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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Reproduction Package for the paper "The early evolution of young massive clusters. II. The kinematic history of NGC 6618 / M 17"

Authors: Stoop, Mitchel;

Reproduction Package for the paper "The early evolution of young massive clusters. II. The kinematic history of NGC 6618 / M 17"

Abstract

Reproduction package for the paper "The early evolution of young massive clusters. II. The kinematic history of NGC 6618 / M 17". This reproduction package aims for open science, with the internal API designation of 'Gold' Authors: M. Stoop, A. Derkink, L. Kaper, A. de Koter, C. Rogers, M.C. Ramírez-Tannus, D. Guo, N. Azatyan Paper DOI: https://doi.org/10.1051/0004-6361/202347383 Arxiv DOI: https://doi.org/10.48550/arXiv.2311.04174 Zenodo DOI: http://doi.org/10.5281/zenodo.8120575 Accepted for publication in Astronomy and Astrophysics (date of acceptance: 2023/10/27) Raw Data ./gaia_files/ gives the ADQL queries on how to obtain the raw data from the Gaia database along with the raw Gaia data itself. ./other_files/ gives the other raw data obtained from other sources. For example the literature, Aladin, parsec isochrones. We have cited the relevant references in the paper for raw data taken from the literature. Optical VLT, SALT, WHT spectra (raw data, software and end-products) described in Appendix A can be requested from Annelotte Derkink. Software MacOS Big Sur 11.6 Jupyter Notebook (6.3.0) Programming languages used: Python (3.9.7) Python packages used: numpy (1.22.3), math (comes with Python), pandas (1.2.1), matplotlib (3.3.3), scipy (1.6.0), os (comes with Python), zero_point (0.0.1) (https://gitlab.com/icc-ub/public/gaiadr3_zeropoint), pyUPMASK (requires os, time, multiprocessing, astropy, pathlib) (https://github.com/msolpera/pyUPMASK) Aladin Desktop (Version 11.0) (https://aladin.u-strasbg.fr/AladinDesktop/), will need java installed Aladin Lite (https://aladin.cds.unistra.fr/AladinLite/) Figures and Tables Figures can be reproduced from the ./figures/ folder. All material and data used are available either in the Raw Data or in the Intermediate Data Jupyter notebooks (.ipynb files) provide the option to execute all code as ready-made to produce the figures: 'Cell' -> 'Run All'. The figures shown in the paper will be saved in ./figures/figures_paper/ folder. Tables can be reproduced from the ./tables/ folder similar to the figures. Tables are saved in .csv files so they can easily be used. Tables are also saved in _latex.csv form for easy implementation in latex. Intermediate data products Intermediate data, such as the determined members of NGC6618 or found runaway stars, can be found in the /output_files/ folder. The 'raw' data is also given here, because small corrections have been applied, which are recommended by the Gaia Consortium. This 'raw' data file is not the same as the one given in the ./gaia_files/ folder! This is to ensure that both the raw and intermediate data products are available. ./modules/ is part of the Python pyUPMASK module. End-to-End analysis scripts The end-to-end analysis to determine the members is given in the Jupyter Notebook 'membership_pyupmask.ipynb'. The end-to-end analysis to search for runaways is given in the Jupyter Notebook 'runaways.ipynb'. Minor 'end-to-end' analysis is done in the relevant figure or table Jupyter Notebook.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average