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This article investigates reduced-order models (ROMs) based on proper orthogonal decomposition for efficient computation of the homogenized diffusion properties of saturated porous media. The homogenized tensor, whose classical expression may be obtained from periodic homogenization techniques, is computed by solving a local problem on an elementary cell that includes one or several circular solid inclusions. The cost of the repeated resolution of this problem by the finite element method for different inclusions radii may be important, and classical model order reduction methods based on the computation of a spatial basis cannot be applied directly. The method proposed in this work to cope with the variability of circular inclusions relies on the introduction of a transformation from a reference domain to the physical domain that admits an exact affine decomposition in the three-dimensional cases, allowing to split the problem into an offline learning phase and an online evaluation phase which does not depend on the number of degrees of freedom of the original full-order solution. Approximate affine decomposition for two-dimensional cases is also provided with an explicit estimation of the truncation error. The efficiency of the proposed algorithm in terms of accuracy and of computing time is evaluated first for 2D and 3D isotropic and anisotropic elementary cells with a single inclusion, and second for a 2D anisotropic cell with multiple inclusions. Furthermore the ROM is used to estimate in quasi-real time the homogenized diffusion tensor for a given probability distribution of the geometry parameters.

Due to the increasing bypass ratios of modern engines, the fan stage is increasingly becoming the dominant source of engine noise. Accordingly, it is becoming more and more important to develop not only efficient but also quiet fan stages. In this paper the noise emission of a fan for an aero-engine with a bypass ratio of 19 is reduced within a multidisciplinary design optimization (MDO) by means of an hybrid noise prediction method while at the same time optimizing the aerodynamic efficiency. The aerodynamic performance of each configuration in the optimization is evaluated by stationary Reynolds-Averaged Navier-Stokes (RANS) simulations. These stationary flow simulations are also used to extract the aerodynamic excitation sources for the analytical fan noise prediction. The resulting large database of the optimization provides new insights into which extent an MDO can contribute to the design of both quiet and efficient fan stages. In addition to that the hybrid approach of numerical flow solutions and analytical description of the noise sources enables to understand the noise reduction mechanisms. In particular, the influence of rotor blade loading on the aerodynamic efficiency and the noise sources as well as the potential of configurations with a comparatively low number of outlet guide vanes (OGV) is explored. The acoustic results of selected configurations are confirmed by unsteady RANS simulations.

Nature features a plethora of extraordinary photonic architectures that have been optimized through natural evolution in order to more efficiently reflect, absorb or scatter light. While numerical optimization is increasingly and successfully used in photonics, it has yet to replicate any of these complex naturally occurring structures. Using evolutionary algorithms inspired by natural evolution and performing particular optimizations (maximize reflection for a given wavelength, for a broad range of wavelength or maximize the scattering of light), we have retrieved the most stereotypical natural photonic structures. Whether those structures are Bragg mirrors, chirped dielectric mirrors or the gratings on top of Morpho butterfly wings, our results indicate how such regular structures might have spontaneously emerged in nature and to which precise optical or fabrication constraints they respond. Comparing algorithms show that recombination between individuals, inspired by sexual reproduction, confers a clear advantage that can be linked to the fact that photonic structures are fundamentally modular: each part of the structure has a role which can be understood almost independently from the rest. Such an in silico evolution also suggests original and elegant solutions to practical problems, as illustrated by the design of counter-intuitive anti-reflective coatings for solar cells.

International audience; Improving phosphor photoluminescence efficiency is a key parameter to boost the performances of many optical devices. In this work, colloidal silver nanocubes, homogeneously spread on a luminescent surface, have proved to help both injecting and extracting light in and out of the photoluminescent layer and hence contributed significantly to the enhancement of the fluorescence. This approach has been applied to two materials: the well-known Y3Al5O12:Ce yellow phosphor and an optical quartz. The emission efficiency, for sol–gel derived YAG:Ce layers, has increased 80% in the presence of an optimal nanoparticle density, whereas for quartz, a weakly fluorescent material, the photoluminescence signal can be enhanced by a 200-fold factor. A physical analysis based on simulations shows that the disorder is an important factor and that the surface density of Ag nanoparticles is a crucial parameter.

