Establishment of Imaging Spectroscopy of Nuclear Gamma-Rays based on Geometrical Optics

• Tanimori, Toru

• Mizumura, Yoshitaka

• Takada, Atsushi

• Miyamoto, Shohei

• Takemura, Taito

• Kishimoto, Tetsuro

• Komura, Shotaro

• Kubo, Hidetoshi

• Kurosawa, Shunsuke

• Matsuoka, Yoshihiro

• Miuchi, Kentaro

• Mizumoto, Tetsuya

• Nakamasu, Yuma

• Nakamura, Kiseki

• Parker, Joseph D.

• Sawano, Tatsuya

• Sonoda, Shinya

• Tomono, Dai

• Yoshikawa, Kei

Abstract

Since the discovery of nuclear gamma-rays, its imaging has been limited to pseudo imaging, such as Compton Camera (CC) and coded mask. Pseudo imaging does not keep physical information (intensity, or brightness in Optics) along a ray, and thus is capable of no more than qualitative imaging of bright objects. To attain quantitative imaging, cameras that realize geometrical optics is essential, which would be, for nuclear MeV gammas, only possible via complete reconstruction of the Compton process. Recently we have revealed that "Electron Tracking Compton Camera" (ETCC) provides a well-defined Point Spread Function (PSF). The information of an incoming gamma is kept along a ray with the PSF and that is equivalent to geometrical optics. Here we present an imaging-spectroscopic measurement with the ETCC. Our results highlight the intrinsic difficulty with CCs in performing accurate imaging, and show that the ETCC surmounts this problem. The imaging capability also helps the ETCC suppress the noise level dramatically by ~3 orders of magnitude without a shielding structure. Furthermore, full reconstruction of Compton process with the ETCC provides spectra free of Compton edges. These results mark the first proper imaging of nuclear gammas based on the genuine geometrical optics.

Journal

• Scientific Reports

  Scientific Reports 7 41511-41511, 2017-02-03

  Springer Nature

Details

• CRID: 1050001335840994688
• NII Article ID: 120005971756
• NII Article ID: 120006360177
• ISSN: 20452322
• HANDLE: 2433/218098
• HANDLE: 20.500.14094/90004312
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • CiNii Articles