Please read the code of conduct, available below.
Merci de lire le code de conduite, disponible ci-dessous.
Particle physics is usually a tough subject to breach when trying to communicate to a wide audience. Between preconceptions and the difficulty to represent clearly what's going on, you can easily get lost in a sea of information (and quarks). No fancy pictures here, we mostly have balls that aren't balls, that don't orbit around other balls that aren't balls and they have a spin but they don't actually spin. Oh also they can be a cat in a box. Got it ? Yeah, me neither.
Basically, talking about the infinitely small is somewhat of a challenge that we don't have to avoid by throwing the word quantum around (looking at you Ant-Man). And we also don't have to be so academic about it.
For a few years now, the CNRS (as well as other organisations) has been involved with Yggdrasil, a festival in Lyon mixing cosplay, steampunk, anime, mangas, medieval fantasy and science-fiction to propose a space dedicated to technology and sciences accessible to basically anyone.
This year, the IN2P3 went to spread the word about neutrinos and particles, often to people who never even heard the word neutrino before and who probably didn't come specifically for the science part of the festival.
This brings us to our main questions : why did we go, how did we think our stand, did it work and why am I going to talk to you about Pokemons ?
In most environments, rainfall infiltrates very quickly into the ground. After crossing the soil it reaches porous rocks and becomes groundwater. Aquifers cover a large part of the world’s continents yet this huge body of water is often forgotten. This is because it is both invisible and very slow. The amount of groundwater is difficult to measure on the field and therefore hard to predict on models. With groundwater being a large part of the drinkable water on Earth and the only source of water during dry months in many places, it is crucial to understand the processes controlling it. We link a very common and studied landscape element : river networks, to groundwater flow. Knowing that groundwater flows directly into rivers, making up most of its discharge - river topography becomes a marker of where the aquifers lies beneath the ground. From this idea, we model real and experimental river networks and the corresponding aquifers. Adding to the numerical predictions, we created a miniature river network in the lab to observe the creation and evolution of channels. Indeed, rivers indicate the presence of aquifers but are also a consequence of the erosion that groundwater causes. The landscapes we observe are a consequence of the equilibrium between flow and erosion.
Scientists working on natural hazards and associated risks play a key role in population information with respect to disaster risk reduction. But they are not always familiar with the socio-cultural and informational contexts of at-risk communities, and identifying the right local partners and intermediaries can be a tricky and time consuming process. Sendai Framework and recent studies target school teachers as relevant mediators for disaster risk education and scientific information. Here, we document and analyze the experience of school teachers’ during the 2018 seismo-volcanic crisis in Mayotte and discuss the benefits and challenges of taking them as partners to better inform at-risk communities during and prior to a crisis. Mayotte case study is interesting because it corresponds to a multi-cultural context with multilingualism, low levels of literacy and precarious living conditions (see Roinsard, 2014). Following the start of an unexpected seismic crisis in May 2018, submarine volcanism was discovered between 5 and 50 km off the east coast of this island where, in living memory, there had never been any volcanic activity. The first months of the crisis were marked by major scientific uncertainties and a perceived lack of information from the inhabitants’ perspective (Fallou et al., 2020; Devès et al., 2022). Our study is built on 14 semi-directive interviews with school teachers and 18 focus groups with schoolers. This comprehensive set of qualitative data allows us to discuss the role of school teachers as intermediaries to spread information between scientists and at-risk communities, prior and following natural events.
For a few years now, lower bounds have been found for Intergalactic Magnetic Fields (IGMF). One of the most plausible explanations for their generation is during first order cosmological phase transitions (PT) such as the Electroweak phase transition (EWPT) or the QCD phase transition (QCDPT).
During these early phase transitions, bubbles of the new phase nucleate and expand inside the old phase until they percolate with each other. These collisions can generate gravitational waves and magnetic fields.
However, if Intergalactic Magnetic Fields were indeed produced during these events, the mechanism that generates them is still unclear for now.
First order PT can be described by restricted a set of 5 parameters .
The data provided by PTA last year coming from a 15 years survey put some new constraints on the Stochastic Gravitational Waves Background.
My goal is then to convert the constraints published by the different PTA collaborations into constraints in the PT parameter space, and, by extension, new constraints on the cosmological magnetic fields produced by first order PT.
To do that I use a model to compute the gravitational waves spectrum generated by first order PT as a function of the 5 key parameters. Then, I use the constraints from PTA on the stochastic gravitational waves background to reject or accept my parameters.
Under some hypothesis I can then convert these new constraints into constraints on the amplitude and the correlation length of the magnetic fields generated at first order PT.
Raising public awareness of water treatment processes is one of the challenges facing our society as part of the prevention and protection of environmental health [1]. Indeed, because of the potential risk of water shortages caused by the effects of climate change and the use of water in many sectors of activity, it is interesting to understand that many difficulties can be encountered when treating contaminated water. In France, many wastewater treatment plants are visible from the roadside, proudly displaying wetlands filled with reeds, but who knows what is treated and how? These wetland treatment plants can be designed to remove various contaminants from water, such as organic or inorganic pollutants. Among them, passive mine water treatment plants have been designed to remove metal contamination using natural methods, including biological and geochemical processes. The discharge limits set for these treatment plants can sometimes challenge these natural processes that are generally dependent on numerous environmental factors. However, the factors controlling the removal efficiency have yet to be identified [2]. In this context, a project in progress aims to monitor a passive mine water treatment plant for one year in order to highlight the parameters needed to understand and improve treatment processes. It aims to understand how micro-organisms and geochemical processes can be involved in remediation strategies.
[1] WHO, Guidelines for drinking-water quality, 2022, 4th ed., Chapter 12, p. 329-490.
[2] Neculita et al., Chemosphere, 2019, vol. 214, p. 491-510.
On July 16th, 1945, during the first nuclear explosion, glasses called trinitites formed as a nuclear by-product. They cover the surface of the explosion crater. The origins of the trinitites remain debated (Bonamici et al., 2017; Eby et al., 2010). Here, a scenario on the trinitites formation is proposed based on the chemical (realized with the Camparis Electron Microprobe) and the silicon and oxygen triple isotopes analysis (made with the CRPG-Nancy ion microprobe IMS1270) of three trinitites.
The trinitites are an assemblage of smaller glass beads and crystals from three chemical families: CaMgFe glasses, feldspar trinitites, and silica trinitites. Their silicon and oxygen isotopic compositions have wide variations between 12.4±0.6‰ and -15.6±0.6‰ for δ30Si and between 23.5±0.5‰ and 1.5±0.5‰ for δ18O. These wide variations are unusual for terrestrial solids. The silicon isotopic compositions can result from condensation and evaporation at high temperatures.
The trinitites chemical families show different origins: (i) the refractory rich CaMgFe trinitites are the result of a silicate vapor condensation (δ30Si<0‰), and (ii) the silica trinitites are mainly a product of melting and evaporating sediments (δ30Si>0‰). So, a scenario for the trinitites formation could be that the explosion vaporized a large amount of material and formed the crater. The surface of the crater had a high-temperature (>1980K) layer of melted sediment (quartz, feldspar…). In the nuclear fireball the silicate vapors condensed rapidly (<10s) into liquid droplets. These droplets fell into the melted sediment layer at the crater surface. Finally, the layer quenched and formed the trinitites.
Nepal's seismicity has been shown to display a seasonality in its temporal distribution, associated with the yearly coming and going of the monsoon. We here investigate the seasonal nature of the East and Central seismicity between 1994 and 2014 using several declustering techniques and highlight the sensitivity of results to declustering techniques. We also probe the slope of the magnitude-frequency distribution (b-value) and showcase its annual variations and sensitivity to sources of biases.
Addressing seismic hazards accurately is one of the major challenges in seismic engineering and seismology. Current analyses predominantly rely on a linear approximation. However, this approach encounters notable limitations, especially close to the surface and the fault zones where stresses and strains introduce material nonlinearity. Nonlinear soil behavior has been widely described in laboratory settings by a reduction of the shear modulus and an increase of damping. These changes, also observed in real data, are accompanied by a shift in resonance frequencies toward lower values and smaller amplification. Nowadays, advancements in global networks and robust signal processing tools facilitate a deeper exploration of soil property changes due to nonlinearity, particularly in situations where this phenomenon is prevalent. This study uses data recorded at the KiK-net (surface/borehole configuration) and KNET (surface configuration) stations in the Iwate Prefecture in Japan. The database includes more than 20 years of records (from the beginning of the operations until December 2022), comprising forty thousand seismic waveforms from earthquakes having magnitudes ranging from 2 to 9. Our methodology involves employing seismic interferometry, accomplished through deconvolution and phase correlation techniques, on the KiK-net data. The interferograms are categorized into three amplitude bins based on Peak Ground Acceleration (PGA): 1-5, 10-25, and 50-80 cm/s2. We stack data in each bin and use the mean interferograms to evaluate velocity changes across different frequencies, establishing the 1-5 cm/s2 PGA bin as our linear reference. Concomitantly, we calculate the phase autocorrelation of waveforms for KNET and KiK-net’s surface records, employing a similar processing approach as interferograms to derive velocity changes. Autocorrelation results are generally larger than those from interferometry, with a mean value of 10% and 5% for KiK-net stations, respectively. Notably, stations with high Vs30 values exhibit significant velocity reduction, indicating the influence of soft soils near the surface. This challenges the ability of Vs30 as an indicator of nonlinear response, suggesting that high Vs30 values may obscure the presence of shallow soft soil layers.
X-ray binaries are systems where a star orbits a neutron star or a stellar mass black hole. Due to the strong potential well of the black hole/neutron star, matter from the companion star is accreted onto the compact object, creating an accretion disk that radiates in the X-ray region of the electromagnetic spectrum. Some X-ray binaries are known to eject matter perpendicularly to the accretion disk, in the form of symmetric plasma bubbles moving away from the black hole at relativistic speeds. Such X-ray binaries are called microquasars.
