Imaging reconstruction method on X-ray data of CMOS polarimeter combined with coded aperture

TL;DR

This paper introduces a novel EM-based imaging reconstruction method for X-ray polarimeters using CMOS sensors and coded apertures, significantly improving accuracy and noise reduction over traditional methods, thus advancing space-based X-ray polarimetry.

Contribution

The paper presents a new EM algorithm-based reconstruction technique tailored for coded aperture X-ray polarimetry with CMOS sensors, addressing artifacts and noise issues in previous methods.

Findings

Enhanced imaging accuracy over balanced correlation method

Background noise reduced to 17%

Validated with X-ray beam experiments

Abstract

X-ray polarization is a powerful tool for unveiling the anisotropic characteristics of high-energy celestial objects. We present a novel imaging reconstruction method designed for hard X-ray polarimeters employing a Si CMOS sensor and coded apertures, which function as a photoelectron tracker and imaging optics, respectively. Faced with challenges posed by substantial artifacts and background noise in the coded aperture imaging associated with the conventional balanced correlation method, we adopt the Expectation-Maximization (EM) algorithm as the foundation of our imaging reconstruction method. The newly developed imaging reconstruction method is validated with imaging polarimetry and a series of X-ray beam experiments. The method demonstrates the capability to accurately reproduce an extended source comprising multiple segments with distinct polarization degrees. Comparative analysis exhibits a significant enhancement in imaging reconstruction accuracy compared to the balanced correlation method, with the background noise levels reduced to 17%. The outcomes of this study enhance the feasibility of Cube-Sat imaging polarimetry missions in the hard X-ray band, as the combination of Si CMOS sensors and coded apertures is a promising approach for realizing it.