Medical physics is a research field of applying the concepts and methods of physical sciences to medicine, especially radiology including radiation therapy. Intensity modulated radiation therapy (IMRT) is a state of the art technology of radiation therapy which has been developed based on the achievements in medical physics. Managing uncertainty including a detection of unacceptable error is a central task in safe and accurate delivery of IMRT to patients. We developed a machine learning models to automatically detect several errors possibly occur in IMRT dose calculation and IMRT dose delivery system of medical linear accelerator. The models are based on radiomics analysis of X-ray fluence distributions which is a method of extracting a large number of features from medical images. The proposed models showed superior performance to the conventional methods and may expand the possibilities of automatic error detection of IMRT.

Since being invented in the 1950s, the Markov chain Monte Carlo method has evolved within the paradigm of detailed balance, namely, reversibility. However, detailed balance is not necessary for numerical integration, and net probability flow can significantly accelerate distribution convergence. Efficient non-reversible Monte Carlo algorithms controlling probability flow, such as the lifting technique, have been recently developed for solving many-body problems. In this article, we explain the idea of lifting and review lifted Monte Carlo algorithms, including the event-chain Monte Carlo method and the directed worm algorithm.

Foam droplet put on a vertical wall sometimes loses its solution by liquid pinch-off from the bottom of the droplet. To address when it happens, we carried out a model experiment where an amount of foam confined in a Hele-Shaw cell is put under the gravity. “Pinch-off” and “No pinch-off” modes are found, and the lower onset of the Pinch-off mode is clarified from experiment and theory.

Minus Sample -1^-1-1^-1

The Belle II experiment aims to discover deviation from the Standard Model of particle physics as evidence of new physics using the electron-positron collision data with a center of mass energy of √s=10.58 GeV. For reaching the target integrated luminosity of 50 ab^-1, the accelerator and detector were upgraded from its predecessor, the Belle experiment. The experiment has been performed since 2018 and data were steadily accumulated. As of December 2021, the integrated luminosity of the recorded data was 268 f b^-1. Analyzing data in the first two and a half years, we recently published the results of the dark sector searches and the B^±→K^±νν branching ratio measurement. The dark sector searches in Belle II have sensitivities in mass regions of O(1) GeV/c². From the analysis of a few hundred pb^-1 data, no signature of the dark sector particle was observed. The search sensitivity will be improved by increasing the amount of the data. In the B^±→K^±νν measurement, we used 63 f b^-1 data and obtained an upper limit of the branching ratio, 4.1×10^-5 in a confidence level of 90%, which is comparable to the prior experiments. This article describes the detector upgrades, operation experience, and recent physics results in Belle II.

Recent theory on an organic conductor HMTSF-TCNQ shows that it is a nodal line semimetal with Dirac electrons and its large diamagnetic susceptibility is originated from the interband effect of magnetic field in the Dirac electron system. The temperature dependence of the magnetic susceptibility measured experimentally is reproduced quite well by the theory. Furthermore, in α-(BETS)₂I₃, it is shown that the energy gap in the Dirac electrons induced by spin-orbit interaction leads to spin Hall effect. Similar orbital magnetism in α-(BETS)₂I₃ is also discussed.