Quantum illumination protocols can be implemented to improve imaging performance in the low photon flux regime even in the presence of both background light and sensor noise. However, the extent to which this noise can be rejected is limited by the rate of accidental correlations resulting from the detection of photon or noise events that are not quantum-correlated. Here we present an improved protocol that rejects up to $$\gtrsim 99.9\%$$ ≳ 99.9 % of background light and sensor noise in the low photon flux regime, improving upon our previous results by an order of magnitude. This improvement, which requires no information regarding the scene or noise statistics, will enable extremely low light quantum imaging techniques to be applied in environments previously thought difficult and be an important addition to the development of covert imaging, quantum microscopes, and quantum LIDAR.

Surface-enhanced infrared absorption (SEIRA) spectroscopy is a powerful technique for a label-free identification of molecular species. The low infrared absorption cross sections of molecules are made up for the huge electromagnetic field enhancement provided by the resonant excitation of collective electron oscillations in metallic nanoantennas. Since these surface plasmons are localized at the nanometer scale, a minute amount of materials is detected leading to a weak SEIRA signal. The design of actual plasmonics detectors is a trade-off between the detection of very small volumes of molecules and the signal to noise ratio level. We demonstrate that an epsilon-near-zero (ENZ) material combined with nano-slits lifts this constraint and provides both extreme enhancement factor up to 107 and highly contrasted SEIRA signal for an extremely low amount of material of interest. These results are explained by the modification of the electromagnetic field of the gap plasmon mode sustained by the slits in the presence of the ENZ material. We propose to implement this concept with a semiconductor whose doping level engineering provides a versatile way to scan the whole molecules' fingerprint frequency range.

International audience; We study the effect of electron spill-out and of nonlocality on the propagation of light inside a gap between two semi-infinite metallic regions. We compare the predictions of a local response model taking into account only the spill-out, to the predictions of a quantum hydrodynamic model able to take both phenomena into account. We show that only the latter is able to correctly retrieve the correct limit when the gap closes, while the local model suffers from undesirable features (divergence of the fields, overestimation of the losses). Finally, we show that, to a certain extent, the correct results can be retrieved using a simple local approach without spill-out or a conventional Thomas-Fermi approximation, but considering an effective gap width.

Light-field cameras allow the acquisition of both the spatial and angular components of the light-field. The conventional way to perform such acquisitions leads to a strong spatio-angular resolution limitation but correlation-enabled plenoptic cameras have been introduced recently that relax this constraint. Here we use a computational version of this concept to acquire realistic light-fields images using a commercial DSLR Camera lens as an imaging system. By placing the image sensor in the focal plane of a lens, within the camera we ensure the acquisition of pure angular components together with the spatial information. We perform an acquisition presenting a high spatio-angular rays resolution obtained through a trade off of the temporal resolution. The acquisition reported is photo-realistic and the acquisition of diffraction limited features is observed with the setup. Finally, we demonstrate the refocusing abilities of the camera.

The ultraconfined light of plasmonic modes put their effective wavelength close to the mean free path of electrons inside the metal electron gas. The Drude model, which can not take the repulsive interactions of electrons into account, then clearly begins to show its limits. In an intermediate length scale where a full quantum treatment is computationally prohibitive, the semiclassical hydrodynamic model, instrinsically non-local, has proven successful. Here we generalize the expression for the absorption volume density and the reciprocity theorem in the framework of this hydrodynamic model. We validate numerically these generalized theorems and show that using classical expressions instead leads to large discrepancies., 10 pages, 8 figures

Nevergrad is an open source platform for black-box optimization. Join the user group! And if you like Nevergrad, please support us by adding a star on GitHub (https://github.com/facebookresearch/nevergrad).

We detail the testbeds which can be found in the photonics and ARCoating test cases in Nevergrad. These testbeds, beyond their practical importance, are especially modular-and like all problems in photonics, possess a very high number of local minima. They constitute simple but crucial design challenges: designing a multilayered structure which can reflect light at a given frequency, reflect light on a whole range of frequencies or cancel the reflectivity ; designing a complex structure able to diffract the blue part of the spectrum and to cancel the reflectivity at any other wavelength.

