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Generative Models of 21cm EoR Lightcones with 3D Scattering Transforms
No full textInternational audienceThe 21cm signal from the Epoch of Reionization (EoR) is observed as a three-dimensional data set known as a lightcone, consisting of a redshift (frequency) axis and two spatial sky plane axes. When observed by radio interferometers, this EoR signal is strongly obscured by foregrounds that are several orders of magnitude stronger. Due to its inherently non-Gaussian nature, the EoR signal requires robust statistical tools to accurately separate it from these foreground contaminants, but current foreground separation techniques focus primarily on recovering the EoR power spectrum, often neglecting valuable non-Gaussian information. Recent developments in astrophysics, particularly in the context of the Galactic interstellar medium, have demonstrated the efficacy of scattering transforms - novel summary statistics for highly non-Gaussian processes - for component separation tasks. Motivated by these advances, we extend the scattering transform formalism from two-dimensional data sets to three-dimensional EoR lightcones. To this end, we introduce a 3D wavelet set from the tensor product of 2D isotropic wavelets in the sky plane domain and 1D wavelets in the redshift domain. As generative models form the basis of component separation, our focus here is on building and validating generative models that can be used for component separation in future projects. To achieve this, we construct maximum entropy generative models to synthesise EoR lightcones, and statistically validate the generative model by quantitatively comparing the synthesised EoR lightcones with the single target lightcone used to construct them, using independent statistics such as the power spectrum and Minkowski Functionals. The synthesised lightcones agree well with the target lightcone both statistically and visually, opening up the possibility of developing for component separation methods using 3D scattering transforms
Euclid: An emulator for baryonic effects on the matter bispectrum
No full textInternational audienceThe Euclid mission and other next-generation large-scale structure surveys will enable high-precision measurements of the cosmic matter distribution. Understanding the impact of baryonic processes such as star formation and AGN feedback on matter clustering is crucial to ensure precise and unbiased cosmological inference. Most theoretical models of baryonic effects to date focus on two-point statistics, neglecting higher-order contributions. This work develops a fast and accurate emulator for baryonic effects on the matter bispectrum, a key non-Gaussian statistic in the nonlinear regime. We employ high-resolution -body simulations from the BACCO suite and apply a combination of cutting-edge techniques such as cosmology scaling and baryonification to efficiently span a large cosmological and astrophysical parameter space. A deep neural network is trained to emulate baryonic effects on the matter bispectrum measured in simulations, capturing modifications across various scales and redshifts relevant to Euclid. We validate the emulator accuracy and robustness using an analysis of \Euclid mock data, employing predictions from the state-of-the-art FLAMINGO hydrodynamical simulations. The emulator reproduces baryonic suppression in the bispectrum to better than 2 for the percentile across most triangle configurations for and ensures consistency between cosmological posteriors inferred from second- and third-order weak lensing statistics
The Online Data Filter for the KM3NeT Neutrino Telescopes
No full textInternational audienceThe KM3NeT research infrastructure comprises two neutrino telescopes located in the deep waters of the Mediterranean Sea, namely ORCA and ARCA. KM3NeT/ORCA is designed for the measurement of neutrino properties and KM3NeT/ARCA for the detection of high\nobreakdashes-energy neutrinos from the cosmos. Neutrinos are indirectly detected using three\nobreakdashes-dimensional arrays of photo\nobreakdashes-sensors which detect the Cherenkov light that is produced when relativistic charged particles emerge from a neutrino interaction. The analogue pulses from the photo\nobreakdashes-sensors are digitised offshore and all digital data are sent to a station on shore where they are processed in real time using a farm of commodity servers and custom software. In this paper, the design and performance of the software that is used to filter the data are presented. The performance of the data filter is evaluated in terms of its purity, capacity and efficiency. The purity is measured by a comparison of the event rate caused by muons produced by cosmic ray interactions in the Earth's atmosphere with the event rate caused by the background from decays of radioactive elements in the sea water and bioluminescence. The capacity is measured by the minimal number of servers that is needed to sustain the rate of incoming data. The efficiency is measured by the effective volumes of the sensor arrays
Climate shocks and banking sector stability: Evidence from El Niño southern oscillation
