AI & ML Practical Magic

A new computer chip uses the quantum flipping of individual electron spins to solve physics problems that are too 'random' for standard processors.

March 31, 2026

Original Paper

MCPT-Solver: An Monte Carlo Algorithm Solver Using MTJ Devices for Particle Transport Problems

Siqing Fu, Lizhou Wu, Tiejun Li, Xuchao Xie, Chunyuan Zhang, Sheng Ma, Jianmin Zhang, Yuhan Tang, Jixuan Tang

arXiv · 2603.28042

The Takeaway

Standard computers are too logical to easily simulate the randomness of nature, like how radiation moves through a shield. By using the natural, unpredictable behavior of magnetic particles as a computational engine, this 'spin-based' hardware solves complex stochastic problems significantly faster than traditional silicon chips.

From the abstract

Monte Carlo particle transport problems play a vital role in scientific computing, but solving them on exiting von Neumann architectures suffers from random branching and irregular memory access, causing computing inefficiency due to a fundamental mismatch between stochastic algorithms and deterministic hardware. To bridge this gap, we propose MCPT-Solver, a spin-based hardware true random number generator (TRNG) with tunable output probability enabled by a Bayesian inference network architectur