Over the last few years, the MeerKAT radio-telescope (SKA-mid precursor) has drastically improved the study of relativistic ejecta from microquasars, showing the ubiquity of large scale jets (up to parsec scales), such as MAXI J1348-630 and MAXI J1820+070. In 2004, two large-scale jets were discovered around the black hole X-ray binary H1743-322, after a major outburst in 2003. The emission of those jets, detected in radio and X-ray with ATCA and Chandra, was consistent with a synchrotron spectrum, due to electrons accelerated up to TeV when the relativistic jets interact with the interstellar medium.
Using an extremely rich and unexploited archive dataset from Very Large Array observations, we carry out a 600-day tracking of the discrete ejecta, in different radio bands. In this work, we present the overall evolution of the jets including motion and kinematics, interaction with the ISM and energy budget. The whole campaign represents one of the most complete dataset to study jets evolution.
The Laser Interferometer Space Antenna (LISA) is poised to become a key space-based gravitational wave (GW) detector, capturing signals from various astrophysical sources, such as merging massive black hole binaries (MBHBs) and Galactic binaries (GBs). However, the presence of MBHB signals, characterized by their loud and broadband nature, poses challenges in accurately estimating the power spectral density (PSD) and detecting other signals within the LISA band.
In this study, we propose a novel approach to address this issue by employing a fast and approximate model of inspiral-merger-ringdown (IMR) to detect and subtract MBHB signals from the data down to the noise level. Our methodology relies on maximizing the likelihood function over extrinsic parameters and the time of coalescence (F-statistic), supplemented by either a mesh-refinement algorithm (Vegas) or Powell's conjugate direction optimization algorithm.
Following the subtraction of MBHB signals, the remaining data is subjected to further analysis using accurate MBHB models, enabling the detection of additional sources. We illustrate the effectiveness of our method using the LDC2a (Sangria) dataset.
The Greenland ice sheet, a critical component of the global climate system, has played a substantial role in rising sea level. Understanding the spatio-temporal changes in Greenland’s ice mass loss resulting from iceberg calving is crucial for comprehending the impacts of climate change.
The mass loss related to calving icebergs can be estimated by combining mechanical simulation of iceberg calving and inversion of seismic data. Seismic signals are generated by the time-varying force produced during iceberg calving on marine-terminating glacier termini and known as glacial earthquakes.
However, differentiating these signals from tectonic events, anthropogenic noise, and other natural noise is challenging due to their complex frequency content (1-100s), multi-phase waveforms and low amplitude. To overcome this difficulty, we use a detection algorithm based on the Short-Time Average over Long-Time Average (STA/LTA) method and combine it with machine learning (Random Forests). Applying this methodology to continuous data offers the possibility to uncover smaller and previously undetected events. As a result, we present a comprehensive catalogue spanning several years and discuss its relevance and reliability. The generated catalogue allows us to develop new methods to better understand the spatio-temporal evolution of the ice-calving activity. Among these, we will initially focus on locating and inverting the force of the largest events, providing a basis for testing new machine learning approaches for the characterisation of the source. This includes extracting properties like the iceberg volume and shape from both large and smaller events, ultimately advancing our understanding of Greenland's ice mass loss dynamics.
The purpose of this PhD thesis is to study the correlation between gamma ray sources and neutrinos in the high energy extra-galactic sky.
This is done by using advanced deep learning techniques to extract physical information about the astrophysical candidates for this study.
For now the data that have been used are the neutrino events from the Icecat-1 catalog from IceCube and the astrophysical sources of the 4FGL-DR4 catalog from Fermi.
A first naive approach have already been implemented :
- Features have been selected and/or created based on the information of the 4FGL-DR4.
- The sources of 4FGL-DR4 have been filtered to keep only AGNs (candidates of extra-galactic neutrino production) and only the best quality events of IceCube have been kept (high probability of being astrophysical in origin)
- To create a machine learning dataset, the sources of the Fermi catalog have been labeled based on their vicinity to neutrinos that have been detected by IceCube.
- A machine learning classifier (RF) have been used to classify the astrophysical sources based on the pre-selected features, and a cross validation pipeline have been implemented to assess the results.
A more advanced approach is being implemented based on the light curves of Fermi.
More than 2000 light curves have been generated using fermipy and will be used as time series data with a Pre-train model for time series mining.
This will be compared to the use of a standard transformer (with variational auto encoder) and a ResNeT to obtain some baselines in terms of metrics.
Poly- and perfluoroalkyl substances (PFAS) have been manufactured since the 1950s. One of the main applications of PFAS is as a low-viscosity sealant in aqueous film-forming foam (AFFF) to extinguish hydrocarbon fires. The irrational use of AFFF in firefighting sites contaminated the soil and water system,signaling a serious and complex sanitary and environmental risk. It is therefore important to improve PFAS remediation technologies. The conventional remediation techniques might not be functioning effectively because of the strong C-F bonds, surfactant properties, solubility, and adsorption capacity of these substances. However, some studies showed that in-situ soil flushing with solvent is a successful method for PFAS mobilization. Despite their high desorption performance in removing PFAS, their effectiveness in soils with heterogeneous pore sizes may be constrained. In this context, the use of a non-Newtonian fluid (NNF) can improve the solvent flow in heterogeneous soils and consequently the PFAS desorption. In this study, we show the efficiency of the mixture of polymer and alcohol on PFAS mobilization in heterogeneous soils.
The flushing solution to solubilize PFAS is an aqueous ethanol solution at a fixed volume fraction of 50%. Xanthan gum as a biopolymer was added to this solution at different concentrations to induce a shearthinning behavior of the mixtures. The rheometer was used to examine the ethanol-xanthan rheological behavior of the mixtures. The soil was a blend of 3% of organic materials, 92% of silica sand, and 5% of clay with the same range of grain sizes as representatives of the soil layers usually reported for real polluted sites. At a fixed concentration of PFOS, PFOA, PFBS, and PFHxS, batch studies for understanding the adsorption and desorption behavior were conducted. An aqueous PFAS stock solution containing CaCl2 was added to the soil. The mixture was then stirred and centrifuged. The remaining contaminated soil was used for desorption experiments by adding various solutions such as water, ethanol, and a mixture of ethanol-xanthan with different concentrations of xanthan. To assess the polymer performance in transporting alcohol to solubilize PFAS, 1D column experiments were carried out.
The ethanol-xanthan mixtures homogeneity was confirmed by rheological analyses, which revealed that the addition of ethanol reduces the bulk viscosity of the mixture while maintaining a similar shear thinning behavior. Batch analysis revealed that the longer the PFAS chain, the greater the adsorption capacity, which corresponds to the solubility of each component. The main reason for adsorption is hydrophobic interactions with soil organic matter. In addition, ethanol desorbed more than 85% of the four PFAS components. Furthermore, the presence of xanthan in the mixture has a minor effect on the extraction capacity of ethanol. The efficacy of the injection of the ethanol-xanthan mixture on PFAS desorption and mobilization for various soil grain sizes was assessed using 1D-column experiments.
Depending on the length of the PFAS carbon chain, each component exhibits a different adsorption behavior. Ethanol flushing, as a promising method, has the potential to improve PFAS-contaminated soil remediation. In heterogeneous soils, the presence of xanthan in the flushing solution improves PFAS removal.PFAS contamination is frequently reported due to its applications in various fields. This study fills a gap in existing research by investigating the use of a mixture of ethanol and xanthan as a non-Newtonian fluid for in situ solvent flushing method aiming at removing PFAS from heterogeneous soils. While other PFAS desorption methods have been investigated, this is the first comprehensive study to evaluate the efficiency of this method in heterogeneous soils
On 6 February 2023, the Mw 7.8 Pazarçik earthquake ruptured the left-lateral East Anatolian Fault in southern Türkiye after initiating in the nearby Narli fault zone. It was followed 9 hours later by the Mw 7.5 Elbistan earthquake that occurred on the nearby Surgu-Cardak fault zone. We model the coseismic slip distributions for these two earthquakes using geodetic data, including Sentinel-2 interferograms and pixel offsets, Sentinel-1 image correlation and GNSS. After computing a least-squares solution, we use it as a prior for Bayesian modeling, using perturbed Green’s functions in a 5-layer elastic medium. Most of the slip occurs above 20km. Coseismic slip is quite variable laterally, especially for the Mw 7.8 rupture along the East-Anatolian fault, where we observe multiple stepovers, fault bends and fault junctions.
Magma chamber reservoirs host melt from the deep Earth, which erupts to form the volcanic edifices, the upper oceanic crust, and cools to form the lower gabbroic crust. It also sources heat for hydrothermal circulation and for the formation of black smokers along ocean spreading centres. The top of magma reservoirs is generally imaged using seismic reflection imaging techniques, designed as axial melt lens (AML) reflection, whereas wide-angle seismic data provide smeared low velocity anomaly underneath. Therefore, the precise nature of axial magma reservoirs remains elusive. We propose to characterise the nature of the magma reservoir at the Axial Volcano using a state-of-the-art full waveform inversion applied to ultra-long offset data.
Axial Volcano in the Eastern Pacific Ocean is a large submarine volcano, like a mini-Iceland, which is being formed by the interaction between the intermediate-spreading Juan de Fuca Ridge and the Cobb hotspot. It hosts many hydrothermal vent fields and has erupted three times (1998, 2011 and 2015) in recent years and therefore has been the subject of extensive geological and geophysical studies over the last 30 years, including setting up of a permanent, real time, wired-to-shore, multi-parameter seafloor observatory, a three-dimensional (3D) multi-channel seismic survey, and ultra-long (12 km) multi-channel seismic (MCS) data.
In this study, I plan to use MCS data collected in 2019 on board the US R/V Langseth, comprising of 8 ultra-long offset 2D profiles crossing the volcanic plateau. A 936-channel, 11700-m-long Syntron digital streamer with receiver groups spaced at 12.5 m was towed at a nominal depth of 16 m. The source vessel deployed an array of 36 air guns, totaling approximately 6600 cubic inches in volume, towed at an average depth of 12 m. Shots were fired every 37.5 m along the track, and data were recorded at a sampling rate of 2 ms for 12 s long records.
