Homeopathic Dark Matter, or how diluted heavy substances produce high energy cosmic rays

We point out that current and planned telescopes have the potential of probing annihilating Dark Matter (DM) with a mass of O(100) TeV and beyond. As a target for such searches, we propose models where DM annihilates into lighter mediators, themselves decaying into Standard Model (SM) particles. These models allow to reliably compute the energy spectra of the SM final states, and to naturally evade the unitarity bound on the DM mass. Indeed, long-lived mediators may cause an early matter-dominated phase in the evolution of the Universe and, upon decaying, dilute the density of preexisting relics thus allowing for very large DM masses. We compute this dilution in detail and provide results in a ready-to-use form. Considering for concreteness a model of dark U(1) DM, we then study both dilution and the signals at various high energy telescopes observing gamma rays, neutrinos and charged cosmic rays. This study enriches the physics case of these experiments, and opens a new observational window on heavy new physics sectors.Comment: 39 pages, 11 figures. v2: reference added, fixed technical issue causing 2 figures not to show properly. v3: BBN constraints amended, conclusions unchanged. Matches published versio

Enhancement of the Dark Matter Abundance Before Reheating: Applications to Gravitino Dark Matter

In the first stages of inflationary reheating, the temperature of the radiation produced by inflaton decays is typically higher than the commonly defined reheating temperature $T_{RH} \sim (\Gamma_\phi M_P)^{1/2}$ where $\Gamma_\phi$ is the inflaton decay rate. We consider the effect of particle production at temperatures at or near the maximum temperature attained during reheating. We show that the impact of this early production on the final particle abundance depends strongly on the temperature dependence of the production cross section. For $\langle \sigma v \rangle \sim T^n/M^{n+2}$, and for $n < 6$, any particle produced at $T_{\rm max}$ is diluted by the later generation of entropy near $T_{RH}$. This applies to cases such as gravitino production in low scale supersymmetric models ($n=0$) or NETDM models of dark matter ($n=2$). However, for $n\ge6$ the net abundance of particles produced during reheating is enhanced by over an order of magnitude, dominating over the dilution effect. This applies, for instance to gravitino production in high scale supersymmetry models where $n=6$.Comment: 16 pages, 5 figure

Free-rider Attacks on Model Aggregation in Federated Learning

Free-rider attacks against federated learning consist in dissimulating participation to the federated learning process with the goal of obtaining the final aggregated model without actually contributing with any data. This kind of attacks is critical in sensitive applications of federated learning, where data is scarce and the model has high commercial value. We introduce here the first theoretical and experimental analysis of free-rider attacks on federated learning schemes based on iterative parameters aggregation, such as FedAvg or FedProx, and provide formal guarantees for these attacks to converge to the aggregated models of the fair participants. We first show that a straightforward implementation of this attack can be simply achieved by not updating the local parameters during the iterative federated optimization. As this attack can be detected by adopting simple countermeasures at the server level, we subsequently study more complex disguising schemes based on stochastic updates of the free-rider parameters. We demonstrate the proposed strategies on a number of experimental scenarios, in both iid and non-iid settings. We conclude by providing recommendations to avoid free-rider attacks in real world applications of federated learning, especially in sensitive domains where security of data and models is critical

Influence du procédé d'injection dans la simulation mécanique de thermoplastiques chargés en fibres de verre courtes

Titre du résumé joint : Modélisation du Comportement Cyclique d'un Thermoplastique Renforcé en Fibres de Verre CourtesNational audienceLes thermoplastiques renforcés en fibres de verre courtes présentent un comportement mécanique fortement non-linéaire lorsqu'ils sont soumis à des chargements cycliques, sous différentes conditions hygrothermiques. Une loi de comportement phénoménologique est proposée de façon à décrire différents mécanismes physiques, tells que la viscoplasticité, l'écrouissage ou l'adoucissement cyclique. La microstructure anisotrope, conséquence de la mise en forme par injection, est prise en compte dans le modèle par l'intermédiaire de tenseurs d'orientation

Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization

The aim of Machine Unlearning (MU) is to provide theoretical guarantees on the removal of the contribution of a given data point from a training procedure. Federated Unlearning (FU) consists in extending MU to unlearn a given client's contribution from a federated training routine. Current FU approaches are generally not scalable, and do not come with sound theoretical quantification of the effectiveness of unlearning. In this work we present Informed Federated Unlearning (IFU), a novel efficient and quantifiable FU approach. Upon unlearning request from a given client, IFU identifies the optimal FL iteration from which FL has to be reinitialized, with unlearning guarantees obtained through a randomized perturbation mechanism. The theory of IFU is also extended to account for sequential unlearning requests. Experimental results on different tasks and dataset show that IFU leads to more efficient unlearning procedures as compared to basic re-training and state-of-the-art FU approaches

Multiaxial fatigue models for short glass fibre reinforced polyamide. Part II: Fatigue life estimation

WOSInternational audienceComponents made of short fibre reinforced thermoplastics are increasingly used in the automotive industry, and more frequently subjected to fatigue loadings during their service life. The determination of a predictive fatigue criterion is therefore a serious issue for the designers, and requires the knowledge of the local mechanical response. As the cyclic behaviour of polymeric material is reckoned to be highly nonlinear, even at room temperature, an accurate constitutive model is a preliminary step for confident fatigue design. Constitutive equations for the cyclic behaviour, developed and validated by the authors in Part I of this paper [Launay et al., Int J Fatigue, in press], are applied to the mechanical analysis of fatigue campaigns carried out by Klimkeit et al. and De Monte et al. on specimens made out of polyamide 66 reinforced with 35 wt.% of short glass fibres. Both studies are performed at room temperature, with material conditioned at the equilibrium with air containing 50% of relative humidity (RH50) or dry-as-moulded (DAM). Post-processing the cyclic response in steady-state allows the comparison of several fatigue criteria. The fatigue databases involve various loadings, including the study of multiaxiality and mean-stress effects on different microstructures. Among all physical quantities, the dissipated energy density per cycle ΔWdiss displays the best correlation with the fatigue life

Modelling the influence of temperature and relative humidity on the time-dependent mechanical behaviour of a short glass fibre reinforced polyamide

WOSInternational audiencePolymer matrix composites, and especially short glass fibre reinforced polyamides, are widely used in the automotive industry. Their application on structural components requires a confident mechanical design taking into account the sensitivity of the mechanical response to both temperature T and relative humidity H. In this paper, the constitutive model already developed by the authors (Launay et al., 2011) is applied to describe the non-linear time-dependent behaviour of a PA66-GF35 under various hygrothermal conditions. The extensive experimental database involves testing conditions under and above the glass transition temperature Tg. An equivalence principle between temperature and relative humidity is applied and validated, since the non-linear mechanical response is shown to depend only on the temperature gap T-Tg(H)

The Role of Indole and Other Shikimic Acid Derived Maize Volatiles in the Attraction of Two Parasitic Wasps

