scholarly journals Detection of Fe i in the atmosphere of the ultra-hot Jupiter WASP-121b, and a new likelihood-based approach for Doppler-resolved spectroscopy

2020 ◽  
Vol 493 (2) ◽  
pp. 2215-2228 ◽  
Author(s):  
Neale P Gibson ◽  
Stephanie Merritt ◽  
Stevanus K Nugroho ◽  
Patricio E Cubillos ◽  
Ernst J W de Mooij ◽  
...  
Keyword(s):  
High Resolution ◽  
Temperature Inversion ◽  
Physical Parameters ◽  
Data Sets ◽  
Low Resolution ◽  
Additional Species ◽  
High Resolution Data ◽  
Higher Temperature ◽  
Multiple Species ◽  
Hot Jupiter

ABSTRACT High-resolution Doppler-resolved spectroscopy has opened up a new window into the atmospheres of both transiting and non-transiting exoplanets. Here, we present VLT/UVES observations of a transit of WASP-121b, an ‘ultra-hot’ Jupiter previously found to exhibit a temperature inversion and detections of multiple species at optical wavelengths. We present initial results using the blue arm of UVES (≈3700–5000 Å), recovering a clear signal of neutral Fe in the planet’s atmosphere at >8$\, \sigma$, which could contribute to (or even fully explain) the temperature inversion in the stratosphere. However, using standard cross-correlation methods, it is difficult to extract physical parameters such as temperature and abundances. Recent pioneering efforts have sought to develop likelihood ‘mappings’ that can be used to directly fit models to high-resolution data sets. We introduce a new framework that directly computes the likelihood of the model fit to the data, and can be used to explore the posterior distribution of parametrised model atmospheres via MCMC techniques. Our method also recovers the physical extent of the atmosphere, as well as account for time- and wavelength-dependent uncertainties. We measure a temperature of $3710^{+490}_{-510}$ K, indicating a higher temperature in the upper atmosphere when compared to low-resolution observations. We also show that the Fe i signal is physically separated from the exospheric Fe ii. However, the temperature measurements are highly degenerate with aerosol properties; detection of additional species, using more sophisticated atmospheric models, or combining these methods with low-resolution spectra should help break these degeneracies.

scholarly journals petitRADTRANS

2019 ◽  
Vol 627 ◽  
pp. A67 ◽  
Author(s):  
P. Mollière ◽  
J. P. Wardenier ◽  
R. van Boekel ◽  
Th. Henning ◽  
K. Molaverdikhani ◽  
...  
Keyword(s):  
High Resolution ◽  
Optical Constants ◽  
Emission Spectra ◽  
Transmission Spectra ◽  
Low Resolution ◽  
Cloud Particle ◽  
Hot Jupiters ◽  
Higher Temperature ◽  
Python Package

We present the easy-to-use, publicly available, Python package petitRADTRANS, built for the spectral characterization of exoplanet atmospheres. The code is fast, accurate, and versatile; it can calculate both transmission and emission spectra within a few seconds at low resolution (λ/Δλ = 1000; correlated-k method) and high resolution (λ/Δλ = 106; line-by-line method), using only a few lines of input instruction. The somewhat slower, correlated-k method is used at low resolution because it is more accurate than methods such as opacity sampling. Clouds can be included and treated using wavelength-dependent power law opacities, or by using optical constants of real condensates, specifying either the cloud particle size, or the atmospheric mixing and particle settling strength. Opacities of amorphous or crystalline, spherical or irregularly-shaped cloud particles are available. The line opacity database spans temperatures between 80 and 3000 K, allowing to model fluxes of objects such as terrestrial planets, super-Earths, Neptunes, or hot Jupiters, if their atmospheres are hydrogen-dominated. Higher temperature points and species will be added in the future, allowing to also model the class of ultra hot-Jupiters, with equilibrium temperatures Teq ≳ 2000 K. Radiative transfer results were tested by cross-verifying the low- and high-resolution implementation of petitRADTRANS, and benchmarked with the petitCODE, which itself is also benchmarked to the ATMO and Exo-REM codes. We successfully carried out test retrievals of synthetic JWST emission and transmission spectra (for the hot Jupiter TrES-4b, which has a Teq of ∼1800 K).

