Abstract

Abstract The Hitomi Soft X-ray Spectrometer spectrum of the Perseus cluster, with ∼5 eV resolution in the 2–9 keV band, offers an unprecedented benchmark of the atomic modeling and database for hot collisional plasmas. It reveals both successes and challenges of the current atomic data and models. The latest versions of AtomDB/APEC (3.0.8), SPEX (3.03.00), and CHIANTI (8.0) all provide reasonable fits to the broad-band spectrum, and are in close agreement on best-fit temperature, emission measure, and abundances of a few elements such as Ni. For the Fe abundance, the APEC and SPEX measurements differ by 16%, which is 17 times higher than the statistical uncertainty. This is mostly attributed to the differences in adopted collisional excitation and dielectronic recombination rates of the strongest emission lines. We further investigate and compare the sensitivity of the derived physical parameters to the astrophysical source modeling and instrumental effects. The Hitomi results show that accurate atomic data and models are as important as the astrophysical modeling and instrumental calibration aspects. Substantial updates of atomic databases and targeted laboratory measurements are needed to get the current data and models ready for the data from the next Hitomi-level mission.

Highlights

  • Many major achievements in X-ray studies of clusters of galaxies were made possible by the advent of new X-ray spectroscopic instruments

  • Triggered by the early work on the Hitomi Soft Xray Spectrometer (SXS) data of the Perseus cluster (Hitomi Collaboration et al 2016), and the follow-up work as presented in this paper, several updates to version 3.00 were made leading to SPEX version 3.03, released in November 2016, that is used for the present analysis

  • A detailed comparison on the best-fit spectra shown in appendix 4 reveals several differences in emission features from the baseline model, at levels ranging from a few % up to about 20%

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Summary

Introduction

Many major achievements in X-ray studies of clusters of galaxies were made possible by the advent of new X-ray spectroscopic instruments. We show that this high-resolution spectrum offers a sensitive probe of several important aspects of cluster physics including turbulence, elemental abundance measurements, and structures in temperature and velocity (section 3). We investigate the sensitivity of the related derived physical parameters to various aspects of the spectroscopic codes (section 4) and their underlying atomic data (section 5), spectral (section 6) and astrophysical (sections 7 and 8) modelings, as well as fitting techniques (section 9) By consolidating these systematic factors and by comparing them to statistical uncertainties as well as the systematic factors due to instrumental calibration effects (appendix 3), we can evaluate with what precisions the important quantities can be determined. We do not examine combined effects of different types of systematic factors (e.g., plasma-code dependence in the detailed astrophysical modeling like multitemperature models), which will be separately discussed in the individual topical papers

Data reduction
Baseline model
Systematic factors affecting the derived source parameters: plasma code
A bug in the calculation of trielectronic recombination for
CHIANTI
Systematic factors affecting the derived source parameters: atomic data
Cloudy
H-like ions
Best fit with adjusted line ratios for the x and y lines
Transition probability
Satellite line emission
Ionization equilibrium concentrations
Systematic factors affecting the derived source parameters: plasma modeling
Voigt profiles
Continuum contributions from heavy elements
Maximum principal quantum number n in the calculations
Hyperfine mediated transitions
Ion temperature versus turbulence
Deviations from collisional ionization equilibrium
Effects of the spatial structure of the Perseus cluster
Multi-temperature fitting of the Hitomi SXS data
Helium abundance
Self-absorption by hot gas
Charge exchange contributions
AGN contribution
Optimal binning versus other binning
10 An improved model
11.1 Important factors
11.2 Atomic data needs
Energy-scale correction
Effective-area correction factor
Binning of the data
Velocity-gradient correction
Response matrices
Non-X-ray background
Effective area
ARF with the latest aharfgen
Findings
Effects of the gain correction factor
Full Text
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