Can we predict the weather or the climate?
According to everyone's experience, predicting the weather reliably for more than a few days seems an impossible task for our best weather agencies. Yet, we all know of examples of “weather sayings” that allow wise old persons to predict tomorrow’s weather without solving the equations of motion, and sometimes better than the official forecast. On a longer scale, climate model have been able to predict the variation of mean Earth temperature due to CO2 emission over a period of 50 year rather accurately.
In the late 50’ and 60’s, Lewis Fry Richardson, then Edward Lorenz set up the basis on the resolution of this puzzle, using observations, phenomenological arguments and low order models.
Present progress in mathematics, physics of turbulence, and observational data now allow to go beyond intuition, and test the validity of the butterfly effect in the atmosphere and climate. For this, we will use new theoretical and mathematical tools and new numerical simulations based on projection of equations of motion onto an exponential grid allowing to achieve realistic/geophysical values of parameters, at a moderate computational and storage cost.
The goal of this PhD is to implement the new tools on real observations of weather maps, to try and detect the butterfly effect on real data. On a longer time scale,, the goal will be to investigate the “statistical universality” hypothesis, to understand if and how the butterfly effect leads to universal statistics that can be used for climate predictions, and whether we can hope to build new “weather sayings” using machine learning, allowing to predict climate or weather without solving the equations.
Development of an X-ray detection system for particle ID of superheavy nuclei
The synthesis and study of the superheavy nuclei (SHN) is still one of the major challenges of modern nuclear physics. Experimental studies of hitherto unknown nuclei depend crucially on their identification in terms of atomic charge Z and nuclear mass A. To complete particle ID capabilities of the separator-spectrometer set-up S3 at GANIL-SPIRAL2, already providing a mass resolution sufficient to resolve the A of SHN, its focal plane detection system SIRIUS will be provided with X-ray detection for Z identification of the species of interest. The development of an X-ray detection system array, employing thin germanium crystals with thin entrance windows (based on so-called Low-Energy Photon Spectrometers (LEPS)), its integration in the SIRIUS set-up as well as its in-beam test and use for SHN decay spectroscopy will be the main tasks of the Ph.D. thesis. The Ph.D. student will be involved in SHN spectroscopic studies at GANIL and international accelerator laboratories like ANL, which serve as efficient preparation of the experiment campaigns planned at S3 which is scheduled to come online in 2024. This Ph.D. thesis work is an important ingredient for the preparation of the detection instrumentation needed for the S3 operation.
Study of reaction mechanisms for the synthesis of super-heavy elements
One of the main activities in nuclear physics is the study of the properties of the exotic nuclei up to the limits of the nuclear chart, in regions with extreme proton-neutron ratios (proton/neutron driplines) and at the highest masses A and atomic numbers Z. The so-called super-heavy nuclei (SHN) are expected to exist beyond the liquid drop limit of existence defined by a vanishing fission barrier, thanks to the quantum mechanical shell effects. These nuclei are particularly interesting because they are at the limit between few-body and large n-body physics: the magic proton and neutron numbers, Z and N, are replaced by a magic region or island extended in Z and N.
The synthesis of these very and super-heavy nuclei by fusion-evaporation reactions is an experimental challenge due to the extremely low cross-sections. Modelling the complete reaction in order to guide the experiments is also a difficult challenge, as models developed for lighter nuclei cannot simply be extrapolated. Fusion reactions are hindered compared to what is observed with light nuclei, because the very strong Coulomb interaction is enhanced by the strong repulsion caused by the large number of positive charges (protons) in the system in competition with the attractive strong (nuclear) force in a highly dynamic regime. The predictive power of the models needs to be improved, although the origin of the hindrance phenomenon is qualitatively well understood. The quantitative ambiguities are large enough to observe a few orders of magnitude differences in the fusion probabilities calculated by different models. A small change in the cross-section could result in many months being required to perform successful experiments.