scholarly journals Reconstruction of Axial Tomographic High Resolution Data from Confocal Fluorescence Microscopy: A Method for Improving 3D FISH Images

2000 ◽  
Vol 20 (1) ◽  
pp. 7-15 ◽  
Author(s):  
R. Heintzmann ◽  
G. Kreth ◽  
C. Cremer
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Axial Direction ◽  
Laser Scanning Microscopy ◽  
Three Dimensions ◽  
Confocal Laser ◽  
Data Sets ◽  
Data Set ◽  
High Resolution Data ◽  
3D Data

Fluorescent confocal laser scanning microscopy allows an improved imaging of microscopic objects in three dimensions. However, the resolution along the axial direction is three times worse than the resolution in lateral directions. A method to overcome this axial limitation is tilting the object under the microscope, in a way that the direction of the optical axis points into different directions relative to the sample. A new technique for a simultaneous reconstruction from a number of such axial tomographic confocal data sets was developed and used for high resolution reconstruction of 3D‐data both from experimental and virtual microscopic data sets. The reconstructed images have a highly improved 3D resolution, which is comparable to the lateral resolution of a single deconvolved data set. Axial tomographic imaging in combination with simultaneous data reconstruction also opens the possibility for a more precise quantification of 3D data. The color images of this publication can be accessed from http://www.esacp.org/acp/2000/20‐1/heintzmann.htm. At this web address an interactive 3D viewer is additionally provided for browsing the 3D data. This java applet displays three orthogonal slices of the data set which are dynamically updated by user mouse clicks or keystrokes.

The use of Mo Kα radiation in the assignment of the absolute configuration of light-atom molecules; the importance of high-resolution data

2014 ◽  
Vol 70 (4) ◽  
pp. 660-668 ◽  
Author(s):  
Eduardo C. Escudero-Adán ◽  
Jordi Benet-Buchholz ◽  
Pablo Ballester
Keyword(s):  
High Resolution ◽  
Crystal Structures ◽  
Structure Determination ◽  
Great Majority ◽  
Data Sets ◽  
Light Atom ◽  
High Resolution Data ◽  
The Absolute ◽  
Absolute Structure

Recent studies have confirmed the usefulness of the Hooft and Parsons methodologies for determination of the absolute crystal structures of enantiopure light-atom compounds using CuKα radiation. While many single-crystal diffractometers used for small-molecule structure determination are equipped with molybdenum anodes, use of data from such instruments for the absolute structure determination of light-atom crystal structures is rarely documented and has often been found to be unsuccessful. The Hooft and Parsons methodologies have been applied to 44 data sets obtained from single crystals containing light-atom molecules of known chirality using Mo Kαradiation. Several factors influencing the calculation of accurate and precise values for the Hooft and Parsons parameters obtained from these data sets have been identified, the inclusion of high-resolution diffraction data being particularly important. The correct absolute structure was obtained in all cases, with the standard uncertainties of the final absolute structure parameters below 0.1 for the great majority.

The influence of resolution on scale-dependent clustering in fracture spacing data

2016 ◽  
Vol 4 (3) ◽  
pp. T387-T394 ◽  
Author(s):  
Ankur Roy ◽  
Atilla Aydin ◽  
Tapan Mukerji
Keyword(s):  
High Resolution ◽  
Spatial Data ◽  
Reservoir Characterization ◽  
Data Capture ◽  
Low Resolution ◽  
Data Set ◽  
Bootstrap Analysis ◽  
High Resolution Data ◽  
Fracture Spacing ◽  
Resolution Data

