scholarly journals Organic Electrochromic Polymers: State-of-the-Art Neutral Tint Multichromophoric Polymers for High-Contrast See-Through Electrochromic Devices (Adv. Funct. Mater. 29/2016)

2016 ◽  
Vol 26 (29) ◽  
pp. 5239-5239
Author(s):  
Mauro Sassi ◽  
Matteo M. Salamone ◽  
Riccardo Ruffo ◽  
Giorgio E. Patriarca ◽  
Claudio M. Mari ◽  
...  
Keyword(s):  
State Of The Art ◽  
High Contrast ◽  
Electrochromic Devices ◽  
Electrochromic Polymers

scholarly journals State-of-the-Art Neutral Tint Multichromophoric Polymers for High-Contrast See-Through Electrochromic Devices

2016 ◽  
Vol 26 (29) ◽  
pp. 5240-5246 ◽  
Author(s):  
Mauro Sassi ◽  
Matteo M. Salamone ◽  
Riccardo Ruffo ◽  
Giorgio E. Patriarca ◽  
Claudio M. Mari ◽  
...  
Keyword(s):  
State Of The Art ◽  
High Contrast ◽  
Electrochromic Devices

scholarly journals A triple star in disarray

2020 ◽  
Vol 644 ◽  
pp. A114
Author(s):  
M. Kasper ◽  
K. K. R. Santhakumari ◽  
T. M. Herbst ◽  
R. van Boekel ◽  
F. Menard ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Near Infrared ◽  
State Of The Art ◽  
High Contrast ◽  
Compelling Evidence ◽  
T Tauri ◽  
Reflected Light ◽  
First Time ◽  
Triple Star ◽  
Outflow System

Aims. T Tauri remains an enigmatic triple star for which neither the evolutionary state of the stars themselves, nor the geometry of the complex outflow system is completely understood. Eight-meter class telescopes equipped with state-of-the-art adaptive optics provide the spatial resolution necessary to trace tangential motion of features over a timescale of a few years, and they help to associate them with the different outflows. Methods. We used J-, H-, and K-band high-contrast coronagraphic imaging with VLT-SPHERE recorded between 2016 and 2018 to map reflection nebulosities and obtain high precision near-infrared (NIR) photometry of the triple star. We also present H2 emission maps of the ν = 1-0 S(1) line at 2.122 μm obtained with LBT-LUCI during its commissioning period at the end of 2016. Results. The data reveal a number of new features in the system, some of which are seen in reflected light and some are seen in H2 emission; furthermore, they can all be associated with the main outflows. The tangential motion of the features provides compelling evidence that T Tauri Sb drives the southeast–northwest outflow. T Tauri Sb has recently faded probably because of increased extinction as it passes through the southern circumbinary disk. While Sb is approaching periastron, T Tauri Sa instead has brightened and is detected in all our J-band imagery for the first time.

Simplified All‐Solid‐State WO 3 Based Electrochromic Devices on Single Substrate: Toward Large Area, Low Voltage, High Contrast, and Fast Switching Dynamics

2020 ◽  
Vol 7 (3) ◽  
pp. 1901663 ◽  
Author(s):  
Pierluigi Cossari ◽  
Marco Pugliese ◽  
Cataldo Simari ◽  
Alessio Mezzi ◽  
Vincenzo Maiorano ◽  
...  
Keyword(s):  
Solid State ◽  
Low Voltage ◽  
High Contrast ◽  
Electrochromic Devices ◽  
Large Area ◽  
Fast Switching ◽  
Single Substrate ◽  
Switching Dynamics

scholarly journals Intrinsic dimension estimation for locally undersampled data

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Vittorio Erba ◽  
Marco Gherardi ◽  
Pietro Rotondo
Keyword(s):  
State Of The Art ◽  
High Contrast ◽  
Challenging Problem ◽  
Intrinsic Dimension ◽  
Dimension Estimation ◽  
Correlation Integral ◽  
Curved Manifolds ◽  
The Core ◽  
Invariant Object Recognition ◽  
Undersampled Data

AbstractIdentifying the minimal number of parameters needed to describe a dataset is a challenging problem known in the literature as intrinsic dimension estimation. All the existing intrinsic dimension estimators are not reliable whenever the dataset is locally undersampled, and this is at the core of the so called curse of dimensionality. Here we introduce a new intrinsic dimension estimator that leverages on simple properties of the tangent space of a manifold and extends the usual correlation integral estimator to alleviate the extreme undersampling problem. Based on this insight, we explore a multiscale generalization of the algorithm that is capable of (i) identifying multiple dimensionalities in a dataset, and (ii) providing accurate estimates of the intrinsic dimension of extremely curved manifolds. We test the method on manifolds generated from global transformations of high-contrast images, relevant for invariant object recognition and considered a challenge for state-of-the-art intrinsic dimension estimators.

High-contrast ratio and long lifetime polymer electrochromic devices (ECDs)

2005 ◽  
Author(s):  
Dai Ning ◽  
Chunye Xu ◽  
Lu Liu ◽  
Calen Kaneko ◽  
Minoru Taya
Keyword(s):  
Contrast Ratio ◽  
High Contrast ◽  
Electrochromic Devices ◽  
Long Lifetime

scholarly journals Supervised detection of exoplanets in high-contrast imaging sequences

2018 ◽  
Vol 613 ◽  
pp. A71 ◽  
Author(s):  
C. A. Gomez Gonzalez ◽  
O. Absil ◽  
M. Van Droogenbroeck
Keyword(s):  
State Of The Art ◽  
Low Rank ◽  
Machine Learning Techniques ◽  
High Contrast ◽  
Post Processing ◽  
Learning Context ◽  
Contrast Imaging ◽  
Characteristic Analysis ◽  
High Contrast Imaging ◽  
Learning Techniques

Context. Post-processing algorithms play a key role in pushing the detection limits of high-contrast imaging (HCI) instruments. State-of-the-art image processing approaches for HCI enable the production of science-ready images relying on unsupervised learning techniques, such as low-rank approximations, for generating a model point spread function (PSF) and subtracting the residual starlight and speckle noise. Aims. In order to maximize the detection rate of HCI instruments and survey campaigns, advanced algorithms with higher sensitivities to faint companions are needed, especially for the speckle-dominated innermost region of the images. Methods. We propose a reformulation of the exoplanet detection task (for ADI sequences) that builds on well-established machine learning techniques to take HCI post-processing from an unsupervised to a supervised learning context. In this new framework, we present algorithmic solutions using two different discriminative models: SODIRF (random forests) and SODINN (neural networks). We test these algorithms on real ADI datasets from VLT/NACO and VLT/SPHERE HCI instruments. We then assess their performances by injecting fake companions and using receiver operating characteristic analysis. This is done in comparison with state-of-the-art ADI algorithms, such as ADI principal component analysis (ADI-PCA). Results. This study shows the improved sensitivity versus specificity trade-off of the proposed supervised detection approach. At the diffraction limit, SODINN improves the true positive rate by a factor ranging from ~2 to ~10 (depending on the dataset and angular separation) with respect to ADI-PCA when working at the same false-positive level. Conclusions. The proposed supervised detection framework outperforms state-of-the-art techniques in the task of discriminating planet signal from speckles. In addition, it offers the possibility of re-processing existing HCI databases to maximize their scientific return and potentially improve the demographics of directly imaged exoplanets.

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