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Looking for observational signatures of early binary black hole systems
No full textInternational audienceContext. A lot of recent studies have focused on the observables associated with near merger binary black-holes (BBHs) embedded in a circumbinary disk (CBD) but we still we lack knowledge of observables of BBHs in their early stage. In that stage the separation between the two black holes is so large that both black holes could potentially retain their individual accretion disk existing before the creation of the BBH. For such early BBH systems, it is interesting to look for observables originating in those individual disks whose structure is likely to differ from mini-disks often observed in simulations of later stages of BBHs. Aims. In a companion paper we presented a set of hydrodynamical simulations of an individual disk surrounding a primary black hole while being impacted by the presence of a secondary black-hole in an early BBH system, leading to the creation of three well-known characteristic features in the disk's structure. Here we explore the imprints of these three features on the observables associated with the thermal emission of the pre-existing black hole disk. The aim is two-fold, first to see which observables are best suited for detecting those early systems and, secondly, what could be extrapolated about these systems from observations. Methods. We used general relativistic ray-tracing in order to produce synthetic observations of the thermal emission emitted by early BBHs with different mass ratio and separations in order to search for distinctive observational features of early systems. Results. We found that in the case of early BBH with pre-existing disk(s) a necessary, although not unique, observational feature is the truncation of their disk(s). Conclusions. Such observable could be used for automated search of potential BBHs and discriminate some existing candidates
Distribution trends of soil fauna with different body sizes and feeding habits across altitudinal climate zones on Mount Gongga, China
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The SRG/eROSITA all-sky survey: The morphologies of clusters of galaxies: II. The intrinsic distributions of morphological parameters
No full textInternational audienceX-ray selected surveys of clusters of galaxies have been reported to contain more regular cool core clusters compared to samples selected using the Sunyaev-Zel'dovich (SZ) effect. Morphology population studies on X-ray selected clusters will be biased without taking into account selection, as cool cores are more easily detected at low redshifts, but can be mistaken for point sources at high redshift. eROSITA, aboard SRG, found over 12000 optically-identified clusters in its first survey, eRASS1. Taking account of the selection function obtained from simulations, we obtain using a Bayesian framework the intrinsic distribution of morphological parameters, including the concentration, central density, cuspiness, ellipticity and slosh. We construct scaling relations for the parameters as a function of redshift (z) and luminosity (LX), and study their distribution within z or LX bins. We find that the concentration in a scaled aperture evolves positively with LX, similarly to the central scaled density, and negatively with z. When using a fixed aperture, its evolution with LX is lower, but also dependent on the choice of cluster centre. The mean ellipticity does not significantly evolve with z or LX. eRASS1 clusters show indications of higher concentrations compared to SZ-selected objects, even after taking account the selection; this suggests that if our X-ray selection model is correct SZ-selected clusters may also suffer from morphological selection effects. We compare different parameter distribution models in bins of z and LX. The distribution of concentration and ellipticity is generally consistent with a normal one, but other parameters such as the central density and cuspiness strongly favour more complex distributions. However, modelling of all clusters as a single population generally prefers non-normal distributions. [abridged
Estimating the upper depth of subsurface water on the Greenland Ice Sheet using multi-frequency passive microwave remote sensing, radiative transfer modeling, and machine learning
No full textInternational audienceAs the Arctic warms, surface melt extends into the Greenland Ice Sheet's accumulation zone, where much of the water infiltrates into the snowpack. This makes monitoring the subsurface water depth and spatial extent important for accurate ice sheet runoff estimations. Subsurface water can be detected using remotely sensed microwave brightness temperatures (TB). We use vertically polarized TB at 1.4 GHz from Soil Moisture and Ocean Salinity satellite (SMOS) and at 6.9, 10.7, and 18.7 GHz from the Advanced Microwave Scanning Radiometers (AMSR-E/2) to estimate the upper depth of liquid water (UDLW) on the ice sheet accumulation area. We build a catalogue of simulated UDLW and TB: realistic UDLW are modeled by the Geological Survey of Denmark and Greenland (GEUS) snow model, forced by the Copernicus Arctic Regional Reanalysis (CARRA), and the corresponding TB are calculated by the Snow Microwave Radiative Transfer (SMRT) model at 19 sites. We train on this catalogue an ensemble of cross-validated Random Forest (RF) models to predict UDLW and its uncertainty from TB at four frequencies. On hold-out modeled data and for water within 5 m of the surface, the RF ensemble achieves a median RMSE of 0.68 m and mean error of −0.09 m. Our retrieval, when applied to observed TB, matches within 2 m UDLW inferred from subsurface temperature profiles down to 4–6 m depth. Performances decrease beyond 5 m depth and for low liquid water amounts. Our retrieval produces daily UDLW maps over the ice sheet's accumulation area during 2010–2023 which reveal the seasonal evolution of UDLW, deliver the first quantitative estimates of subsurface liquid water depth on the ice sheet and offer new insights into meltwater infiltration and storage processes
Configurational Energy as a Microstructural Descriptor of Failure Precursors in 2D Frictional Granular Materials