International audience; We optimize multilayered anti-reflective coatings for photovoltaic devices, using modern evolutionary algorithms. We apply a rigorous methodology to show that a given structure, which is particularly regular (i.e. essentially periodic), emerges spontaneously and systematically for a very broad range of conditions. The very regularity of the structure allows for a thorough physical analysis of how the design operates. This allows to understand that the central part is a photonic crystal utilized as a buffer for light, and that the external layers have the purpose of reducing the impedance mismatch between the outer media and the Bloch mode supported by the photonic crystal. This shows how optimization can suggest new design rules and be considered as a source of inspiration. Finally, we fabricate these structures with easily deployable techniques.

Choosing automatically the right algorithm using problem descriptors is a classical component of combinatorial optimization. It is also a good tool for making evolutionary algorithms fast, robust and versatile. We present Shiwa, an algorithm good at both discrete and continuous, noisy and noise-free, sequential and parallel, black-box optimization. Our algorithm is experimentally compared to competitors on YABBOB, a BBOB comparable testbed, and on some variants of it, and then validated on several real world testbeds., Accepted at GECCO 2020

Nevergrad is a derivative-free optimization platform gathering both a wide range of optimization methods and a wide range of test functions to evaluate them upon. Some of these functions have very particular structures which standard methods are not able to use. The most recent feature of Nevergrad is the ability to conveniently define a search domain, so that many algorithms in Nevergrad can automatically rescale variables and/or take into account their possibly logarithmic nature or their discrete nature, but also take into account any user-defined mutation or recombination operator. Since many problems are efficiently solved using specific operators, Nevergrad therefore now enables using specific operators within generic algorithms: the underlying structure of the problem is user-defined information that several families of optimization methods can use and benefit upon. We explain how this API can help analyze optimization methods and how to use it for the optimization of a structured Photonics physical testbed, and show that this can produce significant improvements.

When calculating broadband fan noise caused by rotor-stator wake interaction analytically, information about the airflow, particularly about the turbulence in the rotor wakes, is necessary. During the pre-design phase, two-dimensional streamline methods are commonly used. These provide only general flow quantities like mean-flow velocities or total-pressure losses. Turbulent parameters such as turbulent kinetic energy and turbulent integral length scale need to be deduced from these quantities. There are several models mentioned in the literature which correlate the wake size with the wake turbulence. But they usually comprise calibration factors that need to be assessed empirically by numerical simulations or measurements. The contribution of the paper is to present an updated semi-empirical model for rotor-wake turbulence quantities, derived on the basis of an extensive comparison of the model with measurements and numerical simulations on four different turbofan stages. A recalibration of the empirical factors improved the noise prediction by 8 dB, reaching an accuracy of 2 dB. In addition, it is shown, that the endwall flow is responsible for large variance in the noise prediction, and may have a contribution of up to 2 dB to the overall sound power.

We present a full-field quantum imaging scheme using a quantum illumination protocol that exploits the spatial correlations between entangled photon-pairs. In doing so we exhibit an advantage for this scheme over the corresponding classical scheme in the presence of increasing levels of noise and loss.

Conventionally, fan stages are designed with more stator vanes than rotor blades. These fan stages provide a tonal noise advantage as the blade passing frequency tone is cut-off. Contrary to conventional cut-off designs, low-count OGV (Outlet Guide Vane) designs are fan stages with fewer stator vanes than rotor blades. Low-count OGV designs benefit from lower broadband noise due to the reduced number of stator vanes. However, the blade passing frequency tone may no longer be cut-off. Therefore, we assess tonal noise reduction mechanisms for subsonic low-count OGV fan stages. We use an analytical and a numerical method to predict the rotor–stator interaction noise for different blade count pairings. The results indicate that the mode phase propagation angle and the cut-on factor are two acoustic parameters that dominantly influence the noise excitation. For certain blade count pairings an acoustic benefit exists if the mode phase propagation angle is congruent to the stator leading edge angle and / or if the mode is away from the cut-off limit. Moreover, reducing the rotor tip speed allows, for some configurations, a cut-off design even with fewer stator vanes than rotor blades (inverse cut-off). Overall, the study shows promising possibilities to reduce tonal interaction noise for low-count OGV fan stages.