No full textInternational audienceThis study introduces a novel ex ante approach to assess the short-term impact of climate shocks on banking sector stability by examining the effect of El Niño Southern Oscillation (ENSO) on banking sector distance-to-default. Using dynamic panel data econometric modeling, we investigate the macroeconomic implications of ENSO-induced climate shocks, such as El Niño and La Niña events, on banking sector stability in 51 countries across three regions particularly exposed to the consequences of ENSO oscillations (East Asia and Pacific, Latin America and the Caribbean, and Sub-Saharan Africa) during the period 2000–2020. Our findings show that the adverse effects of these climate shocks on banking sector stability are unevenly distributed among countries, with more pronounced and robust adverse effects of El Niño events in the short-term, particularly in Latin America and the Caribbean and, to a lesser extent, Sub-Saharan Africa. We also document the short-term adverse effects of La Niña events for Latin American and the Caribbean countries. Further estimates suggest that the increase in non-performing loans is a key transmission channel linking El Niño events to banking sector stability. As global warming should intensify the frequency and magnitude of ENSO's cyclical pattern, these findings can help estimate the potential adverse effects of climate change-related natural disasters on banking sector stability and inform future mitigation and adaptation policies
Integrating problem structuring methods with formal design theory: collective water management policy design in Tunisia
No full textInternational audienceGroundwater management, especially in Mediterranean regions such as Tunisia, is challenging due to diverse stakeholder interests and the arid climate, which makes the sustainability of water resources extremely difficult. This paper proposes an innovative approach to the design of decision and policy alternatives by combining Problem Structuring Methods (PSMs) and the participatory tool based on the Concept-Knowledge (C-K) theory, named Policy-Knowledge, Concepts, Proposals (P-KCP). In a multi-methodological perspective, using Cognitive Maps and Value Trees in combination with P-KCP, the study aims to innovatively generate alternatives to address the sustainability issue of the case study, namely collective groundwater management. The paper provides a practical and adaptable guide to fostering innovation for policy design and generation of alternatives. By bridging decision theory and design theory, the study addresses the methodological gap in alternatives generation and highlights the role of C-K theory for supporting innovative design processes. Integrating PSMs and C-K theory, the multi-methodology advocates participatory approaches to address complex sustainability challenges, provides an adaptable, replicable tool, and encourages the creation of unconventional solutions. Ultimately, this paper offers new collective practices for groundwater management, expanding the set of alternatives through the integration of PSMs and C-K theory and reflecting on the applied multi-methodology
Localizing the Ising CFT from the ground state of the Ising model on the fuzzy sphere
No full textInternational audienceWe locate the phase-transition line for the Ising model on the fuzzy sphere from a finite-size scaling analysis of its ground-state energy. This is similar to what was used to locate the complex CFT of the 5-state Potts model in dimension [PRL 133 (2024) 077101]. There it was shown that a CFT is characterized by a stationarity condition for the measured effective central charge. Our strategy is to write the ground-state energy as , and to search for a minimum of as a function of the couplings. This procedure finds the critical curve of [PRX 13 (2023) 021009] with good precision, and their sweet spot as well. We find similar results when normalizing by the gap to the stress tensor tensor or first parity-odd operator
Pigment‐Macromolecule Complexes Isolation from Sea Urchin Biomineral Waste for Coloring Materials
No full textInternational audienceThe production and widespread use of synthetic pigments and dyes have significant environmental and health impacts. Despite this, synthetic colorants remain dominant due to their wide color range, high stability, strong tinting power, and lower cost compared to natural alternatives. Therefore, to offer sustainable and competitive substitutes, eco‐friendly methods for producing bio‐based pigments with similar performance are essential. Herein, a methodology has been developed to extract the entire colored organic fraction occluded within seashell biomineral waste, which comprises pigments and pigment‐macromolecule complexes. This process involves an optimized cleaning procedure of the biomineral soft tissues, a tailored biochemical extraction, and detailed characterization of the extracted fraction. Applied to sea urchin skeletons, this method successfully isolates polyhydroxylated naphthoquinone (PHNQ)‐macromolecule complexes. These complexes show superior pH stability in purple hues compared to free PHNQ, which shifts from red to purple in basic conditions. Notably, the approach enhances colorant yield by up to five times. These results, together with mineral pigment synthesis and fabric dyeing assays performed with the extracted colored organic fraction, contribute to a better understanding of the origin of color in biominerals and reveal the versatility of these natural pigments for environmentally friendly coloring of both organic and inorganic materials
Euclid Quick Data Release (Q1). First Euclid statistical study of galaxy mergers and their connection to active galactic nuclei
