@data{10.22002/D1.11545
title = {Planet Nine reference population, Version 2.0},
author = {Brown, Michael},
doi = {10.22002/D1.11545},
abstract = {A set of 100,000 synthetic orbital elements and physical properties of Planet Nine draw from the distributions presented in the analysis of Brown and Batygin (2021a). The collection includes the entire reference data set, along with results from the Zwicky Transient Facility search for Planet Nine of Brown and Batygin (2021b) and constraints from the Dark Energy Survey analysis of Belyakov et al. (2022). Example software is included to make useful diagnostic plots.
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Brown, M. (2022). Planet Nine reference population, Version 2.0 (Version 2.0). CaltechDATA. https://doi.org/10.22002/D1.11545
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},
year = {2022},
}
@data{10.22002/D1.2098
title = {Planet Nine reference population},
author = {Brown, Michael},
doi = {10.22002/D1.2098},
abstract = {A set of 100,000 synthetic orbital elements and physical properties of Planet Nine draw from the distributions presented in the analysis of Brown and Batygin (2021a).
The collection includes the entire reference data set, along with results from the Zwicky Transient Facility search for Planet Nine of Brown and Batygin (2021b). Example software is included to make useful diagnostic plots.
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Brown, M. (2021). Planet Nine reference population (Version 1.0). CaltechDATA. https://doi.org/10.22002/D1.2098
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},
year = {2021},
}
@data{10.22002/D1.1976
title = {Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”},
author = {Frankenberg, Christian},
doi = {10.22002/D1.1976},
abstract = {We provide data analysis software and supplementary text for a comment in the Science journal, titled: Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”
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Frankenberg, C. (2021). Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis” (Version 1.0). CaltechDATA. https://doi.org/10.22002/D1.1976
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},
year = {2021},
}
@data{10.22002/D1.1954
title = {Collection of python scripts used to reduce and analyze USANS data},
author = {Ford, Rachel},
doi = {10.22002/D1.1954},
abstract = {Data reduction and correction are the processes by which raw output from a small angle scattering instrument is converted to absolute units (1/cm), enabling direct comparison to corrected data from other instruments. Specifically, the raw scattering angle is converted to wavevector Q, raw detector counts are scaled according to the incident intensity of the beam, any defects in the detector are accounted for, and normalized counts are converted to units of 1/cm.
To reduce data from the ultra-small angle neutron scattering instrument at the NIST Center for Neutron Research (NCNR), including correction with a model Q-dependent background function, we wrote a series of python scripts. We follow the protocol outlined in the help file of the NCNR USANS Reduction Macros for Igor, but our scripts are amenable to reducing many measurements at once. More information can be found in Appendix A of Rachel Ford’s PhD thesis.
We also include the script used to search for a fit to the Q-dependent background (QDB). This step is optional, depending on your needs, and if used, should be applied between steps 2 & 3 in the reduction procedure.
A program to computationally slit-smear SANS data, described by a linear combination of power laws, is also included. Smearing SANS data enables one to directly compare SANS and USANS data for a single sample, which spans five decades in Q.
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Ford, R. (2021). Collection of python scripts used to reduce and analyze USANS data (Version 1.0). CaltechDATA. https://doi.org/10.22002/D1.1954
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Unique Views: 3
Unique Downloads: 0
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},
year = {2021},
}
@data{10.22002/D1.1438
title = {Engineering multiple levels of specificity in an RNA viral vector},
author = {Gao, Xiaojing and Chong, Lucy and Ince, Michaela and Kim, Matthew and Elowitz, Michael},
doi = {10.22002/D1.1438},
abstract = {Flow data, images, and scripts required to generate figures.
Flow cytometry, time-lapse microscopy and MATLAB/Python scripts used to generate figures.
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Gao, X., Chong, L., Ince, M., Kim, M., & Elowitz, M. (2020). Engineering multiple levels of specificity in an RNA viral vector (Version 1.0). CaltechDATA. https://doi.org/10.22002/D1.1438
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Unique Views: 16
Unique Downloads: 1
between May 26, 2020 and July 12, 2021
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},
year = {2020},
}
@data{10.22002/D1.1329
title = {Supplementary data files for Stolper et al. American Mineralogist paper 2020},
author = {Stolper, Edward M.},
doi = {10.22002/D1.1329},
abstract = {Original output files from Perple_X calculations with Jennings and Holland 2015 calibration and from alphaMELTS 2 with pMELTS calibration, sufficient to reproduce all of the figures and calculations in Stolper et al. (2020) American Mineralogist paper.
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Stolper, E. M. (2019). Supplementary data files for Stolper et al. American Mineralogist paper 2020 (Version 1.0). CaltechDATA. https://doi.org/10.22002/D1.1329
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Unique Views: 48
Unique Downloads: 13
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},
year = {2019},
}