At GANIL, in collaboration with other institutes, we have developed a model that describes all the three steps of the reaction to synthesise super-heavy nuclei. Future developments will focus on finding ways to assess the models in order to improve their predictive power, including the design of dedicated experiments to constrain the so-called fusion hindrance. Of course, a careful uncertainty analysis, which is new in theoretical nuclear physics, will be necessary to assess the different ideas. Standard methods as well as state-of-the-art data analysis methods such as Bayesian analysis may be used.
This PhD work will be done in collaboration with the experimental group at GANIL and a research team in Warsaw (Poland). Depending on the skills of the student, the thesis will be more oriented towards formal developments or towards the experiments at the new S3 facility at Spiral2. Participation in experiments is possible.
Scaling of cytoskeletal organization in relation to cell size and function
Each cell type, defined by its function and state, is characterized by a specific size range. Indeed, cell size within a specific cell type displays a narrow distribution that can vary from as much as several orders of magnitude between smaller cells, such as red blood cells, and large muscle cells. Interestingly, this size characteristic is essentially maintained during the life cycle of an individual and highly conserved among mammals. Altogether, these features suggest that maintaining “the right size” for a given cell could play an important role in performing its function.
The actin cytoskeleton, that can form different stable while dynamic intracellular architectures, plays a major role in the structural plasticity of cells in response to changes in shape and size. Our recent work suggests that actin networks developed within a cell scale with the actual size and volume of the cell. However, how cells adapt the turnover and organization of their numerous structures assembled from a limiting pool of actin monomers remains to be understood.
In this project, we thus propose to study the organization and dynamics of actin networks in selected cell types displaying distinct sizes. In particular, our study will focus on characterizing the impact of such networks organization/dynamics on different cellular functions such as cell migration or adaptability to environmental cues. The feedback between cytoskeletal architecture dynamics, cell size and function will also be addressed by perturbing the organization and dynamics of the actin cytoskeleton in these cells.
PRObablistic on-edge learning for SPINtronic-based neuromorphic systems
The hired joint UGA – KIT PHD candidate should be able to cover the work of the workpackage 1 and 2. He/she will also participate to technical meetings and have a good understanding on how the tasks of the other technical workpackages are executed, mainly by the partners with internal effort. As a whole, the PHD candidate will develop and optimize compact Computing in Memory architectures, provide high level models for further integration in large scale designs, perform validation of all proofs of concepts of new architectural implementations. He/she will be involved also in the design of algorithmic implementations of Bayesian Neural Networks adapted to the architecture. More in details, he/she will work on the following directions:
Design and optimization of the probabilistic neural networks, will be executed mostly in SPINTEC Laboratory in Grenoble, that will include:
1. full design stack of hardware accelerator without selector transistor for frequent Read and Write operations.
2. Design and validate an innovative architectural approach able to compensate for sneaky paths phenomena.
3. High-level modeling of the full crossbar architecture that includes the stochastic component.
4. Propose a full simulation and validation flow scalable to scaled to realistic architecture size and parameters that implement Bayesian tasks.
5. Perform Delay, power consumption and area overhead figures of merit
Research of nanostructured oxides for CO2 capture assisted by synthesis robot and artificial intelligence.
The advent of robotic syntheses assisted by artificial intelligence opens up countless perspectives for the discovery of new nanomaterials, while raising the question of correctly validating these approaches. The goal of this thesis is to discover new nanostructured oxides to make CO2 capture and sequestration energetically efficient. This will require to 1) confirm or disprove that the automated preparation method (mixing robot coupled with a characterization platform by X-ray diffusion and gas analysis) is an approach representative of standard preparation methods, or if the automation is a new preparative approach independent of standard methods, and 2) confirm or disprove that the exploration of the vast space of parameters (nature of oxides, nanostructuring agents, injection laws) makes it possible to exceed the performances of the best current materials.
