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Spin-transfer torque effects in the dynamic forced response of the magnetization of nanoscale ferromagnets in superimposed ac and dc bias fields in the presence of thermal agitation
No full textInternational audienceSpin-transfer torque (STT) effects on the stationary forced response of nanoscale ferromagnets subject to thermal fluctuations and driven by an ac magnetic field of arbitrary strength and direction are investigated via a generic nanopillar model of a spin-torque device comprising two ferromagnetic strata representing the free and fixed layers and a nonmagnetic conducting spacer all sandwiched between two Ohmic contacts. The STT effects are treated via Brown's magnetic Langevin equation generalized to include the Slonczewski STT term thereby extending the statistical moment method [Y. P. Kalmykov et al., Phys. Rev. B 88, 144406 (2013)] to the forced response of the most general version of the nanopillar model. The dynamic susceptibility, nonlinear frequency-dependent dc magnetization, dynamic hysteresis loops, etc. are then evaluated highlighting STT effects on both the low-frequency thermal relaxation processes and the high-frequency ferromagnetic resonance, etc., demonstrating a pronounced dependence of these on the spin polarization current and facilitating interpretation of STT experiments
Biological organisation as closure of constraints.
No full textInternational audienceWe propose a conceptual and formal characterisation of biological organisation as a closure of constraints. We first establish a distinction between two causal regimes at work in biological systems: processes, which refer to the whole set of changes occurring in non-equilibrium open thermodynamic conditions; and constraints, those entities which, while acting upon the processes, exhibit some form of conservation (symmetry) at the relevant time scales. We then argue that, in biological systems, constraints realise closure, i.e. mutual dependence such that they both depend on and contribute to maintaining each other. With this characterisation in hand, we discuss how organisational closure can provide an operational tool for marking the boundaries between interacting biological systems. We conclude by focusing on the original conception of the relationship between stability and variation which emerges from this framework
On the Predictability of the Winter Euro-Atlantic Climate: Lagged Influence of Autumn Arctic Sea Ice
No full textInternational audienceSatellite-derived sea ice concentration (SIC) and reanalyzed atmospheric data are used to explore the predictability of the winter Euro-Atlantic climate resulting from autumn SIC variability over the Barents– Kara Seas region (SIC/BK). The period of study is 1979/80–2012/13. Maximum covariance analyses show that the leading predictand is indistinguishable from the North Atlantic Oscillation (NAO). The leading covari-ability mode between September SIC/BK and winter North Atlantic–European sea level pressure (SLP) is not significant, indicating that no empirical prediction skill can be achieved. The leading covariability mode with either October or November SIC/BK is moderately significant (significance levels ,10%), and both predictor fields yield a cross-validated NAO correlation of 0.3, suggesting some empirical prediction skill of the winter NAO index, with sea ice reduction in the Barents–Kara Seas being accompanied by a negative NAO phase in winter. However, only November SIC/BK provides significant cross-validated skill of winter SLP, surface air temperature, and precipitation anomalies over the Euro-Atlantic sector, namely in southwestern Europe. Statistical analysis suggests that November SIC/BK anomalies are associated with a Rossby wave train–like anomaly across Eurasia that affects vertical wave activity modulating the stratospheric vortex strength, which is then followed by downward propagation of anomalies that impact transient-eddy activity in the upper troposphere, helping to settle and maintain the NAO-like pattern at surface. This stratospheric pathway is not detected when using October SIC/BK anomalies. Hence, only November SIC/BK, with a one-month lead time, could be considered as a potential source of regional predictability
Sparse and spurious: dictionary learning with noise and outliers
No full textThis is a substantially revised version of a first draft that appeared as a preprint titled "Local stability and robustness of sparse dictionary learning in the presence of noise", http://hal.inria.fr/hal-00737152International audienceA popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictionary. While this paradigm has led to numerous empirical successes in various fields ranging from image to audio processing, there have only been a few theoretical arguments supporting these evidences. In particular, sparse coding, or sparse dictionary learning, relies on a non-convex procedure whose local minima have not been fully analyzed yet. In this paper, we consider a probabilistic model of sparse signals, and show that, with high probability, sparse coding admits a local minimum around the reference dictionary generating the signals. Our study takes into account the case of over-complete dictionaries, noisy signals, and possible outliers, thus extending previous work limited to noiseless settings and/or under-complete dictionaries. The analysis we conduct is non-asymptotic and makes it possible to understand how the key quantities of the problem, such as the coherence or the level of noise, can scale with respect to the dimension of the signals, the number of atoms, the sparsity and the number of observations
An assessment of trends in technology use, innovative work practices and employees’ attitudes in Europe
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Mathematical justification of macroscopic models for diffusion MRI through the periodic unfolding method