It is a common practice to analyze fracture spacing data collected from scanlines and wells at various resolutions for the purposes of aquifer and reservoir characterization. However, the influence of resolution on such analyses is not well-studied. Lacunarity is a parameter that is used for multiscale analysis of spatial data. In quantitative terms, at any given scale, it is a function of the mean and variance of the distribution of masses captured by a gliding a window of that scale (size) across any pattern of interest. We have described the application of lacunarity for delineating differences between scale-dependent clustering attributes of data collected at different resolutions along a scanline. Specifically, we considered data collected at different resolutions from two outcrop exposures, a pavement and a cliff section, of the Cretaceous turbititic sandstones of the Chatsworth Formation widely exposed in southern California. For each scanline, we analyzed data from low-resolution aerial or ground photographs and high-resolution ground measurements for scale-dependent clustering attributes. High-resolution data show larger values of scale-dependent lacunarity than their respective low-resolution counterparts. We further performed a bootstrap analysis for each data set to test for the significance of such clustering differences. We started with generating 300 realizations for each data set and then ran lacunarity analysis on them. It was seen that lacunarity for higher resolution data set lay significantly outside the upper 90th percentile values, thus proving that higher resolution data are distinctly different from random and fractures are clustered. We have therefore postulated that lower resolution data capture fracture zones that had relatively uniform spacing, whereas higher resolution data capture thin and short splay joints and sheared joints that contribute to fracture clustering. Such findings have important implications in terms of understanding organization of fractures in fracture corridors, which in turn is critical for modeling and upscaling exercises.

scholarly journals Quantitative 3D imaging of the cranial microvascular environment at single-cell resolution

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Alexandra N. Rindone ◽  
Xiaonan Liu ◽  
Stephanie Farhat ◽  
Alexander Perdomo-Pantoja ◽  
Timothy F. Witham ◽  
...  
Keyword(s):  
High Resolution ◽  
Single Cell ◽  
Blood Vessels ◽  
3D Imaging ◽  
Conditional Knockout ◽  
Cranial Bone ◽  
Data Sets ◽  
Bone Biology ◽  
High Resolution Data ◽  
Resolution Data

AbstractVascularization is critical for skull development, maintenance, and healing. Yet, there remains a significant knowledge gap in the relationship of blood vessels to cranial skeletal progenitors during these processes. Here, we introduce a quantitative 3D imaging platform to enable the visualization and analysis of high-resolution data sets (>100 GB) throughout the entire murine calvarium. Using this technique, we provide single-cell resolution 3D maps of vessel phenotypes and skeletal progenitors in the frontoparietal cranial bones. Through these high-resolution data sets, we demonstrate that CD31hiEmcnhi vessels are spatially correlated with both Osterix+ and Gli1+ skeletal progenitors during postnatal growth, healing, and stimulated remodeling, and are concentrated at transcortical canals and osteogenic fronts. Interestingly, we find that this relationship is weakened in mice with a conditional knockout of PDGF-BB in TRAP+ osteoclasts, suggesting a potential role for osteoclasts in maintaining the native cranial microvascular environment. Our findings provide a foundational framework for understanding how blood vessels and skeletal progenitors spatially interact in cranial bone, and will enable more targeted studies into the mechanisms of skull disease pathologies and treatments. Additionally, our technique can be readily adapted to study numerous cell types and investigate other elusive phenomena in cranial bone biology.

scholarly journals Paired refinement under the control of PAIREF

IUCrJ ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 681-692
Author(s):  
Martin Malý ◽  
Kay Diederichs ◽  
Jan Dohnálek ◽  
Petr Kolenko
Keyword(s):  
High Resolution ◽  
Diffraction Data ◽  
Structure Refinement ◽  
Data Sets ◽  
High Resolution Data ◽  
Density Maps ◽  
New Feature ◽  
And Control ◽  
The Impact ◽  
Resolution Data

Crystallographic resolution is a key characteristic of diffraction data and represents one of the first decisions an experimenter has to make in data evaluation. Conservative approaches to the high-resolution cutoff determination are based on a number of criteria applied to the processed X-ray diffraction data only. However, high-resolution data that are weaker than arbitrary cutoffs can still result in the improvement of electron-density maps and refined structure models. Therefore, the impact of reflections from resolution shells higher than those previously used in conservative structure refinement should be analysed by the paired refinement protocol. For this purpose, a tool called PAIREF was developed to provide automation of this protocol. As a new feature, a complete cross-validation procedure has also been implemented. Here, the design, usage and control of the program are described, and its application is demonstrated on six data sets. The results prove that the inclusion of high-resolution data beyond the conventional criteria can lead to more accurate structure models.

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