate the scaling relations between key physical properties, such as soft band X-ray luminosity, temperature, gas mass, and the low-scatter mass proxy $Y_{\rm X}$, for the galaxy groups and clusters detected in the first eROSITA All-Sky Survey (eRASS1). Our analysis fully accounts for selection effects and the redshift evolution of the observable distributions. We construct a high-purity sample of $3061$ galaxy groups and clusters spanning the redshift range $0.05<z<1.07$ and mass range of $1.1\times10^{13}<M_{500}/$M$_{\odot}<1.6\times10^{15}$. This represents the largest sample to date used for scaling relation analysis. The selection function, derived from state-of-the-art simulations of the eROSITA sky, is rigorously incorporated into o
We present the weak-lensing mass calibration and constrain the BCG (brightest cluster galaxy) stellar-mass-to-halo-mass-and-redshift ($M_{\star,\mathrm{BCG}}-M-z$) relation for a sample of $124$ galaxy clusters and groups at redshift $0.1<z<0.8$ from the first Data Release of the $eROSITA$ All-Sky Survey (eRASS1), using data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program. The cluster survey is conducted by the $eROSITA$ X-ray telescope aboard the Spectrum-Roentgen-Gamma (SRG) space observatory. The cluster sample is X-ray-selected and optically confirmed with a negligibly low contamination rate ($\approx5%$). On a basis of individual clusters, the shear profiles of $96$ clusters are derived using the HSC Three-Year (HSC-Y3) weak-lensing data, while the BCG stellar masses of $101$ clusters are estimated using the SED template fitting to the HSC five-band ($grizY$) photometry. The observed X-ray photon count rate is used as the mass proxy, based on which individual halo masses are obtained at the given count rate in a population modelling while accounting for systematic uncertainties in the weak-lensing modelling through a simulation-calibrated weak-lensing mass-to-h
In this paper, we model the locations of five major banks in mainland France, two lucrative and three cooperative institutions based on socio-economic considerations. Locations of banks are collected using web scrapping and constitute a bivariate spatial point process for which we estimate nonparametrically summary functions (intensity, Ripley and cross-Ripley's K functions). This shows that the pattern is highly inhomogenenous and exhibits a clustering effect especially at small scales, and thus a significant departure to the bivariate (inhomogeneous) Poisson point process is pointed out. We also collect socio-economic datasets (at the living area level) from INSEE and propose a parametric modelling of the intensity function using these covariates. We propose a group-penalized bivariate composite likelihood method to estimate the model parameters, and we establish its asymptotic properties. The application of the methodology to the banking dataset provides new insights into the specificity of the cooperative model within the sector, particularly in relation to the theories of institutional isomorphism.
We propose ARTI-6, a compact six-dimensional articulatory speech encoding framework derived from real-time MRI data that captures crucial vocal tract regions including the velum, tongue root, and larynx. ARTI-6 consists of three components: (1) a six-dimensional articulatory feature set representing key regions of the vocal tract; (2) an articulatory inversion model, which predicts articulatory features from speech acoustics leveraging speech foundation models, achieving a prediction correlation of 0.87; and (3) an articulatory synthesis model, which reconstructs intelligible speech directly from articulatory features, showing that even a low-dimensional representation can generate natural-sounding speech. Together, ARTI-6 provides an interpretable, computationally efficient, and physiologically grounded framework for advancing articulatory inversion, synthesis, and broader speech technology applications. The source code and speech samples are publicly available.