After herbivore attack, plants release a plethora of different volatile organic compounds (VOCs), which results in odor blends that are attractive to predators and parasitoids of these herbivores. VOCs in the odor blends emitted by maize plants (Zea mays) infested by lepidopteran larvae are well characterized. They are derived from at least three different biochemical pathways, but the relative importance of each pathway for the production of VOCs that attract parasitic wasps is unknown. Here, we studied the importance of shikimic acid derived VOCs for the attraction of females of the parasitoids Cotesia marginiventris and Microplitis rufiventris. By incubating caterpillar-infested maize plants in glyphosate, an inhibitor of the 5-enolpyruvylshikimate-3-phospate (EPSP) synthase, we obtained induced odor blends with only minute amounts of shikimic acid derived VOCs. In olfactometer bioassays, the inhibited plants were as attractive to naive C. marginiventris females as control plants that released normal amounts of shikimic acid derived VOCs, whereas naive M. rufiventris females preferred inhibited plants to control plants. By adding back synthetic indole, the quantitatively most important shikimic acid derived VOC in induced maize odors, to inhibited plants, we showed that indole had no effect on the attraction of C. marginiventris and that M. rufiventris preferred blends without synthetic indole. Exposing C. marginiventris females either to odor blends of inhibited or control plants during oviposition experiences shifted their preference in subsequent olfactometer tests in favor of the experienced odor. Further learning experiments with synthetic indole showed that C. marginiventris can learn to respond to this compound, but that this does not affect its choices between natural induced blends with or without indole. We hypothesize that for naïve wasps the attractiveness of an herbivore-induced odor blend is reduced due to masking by nonattractive compounds, and that during oviposition experiences in the presence of complex odor blends, parasitoids strongly associate some compounds, whereas others are largely ignore

Multiaxial fatigue models for short glass fiber reinforced polyamide - Part I: Nonlinear anisotropic constitutive behavior for cyclic response

WOSInternational audienceComponents made of short glass fiber reinforced (SGFR) thermoplastics are increasingly used in the automotive industry, and more frequently subjected to fatigue loadings during their service life. The determination of a predictive fatigue criterion is therefore a serious issue for the designers, and requires the knowledge of the local mechanical response under a large range of environmental conditions (temperature and relative humidity). As the cyclic behavior of polymeric material is reckoned to be highly nonlinear, even at room temperature, an accurate constitutive model is a preliminary step for confident fatigue design. The injection molding process induces a complex fiber orientation distribution (FOD), which affects both the mechanical response and the fatigue life of SGFR thermoplastics. This paper presents an extension of the constitutive behavior proposed by the authors in a previous work [Launay et al., Int J Plasticity, 2011], in order to take into account the influence of the local FOD on overall anisotropic elastic and viscoplastic properties. The proposed model is written in a general 3D anisotropic framework, and is validated on tensile samples with various FOD and loading histories: monotonic tensions, creep and/or relaxation steps, cyclic loadings. In Part II of this paper [Launay et al., Int J Fatigue, 2012], this constitutive model will be applied to the simulation of different fatigue samples subjected to multiaxial cyclic loadings

PSF reconstruction for NAOS-CONICA

Adaptive optics (AO) allows one to derive the point spread function (PSF) simultaneously to the science image, which is a major advantage in post-processing tasks such as astrometry/photometry or deconvolution. Based on the algorithm of \citet{veran97}, PSF reconstruction has been developed for four different AO systems so far: PUEO, ALFA, Lick-AO and Altair. A similar effort is undertaken for NAOS/VLT in a collaboration between the group PHASE (Onera and Observatoire de Paris/LESIA) and ESO. In this paper, we first introduce two new algorithms that prevent the use of the so-called "$U\_{ij}$ functions" to: (1) avoid the storage of a large amount of data (for both new algorithms), (2) shorten the PSF reconstruction computation time (for one of the two) and (3) provide an estimation of the PSF variability (for the other one). We then identify and explain issues in the exploitation of real-time Shack-Hartmann (SH) data for PSF reconstruction, emphasising the large impact of thresholding in the accuracy of the phase residual estimation. Finally, we present the data provided by the NAOS real-time computer (RTC) to reconstruct PSF ({\em (1)} the data presently available, {\em (2)} two NAOS software modifications that would provide new data to increase the accuracy of the PSF reconstruction and {\em (3)} the tests of these modifications) and the PSF reconstruction algorithms we are developing for NAOS on that basis.Comment: 12 pages & 13 figures. To be published in the proceedings of the SPIE conference Advances in Adaptive Optics - Astronomical Telescopes & Instrumentation, 24-31 May 2006, Orland