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132 Research products, page 1 of 14

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  • Open Access English
    Authors: 
    Bell, Taylor J.; Ahrer, Eva-Maria; Brande, Jonathan; Carter, Aarynn L.; Feinstein, Adina D.; Guzman Caloca, Giannina; Mansfield, Megan; Zieba, Sebastian; Piaulet, Caroline; Benneke, Björn; +5 more
    Publisher: Zenodo
    Project: NSF | Graduate Research Fellows... (1746045)

    Eureka! is a data reduction and analysis pipeline for exoplanet time-series observations, with a particular focus on James Webb Space Telescope (JWST) data. JWST was launched on December 25, 2021 and over the next 1-2 decades will pursue four main science themes: Early Universe, Galaxies Over Time, Star Lifecycle, and Other Worlds. Our focus is on providing the astronomy community with an open source tool for the reduction and analysis of time-series observations of exoplanets in pursuit of the fourth of these themes, Other Worlds. The goal of Eureka! is to provide an end-to-end pipeline that starts with raw, uncalibrated FITS files and ultimately yields precise exoplanet transmission and/or emission spectra. The pipeline has a modular structure with six stages, and each stage uses a "Eureka! Control File" (ECF; these files use the .ecf file extension) to allow for easy control of the pipeline's behavior. Stage 5 also uses a "Eureka! Parameter File" (EPF; these files use the .epf file extension) to control the fitted parameters. We provide template ECFs for the MIRI, NIRCam, NIRISS, and NIRSpec instruments on JWST and the WFC3 instrument on the Hubble Space Telescope (HST). These templates give users a good starting point for their analyses, but Eureka! is not intended to be used as a black box tool, and users should expect to fine-tune some settings for each observation in order to achieve optimal results. At each stage, the pipeline creates intermediate figures and outputs that allow users to compare Eureka!'s performance using different parameter settings or to compare Eureka! with an independent pipeline. The ECF used to run each stage is also copied into the output folder from each stage to enhance reproducibility. Finally, while Eureka! has been optimized for exoplanet observations (especially the latter stages of the code), much of the core functionality could also be repurposed for JWST time-series observations in other research domains thanks to Eureka!'s modularity.

  • Research software . 2022
    Open Access English
    Authors: 
    Carifio, Jonathan; Gaibler, Volker; Homeier, Derek; Norman, Henrik; Otor, O. Justin; Robitaille, Thomas P.; Subbarao, Jeffrey; Williams, Peter K. G.; ZuHone, John;
    Publisher: Zenodo
    Project: NSF | WorldWide Telescope Trans... (1550701)

    pywwt is the official toolkit for accessing AAS WorldWide Telescope (WWT) from Python. Learn more at the pywwt website.

  • Research software . 2022
    Open Access English
    Authors: 
    Carifio, Jonathan; Gaibler, Volker; Norman, Henrik; Otor, O. Justin; Robitaille, Thomas P.; Subbarao, Jeffrey; Williams, Peter K. G.; ZuHone, John;
    Publisher: Zenodo
    Project: NSF | WorldWide Telescope Trans... (1550701)

    pywwt is the official toolkit for accessing AAS WorldWide Telescope (WWT) from Python. Learn more at the pywwt website.

  • Research software . 2022
    Open Access English
    Authors: 
    Carifio, Jonathan; Gaibler, Volker; Norman, Henrik; Otor, O. Justin; Robitaille, Thomas P.; Subbarao, Jeffrey; Williams, Peter K. G.; ZuHone, John;
    Publisher: Zenodo
    Project: NSF | WorldWide Telescope Trans... (1550701)

    pywwt is the official toolkit for accessing AAS WorldWide Telescope (WWT) from Python. Learn more at the pywwt website.

  • Open Access English
    Authors: 
    Roland Meyer; Thomas Wies; Sebastian Wolff;
    Publisher: Zenodo
    Project: NSF | SHF: Small:Verifying Comp... (1815633)

    Verifying fine-grained optimistic concurrent programs remains an open problem. Modern program logics provide abstraction mechanisms and compositional reasoning principles to deal with the inherent complexity. However, their use is mostly confined to pencil-and-paper or mechanized proofs. We devise a new separation logic geared towards the lacking automation. While local reasoning is known to be crucial for automation, we are the first to show how to retain this locality for (i) reasoning about inductive properties without the need for ghost code, and (ii) reasoning about computation histories in hindsight. We implemented our new logic in a tool called plankton and used it to automatically verify challenging concurrent search structures that require inductive properties and hindsight reasoning, such as the Harris set. The present artifact provides this implementation in order to reproduce our evaluation.

