Understanding the individual and the macroscopic transport properties of motile micro-organisms like bacteria is a timely question relevant to many technological applications. This is for example crucial in a medical context where the contamination via physiological conducts or the penetration of mucus barriers, is responsible for the outbreak of serious diseases. It is also relevant to the development of novel drug delivery technologies or environmental remediation strategies suited to fight oil spills or heavy metal pollutions.
Moreover, at the fundamental level, this question is also receiving a lot of attention. Fluids loaded with swimming micro-organisms has become a rich domain of applications for the statistical physics of “active matter” where the existence of microscopic sources of energy borne in the motile character of the particles leads to numerous original effects.
In this presentation, I will review several example we address experimentally in the lab and which lead us to revisit standard concepts of the physics of suspensions like Brownian motion, hydrodynamics dispersion or rheological response. I will also present new experiments showing how the motility of the bacteria can be controlled such as to extract work macroscopically.

Over the last two decades, Cosmology has experienced a sort of revolution, where a flood of data of unprecedented accuracy has become available by means of a number of different ground-based and satellite experiments. A particularly striking example is given by the analysis of Cosmic Microwave Background radiation (CMB); loosely speaking, CMB can be viewed as a snapshot of the Universe taken at the age of recombination, i.e. "soon after" the Big Bang: very detailed maps have been produced by the NASA satellite WMAP (2003-2009) and by the ESA satellite Planck (2013-2018). The analysis of these maps entails a number of extremely interesting mathematical questions, mostly related to the geometry of spherical random fields. In this talk, we shall be concerned in particular with issues related to detection of point sources (Galaxies) in CMB Data; we shall discuss in particular the connection with spherical wavelets, distribution of critical points for spherical random fields, and multiple testing procedures.

Collective decision-making in biological systems requires all individuals in the group to go through a behavioural change of state. During this transition, fast and robust transfer of information is essential to prevent cohesion loss. The mechanism by which natural groups achieve such robustness, however, is not clear. I will present anl change of state. During this transition, fast and robust transfer of information is essential to prevent cohesion loss. experimental study of starling flocks performing collective turns and show that information about direction changes propagates across the flock with a linear dispersion law and negligible attenuation, hence minimizing group decoherence. These results contrast starkly with the previous models of collective motion, which predicted diffusive transport of information. Building on spontaneous symmetry breaking and conservation-law arguments, I will present a novel theory that correctly reproduces linear and undamped propagation. Essential to this framework is the inclusion of the birds’ behavioural inertia. The theory not only explains the data, but also predicts that information transfer must be faster the stronger the group’s orientational order, a prediction accurately verified by the data. These results suggest that swift decision-making may be the adaptive drive for the strong behavioural polarization observed in many living systems.

Non uniform growth of thin sheets can lead to the formation of elaborate three-dimensional configurations and to induce non trivial shape transformations. In particular, complicated configurations appear in thin sheets when growth leads to geometrical frustration, as often occurs in biological tissues.

I will present examples of different types of systems and discus different types of self shaping principles, together with the theoretical framework of incompatible elasticity which is used to study such systems. Experimental methods for the construction of “programmed” responsive sheets will be reviewed and the connection of the topic to shape selection in chemical and biological systems, as well as to design and art, will be presented

The magnetization of a ferromagnet is known to form patterns in order to minimize the sum of exchange and stray-field energy (even in the absence of a strong crystalline anisotropy, as in soft materials like Permalloy). Depending on the geometry of the sample, the magnetization features domains, in which it is nearly constant, separated by comparatively sharp transition layers (i.e. walls). Even if the sample comes in form of a thin film (thickness in nanometer range), the energy landscape features many local minimizers --- to the effect that the switching route is complicated and hysteresis occurs. Despite a small film thickness, direct numerical simulation often is not an option for realistic lateral sample sizes and material parameters: The problem resides in the widely separated length scales and the expensive three-dimensional stray-field computation. For a number of specific patterns, we have adopted a different strategy: After identifying the relevant parameter regime, we derived an appropriate (dimensionally) reduced model, which capitalizes on the scale separation, and that is numerically tractable. We shall present several examples, including quantitative comparison with experimental data (Kerr microscopy). Our experimental collaborator is R. Schafer (IWF Dresden).

Glassy materials are characterized by being solid (for all practical purpose) at low temperature in absence of a sharp transition from the liquid phase to the solid state.  They are ubiquitous in nature: among them, we find window glasses, wax, honey, mozzarella cheese... In spite of the very strong experimental and theoretical effort done in the last century, there are many questions that are opened.
During this seminar, I would also stress some progress that has been done in the recent years on hard spheres models
of glasses.

A fundamental challenge in neuroscience is understanding how the central nervous system (CNS) succeeds in coordinating the many degrees-of-freedom of the musculoskeletal system to control limb movements. A long-standing hypothesis is that the CNS relies on muscle synergies, coordinated activations of groups of muscles, to simplify motor control. Evidence that the combinations of a small number of muscle synergies underlies the generation of muscle activation patterns has come from several studies performed in the last two decades with different species and experimental tasks. Muscle synergies, extracted from multi-muscle electromyographic (EMG) recordings using decomposition algorithms such as non-negative matrix factorization, capture regularities in the spatial, temporal, and spatiotemporal organization of the muscle patterns. However, whether muscle synergies are only a parsimonious description of the regularities of the motor commands rather than a key feature of their neural organization is still debated. Further support for a neural organization of muscle synergies has come from testing muscle synergies as a causal model and from identifying their neural substrates. If muscle synergies are organized by the CNS they must affect the difficulty in learning or adapting motor skills. An experiment with human subjects using myoelectric control of a mass in a virtual environment has tested the prediction that it must be harder to adapt to perturbations that require new or modified synergies than to adapt to perturbations that can be compensated by recombining existing synergies. To identify neural substrates of muscle synergies, hand movements were evoked by electrical stimulation of motor cortical areas of non-human primates. The evoked muscle activation patterns could be accurately reconstructed by the combinations of a few muscle synergy highly similar those extracted from voluntary hand movements, suggesting a cortico-spinal organization of muscle synergies. In sum, these results suggest that muscle synergies are modular elements organized by the CNS to provide a low-dimensional representation of the motor commands allowing to control the musculoskeletal system by directly mapping goals into a small number of synergy combination parameters.