This paper is focused on the application of an analytical model, which was previously developed and published for the prediction of buzz-saw noise emitted by supersonic fan rotors. The application test cases are six different fan stages equipped with hardwall inlet ducts and clean inflow conditions. The model is validated through a comparison with experimental sound power levels measured along the working line of each fan in high subsonic, transonic and supersonic regimes. In terms of overall evolution and maximum levels, the model provides a reasonable prediction; the sensitivity to parameters such as the intake axial Mach number or the intake duct length is well reproduced. However the significant discrepancies observed locally show that the prediction of buzz-saw noise is still a difficult task. The model is then extended to the case of distorted mean flow impinging on the rotor. Following this extension, the maximum levels of buzz-saw noise are expected to occur over a wider range of Mach number compared to the case with clean inflow.

We use a spatial light modulator and a genetic algorithm to manipulate the spatial profile of the pump beam of a down-conversion source in order to improve its Klyshko efficiency.

International audience; Recent experiments have shown that spatial dispersion may have a conspicuous impact on the response of plasmonic structures. This suggests that in some cases the Drude model should be replaced by more advanced descriptions that take spatial dispersion into account, like the hydro-dynamic model. Here we show that nonlocality in the metallic response affects surface plasmons propagating at the interface between a metal and a dielectric with high permittivity. As a direct consequence, any nanoparticle with a radius larger than 20 nm can be expected to be sensitive to spatial dispersion whatever its size. The same behavior is expected for a simple metallic grating allowing the excitation of surface plasmons, just as in Woods famous experiment. Finally, we carefully set up a procedure to measure the signature of spatial dispersion precisely, leading the way for future experiments. Importantly, our work suggests that for any plasmonic structure in a high permittivity dielectric, nonlocality should be taken into account.

The production of pairs of entangled photons simply by focusing a laser beam onto a crystal with a nonlinear optical response was used to test quantum mechanics and to open new approaches in imaging. The development of the latter was enabled by the emergence of single-photon-sensitive cameras that are able to characterize spatial correlations and high-dimensional entanglement. Thereby, new techniques emerged, such as ghost imaging of objects — in which the quantum correlations between photons reveal the image from photons that have never interacted with the object — or imaging with undetected photons by using nonlinear interferometers. In addition, quantum approaches in imaging can also lead to an improvement in the performance of conventional imaging systems. These improvements can be obtained by means of image contrast, resolution enhancement that exceeds the classical limit and acquisition of sub-shot-noise phase or amplitude images. In this Review, we discuss the application of quantum states of light for advanced imaging techniques. Using quantum states of light for imaging both reveals quantum phenomena and enables new protocols that result in images that surpass classical limitations. Such systems require both quantum light sources and often the ingenious use of detector technologies.

Extracting as much information as possible about an object when probing with a limited number of photons is an important goal with applications from biology and security to metrology. Imaging with a few photons is a challenging task as the detector noise and stray light are then predominant, which precludes the use of conventional imaging methods. Quantum correlations between photon pairs has been exploited in a so called ‘heralded imaging scheme’ to eliminate this problem. However these implementations have so-far been limited to intensity imaging and the crucial phase information is lost in these methods. In this work, we propose a novel quantum-correlation enabled Fourier Ptychography technique, to capture high-resolution amplitude and phase images with a few photons. This is enabled by the heralding of single photons combined with Fourier ptychographic reconstruction. We provide experimental validation and discuss the advantages of our technique that include the possibility of reaching a higher signal to noise ratio and non-scanning Fourier Ptychographic acquisition.

