The birth of a neutron star with an extremely strong magnetic field, called a magnetar, has emerged as a promising scenario to power a variety of outstanding explosive events. This includes gamma-ray bursts, among the most luminous events observed up to high redshift and therefore useful as cosmological probes, but also supernovae with extreme kinetic energies called hypernovae and other classes of super-luminous supernovae. Simple phenomenological models, where the magnetar rotation period and magnetic field are adjusted, can explain many of these observations but lack a sound theoretical basis. The goal of this proposal is to develop an ab initio description of magnetar powered explosions in order to delineate the role they play for the production of gamma-ray bursts and super-luminous supernovae. This is urgently needed to interpret the growing diversity of explosions observed with ongoing transient surveys (iPTF, CRTS, Pan-STARRS) and in the perspective of future programs of observations such as SVOM and LSST. By using state-of-the-art numerical simulations, the following outstanding questions will be addressed: 1) What is the origin of the gigantic magnetic field observed in magnetars? The physics of the magnetic field amplification in a fast-rotating nascent neutron star will be investigated thoroughly from first principles. By developing the first global protoneutron star simulations of this amplification process, the magnetic field strength and geometry will be determined for varying rotation rates. 2) What variety of explosion paths can be explained by the birth of fast-rotating magnetars? Numerical simulations of the launch of a hypernova explosion and a relativistic GRB jet will provide the first self-consistent description of both events from a millisecond magnetar. Furthermore, the new understanding of magnetic field amplification will be used to improve the realism of these simulations.

Wetlands, fragile ecosystems that play an important role in the global water and carbon cycles, cover a non-negligible part of the terrestrial surface and render numerous services to humankind. Their role as carbon sinks or CO2 and CH4 sources depends on the prevailing hydrological conditions and is sensitive to rising atmospheric CO2 concentrations, regional climate change, as well as to water management and land use. Modifications of carbon and water dynamics within wetlands are already detectible and can be expected to amplify during the coming decades. Yet, numerous gaps of knowledge exist concerning their CO2 and CH4 flux quantifications and future dynamics, partly due to scarce global databases, and modelling of these dynamics are still highly uncertain. Focusing on China, where extensive wetlands exist and are projected to undergo vast changes, this project aims to analyse the response of wetland carbon emissions to changing hydrological conditions and atmospheric CO2 concentrations, taking into account contrasted regional land use and water management scenarios. An integrated approach combining measurements of CO2 and CH4 fluxes in numerous wetland types of China with new parameterizations of a dynamic vegetation model coupled with a hydrological model is proposed. The project covers changes occurring through the 20th and 21st centuries. It will be undertaken by the Researcher with two world leading teams in Earth System sciences, bringing in both expertise in modelling the terrestrial carbon cycle, datasets and knowledge of ecological processes. The research will deepen and broaden the Researcher’s competences, build long-term skills and collaborations, promote transfer of knowledge to China and contribute to European excellence and competitiveness. Special attention will be given to disseminating results to both the general public and the non-academic sector through a secondment.

The technology of femtosecond lasers now makes it possible to reach enormous light intensities with only moderate amounts of energy. These so-called Ultra-High Intensity (UHI) lasers have led to the development of a very active research field, which studies the interaction of light with matter at these extreme intensities. This field is largely motivated by the prospects of generating compact sources of high-energy particles and short-wavelength light, which are being foreseen for applications in particle physics, material science, nuclear fusion technology, medicine. The actual feasibility of the promising applications of UHI lasers will largely depend on the availability of more reliable and controlled laser systems. In this context, the recent results obtained in the framework of the ERC project PLASMOPT have shown that both major obstacles and great prospects towards this goal are related to space-time couplings (STC) – i.e. a spatial dependence of the laser pulse temporal structure. Yet, there is still no device capable of measuring these STC. The goal of the present project is thus to bring up on the market the first STC measurement device, called TERMITES. This will allow identifying the source of the residual STC, and then eliminating them to reach optimal performances, thus reducing the cost needed to reach a given laser peak intensity by hundreds of k€ or more. It will also have indirect societal benefits, by contributing to the maturation of the technology of UHI lasers, and thus favouring their foreseen societal and industrial applications. Two key tasks of this project are 1- building two to three industrial demonstrators of TERMITES and 2- using these demonstrators to perform a test and validation campaign on a representative set of fs lasers. Depending on the findings of this campaign, this device will be commercialized either through a technology transfer through licensing to an existing company, or through a start-up creation.

The artificial intelligence community, inspired by the tremendous progress made in neuroscience, has recently proposed powerful algorithms to enable effective real-time decision making based on a limited volume of noisy sensory data. However, implementing such algorithms in low-power devices remains a challenge due to the energy inefficiency that comes from separating logic and memory in current electronic systems. For the past 10 years, research groups have been developing alternative electronic components and systems, such as brain inspired computing architectures and novel resistive memory technologies to address this design bottleneck. The critical feature for these new technologies to perform at their best is a very high-density, reliable, non-volatile memory with infinite endurance. This ideal memory does not exist today, and it is unlikely it will ever exist. This project takes inspiration from the insect’s nervous system. The general aim of DIVERSE is to enable learning from a very limited volume of noisy data based on imperfect, limited density, low endurance, resistive memories. Unlike digital systems, insects are not very good at performing precise calculations, but they excel at making extremely energy-efficient real time decisions by combining sensory data recorded in noisy environments. I thus propose to take inspiration from the well-studied cricket’s nervous system and to use my experience and skills in resistive memories to develop a new technology that expresses robust cognitive behaviour while interacting with the environment. This cross-disciplinary work will lead to the fabrication of an innovative hardware/software platform with extremely high power efficiency and robust cognitive computing capabilities. This new technology will open new perspectives in dynamically developing areas including service and consumer robotics, implantable medical diagnostic microchips and wearable electronics.