Time reversal invariance test in nuclear beta decay: Analysis of the data of MORA at JYFL
The Matter’s Origin from RadioActivity (MORA) experiment searches for a sign of CP violation in nuclear beta decay, via the precise measurement of the so-called D correlation. An innovative technique of in-trap ion polarization for such a measurement enables attaining unprecedented sensitivity to New Physics, which could explain the matter-antimatter asymmetry observed in the universe. With a goal in sensitivity on a non-zero D of a few 10-4, the measurement that MORA is undertaking at Jyväskylä will be competitive with the best limit obtained so far on a non-zero D correlation in neutron decay [5]. To attain such precision regime several weeks of data taking are required along the coming years (2025-2027) at Jyväskylä, both for 23Mg+ and 39Ca+. The data analysis has to be undertaken in parallel. Crosschecks and adaptation of existing simulations of individual detectors of MORA, performed with GEANT4 and PENELOPE Monte Carlo codes, are required to pursue the investigation of systematics effects potentially affecting the final sensitivity on D. Dissemination of the results of the data analysis at national and international conferences will be asked to the PhD student.
Development of a dosimetry system to track alpha particles in in vitro assays for Targeted Alpha Therapy
Targeted Alpha Therapy (TAT) is a promising new method of treating cancer. It uses radioactive substances called alpha-emitting radioisotopes that are injected into the patient's body. These substances specifically target cancer cells, allowing the radiation to be concentrated where it is needed most, close to the tumors. Alpha particles are particularly effective because of their short range and ability to target and destroy cancer cells.
As with any new treatment, TAT must undergo preclinical studies to test its effectiveness and compare it to other existing treatments. Much of this research is done in laboratory, where cancer cells are exposed to these radioactive substances to observe their effects, such as cell survival. However, assessing the effects of alpha particles requires special methods because they behave differently than other types of radiation.
Recently, a method for measuring the radiation dose received by cells in laboratory experiments has been successfully tested. This method uses detecto
Physics & control of dissipative divertor regime in WEST tokamak experiments
The success of the magnetic confinement fusion program relies on the control of the interaction between the hot confined plasma, where the fusion reactions take place, and the wall of the vacuum vessel in which this plasma is maintained. Currently, this interaction is managed by a hardware and magnetic configuration called the divertor, which aims to concentrate the lost plasma fluxes through a dedicated volume (the divertor volume) towards high flux components (surface components of the divertor). The control of dissipative phenomena in this divertor volume is a critical objective that shall allow maintaining high confinement performances in the core (hot plasma) while maintaining fluxes to the components below technological limits. The WEST tokamak, currently operated at CEA Cadarache, has as its main objective the control of this interaction, in close support with the ITER project. The thesis project aims to improve the physical understanding of the control experiments started on WEST, through advanced experimental analysis, to the optimization of a robust and generic control model that can be deployed on WEST to conduct scenarios representative of ITER conditions. The project will also be part of a very active international context on the subject, both in Europe (EUROfusion Activities), in Asia and in the United States, offering a wide spectrum of visibility and possibilities for collaborations and developments. The results will be published in peer-reviewed journals with possibly high impact factors, and may be presented at international conferences.
Quantification and Optimization of the Mechanical State of Nb3Sn Superconductors during the Heat Treatment
In agreement with the CERN’s advertised will for the implementation of a super-collider, FCC type, high field superconducting electromagnets, based on Nb3Sn, are being developed. In the framework of the HFM (High Field Magnets) European collaboration, the LEAS at CEA Paris-Saclay is designing, manufacturing, and testing superconducting magnet demonstrators generating up to 16 T. Nb3Sn conductors require a heat treatment at 650 °C. During this heat treatment, several physico-chemical phenomena lead to the formation of the Nb3Sn superconducting phase. These phenomena induce a mechanical state impacting the superconducting properties of the material. A study of the different phenomena inducing dimensional changes inside the conductors would allow estimating the stresses inside the Nb3Sn superconducting phase following the heat treatment. The goal of this thesis is to study, using modeling and experiments, the thermomechanical state of the conductors during the heat treatment in order to estimate the internal stresses and their impact on the superconducting performances. The results will allow the improvement of the Nb3Sn superconducting properties in view of the production of high field magnets for future accelerators.