International audience; Suite au séminaire déambulatoire intitulé À pied d'œuvre va savoir le sens de la ville, réalisé à Besançon le 25 octobre 2018, dans le cadre du pôle de recherche CCM (Conception, Création, Médiations) du laboratoire ELLIADD (Edition, Littératures, Langages, Informatique, Arts, Didactique, Discours), il s'agira de réaliser un atelier déambulatoire. L'intention est de pratiquer la marche comme modalité d'apprentissage à l'attention, à la réflexion et à l'invention.Marcher en commun pour apprendre le divers. Marcher pour mettre en action l'entièreté du corps et s'orienter vers le connaissable. En commun car le savoir ne peut se constituer qu'en existant comme bien commun. Pour apprendre le divers afin d'inventer ce qui nous est, de prime abord, étranger.Prendre connaissance, c'est faire ce mouvement confiant vers l'inconnu qui altère nos certitudes. Faire connaissance, c'est entrer en confiance. Connaître c'est co-naître, « naître avec », un acte qui porte foi à la solidité de la connaissance.

Aircraft propulsion will continue to rely on gas turbine technology for the next decades to come. Thus, to achieve environmental agreements, ensure engine safety, and retain economic competitiveness, ongoing development with a multidisciplinary design approach is indispensable. In the present study, the multi-criteria analysis of the fan, a decisive component in modern aero engines, is examined. In particular, the interaction of the fan blades with the fan casing is analyzed and an appropriate design approach, including automatic optimization, is used. As one part of the disciplines conjunction, an automated aeroacoustic approach is realized. The aerodynamic and acoustic fitness functions and constraints are based on Reynolds-Averaged Navier–Stokes (RANS) simulations of the fan stage. PropNoise, a fast analytical prediction tool for fan noise, is used. It has been under development since recent years and is already validated on several test cases. Preliminary studies have shown that the flow in the rotor tip region is a major contributor to the broadband noise emission. Based on this, the optimization process focuses on the variation of the casing contour around the fan blades. The impact of the modified flow field in the rotor tip region concerning the aeroelastic behavior is also investigated. As aeroelastic evaluation requires a high level of know-how and is very time consuming, it is linked to the optimization process chain by a discrete evaluation of selected members. This allows a simultaneous adjustment of the design in case of aeroelastic issues. Furthermore, the impact of the fan modifications regarding the overall engine performance is evaluated. Off-design cycle calculations allow incorporating such detailed studies in a global engine optimization.

International audience; The group velocity of a plasmonic guided mode can be written as the ratio of the flux of the Poynting to the integral of the energy density along the profile of the mode. This theorem, linking the way energy propagates in metals to the properties of guided modes and Bloch modes in a multilayer, provides a unique physical insight in plasmonics. It allows to better understand the link between the negative permittivity of metals and the wide diversity of exotic phenomenon that occur in plasmonics-like the slowing down of guided modes, the high wavevector and the negative refraction. Deeply subwavelength metallic structures give us an unprecedented control of visible light, allowing to focus, concentrate, absorb, scatter light very efficiently, or to even enhance the emission of light by fluorophores[1] at totally new levels. Metals actually present a very peculiar optical response that dielectrics are totally incapable of-which can be linked to the presence of a free electron gas, a plasma, inside even the tiniest metallic nanoparticles[2]. Plasmonic resonators are the smallest optical resonators possible and their resonances can always be linked to the excitation of some kind of plasmonic guided mode. There is thus a large diversity of these modes, from the well known surface plasmon[3] to long and short-range surface plasmons[4], gap-plasmons[5] or modes supported by hyperbolic metallo-dielectric multilayers[6]. Most of them present very high wavevectors which explains the reduced size of the plasmonic resonators[7, 8]: they are essentially cavities for guided modes with very small effective wavelength. One must finally underline that exotic phenomena like negative refraction may also occur in metallo-dielectric multilayers[9-12]. All these features lack a unified view that would enable to give a physical insight into the reasons why large wavevector guided modes and negative refraction are common in plasmon-ics and very exotic in dielectric structures-requiring the careful tailoring of photonic crystals, for instance[13, 14]. We think that considering the way that energy flows when such modes propagate provides this kind of insight. The average flux of the Poynting vector has actually been used in the context of metamaterial and negative index materials as a useful tool to predict in which direction a mode really propagates (i.e. the sign of its group velocity). Such a approach relies on a theorem showing that the energy velocity is equal to the group velocity for modes propagating in non-dispersive, dielectric media[15, 16]. This theorem has been mostly ignored because, except in a few cases like when a mode approaches a cutoff condition, the group velocity does not present any exotic behaviour. Assuming this link holds even in the case of plasmonic or metamaterial waveguides, it can prove very useful to determine the sign of the group velocity by simply using the profile of the guided modes at a given frequency without having to actually compute the dispersion relation[17-19]. However, the optical response of metals is linked to the presence of free electrons, that transport a part of the guided mode energy and whose kinetic energy can not be neglected. For a plane wave propagating in a plasma, provided the energy of the electrons is taken into account both in the energy flux and in the energy density, it has been shown by Bers[20] that the energy and flux velocity are the same. This underlines that Yariv and Yeh's theorem[15] can not be applied to plasmonic waveguides. Since metals are highly dispersive and can be considered as boxes containing a real plasma, it is even surprising that computing the average flux of the Poynting vector could be successful in predicting the sign of the group velocity. Here we show that it is actually possible to generalize Yariv and Yeh's theorem in the context of dispersive media, including metals. This means that there is no need to modify the expression of the energy flux and only to adapt the energy density expression, to make the theorem valid-despite what has been established for plasma[20]. Said otherwise, the group velocity of a guided mode in a plasmonic multilayer is equal to the energy velocity of the electromagnetic field alone, and the energy transported by the free electrons, while not negligible[20], can be completely ignored. We then show using several examples how considering the energy velocity can provide a unifying vision of the optical response of plasmonic multilayers. We consider a multilayered structure invariant in the x and y directions, and a guided mode, solution of Maxwell's equations presenting a e i(k x x−ω t) dependency in x and t. We will assume the mode is p-polarized, because nothing exotic occurs for the s polarization in metallo-dielectric structures. Maxwell's

