HAL-OBSPM
Not a member yet
37663 research outputs found
Sort by
Climate change impacts on Robusta coffee production in Vietnam
No full textInternational audienceThe Central Highlands of Vietnam is the largest Robusta coffee ( Coffea canephora Pierre ex A.Froehner) growing region in the world. This study identifies the most important climatic variables that determine the current distribution of coffee in the Central Highlands and builds a ‘coffee suitability’ model to assess changes in this distribution due to climate change scenarios. A neural network-based suitability model was trained on coffee occurrence data derived from national statistics on coffee-growing areas. Bias-corrected regional climate models, adjusted to reduce systematic deviations from observed patterns, were used for two climate change scenarios (RCP8.5 and RCP2.6) to assess changes in suitability for three future time periods (2038–2048, 2059–2069, 2060–2070) relative to the 2009–2019 baseline. Average expected losses in suitable areas were 62% and 27% for RCP8.5 and RCP2.6, respectively. The loss in suitability due to RCP8.5 is particularly pronounced after 2060. Increasing mean minimum temperature during the harvest (October–November) and growing season (March–September), and decreasing precipitation during the late growing season (July–September) mainly determined the loss in suitable areas. Given these risks, adaptation strategies such as shade management, soil conservation, and the development of climate-resilient varieties are essential to sustain coffee production in the region
Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks
No full textInternational audienceStrong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust, automated methods capable of handling the immense data volume generated. In this work, we present an advanced deep learning (DL) framework based on mask region-based convolutional neural networks (Mask R-CNNs), designed to autonomously detect and segment bright, strongly-lensed arcs in Euclid's multi-band imaging of galaxy clusters. The model is trained on a realistic simulated data set of cluster-scale SL events, constructed by injecting mock background sources into Euclidised Hubble Space Telescope images of 10 massive lensing clusters, exploiting their high-precision mass models constructed with extensive spectroscopic data. The network is trained and validated on over 4500 simulated images, and tested on an independent set of 500 simulations, as well as real Euclid Quick Data Release (Q1) observations. The trained network achieves high performance in identifying gravitational arcs in the test set, with a precision and recall of 76% and 58%, respectively, processing 2'x2' images in a fraction of a second. When applied to a sample of visually confirmed Euclid Q1 cluster-scale lenses, our model recovers 66% of gravitational arcs above the area threshold used during training. While the model shows promising results, limitations include the production of some false positives and challenges in detecting smaller, fainter arcs. Our results demonstrate the potential of advanced DL computer vision techniques for efficient and scalable arc detection, enabling the automated analysis of SL systems in current and future wide-field surveys. The code, ARTEMIDE, is open source and will be available at github.com/LBasz/ARTEMIDE
Parameterizing Noise Covariance in Maximum-Likelihood Component Separation
No full textInternational audienceWe introduce a noise-aware extension to the parametric maximum-likelihood framework for component separation by modeling correlated noise as a harmonic-space power law. This approach addresses a key limitation of existing implementations, for which a mismodelling of the statistical properties of the noise can lead to biases in the characterization of the spectral laws, and consequently biases in the recovered CMB maps. We propose a novel framework based on a modified ridge likelihood embedded in an ensemble-average pipeline and derive an analytic bias correction to control noise-induced foreground residuals. We discuss the practical applications of this approach in the absence of true noise information, leading to the choice of white noise as a realistic assumption. As a proof of concept, we apply this methodology to a set of simplified, idealized simulations inspired by the specifications of the proposed ECHO (CMB-Bhrat) mission, which features multi-frequency, large-format focal planes. We forecast the upper limit on the tensor-to-scalar ratio, , under a suite of realistic noise scenarios. Our results show that for an optimistic full sky observation, ECHO can achieve even in the presence of significant correlated noise, demonstrating the mission's capability to probe primordial gravitational waves with unprecedented sensitivity. Without degrading the statistical performance of the traditional component separation, this methodology offers a robust path toward next-generation B-mode searches and informs instrument design by quantifying the impact of noise correlations on cosmological parameter recovery
The most metal-poor stars
No full textInternational audienceThe most metal-poor stars found in the Galaxy and in nearby galaxies are witnesses of the early evolution of the Universe. In a general picture in which we expect the metallicity to increase monotonically with time, as a result of the metal production in stars, we also expect the most metal-poor stars to be the most primitive objects accessible to our observations. The abundance ratios in these stars provide us important information on the first generations of stars that synthesised the nuclei that we observe in these stars. Because they are so primitive the modelling of their chemical inventory can be often satisfactorily achieved by assuming that all the metals were produced in a single supernova, or just a few. This is simpler than modelling the full chemical evolution, using different sources, that is necessary at higher metallicity. The price to pay for this relative ease of interpretation is that these stars are extremely rare and require specifically tailored observational strategies in order to assemble statistically significant samples of stars. In this review we try to summarise the main observational results that have been obtained in the last ten years
Combined Classical and Quantum Accelerometers for Future Satellite Gravity Missions
