Multimodal influences on learning walks in desert ants (Cataglyphis fortis)

Ants are excellent navigators using multimodal information for navigation. To accurately localise the nest at the end of a foraging journey, visual cues, wind direction and also olfactory cues need to be learnt. Learning walks are performed at the start of an ant’s foraging career or when the appearance of the nest surrounding has changed. We investigated here whether the structure of such learning walks in the desert ant Cataglyphis fortis takes into account wind direction in conjunction with the learning of new visual information. Ants learnt to travel back and forth between their nest and a feeder, and we then introduced a black cylinder near their nest to induce learning walks in regular foragers. By doing this across days with different wind directions, we were able to probe how ants balance different sensory modalities. We found that (1) the ants’ outwards headings are influenced by the wind direction with their routes deflected such that they will arrive downwind of their target, (2) a novel object along the route induces learning walks in experienced ants and (3) the structure of learning walks is shaped by the wind direction rather than the position of the visual cue

Optimization and Quality Assessment of Baryon Pasting for Intracluster Gas using the Borg Cube Simulation

Synthetic datasets generated from large-volume gravity-only simulations are an important tool in the calibration of cosmological analyses. Their creation often requires accurate inference of baryonic observables from the dark matter field. We explore the effectiveness of a baryon pasting algorithm in providing precise estimations of three-dimensional gas thermodynamic properties based on gravity-only simulations. We use the Borg Cube, a pair of simulations originating from identical initial conditions, with one run evolved as a gravity-only simulation, and the other incorporating non-radiative hydrodynamics. Matching halos in both simulations enables comparisons of gas properties on an individual halo basis. This comparative analysis allows us to fit for the model parameters that yield the closest agreement between the gas properties in both runs. To capture the redshift evolution of these parameters, we perform the analysis at five distinct redshift steps, spanning from $z=0$ to $2$. We find that the investigated algorithm, utilizing information solely from the gravity-only simulation, achieves few-percent accuracy in reproducing the median intracluster gas pressure and density, albeit with a scatter of approximately 20%, for cluster-scale objects up to $z=2$. We measure the scaling relation between integrated Compton parameter and cluster mass ($Y_{500c} | M_{500c}$), and find that the imprecision of baryon pasting adds less than 5% to the intrinsic scatter measured in the hydrodynamic simulation. We provide best-fitting values and their redshift evolution, and discuss future investigations that will be undertaken to extend this work.Comment: 14 pages, 8 figures, 3 tables; accepted in the Open Journal of Astrophysic

High-efficiency micromorph silicon solar cells with in-situ intermediate reflector deposited on various rough LPCVD ZnO

Light management using intermediate reflector layers (IRL) and advanced front transparent conductive oxide (TCO) morphologies is needed to rise the short-circuit current density (Jsc) of micromorph tandem solar cells above 14 mA/cm2. For micromorph cells deposited on surface-textured ZnO layers grown by low-pressure chemical vapour deposition (LPCVD), we study the interplay between the front TCO layer and the IRL and its impact on fill factor and current matching conditions. The key role of the angular distribution of the light scattered by the front LPCVD ZnO layer is highlighted. A micromorph cell with 11.1% stabilized conversion efficiency is demonstrated. By increasing the bottom cell thickness and adding an antireflection coating, a Jsc value of 13.8 mA/cm2 is achieved. This remarkably high Jsc yields 13.3% initial conversion efficiency

LATEST DEVELOPMENTS ON MICROMORPH TANDEM CELLS AT IMT

The latest developments on micromorph tandem cells in small area laboratory and large area industrial PE-CVD systems are reviewed. We report on a 13.3% initial efficiency micromorph tandem cell deposited in our small area system. The development of an in-situ silicon oxide based intermediate reflector layer (SOIR) was essential in order to achieve such high efficiencies. We describe its detailed material structure and discuss optical management aspects for different cell configurations. In our large area industrial R&D reactor the highest efficiency so far obtained is a 11.0% initial efficiency micromorph tandem cell. We discuss in detail the role of pressure and silane depletion on the cell parameters of single junction microcrystalline cells and present efficiency trends decreasing from 8.2% to 7.0% with deposition rates increasing from 0.3 nm/s to 1.2 nm/s

Micromorph tandem solar cells grown at high rate with in-situ intermediate reflector in industrial KAI PECVD reactors

We report on the latest results of tandem micromorph (a-Si:H/μc-Si:H) silicon solar cells fabricated in commercial Oerlikon Solar KAI-S and KAI-M PECVD reactors. First developments of in-situ silicon oxide based intermediate reflector (SOIR) in KAI reactors are as well presented. Under low depletion conditions (silane concentration 1cm2, with a deposition rate of 0.55 nm/s for microcrystalline silicon and an ex-situ silicon oxide-based intermediate reflector (SOIR). Under high depletion conditions, the growth rate could be raised up to 1.2 nm/s, in a modified KAI-M reactor, and the highest initial efficiency reached so far is 9.7% with in-situ SOIR and top cell thickness of ∼ 230 nm. Promising micromorph solar cells are thus produced under conditions that are highly favorable to low-cost fabrication of tandem modules at an industrial level

Robust Matrix Completion

This paper considers the problem of recovery of a low-rank matrix in the situation when most of its entries are not observed and a fraction of observed entries are corrupted. The observations are noisy realizations of the sum of a low rank matrix, which we wish to recover, with a second matrix having a complementary sparse structure such as element-wise or column-wise sparsity. We analyze a class of estimators obtained by solving a constrained convex optimization problem that combines the nuclear norm and a convex relaxation for a sparse constraint. Our results are obtained for the simultaneous presence of random and deterministic patterns in the sampling scheme. We provide guarantees for recovery of low-rank and sparse components from partial and corrupted observations in the presence of noise and show that the obtained rates of convergence are minimax optimal