Researchers have developed a highly efficient method to investigate systems with long-range interactions that were previously puzzling to experts. These systems can be gases or even solid materials ...

Particle physicists are building innovative machine-learning algorithms to enhance Monte Carlo simulations with the power of AI. Originally developed nearly a century ago by physicists studying ...

Monte Carlo methods have become indispensable in simulating light transport due to their flexibility in handling complex phenomena such as scattering, absorption, and emission in heterogeneous media.

Monte Carlo simulations have emerged as an indispensable tool in gamma‐ray spectrometry and detector calibration, offering nuanced insights into particle interactions and detector responses. By ...

Impact of the First Wave of COVID-19 Pandemic on Radiotherapy Practice at Tata Memorial Centre, Mumbai: A Longitudinal Cohort Study Recently, a semimobile RO system has been developed by building an o ...

Objectives This study assessed whether a previously developed Monte Carlo simulation model can be reused for evaluating various strategies to minimise time-to-treatment in southwest Netherlands for ...

I am looking to estimate the potential for failure in a complex system using Monte Carlo simulation. I am quite familiar with using MC for engineering simulations, but have never approached the ...