No full textInternational audienceCold atom interferometry based quantum accelerometers (Q-ACCs) are very promising for future satellite gravity missions thanks to their strength in providing long-term stable and precise measurements of non-gravitational accelerations. However, their limitations due to the low measurement rate and the existence of ambiguities in the raw sensor measurements call for hybridization of the Q-ACC with a classical one (e.g., electrostatic) with higher bandwidth. While previous hybridization studies have so far considered simple noise models for the Q-ACC and neglected the impact of satellite rotation on the phase shift of the accelerometer, we perform here a more advanced hybridization simulation by implementing a comprehensive noise model for the satellite-based Q-ACCs and considering the full impact of rotation, gravity gradient, and self-gravity on the instrument. We perform simulation studies for scenarios with different assumptions about quantum and classical sensors and satellite missions. The performance benefits of the hybrid solutions, taking the synergy of both classical and Q-ACCs into account, will be quantified. We found that implementing a hybrid accelerometer onboard a future gravity mission improves the gravity solution by one to two orders in lower and higher degrees. In particular, the produced global gravity field maps show a drastic reduction in the instrumental contribution to the striping effect after introducing measurements from the hybrid accelerometers
Automated Nanosecond Plasma Jets for Targeted Medical Treatments
No full textInternational audienceCold atmospheric plasma (CAP) has emerged as a transformative tool in medicine, with applications ranging from selective cancer cell inactivation to the acceleration of wound healing. The therapeutic effects of CAP are largely mediated by reactive oxygen and nitrogen species (ROS/RNS), whose precise composition and concentration must be tightly controlled for safe and effective treatment. However, in many current systems, human handling introduces variability that compromises treatment reproducibility and limit accurate estimation of introduction of reactive species onto a treated surface.This study addresses the need for standardization in plasma-based therapies by implementing a modified computer numerical control (CNC) plasma treatment platform to automate and precisely control exposure parameters. By removing human variability, this system enables reproducible treatment conditions across multiple experimental sessions. To better understand the chemistry at the point of application, preliminary diagnostics were performed using fiber-enhanced spontaneous Raman backscattering.Our preliminary results suggest that reactive species profiles can be accurately defined along with the plasma plume with minimal invasiveness. Furthermore, the use of hollow core fiber allows for significant enhanced signalling effects due to its ability to increase the interaction length between the probing light source and the gas sample. As such, this work lays the groundwork for developing standardized plasma treatment protocols supported by real-time diagnostics. Ongoing and future studies will focus on integrating more advanced optical techniques and correlating plasma chemistry with biological effects to further improve the reliability and effectiveness of plasma-based medical interventions
Towards calibration of picosecond O-TALIF
No full textInternational audienceExperimental procedure of obtaining the Xe/O two-photon absorption cross-section ratio is discussed for nanosecond and picosecond TALIF experiments. The same nanosecond capillary discharge with 100% oxygen dissociation at 30 mbar pressure is used as a source of O-atoms
A simple toy model for the electromagnetic variability of lump-dominated circumbinary disks around binary black holes
No full textInternational audienceThe electromagnetic detection of circumbinary disks around pre-merger binary black holes (BBHs) relies on theoretical predictions. These are generally obtained through expensive numerical simulations, but simple or fast toy models are lacking to unleash the potential of these theoretical advances for observational purposes. We aim to present a simple toy model to compute the electromagnetic variability of circumbinary disks around circular-orbit BBHs at relativistic separations, focusing on the impact of disk non-axisymmetries. We assume that the disk is threaded by spiral arms and hosts a hotspot linked to an overdense structure (the {\lq}lump{\rq}) preferably reported in binaries close to equal mass. We build a simple temperature distribution, and estimate its thermal emission, perceived by a distant observer, via a ray-tracing code in a BBH approximate metric. We propose a toy model reproducing the main lightcurve features and show it is consistent with 2D general-hydrodynamical simulations under the assumption of compressional heating and expansional cooling except for purely dynamical effects such as the binary-lump beat. The lightcurve exhibits a main modulation at the lump's period (i.e. a few times the orbital period), due to relativistic Doppler effect, and a shorter one at the orbital-like period, due to spiral arms or the beat. These are more prominent in the optical/UV band for a total binary mass , where the disk energy spectrum peaks. For , a -amplitude lump modulation is detectable with the Vera Rubin Observatory after six months of observation, up to . We proposed a new, simple toy model that can be used, for instance, to test the compatibility of the periodicity of BBH candidate sources with a circumbinary disk origin
Commission Femmes et Astronomie de la SF2A : Women participation in french astronomy 2025
No full textInternational audienceThe Commission Femmes et Astronomie of the French Astronomical Society, has conducted a statistical study aimed at mapping the current presence of women in French professional astronomy and establishing a baseline for tracking its evolution over time. This study follows an initial survey carried out in 2021, which covered eight astronomy and astrophysics institutes (1,060 employees). This year, the scope was expanded to 11 institutes, bringing together a total of 1,525 employees, including PhD students, postdoctoral researchers, academics, as well as technical and administrative staff, representing about 57% of the whole French community. We examined how the proportion of women varies according to career stage, level of responsibility, job security, and income. The results are compared to the 2021-2022 survey and appear to illustrate the well-known "leaky pipeline", with one of the main bottlenecks being access to permanent positions. The study shows that the proportion of women consistently declines with increasing job security, career seniority, qualification level, and salary