After processing these data using a conventional processing strategy to obtain a seismic image, we redatum both the seismic sources and receivers to the seafloor (SOBE), perform conventional first arrival P-wave travel time tomography of the first arrivals, followed by the application a time-domain, full-waveform inversion (FWI) scheme, resulting in the generation of high-resolution velocity models of Axial Volcano magmatic system possibly down to 6 km below the seafloor. We should be able to characterise the detailed nature of the magma reservoir, including their internal structures (imbricated sill, melt/mush zonation) and magma plumbing system and link them with eruptions dynamics at the seafloor.
The traditional understanding of plate tectonics posits rigid plates primarily undergoing deformation at narrow plate boundaries. However, the equatorial Indian Ocean presents a unique scenario with a diffused deformation zone spanning approximately 3000 km within the Indo-Australian plate. Past investigations have identified N-S compression in the Central Indian Ocean basin and strike-slip motion along N-S trending reactivated fracture zones of a fossil spreading center in the Wharton Basin located at the eastern margin of the Indian Ocean. Recently, the massive Wharton Basin twin earthquakes of April 11, 2012, challenged the existing conceptions in two significant ways. Firstly, their substantial magnitudes (Mw 8.6 and 8.2) underscored the potential for a significant localized deformation along a previously identified fracture zone (F6a), suggesting its candidacy as a nascent plate boundary between India and Australia. Secondly, the foreshock ruptured along a complex set of faults oblique to the presumed north-south direction of slip motion along fracture zones, indicating the existence of additional fault systems. To address these fundamental challenges, the MIRAGE experiment was launched, gathering a comprehensive suite of geophysical data in the Wharton Basin, encompassing high-resolution bathymetry over ~90,000 km2 and 12 seismic lines totaling 3450 km in length, intersecting two IODP borehole sites. The objectives of my Ph.D. project entail analyzing the MIRAGE dataset to: (1) Assess intra-plate deformation regionally and explore the potential of F6a as a nascent plate boundary, (2) Investigate the relationship between north-south trending fracture zones and newly discovered oblique shear zones, and (3) Probe into the role of intra-plate deformation in the subduction process.
Significant geogenic carbon dioxide (CO2) emissions have been reported worldwide at plate boundaries in both volcanic and non-volcanic contexts. Specific hydrothermal manifestations observed at the surface show large CO2 emissions that remain difficult to quantify precisely. These include “CO2 rivers”, which are turbulent, negatively buoyant flows that propagate near the surface following the topography and entrain large amounts of air due to wind shear. Understanding their temporal variations, possibly related to tectonic deformation and earthquakes, is crucial to mitigate the associated hazards and risks to the population. Here, we develop a statistical analysis to constrain CO2 dispersion in the first atmospheric layers using the numerical model TWODEE, a 2D shallow-layer code for dense flow dispersion. We apply the analysis to the Syabru-Bensi hydrothermal system located in the upper Trisuli Valley, central Nepal, where metamorphic CO2 is produced at depth and released at the surface on slopes and alluvial terraces. This system was severely affected by the 2015 Gorkha earthquake crisis. Constrained by CO2 concentration data at different heights above the ground and by surface CO2 fluxes, our simulations help to identify different turbulent zones from the CO2 source, to predict the spatiotemporal variations of CO2 concentration at different heights above the ground under various conditions, and to estimate the total CO2 emission. We obtain significant differences between interseismic and postseismic regimes, following the Gorkha earthquake. Our study provides a better characterisation of the atmospheric CO2 dispersion and opens promising perspectives for the airborne detection of geogenic CO2 in Himalayan valleys.
With rates locally exceeding one centimeter of denudation per year [1,2], i.e., more than 100 t/ha/year, the Durance basin in the French Alps is one of the world’s most heavily eroding areas [3]. A combination of favorable conditions explains this phenomenon, including a very steep topography, sparse vegetation and a particular susceptibility of the Jurassic black marls, also called Terres Noires, to seasonal climatic forcing [4]. The Draix-Bléone observatory uses hydro- sedimentary stations to instrument several of these small, non-anthropized catchments, where hydrological responses to seasonal storms are rapid and intense [5]. The work presented combines the use of LiDAR time series from airborne, UAV and ground measurements, with sediment flux chronicles recorded at the outlet of the Laval catchment, a small steep watershed (0.86 m2), to address questions of upstream/downstream transport modalities. An assessment of the potential of remote sensing methods for attributing the contributions of each critical zone compartment (channel, gullies, landslides, etc.) to the erosive dynamics of this basin and its connectivity is carried out.
References :
[1] N. Mathys, S. Brochot, M. Meunier and D. Richard (2003). Erosion quantification in the small marly experimental catchments of Draix (Alpes de Haute Provence, France). Calibration of the ETC rainfall-runoff-erosion model. CATENA. 50(2–4):527–548. DOI : 10.1016/S0341-8162(02)00122-4.
[2] A. Carriere, C. Le Bouteiller, G. E. Tucker, S. Klotz, and M. Naaim (2020). Impact of vegetation on erosion: Insights from the calibration and test of a landscape evolution model in alpine badland catchments. Earth Surf. Process. Landf., 45(5):1085–1099. DOI : 10.1002/esp.4741.
[3] D. E. Walling (1998). Measuring sediment yield from river basins. in Soil Erosion Research Methods (R. Lal, Ed.). Soil and Water Conservation Society, Iowa, USA, pp 39–73.
[4] L. Descroix and N. Mathys (2003). Processes, spatio-temporal factors and measurements of current erosion in the French Southern Alps: A review. Earth Surf. Process. Landf. 28( 9): 993–1011. DOI : 10.1002/esp.514.
[5] Draix-Bleone Observatory. (2015). Observatoire hydrosédimentaire de montagne Draix- Bléone [Data set]. Irstea. DOI : 10.17180/obs.draix
The Deep Underground Neutrino Experiment (DUNE) is a cutting-edge international neutrino experiment under construction now in US, which uses Liquid Argon Time Projection Chambers (LArTPCs) as its main detector technology for particle identification on the far site in the SURF facility in South Dakota. The far detector (FD) modules will be able to detect longbeam neutrinos (generated by a source at the near site in FNAL) but also neutrinos from natural sources (like solar and cosmic rays). In this work, I am focusing on atmospheric neutrinos, created in Earth’s atmosphere by cosmic rays interactions. In order to determine the moving direction of an atmospheric neutrino, identifying its interaction vertex in the LArTPC is an essential first step. This allows it to determine the distance the neutrino traveled before interacting, and hence make it possible to calculate its oscillation probability. I will present the performance of the reconstruction algorithm for the interaction vertex of such neutrinos in the DUNE FD LArTPCs. Using a simulated sample of atmospheric neutrinos, I will show the present performance (resolutions and reconstruction efficiency) of vertex reconstruction in DUNE’s FD. I will also present my work on identifying failure points and improving the algorithm using deep learning techniques. Further development prospects will also be discussed.
Optical satellite images are proving to be a valuable tool for quantifying the deformation of the ground surface caused by an earthquake, especially in the direct vicinity of the co-seismic surface rupture, where InSAR often saturates, due to the amplitude of the displacement. When comparing an image acquired before the earthquake with an image acquired after, using correlation to measure pixel displacement, some areas may pose a problem, due to the effect of diachronism. The objective of this work is to try to solve this problem, using machine learning. We believe it is possible to train a neural network with synthetic examples of pre- and post-earthquake satellite image pairs to directly measure the displacement field. To that end, we created a training dataset, based on real satellite images (Sentinel-2), in which synthetic displacement was added. This dataset is used to train a CNN (convolutional neural network) ent-to-end, to measure displacement field more robustly against the effects of diachronism.
My thesis topic deals with integrating multisource data to improve seismic risk assessment in northern Morocco, located on the active tectonic plate boundary between Africa and Eurasia. The main objective is to further estimate the seismic hazard in the region and provide a comprehensive background for urban planning to mitigate seismic risk. My research is based on seismic analysis, space geodesy (GNSS and InSAR techniques), and field observations. Through the application of statistical methods and waveform analysis, seismic data processing enables seismic event patterns to be determined. Simultaneously, space geodesy monitors ground movements by integrating ground-based GNSS measurements and satellite-based InSAR data. In addition, field surveys, including geological studies and fault mapping, offer a valuable contribution to our overall understanding of fault behavior and seismic activity. Yet, preliminary findings with Gutenberg-Richter law illuminate seismic event occurrence frequencies in a frame time of 100 years. On the other hand, field observations have been carried out in the region and allowed to characterize neotectonic activity and stress orientation. Ultimately, this study sets the stage for further research efforts aimed at deepening understanding and building resilience towards earthquake risk reduction. However, it's important to note that data availability is a critical key, nevertheless challenges related to interpretation uncertainties and modeling limitations. which can limit the scope and accuracy in the region.
Keywords: Seismic analysis; Space Geodesy; field observation; Earthquake hazard, Northern Morocco.
Understanding the rupture mechanism, distribution, and migration of seismicity following a large earthquake depends on the quality of available earthquake catalogs (uncertainties, completeness magnitude, etc.). In this study, we investigate the aftershock sequence recorded by several temporary arrays deployed in the zone of the 2010 Mw 8.8 Maule earthquake in Chile, using a combination of deep learning algorithms and template matching for earthquake detection and location. Our aim is to enhance the completeness of the earthquake catalog by analyzing a spatio-temporally sparse seismic network. We employed the Backprojection and Matched Filter (BPMF) workflow (Beaucé et al., 2021), which began with the detection and location of an initial catalog comprising 52,679 earthquakes. Subsequent relocation using the NonLinLoc algorithm improved the accuracy of the spatial distribution, thereby aiding in the creation of a template database. This resulted in a final catalog containing 470,066 earthquakes after template matching, outnumbering the initial catalog by a factor of 12. Our results highlight the spatio-temporal distribution of the aftershock sequence over one year and identify two prominent seismic cluster zones: a shallower cluster in the Pichilemu-Vichuquén zone (33.5°S and 35°S), and a deeper one associated with megathrust activity near Concepción (37°S and 38°S). There is high spatial variability of the b-value, which could be attributed to fluctuating post-seismic activity and/or the activation of diverse fault systems in the rupture zone. Our findings underscore the potential of new techniques to analyze seismic activity from old and sparse datasets, enhancing understanding of subduction processes.
