A Joint Chandra and Swift View of the 2015 X-Ray Dust Scattering Echo of V404 Cygni

TL;DR

This study combines Chandra and Swift X-ray observations to analyze the 2015 dust scattering echo of V404 Cygni, revealing detailed dust cloud structures, their properties, and improving dust scattering models.

Contribution

It introduces a method to precisely determine dust cloud distances and column densities using combined high-resolution X-ray data and a new spectral dust scattering model.

Findings

Eight dust rings identified with precise distances

Significant variation in dust cloud column densities

Steeper dust distribution models fit the data better

Abstract

We present a combined analysis of the Chandra and Swift observations of the 2015 X-ray echo of V404 Cygni. Using stacking analysis, we identify eight separate rings in the echo. We reconstruct the soft X-ray lightcurve of the June 2015 outburst using the high-resolution Chandra images and cross-correlations of the radial intensity profiles, indicating that about 70% of the outburst fluence occurred during the bright flare at the end of the outburst on MJD 57199.8.By deconvolving the intensity profiles with the reconstructed outburst lightcurve, we show that the rings correspond to eight separate dust concentrations with precise distance determinations. We further show that the column density of the clouds varies significantly across the field of view, with the centroid of most of the clouds shifted toward the Galactic plane, relative to the position of V404 Cyg, invalidating the assumption of uniform cloud column typically made in attempts to constrain dust properties from light echoes. We present a new XSPEC spectral dust scattering model that calculates the differential dust scattering cross section for a range of commonly used dust distributions and compositions and use it to jointly fit the entire set of Swift echo data. We find that a standard Mathis-Rumpl-Nordsieck model provides an adequate fit to the ensemble of echo data. The fit is improved by allowing steeper dust distributions, and models with simple silicate and graphite grains are preferred over models with more complex composition.