Masafumi Niwano, Tokyo Institute of Technology
A GPU-accelerated image reduction pipeline
We have developed a high-speed image reduction pipeline that utilizes Graphics Processing Units (GPUs) as hardware accelerators. Astronomers aim to detect the electromagnetic counterparts of gravitational-wave sources as soon as possible and conduct systematic multi-wavelength follow-up observations. Therefore, high-speed image processing is crucial. We have developed a new image-reduction pipeline for our robotic telescope system, which employs a GPU via the Python package CuPy for high-speed image processing. As a result, the new pipeline has achieved a processing speed more than 40 times faster than the previous one, while retaining the same functions.

Nobuyuki Kawai, Tokyo Institute of Technology
High precision optical photometry of high-mass X-ray binaries
High-mass X-ray binaries, which contain neutron stars, are potential progenitor systems of merging double neutron star binaries, making their system parameters a topic of interest. Our study reveals that the precise continuous light curve acquired with TESS can be effectively modeled by considering the tidally distorted companion, which is irradiated with X-rays from the neutron star. Additionally, our investigation into the light curves of Be X-ray binaries uncovered oscillations that are time-varying and may be attributed to the neutron star's perturbation on the companion star.