The quest for B-mode polarization of the Cosmic Microwave Background is among the main challenges in Observational Cosmology. Measurement of B-mode polarization in the CMB will be clear evidence of the presence of primordial gravitational waves which are theoretically expected to be produced during inflation about $10^{-35}$ seconds after the Planck epoch. The B-mode measurement is perhaps the most difficult cosmological challenge because the expected signal is very small. It requires high sensitivity and negligible instrument systematic effects with wide frequency coverage in order to separate the primordial signal from foreground emissions.
QUBIC (QU Bolometric Interferometer for Cosmology) is a novel instrument concept dedicated to the search for B-modes by measuring the Q and U polarization modes. It brings together the advantages of bolometers with high sensitivity and those of interferometers that have exquisite control of instrument systematic effects. The interferometric nature of QUBIC also allows spectro-imaging and improved spectral resolution with respect to imagers, providing a significant advantage concerning foreground removal. The Technological Demonstrator was inaugurated in Nov. 2022 at the QUBIC site at 5000m a.s.l. in the province of Salta in Argentina and is currently undergoing commissioning. Observations are expected to start early in 2024.
The poster will present the current state of our knowledge on Inflation and CMB, the technical features implemented in QUBIC to respond to the constraints associated with the observation of B modes of polarization as well as part of my work on the algorithms for reconstructing sky maps and their analysis to obtain the cosmological parameters that interest us.
Shallow creep, as a widespread phenomenon in the earthquake cycle, plays an important role in understanding the behavior of faults and seismic hazards. InSAR has been widely used to measure the interseismic deformation of strike-slip faults. In the previous study, we used the phase gradient stacking method to obtain the strain rate maps along the North Anatolian Fault (NAF) and found that the spatial distribution of the shallow creep and the coseismic slip has a close relationship. However, the large earthquakes on the NAF occurred before the Sentinel-1 satellite started acquiring data, and we wanted to investigate the fault creep characteristic before the earthquake, so we utilized several recent large earthquakes on the East Anatolian Fault (EAF). The EAF was recently ruptured by the 2020 Mw6.8 Elazig, and 2023 Mw7.8/Mw7.6 Kahramanmaras earthquake sequence, providing a unique opportunity to investigate the relation between shallow creep and earthquakes along strike-slip fault. It will provide a better understanding of the creep behavior during the seismic cycle and combine the coseismic slip distributions with an assessment of the seismic hazard of the seismic gap on the EAF.
In seismic hazard assessment, using Vs30 proxies and 1D shear wave velocity profiles often leads to underestimated ground motion, especially in complex geological areas like Greater Beirut (GB). This metropolis, near active seismic faults and with a history of significant earthquakes (551, 1202, 1837), features diverse soil types, necessitating detailed geotechnical subsurface modeling. Our study developed a 3D geotechnical model for GB, using data from around 500 boreholes, 700 geophysical measurements, a refined DEM, and geological insights. The model shows bedrock elevation and geological strata variations, with sediment depths reaching 70 meters. By integrating H/V measurements and borehole data, we estimated the average shear wave velocity (Vs-mean) across GB. To fill data gaps in southern GB, we used a Random Forest machine learning model, trained on interpolated points from Kriging in the central part of the model. This approach ensured a continuous and comprehensive representation of subsurface conditions, even in areas with limited data. Building on this foundation, our ongoing work involves detailed seismic simulations to predict ground motion amplification in Beirut. Using a 3D hexahedral mesh generated via open-source Python code, we will conduct full 3D numerical simulations of seismic wave propagation using the spectral element method ( Komatitsch and Tromp, 2002; Komatitsch and Tromp, 2002; Komatitsch et al., 2023). These simulations aim to provide valuable insights into the seismic response of Beirut’s subsurface, contributing to the city’s earthquake preparedness and risk mitigation strategies. The presentation will showcase the first seismic scenarios based on our 3D geotechnical model.
Volcanic eruptions threaten neighbouring populations. The goal of volcanoes’ monitoring is therefore to anticipate the onset of eruptions and track their evolution over time in order to assist in decision-making during the crisis. This requires to detect and map changes at the surface of an erupting volcano in near-real time. Going on the field during an eruption may be very risky especially in an explosive context. Besides ground-based instruments may be inoperative or even destroyed during eruptions, and many volcanoes are not equipped with a ground-based monitoring network. In such a context, satellite imagery could help. The remarkable improvements of the Synthetic Aperture Radar (SAR) technology in terms of spatial and temporal resolution, along with its capability to image the Earth’s surface day and night, under any weather conditions (cloud cover, eruptive plume), make it the most promising technique to support co-eruptive monitoring. The Capella Space company provides high-resolution (~1 m) SAR images, allowing to observe volcanic cones, craters, lava domes or lava flows with an unprecedented level of detail. We took advantage of this fine spatial resolution to: (1) detect the topographic changes that occurred at the surface of the Piton de la Fournaise volcano, La Réunion island, between 2009 and 2021 using the Radiometric Terrain Correction (RTC) method; (2) track the growth of the lava dome that formed during the April 2023 eruption of the Shiveluch volcano, Kamchatka, using the Scale-Invariant Feature Transform (SIFT) method.
Chondrites are primitive and undifferentiated meteorites. These objects have a composition that has remained largely unchanged since the early stages of the solar system formation. They are therefore extensively studied to understand planetary formation, particularly that of Earth, including the origin of its volatiles.
Sulfur has four stable isotopes, allowing for the measurement of mass-independent isotopic signatures. Meteorites show a range of 33S and 36S mass-independent anomalies of ~0.5‰, although the precision on 36S has remained typically larger than 0.25‰. We make use of these anomalies in chondrites to evaluate the parent bodies of Earth.
So far, no high-precision data has been acquired for CI chondrites, although they have been invoked as a potential carrier of volatiles to planets. We developped a higher-precision analytical method for the measurement of 33S but also 36S in natural samples. By increasing the counting time, we were able to divide the uncertainty on 36S by a factor of 4, i.e., from ~0.25‰ down to 0,06‰ (95% confidence interval).
We applied our analytical approach to the Orgueil meteorite (CI). We sequentially extracted sulfates, elemental sulfur, and sulfides. We find that various splits of the Orgueil chondrite all show substantial amounts of oxidized sulfur. We determined their S isotope composition and find that they are no match with Earth.
The oxidation pattern on this CI chondrite is not fully understood yet. We anticipate that a comparison with Ryugu split will provide constraints on the origins of oxidized sulfure on CI. In the meantime, we tentatively conclude that the S isotopic data do not seem to support a substantial contribution of CI to Earth.
The collision of the Indian and Eurasian plates has resulted in high-altitude Tibetan Plateau with profound seismic activity. Within this natural geological laboratory, a symphony of geodynamic phenomena unfolds, including plate underthrusting, tearing, mantle upwelling and rift formation. In this study, we apply the seismic box tomography to the southern Tibetan Plateau, aiming to quantify the density as well as bulk and shear moduli, which provides us with crucial physical constraints on the compositional and thermal structures of a highly deformed lithosphere in southern Tibetan Plateau.
In order to obtain the three-dimensional lithosphrical structure, we perform full-waveform inversion of teleseismic (30°−90°) surface- and body-wave waveforms recorded by the Hi-CLIMB network, a densely distributed (5−10 km station spacing) N-S oriented linear seismic array deployed during 2002 and 2005. In our iterative hierarchical inversion workflow, we calculate the sensitivity kernels based on the adjoint method and the model is updated by the L-BFGS algorithm. Data covariance matrices are introduced to control the data quality and objective weighting functions for different seismic events. We will present our preliminary results of the on-going study with comparison to existing models.
The core-mantle boundary appears as a complex region at the interface between the fast-moving core flows and the slowly convecting mantle, which could play a role in understanding sudden changes in the secular variation of the geomagnetic field, the ‘geomagnetic jerks’. One hypothesis suggests that temporal variations in CMB topography may be involved, potentially affecting core flows at the top of the core (Mandea et al, 2015). Measured by the GRACE satellites from 2002 to 2017, the spatio-temporal variations in the Earth's gravity field can provide us new constraints on SUCH mass redistributions at the core mantle boundary.
To separate superimposed contributions in the total gravity field and guide the identification of their sources by pattern recognition, we use the second-order spatial derivatives of the gravity potential at different spatial scales. Combining this tool with a multi-scale temporal analysis, we can select rapid signals at large spatial scale, concomitant with geomagnetic jerks. Then, to investigate their sources at depth, we compare the observed gravity signals with gravity variations associated with water cycle sources. The results of our current investigation are discussed here.
Oceanic Transform faults (OTF) are active, mainly strike-slip, tectonic plate boundaries, which segment Mid Oceanic Ridge axes. Along subduction zones, areas where Oceanic Fracture Zone (OFZ), the seismically inactive extension of OTF are being subducted, seem to be associated with higher seismic activity, thicker crust formation and distinct chemical signatures in produced arc lavas. As all these processes have significant impact on human societies, understanding how and why subducting OFZs influence the dynamics of subduction zones is therefore crucial.
My PhD project is thus two folds. It aims first at investigating the lithospheric architecture of OTF and OFZ through the study of (meta)gabbros deformed and collected at OTF. Samples mainly come from the Vema and Kane segmenting the Mid-Atlantic Ridge. Integrated (micro)structural-petro-geochemical characterization of these samples will be carried out to determine their composition and deformation history, to elucidate the chemical and rheological changes, and fluid-rock interaction processes, occurring in magmatic rocks deforming on OTF. Results and processes will be compared with gabbros, deformed at oceanic detachment faults on mid-ocean ridges. These quantified new compositional and rheological parameters of OFZ will then be implemented in a lithospheric-scale thermomechanical model of subduction including an OFZ. The modelling will be conducted to explore the impact of OFZ-subduction on geochemical cycles and the long-term dynamics of subduction zones, including the nature of metamorphic reactions within the slab, fluid flux, depth of fluid release and stress-strain condition.
