For the last 15 years, optics has undergone a remarkable evolution towards ever decreasing sizes, better integration in complex systems, and more compact devices readily available to mass markets. Whereas traditional optics is at the centimeter scale, newly developed techniques use nanoscale objects to control, guide, and focus light. From the capability to shape metallic and dielectric nanostructures has emerged the field of nanophotonics. Advances in nanophotonics offer the possibility to control the material’s optical properties to create artificial materials with electromagnetic properties not found in nature. Man-made 3D metamaterials have interesting fundamental aspects and present many advantages with respect to conventional devices. Unexpected effects have led to the development of interesting applications like high resolution lenses and cloaking devices. Inspired by this new technology, we have developed new 2D metamaterials. Our flat metamaterials (metasurfaces) are much simpler to manufacture than their 3D counterparts. By depositing a set of nanostructures at an interface, we can immediately control the light properties; unlike refractive optical components, the wavefront is modified without propagation. As of today, these interfaces are created using metallic nanostructures and work in the infrared. In this ERC, we plan to extend the concept of optical metasurfaces in the visible which is the most important wavelength range for applications. By combining with optically active semiconductors such as InGaAlN, we will add optical gain and modulation capability to the system to create new, efficient optoelectronic devices. The response of the metasurfaces is tunable by changing the environment surrounding the nanostructures. We will use this property to create ultrathin reconfigurable flat devices. Metasurfaces will be integrated with AlN/GaN to modulate light at high frequencies and further exploited to control polariton gases in solid state metasystems.

The explanation for the distinct low temperature behavior of amorphous solids (glasses) is a long-standing open question. Specific puzzles include the nature of the low energy excitations (LEEs) that are responsible for their low temperature thermal and mechanical behavior and the origin of the remarkable universality of their low temperature mechanical dissipation. The phenomenological tunneling model proposes that the LEEs are atomic-scale tunneling two level systems (TLSs) and successfully explains much of the low temperature behavior of glass, but not the universality. Recently, individual TLSs were probed in the amorphous tunnel junction of superconducting qubits, but such dielectric measurements might not access the LEEs responsible for universality. In contrast, I propose to search for individual TLSs using purely mechanical measurements. The glass samples containing the TLSs will be nanomechanical resonators, and the strain coupling between the mechanical mode and the TLS will be used to control the quantum state of the latter. This strain coupling allows coherent state transfer between the mechanical mode and the TLS. Identifying individual TLSs and controlling their quantum state in this manner will demonstrate that the LEEs responsible for the characteristic low temperature properties of glass are indeed TLSs. Furthermore, these measurements will reveal the characteristics of individual TLSs and their interactions with their environment, in contrast to bulk measurements in which, according to the model, the effects of many TLSs are averaged. The results of the proposed study may therefore strongly support the tunneling model. This would require reconsideration of potential explanations for universality which are thought to be inconsistent with the existence of TLSs. Alternatively, if the hypothesized TLSs are absent, then the tunneling model must be replaced by a new interpretation of the low temperature properties of glass.

Temporal environmental variation in natural systems includes a large component of random fluctuations, the magnitude and predictability of which is modified under current climate change. The need for predicting eco-evolutionary impacts of plastic and evolutionary responses to changing environments is still hampered by lack of strong experimental evidence. FluctEvol aims at shedding a new light on population responses to stochastic environments, and facilitating their prediction, using a unique combination of approaches. First, theoretical models of evolution and demography under a randomly changing optimum phenotype will be designed and analysed, producing new quantitative predictions. Second, statistical methodologies will be developed, and employed in meta-analyses of long-term datasets from natural populations. And third, large-scale and automated experimental evolution in stochastic environments will be carried out with the micro-alga Dunaliella salina, an extremophile that thrives at high and variable salinities. We will manipulate the magnitude and predictability of fluctuations in salinity, and use high-throughput phenotyping and candidate-gene sequencing to analyse the evolution of plasticity for traits involved in salinity adaptation in this species: glycerol and carotene content. We will thus combine the benefits of experimental evolution in microbes (short generations, ample replication) with a priori knowledge of ecologically relevant adaptive traits, allowing for hypothesis-driven experiments. The success of this project in increasing our predictive power about eco-evolutionary dynamics is warranted by the experience of the PI, at the interface between theoretical and empirical approaches. Our experiments will have relevance beyond academia, as we will modify through evolution the plasticity of traits (accumulation of energetic cell metabolites) that are direct targets for bioindustry, thus potentially overcoming current limitations in productivity.

Bacterial vaginosis (BV) is a polymicrobial syndrome that modifies vaginal secretions and increases risks of reproductive complications and most sexually transmissible infections. This syndrome is associated with a shift in vaginal microbiota composition from lactic-acid producing bacteria to specific bacterial communities. Concomitant with such shift, sialidases can be detected in vaginal secretions where they release sialic acids (SA), sugar molecules that some bacteria can use as a nutrient source and to escape host’s immunity. While the presence of sialidases is used as a BV diagnosis method, we still know little about SA metabolism in the species associated with BV, and even less about SA-related interactions in the community. The proposed project will directly address this question with the ultimate aim of understanding the role of SA metabolism in the transition from health to disease. I will focus my research on the three most prevalent BV-associated bacteria: Gardnerella vaginalis, Prevotella bivia and Atopobium vaginae. First, I will investigate the genomic organization and distribution of the genes involved in SA metabolism. Second, I will link these genotypes to phenotypes by experimentally assessing the expression of those genes in clinical samples from BV-positive and negative women. Third, I will assess the evolutionary stability of SA metabolism genes and bring insight into the respective roles of SA availability and host’s immune system in the evolution of bacterial SA metabolism. Finally, I will create ex-vivo minimal model communities of BV bacteria and examine the ecological interactions between species. By going beyond a taxonomic description to better understand eco-evolutionary functioning, this project will expand our view of the BV microbiome both at the species level, examining in particular intraspecies diversity in genetic composition and expression, and at the community level through the investigation of SA-related interactions.

Concepts are mental representations that organize experience. They are the building blocks of ideas (e.g., the thought “birds are animals” requires the knowledge of both the concepts “birds” and the concept “animal”). They enable inductive reasoning and predictive inferences which guide behavior and explanation. Some concepts are already present in infancy. These early concepts are richer than previously thought. However, much of the abstract and sophisticated concepts that make human cognition so special (e.g., scientific concepts) are not present at birth. Thus one of the most exciting challenges in psychology is to understand how abstract concepts develop. Much of the abstract concepts that form the basis of our ability to organize the world and make inferences (e.g. “animal”, “artefact”, “alive beings”) have non-observable shared properties (e.g., a cat and a flower are perceptually quite different, but both belong to the concept alive beings). Thus, the refinement of abstract concepts requires access to cultural cues, mostly via language, which provide information beyond what can be obtained through the senses.,, The goal of this project is to explore how children’s conceptual development can benefit form the language they hear around them. To capture the complexity of the linguistic input as well as the children developing conceptual knowledge, I use methods from the growing field of dynamic networks. I will carry out my research at the Institute of Complex Systems, Paris Île-de-France (ISC-PIF). I will also use the model to provide insights about how scientific concepts can be taught efficiently at school. To this end, I will collaborate with experts in science education at the secondment foundation La Main à La pâte (LAMAP), which is the leading French NGO in developing and promoting best practices in science education.