How can quantum mechanics deliver better imaging performance? Parametric down-conversion sources produce pairs of photons that are correlated in many degrees of freedom, including their spatial positions. By using a camera to detect these pairs of photons it is possible configure imaging systems that can either beat the classical resolution limit or the classical noise limit. We demonstrate how a simple down-conversion source based on a laser and non-linear crystal can be combined with an EMCCD camera to achieve either of these outcomes. Firstly, when both photons pass through the sample, we show a full-field, resolution-enhancing scheme, based on the centroid estimation of the photon pairs. By optimising the software control of the EMCCD camera running in the photon-sparse regime we achieve a resolution enhancement over the equivalent classical limit. Secondly, we show a similar scheme but where only one of the two photons pass through the sample and the other acts as a reference, in this case the ratio of the two resulting images eliminates the background noise of the camera, and background light, achieving an increase in image contrast.

If a picture tells a thousand words, then we might ask ourselves how many photons does it take to form a picture? In terms of the transmission of the picture information, then the multiple degrees of freedom (e.g., wavelength, polarization, and spatial mode) of the photon mean that high amounts of information can be encoded such that the many pixel values of an image can, in principle, be communicated by a single photon. However, the number of photons required to transmit the image information is not necessarily, at least technically, the same as the number of photons required to image an object. Therefore, another equally important question is how many photons does it take to measure an unknown image?

Mobile performance marketing is a growing industry due to the massive adoption of smartphones and tablets. In this paper, we explore Deep Multilayer Perceptrons (MLP) to predict the Conversion Rate (CVR) of mobile users that are redirected to ad campaigns (i.e., if there will be a sale). We analyze recent real-world big data provided by a global mobile marketing company. Using a realistic rolling window validation, we conducted several experiments with different datasets (two sampling and two data traffic modes), in which we measure both the predictive binary classification performance and the computational effort. The modeling experiments include: two data preprocessing methods, the popular one-hot encoding and a proposed Percentage Categorical Pruning (PCP); and two MLP learning modes, offline (reset) and online (reuse). Overall, competitive classification results were achieved by the PCP transform and the two MLP learning modes, producing real-time predictions and comparing favorably against a Convolutional Neural Network and a Logistic Regression., This article is a result of the project NORTE-01-0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by FCT Fundac¸ao para a Ciência e Tecnologia within the Project ˆScope: UID/CEC/00319/2019.

Using quantum states of light allows classical limits of imaging to be surpassed. Using entangled photon pairs we show a contrast enhancement compared to classical imaging techniques.