Calcium rich Plagioclase and amphibole porphyroclasts, with secondary sodium rich plagioclase and amphiboles primarily constitute majority of the samples. Preliminary petrological analyses indicate high temperature ductile deformation such as recrystallisation, grain boundary migration and undulous extinction in ultra-mylonitic zones, accompanied by brittle deformation such as brecciation and fluid-rock interaction. Formation of amphibolite and greenschist facies minerals such as titanite or sphene, actinolite, chlorite and sodium rich plagioclase during these fracture fill episodes suggest low temperature deformation.
Unlike subaerial volcanic activity, deep submarine eruptions are difficult to detect, observe in real-time, and monitor. Here we use high-resolution (~2 m) bathymetry from a Remotely Operated Vehicle (ROV) to document seafloor morphologies associated with the 2018 submarine eruption offshore Mayotte. Optical imagery (videos and still images) from the ROV provides ground-truth for geological interpretations. These data allow to conduct quantitative analyses on fine-scale textures (e.g., type of eruptive product, collapse features, stratigraphic units) and to compute 3D models of submarine outcrops to facilitate the understanding of geological objects. The combination of both bathymetric and optical datasets allows to document and discuss for the first time the fine-scale morphologies associated with the newly formed Fani Maoré submarine volcano and the different eruptive processes, that vary both in space and time.
At the map-scale, the ROV microbathymetry shows: a) large volcanic hummocks; b) hummocky seamounts, collapsed and associated with flat surfaces; and c) smooth seafloor showing low relief volcanic features. We also map collapse features associated with scarps, fissures, pits, and lava tunnels, among others. At the photo-scale, we identify both pillow and lobate lavas, together with various hydrothermal indicators (e.g., chimneys, hydrothermal deposits, shimmering).
Our results provide the first insights on the volcanic processes involved in the formation of this new submarine edifice at a depth of ~ 3500 m. These data will be analyzed to provide a quantitative assessment of the links between the morphological and optical textures, that will be correlated to the temporal evolution of lava flow emplacement during this large submarine eruption. The final goal is to constrain the precise chronology, spatial variability, and mode of lava flow emplacement, in relation to the volumes and fluxes associated with the eruption.
Volcanic environments frequently generate seismic activity. This is the case for La Réunion island's two major volcanic edifices (Piton des Neiges and Piton de la Fournaise), where significant seismic activity is recorded. While the seismicity of Piton de la Fournaise can be easily explained by its volcanic activity (more than three eruptions per year since 2014), the seismic activity of Piton des Neiges (inactive for around 27,000 years) is still poorly understood. We improve the previously available seismicity catalog using template matching, double relocation and focal mechanism determination. Our results suggest that seismic activity beneath Piton des Neiges is probably caused by regional tectonic stresses and edifice loads on pre-existing faults, rather than from deep magma transfers. This conclusion is supported by the presence of several reverse faults with similar orientation and the lack of correlation between seismicity fluctuations and deep magmatic activity.
Large impacts dominated the accretion during the early solar system. They contribute to the
heating, melting, and sometimes vaporization of the impact bodies. Quantifying the frequency of
the different resulting structures’ aftershocks is a key point in understanding the evolution of the
protoplanetary disk. In this study, we work on the behavior of early Earth-like materials under
shocks.
We performed ab initio molecular dynamics simulations using the VASP6 package. The post-
processing analysis was done with the UMD package [1].
We compare the Hugoniot equations of the state of realistic multi-component silicate systems
under different shock conditions. We choose different compositions which are relevant for the
early stage of Earth’s accretion. We monitor changes in the Hugoniot equation of the melts when
the initial density and temperature of the shocked material change. However, changes in the
composition of the major elements do not affect the Hugoniot. The Hugoniot equation provides
realistic PT conditions that the bodies experience as a result of impacts during accretion. Using
thermodynamic integration methods we compute the entropy produced during a shock and the
liquid-vapor dome of the pyrolite in the entropy against temperature phase space. Those hugoniots
in the entropy-temperature diagram give us a precise criterion to estimate if an impact leads to
partial vaporization. Thanks to our results, we can build new scenarios about the physical states
of proto-planets and planetary bodies during the early stages of solar system formation. The
characterization of the physical state of the protoplanetary disk may have a significant impact on
our view of the early degassing of primordial reservoirs and volatile distribution in the early solar
system.
The South China Sea (SCS) is unique among the worldwide supra-subduction oceanic basins as continental rifting occured in the lower plate, long after an orogenic collapse, quite far from the surrounding active subduction zones. Using seismic imaging results and thermo-mechanical modeling, many authors infer an important role of thermal, compositional and structural inheritance during the onset of post-orogenic continental breakup in the SCS. Here we study the interactions between the inheritance mentioned above and the SCS rifting processes by (1) processing Ocean Bottom Seismometers (OBS) refraction data in the southwestern sub-basin and (2) building numerical models to test related rheological heterogeneities. In these models, we study the effect of sedimentary and crustal dipping layers corresponding to former orogenic, thrust related nappes. We also aim to obtain a more detailed result of the lithospheric P-wave velocity structure in the southwestern sub-basin from 30 OBS to better constrain where the crustal structure significantly differs from a wide rift with constant crustal thickness. The observed and modeled deep crustal structures will be used to better understand how the rifting processes relate to the Mesozoic orogenic inheritance.
Neutrinos, electrically-neutral particles interacting exclusively through the weak force, were initially considered massless in the Standard Model. However, the discovery of neutrino oscillations in vacuum and matter by Super-Kamiokande (1998) and the Sudbury Neutrino Observatory (2002), respectively, established that neutrinos are massive. Thus, neutrinos became the first evidence of physics beyond the Standard Model.
Although elusive, neutrinos are everywhere and they are produced from different sources. In particular, neutrinos are produced in large quantities in supernovae. However, to this date, the observation of supernovae through neutrino detection has been limited to a single event, SN1987A. Another possibility for studying supernova neutrinos is through the detection of the Diffuse Supernova Neutrino Background (DSNB) which represents the collective flux of neutrinos emitted by all past supernovae in the universe.
The detection of supernova neutrinos and in particular of the DSNB can provide information about the supernova explosion dynamics and neutrino properties. In this poster, I will present the main findings of my work, which focuses on investigating neutrino decay using supernova neutrinos.
A recent estimation of inorganic nanophase global fluxes across the critical zone indicates that the vast majority of these compounds originate naturally, and are comprised of clays and oxides released from soil [1]. Most of these natural nanophases are carried by rivers, with clays alone accounting for an estimated flux of 103 to 104 Tg per year. Though metal oxide nanophases are less abundant, they play a crucial biogeochemical role, particularly at continental margins. However, the formation and fate of these nanophases are still poorly understood. To gain insight, we take advantage of the unique capabilities of the Landscape Evolution Observatory (LEO) replicate mesoscale hillslopes in Tucson, Arizona, USA to unveil the mechanisms leading to the production of nanophases during soil formation.
The LEO facility consists of three constructed hillslopes, each measuring 30m in length, 10° in slope and covered with 1 m of crushed basalt. This exceptional instrumentation enables us to collect soil and effluent solutions at high frequencies, under a precisely regulated yet temporally variable hydrological irrigation regime, using a complex, field-derived mineral assemblage subjected to weathering under controlled conditions. Effluent samples are analyzed using ICP-ToF-MS in single particle mode. This approach allows us to characterize the nanophases by identifying their multi- and single-element composition, concentration, and mass distribution.
Cadmium is a relative newcomer in stable isotopes geochemistry, although its utilization has gained some traction recently. This element, having one of the lowest 50 % condensation temperature of the moderately volatile elements (T50 = 502K), should be able to provide insights for the characterization of vaporization events. Moreover, it is siderophile and chalcophile, leading to a significant segregation in the core. Thus, study of the core formation could also probably benefit from Cd isotopic surveys.
We propose a new estimation for the isotope composition of the Earth mantle, based on the analysis of a set of mid-oceanic ridge basalts (MORB) and Archean lavas (komatiites). Komatiites were selected because they originate from melts caused by high melting rates, ensuring that no significant isotope fractionation occurs during melting. The most pristine komatiites gave up a δ114Cd = 0.14 ± 0.18 ‰ (2SD, n = 5) composition. Ridge basalts from the Atlantic, Indian and Pacific oceans were characterized by very homogeneous compositions, regardless of their locality. We obtained a mean isotope composition of 0.07 ± 0.10 ‰ (2SD, n = 23). The fact that komatiites and MORB have similar isotope compositions indicate that such melting rates do not produce significant isotope fractionation. From these samples, we determine a bulk silicate Earth isotope composition of 0.11 ± 0.10 ‰ (2SD, n = 28), which is significantly heavier than previously proposed compositions.
The objective of this research is to quantify how dust affects soil and stream chemistry in an upland watershed using experimental and modeling methods. At our field of study, a small (0.54 km$^2$) upland Mediterranean watershed located on Mont Lozère in the National Park of Les Cévennes (France), field observations of calcium in stream water, rain, bedrock, soil, and plants could not be produced from reactive transport simulations of the weathering profile without an exogenous, long-term dust input. This place has been documented to be in the path of Saharan dust exports, but the importance of these depositions had not been yet quantified. Thus, we developed a process-based reactive transport framework by modifying the open source CrunchTope software in order to quantitatively interpret the impacts of dust deposition and solubilization in stream water chemistry, regolith weathering rates, and ecosystem nutrient availability.
By adding a carbonate-rich input consistent with the composition of Saharan dust, both stream water chemistry and elemental mass-transfer coefficients in the soil profile better align with field observations, suggesting that dust has become a significant input to this field site in the last ~10 ka. Over this period, this deposition has introduced far more calcium into the system than what could be supplied by the Ca-poor granitic bedrock. This is the first demonstration of solid phase dust deposition incorporated into a multi-component reactive transport framework. Moreover, this work shows how dust incorporation affects geochemical cycling across upland watersheds beyond the limitations of simplified steady state assumptions, a feature which will enable further research of a variety of Critical Zone systems subject to the effects of environmental change scenarios.
