6 research outputs found

    The early evolution of young massive clusters: The kinematic history of NGC6611 / M16

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    In the first few Myr the massive stars dynamically interact, produce runaways and affect the initial binary population. Observing and interpreting the dynamics of young massive clusters is key to our understanding of the star formation process and predicting the outcome of stellar evolution. We have studied NGC6611 in the Eagle Nebula (M16), a young massive cluster hosting 19 O stars. We used Gaia EDR3 data to determine the membership, age, cluster dynamics and the kinematics of the massive stars including runaways. The membership analysis yields 137 members located at a mean distance of 1706 ±\pm 7 pc. The colour - absolute magnitude diagram reveals a blue and a red population of pre-main-sequence stars, consistent with two distinct populations of stars. In line with earlier studies, the youngest population has a mean extinction AVA_V = 3.6 ±\pm 0.1 mag and an age = 1.3 ±\pm 0.2 Myr, while the older population of stars has a mean extinction AVA_V = 2.0 ±\pm 0.1 mag and an age = 7.5 ±\pm 0.4 Myr. The latter population is more spatially extended than the younger generation of stars. We argue that most of the OB stars belong to the younger population. We identify 8 runaways originating from the center of NGC6611, consistent with the dynamical ejection scenario. We show that ~ 50% of the O stars have velocities comparable to or greater than the escape velocity. These O stars can be traced back to the center of NGC6611 with kinematic ages ranging from 0 to 2 Myr. This suggests that dynamical interactions played an important role in the early evolution of NGC6611, which is surprising considering the low current stellar density. Comparing this to simulations of young massive clusters, the required initial radius of 0.1-0.5 pc is not consistent with that of NGC6611. The O stars could have initially formed in wide binaries and possibly harden through dynamical interactions.Comment: replaced with accepted version to A&A. 28 pages, 15 figure

    Bringing Stellar Evolution & Feedback Together: Summary of proposals from the Lorentz Center Workshop, 2022

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    Stars strongly impact their environment, and shape structures on all scales throughout the universe, in a process known as ``feedback''. Due to the complexity of both stellar evolution and the physics of larger astrophysical structures, there remain many unanswered questions about how feedback operates, and what we can learn about stars by studying their imprint on the wider universe. In this white paper, we summarize discussions from the Lorentz Center meeting `Bringing Stellar Evolution and Feedback Together' in April 2022, and identify key areas where further dialogue can bring about radical changes in how we view the relationship between stars and the universe they live in.Comment: Accepted to the Publications of the Astronomical Society of the Pacifi

    Multiwavelength observations reveal a faint candidate black hole X-ray binary in IGR J17285-2922

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    <h2>Reproduction package for the paper "Multiwavelength observations reveal a faint candidate black hole X-ray binary in IGR J17285-2922"</h2><h4>This is a reproduction package with the internal API designation of 'silver'</h4><h4>Monthly Notices of the Royal Astronomical Society, Volume 507, Issue 1, October 2021, Pages 330–349</h4><h4>Authors: <strong>M. Stoop</strong>, J. van den Eijnden, N. Degenaar, A. Bahramian, S. J. Swihart, J. Strader, F. JimĂ©nez-Ibarra, T. Muñoz-Darias, M. Armas Padilla, A. W. Shaw, T. J. Maccarone, R. Wijnands, T. D. Russell, J. V. Hernández Santisteban, J. C. A. Miller-Jones, D. M. Russell, D. Maitra, C. O. Heinke, G. R. Sivakoff, F. Lewis D. M. Bramich</h4><h4>Paper DOI: https://doi.org/10.1093/mnras/stab2127</h4><h4>Zenodo DOI: https://doi.org/10.5281/zenodo.4664505</h4><p> </p><h2>Raw Data</h2><p> </p><p>- Uncalibrated X-ray data is given in ./raw_data</p><p> </p><p>- Radio data is too large in size to be stored on Zenodo. If you want to acquire these images, but can be found under https://data.nrao.edu searching for project code SF8027</p><p> </p><p>- Raw data for the optical spectra can be acquired by contacting J. van den Eijnden</p><p> </p><h2>Software</h2><p> </p><p>- OS: MacOS Big Sur 11.6</p><p> </p><p>Programming languages:</p><p> </p><p>- Python (3.9.7), matplotlib, numpy, pandas, scipy, linmix</p><p> </p><p>- Jupyter Notebook (6.3.0)</p><p> </p><p>NASA HEASARC's Software:</p><p> </p><p>- xrtpipeline (version 0.13.5)</p><p> </p><p>- caldb in the heasoft package (version 6.26.1)</p><p> </p><p>- xselect (version v2.4g)</p><p> </p><p>- xrtmkarf (version 0.6.3)</p><p> </p><p>- xspec (v. 12.10.1f)</p><p> </p><p>- casa pipeline (5.6.2)</p><p> </p><h2>Figures and Tables</h2><p> </p><p>- scripts and data to make the figures and tables can be found in ./figures_tables</p><p> </p><p>- figure 4, 5, 6, and 7 are made by collaborators. Please contact J. van den Eijnden if you would like access to data files or scripts for these figures.</p><p> </p><p>- X-ray lightcurve fit results in Table 3 is done by collaborators. Please contact J. van den Eijnden if you would like access to data files or scripts for this table.</p><p> </p><h2>Intermediate data products  </h2><p> </p><p>- Intermediate data products can be found in the directory ./intermediate_data</p><p> </p><p>- This includes the calibrated X-ray data, VLA imaging scripts to determine the flux density and spectral index.</p><p> </p><p>- Scripts can also be found here for intermediate data products for several figures (1, 2, 3, 8)</p><p> </p><h2>Scientific-analysis</h2><p> </p><p>- The directory ./scientific_analysis contains scripts and data to reduce the raw data to the intermediate data products.</p><p> </p><p>- ./Xray_files how to calibrate the Swift X-ray spectra</p><p> </p><p>- ./Xray_spectral_evolution contains how the intermediate data products for figure 3</p><p> </p><p>- ./VLA_data_reduction how to reduce the VLA data and determine flux densities and spectral indices</p><p> </p><p>- ./Radio_Xray_Coupling contains the intermediate data products for figure 2</p><p> </p><p>- ./Xray_lightcurve_fitting contains intermediate data products for Table 3 and fitting performed in section 3.4</p><p> </p><p>- ./Orbital_Period contains intermediate data products for Table 4 and Figure 8</p><p> </p><p>- ./xray contains backup files related to the x-ray spectra</p><p> </p><p>- ./radio contains backup files related to the radio data</p><p> </p><p>- the main results (intermediate data products) are the .txt files in this directory</p&gt

    Bringing Stellar Evolution and Feedback Together: Summary of Proposals from the Lorentz Center Workshop

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    Stars strongly impact their environment, and shape structures on all scales throughout the universe, in a process known as "feedback." Due to the complexity of both stellar evolution and the physics of larger astrophysical structures, there remain many unanswered questions about how feedback operates and what we can learn about stars by studying their imprint on the wider universe. In this white paper, we summarize discussions from the Lorentz Center meeting "Bringing Stellar Evolution and Feedback Together" in 2022 April and identify key areas where further dialog can bring about radical changes in how we view the relationship between stars and the universe they live in
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