No full textInternational audienceDiffusion Magnetic Resonance Imaging (dMRI) is a promising tool to obtain useful information on cellular structure when applied to biological tissues. A coupled macroscopic model has been introduced recently through formal homogenization to model dMRI's signal attenuation. This model was based on a particular scaling of the permeability condition modeling cellular membranes. In this article, we explore all the possible scalings and mathematically justify the corresponding limit models, using the periodic unfolding method. We also illustrate through numerical simulations the respective behavior of the limit models when compared to dMRI measurements
Demonstration of relativistic electron beam focusing by a laser-plasma lens
No full textInternational audienceLaser-plasma technology promises a drastic reduction of the size of high-energy electron accelerators. It could make free-electron lasers available to a broad scientific community and push further the limits of electron accelerators for high-energy physics. Furthermore, the unique femtosecond nature of the source makes it a promising tool for the study of ultrafast phenomena. However, applications are hindered by the lack of suitable lens to transport this kind of high-current electron beams mainly due to their divergence. Here we show that this issue can be solved by using a laser-plasma lens in which the field gradients are five order of magnitude larger than in conventional optics. We demonstrate a reduction of the divergence by nearly a factor of three, which should allow for an efficient coupling of the beam with a conventional beam transport line
Gating attosecond pulses in a noncollinear geometry
No full textInternational audienceThe efficient generation of isolated attosecond pulses (IAPs), giving access to ultrafast electron dynamics in various systems, is a key challenge in attosecond science. IAPs can be produced by confining the extreme ultraviolet emission generated by an intense laser pulse to a single field half-cycle or, as shown recently, by employing angular streaking methods. Here, we experimentally demonstrate the angular streaking of attosecond pulse trains in a noncollinear geometry, leading to the emission of angularly separated IAPs. The noncollinear geometry simplifies the separation of the fundamental laser field and the generated pulses, making this scheme promising for intracavity attosecond pulse generation, thus opening new possibilities for high-repetition-rate attosecond sources
Flottement de drapeau : dynamique et couplage
No full textWhen flags flutter, they harvest the wind kinetic energy for producing periodic oscillations. Using flags for generating energy is then possible with flutter. Starting from this simple principle, this thesis deals with flag dynamics in the wind.In a wind tunnel, we study the forces on the flagpole of fluttering flags, focusing on the fluctuations of the flapping moment and drag. In particular, we observe strong variations of forces between different regimes of flutter characterized by a constant number of nodes. Amodel for flags is solved numerically with a Galerkin method and shows that during transitions between flutter regimes, the moment applied to the flagpole decreases because of the decrease of the flag curvature at the flagpole.When the flagpole is an oscillator with configurable inertia and stiffness, we report astrong coupling between the motion of the flag and its flagpole, with a frequency lock-in phenomenon. We study this coupling experimentally, and we show that a “stiffness-damping” parameter regulates the flagpole rotation. Notably, we design a coupling generating peak-to-peak rotations of 80o at wind speed of the order of 10 m/s.En flottant, les drapeaux puisent l’énergie cinétique du vent et produisent des oscillations périodiques. Utiliser des drapeaux pour générer de l’électricité est donc une perspective rendue possible par le flottement. Partant de ce principe très simple, cette thèse porte sur la dynamique des drapeaux dans le vent.En soufflerie, nous étudions les efforts qui s’appliquent sur le mât de drapeaux flottants, en termes de fluctuations de moment et de traînée. En particulier, nous observons de fortes variations d’efforts entre les différents régimes de flottement caractérisés par un nombre constant de noeuds de vibration. Un modèle de drapeau résolu numériquement par une méthode de Galerkin nous montre que lors des transitions entre les régimes de flottement, le moment appliqué au mât diminue fortement du fait de la diminution de la courbure du drapeau à l’encastrement.Lorsque le mât du drapeau est lui-même un oscillateur d’inertie et de raideur paramétrable, nous constatons un couplage fort entre le mouvement du drapeau et du mât avec un phénomène d’accrochage fréquentiel. Nous étudions ce couplage expérimentalement, et nous montrons qu’un nombre de “raideur-amortissement” pilote la rotation du mât. Notamment, nous obtenons un dispositif qui génère des rotations de 80o crête-à-crête à des vitesses de vent de l’ordre de 10 m/s
A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data
No full textInternational audienceMixed-effects models provide a rich theoretical framework for the analysis of longitudinal data. However , when used to analyze or predict the progression of a neurodegenerative disease such as Alzheimer ' s disease , these models usually do not take into account the fact that subjects may be at different stages of disease progression and the interpretation of the model may depend on some implicit reference time. In this paper , we propose a generative statistical model for longitudinal data , described in a univariate Riemannian manifold setting , which estimates an average disease progression model , subject-specific time shifts and acceleration factors. The time shifts account for variability in age at disease-onset time. The acceleration factors account for variability in speed of disease progression. For a given individual , the estimated time shift and acceleration factor define an affine reparametrization of the average disease progression model. This statistical model has been used to analyze neuropsychological assessments scores and cortical thickness measurements from the Alzheimer ' s Disease Neuroimaging Initiative database. The numerical results showed that we can distinguish between slow versus fast progressing and early versus late-onset individuals