Volatile elements play important roles in life development and planetary evolution. Therefore tracking their origin on planets is key for understanding habitability. Nevertheless, how and when they were delivered to Earth is still unclear. Were they accreted during core formation$^{[1]}$ or after (a.k.a. late veneer hypothesis)$^{[2]}$? Was it throughout the accretion process or only within the later stages$^{[3]}$?
In order to answer these questions, we consider a set of elements : sulfur, selenium and tellurium (S, Se, Te). They are similarly depleted on the bulk silicate Earth (BSE) with respect to other elements of similar volatility (e.g. Zn)$^{[1]}$. Planetary processes such as core segregation from an early Earth’s magma ocean may explain their depletion from the BSE since they are both, siderophile (iron-loving) and volatile elements. Although previous studies indicate they should have been delivered to Earth after core formation, these experiments are well below the expected metal-silicate equilibration conditions for early Earth$^{[4]}$, rendering the topic open to debate yet. Consequently, we present new experimental results obtained at direct conditions expected for core-mantle equilibration$^{[5]}$. Significantly, they show striking differences from those obtained at lower pressures and temperatures. With these results, we can argue that volatile elements should not be considered in the context of a late veneer, changing the view on the nature of Earth’s accretion material.
[1] Wood, B. J., et al. (2006). Nature, 441(7095), 825-833. [2] Albarede, F. (2009). Nature, 461(7268), 1227-1233. [3] Suer, T. A., et al. (2017). Earth and Planetary Science Letters, 469, 84-97. [4] Rose-Weston, L., et al. (2009). Geochimica et Cosmochimica Acta, 73(15), 4598-4615. [5] Wade, J., & Wood, B. J. (2005). Earth and Planetary Science Letters, 236(1-2), 78-95.
The JEM-EUSO (Joint Exploratory Missions towards an Extreme Universe Space Observatory) collaboration is developing a series of balloon and orbital telescopes to detect fluorescent UV emission from the Earth atmosphere, with the primary aim to study ultrahigh energy cosmic rays (UHECRs) from space.
The detectors have a wide field-of-view, high temporal resolution (1-2.5 μs) and single photon sensitivity. Currently one of these detectors (Mini-EUSO) is operating onboard the ISS. The last stratospheric balloon mission (EUSO-SPB2) was launched in May 2023. The next generation detectors are in preparation, namely the stratospheric balloon EUSO-SPB3/PBR and orbital space-based detectors K-EUSO and POEMMA. These projects use the same photo-detection modules (PDMs) composed of 36 multi-anode photomultiplier tubes (MAPMTs) with 2304 channels in total. Mini-EUSO uses one PDM, EUSO-SPB2 three, and EUSO-SPB3/PBR uses 4 PDMs. Big space projects such as K-EUSO and POEMMA will use dozens of PDMs.
A new method was developed to characterize the performance of the PDMs and provide absolute calibration of the MAPMTs used in the different JEM-EUSO missions. The characterization includes the photodetection efficiency of each pixel (including sub-pixel structures), their actual surface area, and the double pulse resolution. The method and its application to the EUSO-SPB2 PDMs in different modes of operation will be presented.
Landslides are efficient erosion processes that release large volumes of sediments in rivers, posing threats to nearby population when remobilised during large flood events. Thus, understanding the dynamics and controls of landslides and quantifying the volumes involved in subsequent sediment transfer are crucial for resilient development in mountainous settings.
In this study, we use the very high standing island of Réunion (Indian Ocean) as a natural laboratory to investigate the interaction between landslides, sediment transfer and climatic forcing.
Here, we focus on studying the Grand Éboulis landslide short-term and mid-term dynamics using SAR imagery and photogrammetry. First, we computed cumulative displacement maps and time series every 12 days between 2017 and 2021. These time series reveal velocity fluctuations, including acceleration and/or deceleration episodes, correlated with extreme climatic events such as intense precipitation and drought episodes.
Second, we investigated the mid-term dynamics of Grand Éboulis, spanning from 1966 to 2011, using a series of seven Digital Surface Models. Results indicate numerous catastrophic failures in or near the steepest slopes of the landslide that experience the highest velocity gradients. The sediment volumes involved in such events range from a few tens of thousands to millions of cubic meters, predominantly released into the nearby river and transported away from the landslide.
Overall, our results suggest that the Grand Éboulis landslide is in an active mobilisation phase with a continuous slow displacement primarily influenced by extreme climatic events and with catastrophic failures that release large volumes of sediments in the nearby river.
As of today, the Hubble diagram allows to infer cosmological parameters such as the Dark Energy equation of state (w) with an accuracy reaching a few per cent. Upcoming SNIa samples with O(30,000) SNe (30 times the current worldwide statistics), will allow to reach the per cent level and start probing potential evolutions of w with the redshift. To reach this goal, an effort has to be made to push the level of the systematic uncertainties affecting the distance measurements down to ~0.1%. In particular, luminosity distances are affected by a selection bias called 'Malmquist bias'. Being able to see only the most luminous supernovae at high distances decreases the apparent mean magnitude of the population and therefore, negatively biases the estimation of distances at high redshifts.
In current analyses, the value of this bias is determined by time-consuming simulations based on either a Bayesian framework or a multiple-time fitting approach. As a faster alternative, we present a maximum likelihood-based method relying on a fast computation of the truncated likelihood function and its first-order derivatives. This new method allows us for a given survey to simultaneously estimate the luminosity distances of supernovae and the selection function of the survey. This prevents the distances from being biased and eases the propagation of uncertainties as all the parameters of the model are fitted at the same time. Eventually, we expect the inference of luminosity distances to be faster by a few orders of magnitude when compared to a classic Bayesian framework.
While the isostatic compensation of crustal thickness and density heterogeneity provides the dominant contribution to Earth’s observed topography, a significant difference persists between these two fields, known as ‘residual topography’. This discrepancy arises from dynamic processes within the mantle, primarily driven by time-dependent vertical surface stresses from mantle convection. These mantle convection dynamics also lead to disparities between the observed geoid and the isostatic geoid resulting from crustal heterogeneity, known as the ‘residual geoid.’ The combined consideration of both residual geoid and topography provides unique and fundamental global constraints on the amplitude and spatial distribution of density anomalies in the convecting mantle.
Although isostasy plays a crucial role in residual geoid and topography determination, the precision of constraints is strongly dependent on isostasy calculation quality. The first-order treatment of hydrostatic equilibrium used by classic isostasy theory is insufficient to accurately calculate isostatic geoid anomalies on a compressible, self-gravitating mantle. Thus, using dynamic kernels computed employing a viscous flow model that includes a fully compressible mantle and core (based on the PREM reference model) with self-gravitation, we provide a geodynamically consistent method based on the surface loading response.
Another important consideration is the accuracy of global crustal heterogeneity models. Our analysis shows significant variations in the predicted residual geoid and topographic fields utilizing CRUST1.0 and the most recent ECM1 crustal heterogeneity models. We shed light on the importance and implications of these distinctions for achieving the most precise constraints on density anomalies in the convecting mantle.
Radiation damage significantly impacts the performance of silicon tracking detectors in Large Hadron Collider (LHC) experiments such as ATLAS and CMS, with signal reduction being the most critical effect. While adjusting sensor bias voltage and detection thresholds can help mitigate these effects, generating simulated data that accurately mirrors the performance evolution with the accumulation of luminosity, hence fluence, is crucial.
The ATLAS and CMS collaborations have developed and implemented algorithms to correct simulated Monte Carlo (MC) events for radiation damage effects, achieving impressive agreement between collision data and simulated events.
In preparation for the high-luminosity phase (HL-LHC), the demand for a faster ATLAS MC production algorithm becomes imperative due to escalating collision rates, events, tracks, and hits, imposing strict constraints on available computing resources. This talk outlines the philosophy behind the new algorithm, its implementation strategy, and the essential components involved. The presentation also includes results from closure tests and first evaluation of algorithm performance.
The temporal synchronism between large igneous provinces (LIP) emplacements and mass extinction all along the Phanerozoic reveals a possible link between the two. The release of huge amount of gases during the LIP emplacement is considered to cause major climate and environmental perturbations possibly leading to a biodiversity crisis. However no clear correlation can be drawn between LIP’s properties i.e. the LIP size, the amount of gas released, etc… and the mass extinction severity.
Our primary focus was on investigating the consequences of the Siberian traps emplacement which is considered to be responsible of the end-Permian mass extinction. This biodiversity crisis lead to the disappearance of 90% of the marine species and 75% of the terrestrial species. The Siberian volcanism has produced 3 to 5 millions km3 of magma over a period not exceeding 1 Myr according to U-Pb dating. This volcanism is accompanied by the release of huge amount of gases within the atmosphere, notably CO2 and SO2.
These gases have two sources : the magmatic degassing and the thermogenic degassing generated by the intrusion of magmas in carbonate-rich or evaporite-rich sediments deposited within the Siberian basin. We propose to explicitly model volcanism by considering both short-term and long-term scale processes along the entire LIP emplacement with different scenarios to mimic the sequence of volcanic and thermogenic gas emissions. For this purpose, we employed the biogeochemical model GEOCLIM to simulate the changes of the ocean in term of temperature and pH caused by the LIP emplacement. This approach enables a detailed exploration of the impact of LIP emplacement on the climate and geochemical cycles.
One of the major questions in climate science is to improve the accuracy of sea-level rise prediction, for which mass loss of the polar ice caps has a significant contribution. In this work, the focus is on buoyancy-dominated capsize of large icebergs.
To better quantify ice mass loss due to iceberg calving at marine terminating glaciers, coupling iceberg calving simulation and inversion of the seismic waves generated by these events is necessary. To achieve our task, a complex fluid/structure model of the iceberg capsize is required to obtain accurate forces history acting on the glacier terminus. Therefore, based on our recent work, we implement a Computation Fluid Dynamics (CFD) approach to reach a high fidelity modelling of the iceberg capsize. First work using the experimental data of an iceberg capsize showed the need and ability of CFD computations to precisely reproduce the iceberg kinematics for different cases. We will present more advanced CFD configurations, including the contact between the capsizing iceberg and a rigid glacier front. Computation results are compared and validated against lab scale experiments, where we outline that some 3D effects cannot be neglected. We will also present full scale capsize simulations, in which the mixing of ocean layers occurs. In particular, we will quantify the transport of particles within the ocean to illustrate the potential change of nutriments distribution or of pressure experienced by local fauna due to iceberg calving.
