The Chandra X-ray Survey of Planetary Nebulae (ChanPlaNS): Probing Binarity, Magnetic Fields, and Wind Collisions
J. H. Kastner (1), R. Montez Jr (1), B. Balick (2), D. J. Frew (3), B., Miszalski (4,5), R. Sahai (6), E. Blackman (7), Y.-H. Chu (8), O. De Marco, (3), A. Frank (7), M. A. Guerrero (9), J. A. Lopez (10), V. Rapson (1), A., Zijlstra (11), E. Behar (12), V. Bujarrabal (13)

TL;DR
This study uses Chandra X-ray observations to analyze planetary nebulae, revealing correlations between X-ray emission, nebula structure, and potential binarity, providing insights into wind interactions and evolution timescales.
Contribution
First systematic, volume-limited Chandra survey of planetary nebulae, identifying X-ray emission patterns and their relation to nebula morphology and central star properties.
Findings
70% of surveyed PNe show X-ray emission
X-ray point sources are often harder than expected from single stars
Diffuse X-ray emission is confined within inner shells of young, elliptical PNe
Abstract
We present an overview of the initial results from the Chandra Planetary Nebula Survey (ChanPlaNS), the first systematic (volume-limited) Chandra X-ray Observatory survey of planetary nebulae (PNe) in the solar neighborhood. The first phase of ChanPlaNS targeted 21 mostly high-excitation PNe within ~1.5 kpc of Earth, yielding 4 detections of diffuse X-ray emission and 9 detections of X-ray-luminous point sources at the central stars (CSPNe) of these objects. Combining these results with those obtained from Chandra archival data for all (14) other PNe within ~1.5 kpc that have been observed to date, we find an overall X-ray detection rate of ~70%. Roughly 50% of the PNe observed by Chandra harbor X-ray-luminous CSPNe, while soft, diffuse X-ray emission tracing shocks formed by energetic wind collisions is detected in ~30%; five objects display both diffuse and point-like emission…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