The hot gas in the outskirts of galaxy cluster-sized halos, extending around and beyond the virial radius into nearby accretion regions, remains among one of the least explored baryon components of the large-scale cosmic structure. We present a stacking analysis of 680 galaxy clusters located in the western Galactic hemisphere, using data from the first two years of the SRG/eROSITA All-Sky Survey. The stacked X-ray surface brightness (SB) profile reveals a statistically significant signal extending out to 2 r_200m (~4.5 Mpc). The best-fit SB profile is well described by a combination of terms describing orbiting and infalling gas, with a transition occurring around r_200m. At this radius, the gas number density corresponds to a baryon overdensity of about 30. By integrating the density profile out to r_200m, we inferred a gas fraction exceeding the universal baryon fraction, assuming a typical halo concentration. However, correcting for possible clumping effects reduces the baryon fraction by more than 20%. Additionally, we examined the distribution of hot gas in massive clusters in the IllustrisTNG simulations, from the halo center to the accretion region. This analysis reveals di
Ultralight axions are hypothetical scalar particles that influence the evolution of large-scale structures of the Universe. Depending on their mass, they can potentially be part of the dark matter component of the Universe as candidates commonly referred to as fuzzy dark matter. While strong constraints have been established for pure fuzzy dark matter models, the more general scenario where ultralight axions constitute only a fraction of the dark matter has been limited to only a few observational probes. In this work, we use the galaxy cluster number counts obtained from the first All-Sky Survey (eRASS1) of the SRG/eROSITA mission together with gravitational weak lensing data from the Dark Energy Survey, the Kilo-Degree Survey, and the Hyper Suprime-Cam to constrain the fraction of ultralight axions in the mass range $10^{-32}$ eV to $10^{-24}$ eV. We put upper bounds on the ultralight axion relic density $Ω_\mathrm{a}$ in independent logarithmic axion mass bins by performing a full cosmological parameter inference. We find an exclusion region in the intermediate ultralight axion mass regime with the tightest bounds reported so far in the mass bins around $m_\text{a} = 10^{-27}$ e
Characterising galaxy cluster populations from catalog of sources selected in astronomical surveys requires knowledge of sample incompleteness, known as selection function. The first All-Sky Survey (eRASS1) by eROSITA onboard Spectrum Roentgen Gamma (SRG) has enabled the collection of large samples of galaxy clusters detected in the soft X-ray band over the Western Galactic hemisphere. The driving goal consists in constraining cosmological parameters, which puts stringent requirements on accuracy, flexibility and explainability of the selection function models. We use a large set of mock observations of the eRASS1 survey and we process simulated data identically to the real eRASS1 events. We match detected sources to simulated clusters and we associate detections to intrinsic cluster properties. We train a series of models to build selection functions depending only on observable surface brightness data. We develop a second series of models relying on global cluster characteristics such as X-ray luminosity, flux, and expected instrumental count-rate as well as on morphological properties. We validate our models using our simulations and we rank them according to selected performanc
The cluster mass function traces the growth of linear density perturbations and provides valuable insights into the growth of structures, the nature of dark matter, and the cosmological parameters governing the Universe. The primary science goal of eROSITA, on board the {\it Spectrum Roentgen Gamma (SRG)} mission, launched in 2019, is to constrain cosmology through the evolution of cluster mass function. In this paper, we present the cosmological constraints obtained from 5259 clusters of galaxies detected over an area of 12791~deg$^2$ in the Western Galactic Hemisphere of the eROSITA's first All-Sky Survey (eRASS1). The common footprint region between the eROSITA Survey and DES, KiDS, and HSC surveys is used for calibration of the scaling between X-ray count rate and their total mass through measurements of their weak gravitational lensing signal. eRASS1 cluster abundances constrain the $Λ$CDM parameters, which are the energy density of the total matter to $Ω_{\mathrm{m}}=0.29^{+0.01}_{-0.02}$, and the normalization of the density fluctuations to $σ_8=0.88\pm0.02$ and their combination yields $S_8=σ_8 (Ω_\mathrm{m} / 0.3)^{0.5}=0.86\pm0.01$, consistent and at a similar precision w