Heating of the neutral interstellar medium is known to partly regulate the star formation in galaxies over long time scales and large spatial scales.
While the neutral gas heating is dominated by the photoelectric effect on small dust grains around Milky Way metallicity, the lower dust-to-gas mass ratio together with the higher occurence and luminosity of X-ray sources in metal-poor galaxies suggest that other heating mechanisms may contribute.
We will present a modeling study of the Dwarf Galaxy Survey, which comprises star-forming galaxies down to metallicities well below 1/10 solar metallicity, observed spectroscopically in the mid-IR and far-IR.
We use a photoionization and photodissociation grid to link the ISM signatures with specific heating mechanisms including the photoelectric effect, ionization by cosmic rays and photoionization by UV and X-ray photons.
Specifically, we use a combination of 1D models parametrized as statistical distributions within a Bayesian framework.
Our results confirm for the first time that the photoelectric effect heating becomes negligible below 1/10 metallicity and that X-rays provide significant heating, with an inferred X-ray luminosity that is in good agreement with direct observations.
The method offers an interesting prospective not only to recover the X-ray source nature and impact in low metallicity galaxies, but also to better understand the heating mechanisms and, more generally the star-formation properties, of galaxies in the early Universe.
Charlotte Catrouillet, Maitre de Conférence (IPGP) / Floriane Cangemi, Maitre de Conférence (UPC) / Dimitri Chuard, Chef de projet Ecole des Mines / Aurélie Coudurier-Curveur, SNCF / Baptiste Debret, M, Chargé de Recherche CNRS (IPGP) / Elodie Lebas, F, Phys. Adj. CNAP (IPGP) / Mathieu Ribot, M, ESRI France / Amaury Vallage, M, CEA
The variety of transit times and pathways water takes from infiltration to discharge through a hillslope determines the dynamic storage of the system, the capacity for water-rock-life reactivity, and ultimately the chemical composition of streamflow. The major solute concentrations recorded in these streams are often relatively invariant across a wide range of flow rates. Stable isotope fractionation of metal(loid) elements, such as silicon, are now offering a means to reveal the processes generating this invariance in stream chemistry through the study of concentration - isotope ratio - discharge (C-R-Q) relationships. However, in natural systems the interpretation of silicon isotope signatures (δ^30 Si) is complicated by a mixture of mineral precipitation and plant uptake controls. Here, we use three replicate artificially constructed hillslopes at the Landscape Evolution Observatory (LEO) in Tucson, Arizona as model catchments devoid of vegetation. By using the LEO hillslopes, we limit δ^30 Si fractionation solely to the effects of mineral precipitation. This unique environment enables us to test the effects of varying transit time distributions (TTDs) on δ^30 Si signatures. We collected samples and measured δ^30 Si from the discharge at the outlet of each hillslope during three randomized storm events. Despite highly variable irrigation scenarios, the δ^30 Si in aqueous discharge reflects consistent upgradient fractionation, retaining a signature across the three hillslopes defined by the unique hydrologic flow paths of the system. Our results expand upon previous work attributing intrasite variability in silicon stable isotope signatures to the hydrologic routing of fluid through catchments.
Silicate glasses, whether of industrial or volcanic nature are all made by cooling a high temperature melt to room temperature in a short amount of time. However, oxidoreduction reactions can occur during this quenching process, making the link between high and room temperature redox states complex. Understanding those reactions allow both to better control of the redox state of final glass, but also to retrieve the melting conditions from easy to perform room temperature measurements. The latter being of particular interest in volcanology where redox measurements of lava bombs are used to model the conditions within the magmatic chamber.
The present study uses in situ X-Ray Absorption Near Edge Structure (XANES) Spectroscopy to understand the oxidoreduction processes involved both at high temperature and during the quenching of simplified silicate glasses bearing iron and/or cerium. The results obtained are then compared to room temperature measurements performed using XANES spectroscopy, Raman spectroscopy and optical absorption spectroscopy.
Our finding demonstrates that, in simplified systems where only one multivalent element is present, the high temperature redox state is frozen during quenching. However, this is no longer true when a second multivalent element is introduced in the melt as both elements interact during quenching due to a charge transfer process. This leads to room temperature measurements being harder to link to the melting conditions.
In the present study, we want to determine if plane tree bark can be used as an efficent passive biosensor for the detection of urban NPs. For this purpose, several observations of metallic Nps have been undertaken to determine the localization of NPs within the tree bark and chose the smartest method to extract NPs. Following these observations, many methods to degrade selectively the tree bark organic matter are compared. A particular attention will be paid to the monitoring of the digestion. After assessing the optimum method for degrading the bark, the NPs were extracted. In addition, samples have been spiked by engineered NPs in order to quantify the recovery of the amount of NPs added, and then determine the robustness of the method.
Numerous studies have illustrated that mineral transformations have the capability to induce faulting at elevated pressure and temperature (PT), circumstances in which ductile flow would typically dominate. This mechanism, commonly known as transformational faulting, emerges as a plausible explanation for the puzzling phenomenon of deep-focus earthquakes occurring at depths up to 700 km. Currently, the debate partly revolves around determining why certain phase transformations lead to faulting while others do not. To better understand this phenomenon, we can compare different transformations taking place in similar experimental conditions and see how they do or do not cause strain localization and faulting. We conducted five deformation experiments at the DESY synchrotron using a large volume press. The synchrotron white beam was used to track phases changes in situ by means of powder X-ray diffraction, while acoustic emissions (AEs) were recorded using piezo-ceramic transducers. Two experiments focused on transforming olivine into its high-pressure polymorph, while the other three experiments targeted the quartz – coesite transformation.
The results show that depending on pressure and temperature conditions, as well as on how far from equilibrium they are, quartz and olivine undergo phase transformations at different rates. Specifically, we observed rapid olivine-ringwoodite kinetics at elevated PT, far from equilibrium, while slower kinetics were noted for the quartz-coesite transformation. During these experiments, we gathered data on thousands of AEs and tracked their locations by determining their arrival times on transducers. Interestingly, the spatial distribution of these AEs revealed that for some quartz experiments, AEs originated from fault planes that formed within the initially intact rock cores.
Our study supports the major role of mineral transformations in inducing faulting under high PT. These findings will help better quantify the intricate relationships between mineral transformations and faulting and in turn contribute to a better understanding of the fundamental geological processes behind deep and intermediate earthquakes.
DarkSide-20k is the next generation dual-phase TPC for direct dark matter search with 50 ton underground argon target, currently under construction at LNGS (Italy). With data taking to begin in 2026, DarkSide-20k will achieve cross-section discovery sensitivity of 10$^{-47}$ cm$^2$ searching for interactions of WIMPs with 0.1 TeV/c2 mass. The sensitivity projection relies on innovative technologies such as novel low-noise, high efficiency SiPM and Gd-loaded acrylic neutron veto, and on the extraordinary background rejection power of liquid argon. In this talk, a broad overview will be provided on the status of dark matter search and on recent updates of the experiment.
The distribution and behaviour of light non-aqueous phase liquids (LNAPLs), such as petroleum hydrocarbons, in subsurface environments are influenced by various factors, including flow and porous media characteristics. Description of the LNAPL distribution usually relies on capillary pressure and relative permeability concepts. According to the literature review, dynamic influence must be taken into account to adequately depict the scenario of two-phase flow in the petroleum reservoir applications. However, there is still uncertainty about this question regarding LNAPL redistribution under groundwater level variations.
The understanding of the spatial-temporal distribution of past earthquakes is essential to assess the event recurrence behavior and to estimate the size of potential earthquakes along major strike-slip fault systems. However, the scarcity of paleoseismic data remains a major hurdle in this endeavor. We document a paleoseismic record over the last 8kyr along the central-eastern Altyn Tagh Fault (ATF). The mean recurrence time of these events is 1371±625 yr with a COV of ~0.46, suggesting a quasi-periodic behavior. In the same fault section, 90 horizontal offsets record an average coseismic slip of 5.1 ± 1.4 m for the most recent event (MRE) and suggest at least four older earthquakes plausibly with a similar slip distribution.
We find that at the local scale (fault section) the earthquake recurrence is quasi-periodic along the ATF. However, at the regional scale (fault system) the tectonic strain seems to be released in bursts of seismic activity punctuated by periods of relative quiescence. These bursty periods of seismic activity show mean interevent times of 475 ± 108 yr and are preceded by millennial long-lull periods of 1393 ± 230. Such rupture behavior at the regional scale is evident from a site-to-site correlation of rupture ages along four fault sections of the ATF. Here, we also discuss about some pitfalls to consider when using the current methods to combine paleoseismic data. Finally, we propose a new approach to integrate paleoseismic event data from multiple sites into a single earthquake time history.
In 2016, a new term spread through newspapers with the first detection of gravitational waves by the LIGO detectors. In addition to further proving the theory of General Relativity postulated by Albert Einstein one hundred years prior, this discovery paved the way for a completely new method of observing the Universe. Due to their nature, gravitational waves cannot be blocked by dust or matter, making them ideal for contemplating the very first moments of the Universe. In this talk, I will delve into the science that a galactic-sized gravitational wave detector using dead stars, namely a Pulsar Timing Array (PTA), can accomplish, as well as the current status of the European PTA results.