No full textInternational audienceLocalized deformation in dense granular materials, often culminating in the formation of shear bands, is a key failure mechanism in geotechnical and material systems. However, predicting the onset of such localization remains a fundamental challenge due to the system's inherent inelasticity and microstructural complexity. In this study, we propose that the evolution of internal configuration—characterized by changes in contact topology and stored potential energy—governs the collective mechanical response and encodes precursors to material failure. To quantify this evolving internal state, we introduce the notion of configurational energy, defined as the change in contact‐scale elastic potential energy resulting from a controlled loading—unloading probe. This metric is first formulated at the contact level and subsequently analyzed at the specimen scale using Discrete Element Method (DEM) simulations of biaxial compression. Our results demonstrate that configurational energy captures the system's sensitivity to perturbations and reflects local instability: both positive and negative values emerge at the contact level, with large magnitudes concentrated near regions of active rearrangement. Despite this local variability, the specimen‐scale configurational response remains strictly negative, and its magnitude increases systematically as the material approaches failure. Notably, spatial localization of configurational energy precedes the formation of macroscopic shear bands with an evolving internal length scale, offering a mesoscale energetic signature of incipient failure. These findings establish configurational energy as a physically grounded descriptor of microstructural evolution and a promising tool for anticipating failure in frictional granular systems
From Elements to Isotopes: Fingerprinting Consumer Plastics
No full textInternational audiencePolymer identification alone rarely informs on additive provenance or metal interactions. We tested whether multi-element profiles and selected metal isotopes provide complementary and reproducible fingerprints of consumer plastics. We analyzed 119 items spanning major polymers and colors after microwave digestion. Forty-one elements were quantified by ICP-MS; Cu, Sr, and Pb isotope ratios were measured by MC-ICP-MS on selected purified subsets. Elemental concentrations span over eight orders of magnitude (from Rare Earth Elements (REE) at µg kg⁻¹ to Ca at >10 8 µg kg⁻¹). Non-parametric statistics reveal significant polymer and color effects; polypropylene (PP) shows higher Mg, Si, Cr, and Ni than polyethylene (PE), while color modulates Cu and some REE. Strontium isotope ratios vary widely (⁸⁷Sr/⁸⁶Sr = 0.70765-0.71320), consistent with contributions from disparate mineral fillers and pigments. Copper isotopes are systematically enriched in 65 Cu with variable values (δ⁶⁵Cu = +0.18‰ to +1.35‰), supporting the influence of distinct Cu-based pigment formulations. Lead isotope ratios further discriminate legacy Pb-bearing additives observed in a subset of items, consistent with distinct manufacturing and/or recycled streams. Overall, combined elemental-isotopic fingerprints thus provide complementary, integrated and transferable markers of additive provenance beyond spectroscopic polymer identification. These signatures open new avenues for source apportionment and understanding the fate of environmental plastics
Using Mixed-clay Sediment Gravity Flow Rheology as an Indicator for Flow Velocity and Runout Distance
No full textInternational audienceIt is important to determine whether the dynamics of mixed-clay sediment gravity flows (SGFs) can be predicted from their dominant clay type, because natural SGF deposits can contain mixtures of clay minerals of different cohesive strength, and latitudinal zonation in clay mineral production may influence depositional patterns in mud-rich submarine fans. The present lock-exchange experiments produced high-density SGFs carrying different proportions of strongly cohesive bentonite clay and weakly cohesive kaolinite clay with a fixed 20% volumetric concentration. Head velocity and runout distance of the flows decreased, and starting suspension yield stress increased, as the bentonite fraction increased beyond 20%. However, for bentonite fractions ≤20%, the initial suspensions had lower yield stresses and the flows were more mobile than the pure kaolinite flow, implying that small bentonite fractions reduce the cohesive strength of the suspensions. Predictive equations for the yield stress, head velocity, and runout distance of mixed-clay flows, based on yield stresses of pure-clay constituents, indicate minimal interaction between the constituents for bentonite fractions ≤20%. However, for bentonite fractions >20%, the equations demonstrate an increasingly nonlinear interaction. These results suggest natural SGF dynamics and deposits may be sensitive to the most cohesive clay rather than the dominant clay
TGCAT — A Tool to Analyse the Content of Sea Level Data Portals
No full textInternational audienceThe volume of tide gauge data available to the sea level community has grown substantially, with information distributed across numerous global, national, and institutional data centres. As a result, the main challenge is no longer accessing data, but identifying the most relevant dataset for a given application. Currently, more than 15 global data centres provide sea level information, each tailored to different users and use cases (e.g., real‐time monitoring, delayed‐mode analysis, monthly means). For users unfamiliar with tide gauge data, selecting the appropriate source can be difficult. Tide Gauge CATalog (TGCAT) is a software tool developed to address this challenge. It helps users discover where specific tide gauge data are available and assists data providers and centres in identifying inconsistencies, such as misreferenced stations or discrepancies in metadata. TGCAT collects metadata from global and national sea level data centres to produce intercomparable catalogues. It also allows visualisation of data availability timelines across multiple sources. Written entirely in Python and linked to an online dashboard ( www.sonel.org/tgcat ), TGCAT is designed as an open, community‐based platform. Its goal is to improve data discoverability, support better referencing practices, and help users navigate the complex landscape of tide gauge data portals
Nonconservative Lie series: post-Newtonian binary dynamics at 2.5PN
No full textInternational audienceWe present a fully analytical solution to the dynamics of the non-spinning 2.5 post-Newtonian binary problem, accounting for both the long-term (secular) and short-term (oscillatory) temporal behavior, with no restriction on eccentricity. The radiative degrees of freedom are handled within the nonconservative Hamiltonian framework introduced in a companion paper. In this work, we apply the Lie series method to construct a resonant Birkhoff normal-form and the corresponding generator of the radiation-reaction dynamics. The secular piece reconstructs exactly the Peters-Mathews relations for semi-major axis and eccentricity. The oscillatory piece completes the dynamics and is well suited for gravitational wave templates. The procedure we present in this paper can be systematically employed to cast arbitrary nonconservative systems into extended Hamiltonian form so that the Lie method can be applied