Beyond testing the current cosmological paradigm, cluster number counts can also be utilized to investigate the discrepancies currently affecting current cosmological measurements. In particular, cosmological studies based on cosmic shear and other large-scale structure probes routinely find a value of the amplitude of the fluctuations in the universe S8 smaller than the one inferred from the primary cosmic microwave background. In this work, we investigate this tension by measuring structure evolution across cosmic time as probed by the number counts of the massive halos with the first SRG/eROSITA All-Sky Survey cluster catalog in the Western Galactic Hemisphere complemented with the overlapping Dark Energy Survey Year-3, KiloDegree Survey, and Hyper Suprime-Cam data for weak lensing mass calibration, by implementing two different parameterizations and a model-agnostic method. In the first model, we measure the cosmic linear growth index as γ = 1.19 \pm 0.21, in tension with the standard value of γ = 0.55, but in good statistical agreement with other large-scale structures probes. The second model is a phenomenological scenario in which we rescale the linear matter power spectrum
The spatial distribution of galaxy clusters provides a reliable tracer of the large-scale distribution of matter in the Universe. The clustering signal depends on intrinsic cluster properties and cosmological parameters. The ability of eROSITA onboard Spectrum-Roentgen-Gamma (SRG) to discover galaxy clusters allows probing the association of extended X-ray emission to dark matter haloes. We aim to measure the projected two-point correlation function to study the occupation of dark matter halos by clusters and groups detected by the first eROSITA all-sky survey (eRASS1). We create five volume-limited samples probing clusters with different redshift and X-ray luminosity. We interpret the correlation function with halo occupation distribution (HOD) and halo abundance matching (HAM) models. We simultaneously fit cosmological parameters and halo bias of a flux-limited sample of 6493 clusters with purity > 96%. Results. We obtain a detailed view of the halo occupation for eRASS1 clusters. The fainter population at low redshift (S0: LX = 4.63E43 erg/s, 0.1 < z < 0.2) is the least biased compared to dark matter, with b = 2.95 $\pm$ 0.21. The brightest clusters up to higher redshif
Clusters of galaxies can be used as powerful probes to study astrophysical processes on large scales, test theories of the growth of structure, and constrain cosmological models. The driving science goal of the SRG/eROSITA All-Sky Survey (eRASS) is to assemble a large sample of X-ray-selected clusters with a well-defined selection function to determine the evolution of the mass function and, hence, the cosmological parameters. We present here a catalog of 12247 optically confirmed galaxy groups and clusters detected in the 0.2-2.3 keV as extended X-ray sources in a 13,116deg$^2$ region in the western Galactic hemisphere of the sky, which eROSITA surveyed in its first six months of operation. The clusters in the sample span the redshift range $0.003<z<1.32$. The majority (68%) of these clusters, 8361 sources, represent new discoveries without known counterparts in the literature. The mass range of the sample covers three orders of magnitude from $5\times10^{12}M_{\rm sun}$ to $2\times10^{15}M_{\rm sun}$. We construct a sample for cosmology with a higher purity level (~95%) than the primary sample, comprising 5259 securely detected and confirmed clusters in the 12791deg$^{2}$ c
This paper presents an experimental study on radio frequency (RF) fingerprinting of Bluetooth Classic devices. Our research aims to provide a practical evaluation of the possibilities for RF fingerprinting of everyday Bluetooth connected devices that may cause privacy risks. We have built an experimental setup for recording Bluetooth connection in a radio frequency isolated environment using commercially available SDR (software defined radio) systems, extracted fingerprints of the Bluetooth radio data in the form of carrier frequency offset and scaling factor from 6 different devices, and performed k-nearest neighbors (kNN) classification achieving 84\% accuracy. The experiment demonstrates that no matter what privacy measures are being taken in the protocol layer, the physical layer leaks significant information about the device to unauthorized listeners. In the context of the ever-growing Bluetooth device market, this research serves as a clarion call for device manufacturers, regulators, and end-users to acknowledge the privacy risks posed by RF fingerprinting and lays a foundation for more sizeable Bluetooth fingerprinting analysis research.