Chemical weathering, which involves the breakdown of primary minerals in rocks and the formation of secondary minerals like clay and iron oxides, is a crucial process in the Critical Zone (CZ). It contributes to soil formation, nutrient supply to ecosystems, and the regulation of the long-term carbon cycle. Despite its importance, understanding the complex interplay of climatic, geological, and human-driven factors influencing chemical erosion remains a challenge. To gain insights, we must discern the origins, distribution, and magnitude of chemical weathering fluxes, as they shape the evolution of the CZ and influence soil erosion dynamics amid changing climate conditions and human activities. Two trace elements, Lithium (Li) and Strontium (Sr), serve as potent proxies for weathering. Li is a tracer of the extent of weathering, while Sr trace the signature of weathering sources. We employed these proxies in studying small catchments in the highly eroding European Alps, characterized by varying lithologies, vegetation cover, and physical erosion patterns. Interestingly, we found that Li concentrations in these catchments are more closely linked to hydrological factors than physical erosion processes.
During its formation 4.56 billion years ago, the Earth’s mantle was extensively molten mainly due to the heat released through collisions (Tonks & Melosh, 1993). In particular, the last giant impact that formed the Moon gave rise to a global magma ocean that could have reached the core mantle boundary (Canup, 2004, 2008; Piet et al., 2017). After what, the planet progressively cooled down and this magma ocean started crystallising, a process that has partially shaped the structure and chemical composition of the present-day Earth’s mantle and atmosphere but that is still not well understood. For instance, the composition of the first solid cumulates that formed at depth in this magma ocean remains poorly constrained although highly controlling the Earth’s crystallization path.
Thanks to a cutting edge experimental protocol of melt crystallisation in laser-heated diamond anvil cells (Nabiei et al., 2021), we measured by quantitative EDXS on an analytical transmission electron microscope the composition of the liquidus phase (i.e. the first solid cumulates) of a pyrolitic melt at four different pressures (55, 87, 107 and 130 GPa). As already suggested by previous works (Fiquet et al., 2010; Andrault et al., 2011; Nomura et al., 2014), our experiments show that bridgmanite is the first mineral to crystallize across the whole lower mantle. We further constrained theoretical bridgmanite-ferropericlase cotectics (Boukaré et al., 2015) with our experimental data set and reported them in FeO-MgO-SiO2 ternary diagrams along with the composition of our samples.
Les composés per et polyfluoroalkyles (PFAS) font référence à une classe de substances
chimiques qui contiennent des atomes de carbone liés à des atomes de fluor. C’est une famille de plusieurs milliers de substances inconnues qui limite la compréhension de leur devenir dans
l’environnement [1-2] Les précurseurs oxydables sont des composés chimiques qui peuvent être transformés en PFCA (polyfluoroalkyles carboxyliques) lors de processus d'oxydation, comme ceux rencontrés dans l'environnement ou lors du traitement de l'eau. [3-5] Pour évaluer les précurseurs des PFAS des procédures d'oxydation appelées TOP assay pour “ Total Oxydable Précurseurs” sont utilisées pour convertir les précurseurs en PFCA. Les produits obtenus peuvent ensuite être analysés par des techniques d’analyses ciblés. [6-10] Dans le cadre du projet Européen GREENDEAL PROMISCES (Projet n°101036449), de la méthode TOP Assay, ses protocoles, son application et ses performances dans le domaine de l'analyse des PFAS sont étudiés.
L’approche analytique comprend d’une part des procédures d'oxydations permettant la mesure de la contribution des précurseurs de PFAS dans les rejets de STEP et une analyse ciblée par une chaîne UPLC couplée à un spectromètre de masse en tandem. La dilution isotopique a été utilisée pour la quantification.
Les premiers résultats de l’étude du protocole permettent l’analyse des 56 PFAS. Les performances et l’application aux matrices environnementales (eaux usées) sont étudiés.
Cette procédure mise en parallèle avec l’analyse directe caractérise le gap entre les 56 PFAS et la présence d’autres substances. Elle permet de quantifier l’apport réel dans
l’environnement des rejets de STEP et leur potentiel PFCA qui sont les molécules règlementées à l’heure actuelle. Elle nous donne un aperçu de la nécessité d'un monitoring pertinent pour comprendre les voies de transformation des PFAS.
Persistent per- and polyfluoroalkyl substances (PFAS) result in diffuse pollution.
To address this issue, Trang et al. investigated a low-temperature degradation (80-120°C) of perfluorooctanoic acid (PFOA) (at 36 g/L) using a mixture of dimethyl sulfoxide (DMSO), NaOH (30/1 NaOH/PFOA molar ratio) and milli-Q water (8/1 DMSO/water volume ratio). We explored a more practical degradation process.
PFOA doping concentration (893 mg/L) was selected to decrease the dilution factor and quantify PFOA and by-products at µg/L level, while enabling F- measurements. The degradation process was examined over six days at 120°C.
Ultra-high-pressure liquid chromatograph coupled with a mass spectrometer (UPLC-MS) was performed for quantitation of PFOA, perfluoroheptanoic acid (PFHPa), perfluorohexanoic acid (PFHxA), perfluoropentanoic acid (PFPeA), and perfluorobutanoic acid (PFBA). For fluoride F- analyses, a selective F- electrode was used. SEM-EDS were coupled for NaF characterization of dried surface of 20 µL of the mixture after reaction.
Experiments highlighted the necessity of maintaining at least twice larger the DMSO/H2O volume and twenty to one higher the NaOH/PFOA mole ratio to ensure effective PFOA defluorination while minimizing by-products. PFHpA, PFHxA, PFPeA fell below the limit of quantification after 30 min; PFBA after 12 hours, while surfaces of peaks at 325 m/z, 275 m/z, 229 m/z, 225 m/z and 114 m/z (TFA) by-products were declining versus time without reaching zero after six days. Simultaneously, F- content reached its maximum ( 80% vs total F provided by PFOA) after 18 hours. This maximum is identical to that at 140°C. Experiments are in progress to identify and quantify unusual by-products and carry out mass balance.
Microorganisms are ubiquitous in all the Earth’s surface and sub-surface environments. To date, their number is estimated at ~10^30 cells, which is considerable compared to the number of stars ~10^21 currently known to exist in galaxies in the universe. On Earth, prokaryotes alone account for ~15% of total biomass. Microorganisms are then considered as a major environmental compartment. They are mainly organized as biofilms which are 3D structures where microbial cells are encased in a self-secreted exopolymeric matrix. Particularly, it shows a limited transport of nutrients and elements along the biofilm thickness. Combined with a high metabolic activity, biofilms then exhibit specific and highly reactive pockets in their 3D structure, known as microenvironments, which determine their reactivity with metals for example. It is therefore a challenge to study these microenvironments without destroying the biofilm structure. Confocal laser scanning microscopy (CLSM) is a technique of interest. It enables the structure to be preserved and imaged in 3D using appropriate probes. In this study, we are particularly interested in imaging the redox microenvironments in biofilm in relation to its structure, using a combination of fluorophores that target biofilm structure and highly reactive oxygen-related redox species (ROS).
Monitoring the activity of volcanic edifices is central to the mitigation of volcanic risks and hazards. It implies to monitor and analyse multivariate data which can have complex natures and behaviours. Consequently, observatories need to communicate about the state of the volcano in understanding terms for the population and the decision-makers. The difficult task of analysing large amounts of data could be improved by using machine learning.
Machine learning may be a key method to perform time series analysis on volcanic edifices. Its use could bring new insights and improve the anticipation of eruptions. Indeed, these algorithms are particularly effective in analysing and forecasting time series. Such algorithms are already in use to monitor volcanic activity at Colima (Mexico) and Whakaari (New Zealand) by analysing seismic signals. Yet, the detection of precursor remains a challenging task since volcanoes and their eruption have non-linear evolution.
In this study, we test if and how signals from seismicity and ground deformation can be combined to detect and forecast volcanic eruptions at Piton de la Fournaise. The idea behind is to leverage possible unknown correlations between geophysical signals. We analyse height signals from the past twenty years using various machine learning algorithms (XGBoost and deep neural networks) to predict the current and future state of the volcano.
Since its discovery in 1965, the Cosmic Microwave Background (CMB) has become one of the main cosmological probes for studying the Universe. The CMB is a major piece of evidence in favor of a "hot Big Bang" model, and it has provided us with very precise measurements of the parameters of the standard cosmological model, in particular thanks to ESA's Planck satellite. However, questions remain concerning the origin of the Universe and the first moments after the Big Bang.
Many theories predict that gravitational waves were produced in this very early time, during an epoch of accelerated expansion known as "cosmic inflation". Those waves thus encode invaluable information about the physics that take place at extremely high energies, where our current theories break down. The polarization of the CMB, potentially bearing trace of those events, is one of the most promising probes in that regard.
As a consequence, the next generation experiments will measure the polarized CMB with unprecedented sensitivity and precision, thereby challenging our ability to analyze huge data sets, which will exceed the petabyte ($10^{12}$ bytes) in size. My work, in the Simons Observatory and CMB-S4 collaborations, consists in reconstructing the sky signal observed by the telescopes over many hours of observation, a process known as "map-making". During this operation, we must characterize as well as possible the statistical properties of the reconstructed maps in order to retrieve the full cosmological information at the later stages of the analysis.
KM3NeT/ORCA is a large-volume water-Cherenkov neutrino telescope, currently under construction
at the bottom of the Mediterranean Sea at a depth of 2450 meters. The main goal of this experiment is to
determine the neutrino mass ordering as well as measuring atmospheric neutrino oscillation parameters. Beyond
these goals, the detector also exhibits sensitivity to diverse phenomena such as non-standard neutrino interactions,
sterile neutrinos, and neutrino decay. This contribution describes the state of the art of measuring neutrino oscillations with KM3NeT as well as the use of a machine learning framework for
building Deep Neural Networks (DNN) for energy regression to boost the experiment's sensitivity. By combining
data from six detection units, the optimization of these models attempts to improve the oscillation analysis
by using a sizable data sample of 433 kton-years from KM3NeT/ORCA. The performance of the DNN is
assessed by determining the sensitivity to oscillation parameters in comparison with the conventional energy
reconstruction methods of maximizing a likelihood function. The results demonstrate the DNN’s ability to provide
an improved energy estimate, exhibiting less bias within the context of oscillation analyses. This research not only contributes to the refinement of neutrino detection
methodologies but also serves as an example on how the use of machine learning techniques may improve the
precision of data analyses in the realm of neutrino physics.