  • Open Access English
    Authors: 
    Armstrong, William;
    Publisher: Zenodo
    Project: NSF | Collaborative Research: R... (1821002), NSF | Collaborative Research: R... (1821002)

    Scripts for data processing and visualization for the manuscript "Declining basal motion dominates the long-term slowing of Athabasca Glacier, Canada" by WH Armstrong and others, published in the Journal of Geophysical Research: Earth Surface in 2022. {"references": ["Armstrong, WH, et al. (2022). Declining basal motion dominates the long-term slowing of Athabasca Glacier, Canada. Journal of Geophysical Research: Earth Surface."]}

  • Open Access English
    Authors: 
    Shinevar, William J.; Jagoutz, Oliver; Behn, Mark D.;
    Publisher: Zenodo
    Project: NSF | Collaborative Research: R... (1844340), NSF | Collaborative Research: R... (1722935), NSF | Collaborative Research: R... (1844340), NSF | Collaborative Research: R... (1722935)

    To quantitatively convert upper mantle seismic wave speeds measured into temperature, density, composition, and corresponding and uncertainty, we introduce the Whole-rock Interpretative Seismic Toolbox For Ultramafic Lithologies (WISTFUL). WISTFUL is underpinned by a database of 4485 ultramafic whole-rock compositions, their calculated mineral modes, elastic moduli, and seismic wave speeds over a range of pressure (P) and temperature (T) (P=0.5–6 GPa, T=200–1600˚C) using the Gibbs free energy minimization routine Perple_X, the Holland et al. (2018) solution models, and the Holland and Powell (2011) thermodynamic database. These data are interpreted with a toolbox of MATLAB® functions, scripts, and three general user interfaces (GUIs): WISTFUL_relations, which plots relationships between calculated parameters and/or composition; WISTFUL_geotherms, which calculates seismic wave speeds along geotherms; and WISTFUL_inversion, which inverts seismic wave speeds for best-fit temperature, composition, and density. WISTFUL easily analyzes seismic datasets, integrates into modeling, and acts as an educational tool. The associated G^3 technical report also discusses method validation and uncertainty constraints on this methodology.

  • Open Access English
    Authors: 
    Bruer, Grant; Isaac, Tobin;
    Publisher: Zenodo
    Project: NSF | Collaborative Research: E... (1835792), NSF | Collaborative Research: E... (1835792)

    This code is used to generate the data and plots for the paper "Inferring ice sheet damage models from limited observations using CRIKit." Also available at https://gitlab.com/gbruer/ice-crikit

  • Open Access English
    Authors: 
    Thermoengine, Code Contributors To;
    Publisher: Zenodo
    Project: NSF | Collaborative Research: C... (1725425), NSF | Collaborative Research: C... (1725425)

    The ThermoEngine repository contains Python packages, C code and header files, and C++ and Objective-C class implementations that allow thermodynamic properties of minerals, fluids, and melts to be estimated. The repository also includes phase equilibrium calculators: generic as well as those that implement the MELTS, pMELTS, MELTS+DEW, and Stixrude-Lithgow-Bertelloni thermodynamic model/data collections. The software is designed to facilitate the design and construction of thermodynamic models of single and multi-component solutions, and to automate the implementation of these models as computer codes. Examples in Jupyter notebooks demonstrate how to access the software ecosystem using Python wrappers.

  • Open Access English
    Authors: 
    Xiang, Yang; Lam, Phoebe; Burd, Adrian; Hayes, Christopher;
    Publisher: Zenodo
    Project: NSF | Collaborative Research: G... (1535854), NSF | Collaborative Research: G... (1535854)

    This upload includes MATLAB code and files that are necessary to estimate mass flux and sinking rates from size-fractionated filtered marine particles. The method has been applied to three recent U.S. GEOTRACES cruises in the North Atlantic, Eastern Tropical South Pacific, and Western Arctic Ocean, and could be applied to existing and future size-fractionated filtered particulate measurements in other parts of the global ocean. Please refer to our published paper (DOI: 10.1029/2021GB007292) for more details about the method and results.

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