The first SRG/eROSITA All-Sky Survey (eRASS1) provides the largest intracluster medium-selected galaxy cluster and group catalog covering the western galactic hemisphere. Compared to samples selected purely on X-ray extent, the sample purity can be enhanced by identifying cluster candidates using optical and near-infrared data from the DESI Legacy Imaging Surveys. Using the red-sequence-based cluster finder eROMaPPer, we measured individual photometric properties (redshift $z_λ$, richness $λ$, optical center, and BCG position) for 12,000 eRASS1 clusters over a sky area of 13,116 deg$^2$, augmented by 247 cases identified by matching the candidates with known clusters from the literature. The median redshift of the identified eRASS1 sample is $z=0.31$, with 10% of the clusters at $z>0.72$. The photometric redshifts have an accuracy of $δz/(1+z)<0.005$ for $0.05<z<0.9$. Spectroscopic cluster properties (redshift $z_{\rm spec}$ and velocity dispersion $σ$) are measured a posteriori for a subsample of 3,210 and 1,499 eRASS1 clusters, respectively, using an extensive compilation of spectroscopic redshifts of galaxies from the literature. We infer that the primary eRASS1 samp
The properties of the warm-hot intergalactic medium (WHIM) in cosmic filaments are among the least quantified units in modern astrophysics. The Spectrum Roentgen Gamma/eROSITA All Sky Survey ((SRG/eRASS) provides a unique opportunity to study the X-ray emission of the WHIM. We applied both imaging and spectroscopic stacking techniques to the data of the first four eRASS scans to inspect the X-ray emissions from 7817 cosmic filaments identified from Sloan Digital Sky Survey (SDSS) optical galaxy samples. We obtained a $9σ$ significant detection of the total X-ray signal from filaments in the 0.3--1.2~keV band. Here, we introduce a novel method to estimate the contamination fraction from unmasked X-ray halos, active galactic nuclei, and X-ray binaries associated with filament galaxies. We found an approximately 40\% contamination fraction for these unmasked sources, suggesting that the remaining 60\% of the signal could be coming from the WHIM and a $5.4σ$ detection significance of the WHIM. Moreover, we modeled the temperature and baryon density contrast of the detected WHIM by fitting the stacked spectrum and surface brightness profile. The best-fit temperature $\log(T/\mathrm{K})=
Odd radio circles (ORCs) are a newly discovered class of extended faint radio sources of unknown origin. We report the first detection of diffuse X-ray gas at the location of a low-redshift ORC (z=0.046) known as Cloverleaf ORC. This observation was performed with the XMM-Newton X-ray telescope. The physical extent of the diffuse X-ray emission corresponds to a region of approximately 230 kpc by 160 kpc, lying perpendicular to the radio emission detected by ASKAP. The X-ray spectrum shows characteristics of thermal multiphase gas with temperatures of 1.10+/-0.08 keV and 0.22+/-0.01 keV and a central density of $(4.9\pm0.6)\times10^{-4}$ cm$^{-3}$, indicating that the Cloverleaf ORC resides in a low-mass galaxy group. Using X-ray observations, with hydrostatic equilibrium and isothermal assumptions, we measure the galaxy group to have a gas mass and a total mass of $(7.7\pm 0.8) \times 10^{11}$ M$_{\rm sun}$ and $2.6\pm0.3\times10^{13}$~$M_{\rm sun}$ within the overdensity radius R$_{500}$. The presence of a high-velocity subgroup identified in optical data, the orientation of the brightest cluster galaxy, the disturbed morphologies of galaxies toward the east of the Cloverleaf ORC,
We investigate the impact of AGN feedback, on the entropy and characteristic temperature measurements of galaxy groups detected in the SRG/eROSITA's first All-Sky Survey (eRASS1) to shed light on the characteristics of the feedback mechanisms. We analyze deeper eROSITA observations of 1178 galaxy groups detected in eRASS1. We divide the sample into 271 subsamples and extract average thermodynamic properties, including electron density, temperature, and entropy at three characteristic radii along with the integrated temperature by jointly analyzing X-ray images and spectra following a Bayesian approach. We present the tightest constraints on the impact of AGN feedback through our average entropy and characteristic temperature measurements of the largest group sample used in X-ray studies, incorporating major systematics in our analysis. We find that entropy shows an increasing trend with temperature in the form of a power-law-like relation at the higher intra-group medium temperatures, while for the low mass groups, a slight flattening is observed on the average entropy. Overall, the observed entropy measurements agree well with the earlier measurements in the literature. The compar