No full textInternational audienceGalaxy major mergers are indicated as one of the principal pathways to trigger active galactic nuclei (AGN). We present the first statistical analysis of the major merger and AGN connection in the Euclid Deep Fields, and showcase the statistical power of the Euclid data. We constructed a stellar-mass-complete (M_⋆>10^ M_⊙) sample of galaxies from the quick data release (Q1) in the redshift range z=0.5--2. We selected AGN using X-ray detections, optical spectroscopy, and mid-infrared (MIR) colours, and by processing observations with an image decomposition algorithm. We used convolutional neural networks trained on cosmological hydrodynamic simulations to classify galaxies as mergers and non-mergers. We found a larger fraction of AGN in mergers compared to the non-merger controls for all AGN selections, with AGN excess factors ranging from two to six. The largest excess we observed was in the MIR AGN. Likewise, a generally larger merger fraction (f_̊m merg) was seen in active galaxies than in the non-active controls, with the excess depending on the AGN selection method. Furthermore, we analysed f_̊m merg as a function of the AGN bolometric luminosity (L_̊m bol) and the contribution of the point-source component to the total galaxy light in the IE-band (f_ PSF ) as a proxy for the relative AGN contribution fraction. We uncovered a rising f_̊m merg, with an increasing f_ PSF up to f_ PSF ≃ 0.55, after which we observed a decreasing trend. In the range f_ PSF = 0.3--0.7, mergers appear to be the dominant AGN fuelling mechanism. We then derived the point-source luminosity (L_ PSF ) and showed that f_̊m merg monotonically increases as a function of L_ PSF at z<0.9, with f_ ̊m merg ≥50% for L_ PSF ≃ 2 . Similarly, at , f_̊m merg rises as a function of L_ PSF though mergers do not dominate until L_ PSF ≃ 10^ . For the X-ray and spectroscopically detected AGN, we derived the bolometric luminosity, L_ bol, which has a positive correlation with f_ merg for X-ray AGN, while there is a less pronounced trend for spectroscopically selected AGN due to the smaller sample size. At L_ bol AGN mostly reside in mergers. We conclude that mergers are most strongly associated with the most powerful and dust-obscured AGN, which are typically linked to a fast-growing phase of the supermassive black hole, while other mechanisms, such as secular processes, might be the trigger of less luminous and dominant AGN.</jats:p
Transfer learning for wind speed forecasting: A scalable approach for data-scarce environments
No full textInternational audienceAccurate wind speed forecasting plays a central role in the integration of wind energy into modern power systems. However, in many regions, the deployment of data-driven models is limited by the scarcity of historical wind measurements. This study investigates the potential of transfer learning (TL) to address this issue by reusing models trained on data-rich locations to forecast wind speed in underinstrumented sites. Using a dataset from 70 meteorological stations across Spain, spanning diverse climatic conditions, we compared TL with conventional direct learning (DL) using Extreme Learning Machine (ELM) and Autoregressive (AR) models. Forecasts were performed over horizons ranging from 30 minutes to 6 hours and evaluated using normalized Root Mean Squared Error (nRMSE) and normalized Mean Absolute Error (nMAE). Across 4,830 TL experiments, results show that TL achieves forecast accuracy close to that of DL, with average nRMSE ranging from 0.297 (TL) to 0.292 (DL) for 30-minute horizons, and from 0.674 to 0.640 for 360-minute forecasts. These findings confirm that TL is a robust and scalable approach for wind speed forecasting in data-scarce environments. The methodology opens promising avenues for the deployment of forecasting tools in regions where traditional data-driven models remain inapplicable due to limited local measurements
High alpine preglacial caves modified by glacial processes and late condensationcorrosion in the Scerscen Valley (Valmalenco, Western Alps, Italy)
No full textInternational audienceThe Scerscen Valley (western Italian Alps) is home to caves at an altitude of around 2600 m, opening close to the Speleogenesis edge of a glacier. The aim of the research as part of a multi-disciplinary project was to reconstruct the evolution Alpine Cosmogenic GeomorphologyHydrogeologyglaciersburial dating of cosmonucleide some the of caves the related most burial recent to dating, the processes, geological recorded such and morphology paleoenvironmental as condensation-corrosion and micrometeorology, evolution and of sediment the carried area deposition. and out mineralogical to evaluate We the performed identifirole of cation by XRD, and hydrogeology using dye tracing and physical and chemical analyses. The cosmonucleide dating of quartz pebbles showed that the Veronica Cave is the oldest, with deposits dated at 1.3 ± 0.4 Ma, and possibly even older. It certainly formed at a much lower altitude (approx. 1300 m a.s.l. or lower) during the Alpine uplift. The Morgana and Marsooi caves, given the smaller volume of their phreatic conduits (1/3 of Veronica), are possibly more recent, formed during interglacials and evolved close to a glacial body. The caves initiated in dolomitic marble under the influence of sulfuric acid speleogenesis (SAS) due to pyrite oxidation. The conduits were then enlarged dramatically under phreatic conditions. The caves have evolved since their preglacial formation, with phases of filling by fluvio-glacial sediments and unclogging. Water tracing and physico-chemical analysis attest to a well-karstified aquifer, with rapid water circulation (>20 m/h) and low temperatures (~2 °C), draining towards the main spring, "La Prediletta", located at the foot of the dolomitic marbles. Microclimatic records (cave temperature and humidity) show seasonal cycles of condensation and evaporation, influenced by air exchanges with the outside atmosphere. These processes contributed to the formation of secondary minerals by evaporation (gypsum, hydromagnesite…) and, above all, to the significant enlargement of passages by the retreat of walls with characteristic morphologies (facets and grooved walls). The Scerscen caves bear witness to a long geological and climatic history, from their formation before the Mid-Pleistocene ice ages to their present-day evolution. They offer valuable insights into karst processes in the high mountains, and interactions between glaciers and aquifers