X-Ray-to-Radio Offset Inference from Low-Count X-Ray Jets
Karthik Reddy, Markos Georganopoulos, Eileen T. Meyer

TL;DR
This study detects positional offsets between X-ray and radio emissions in low-count extragalactic jets using a novel algorithm, challenging existing emission models and providing new insights into jet physics.
Contribution
Introduces the use of LIRA for analyzing low-count X-ray jets, enabling detection of offsets previously obscured in shallow observations.
Findings
55% of knots with offsets have X-ray peaks upstream of radio
Detected offsets challenge one-zone emission models
Non-detection of two previously claimed X-ray jets
Abstract
Observations of positional offsets between the location of X-ray and radio features in many resolved, extragalactic jets indicates that the emitting regions are not co-spatial, an important piece of evidence in the debate over the origin of the X-ray emission on kpc scales. The existing literature is nearly exclusively focused on jets with sufficiently deep Chandra observations to yield accurate positions for X-ray features, but most of the known X-ray jets are detected with tens of counts or fewer, making detailed morphological comparisons difficult. Here we report the detection of X-ray-to-radio positional offsets in 15 extragalactic jets from an analysis of 22 sources with low-count Chandra observations, where we utilized the Low-count Image Reconstruction Algorithm (LIRA). This algorithm has allowed us to account for effects such as Poisson background fluctuations and nearby point…
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