When Nanomagnets Do the Math: France’s New Machine for Impossible Choices

What happened

French researchers have demonstrated a hybrid nanoelectronic experimental "Ising machine" designed to solve difficult combinatorial optimization problems more efficiently. The work was conducted by researchers from CEA-Leti and Spintec in Grenoble and the Centre for Nanoscience and Nanotechnology at Université Paris-Saclay, and reported in Nature Communications. The system combines hafnium-oxide resistive random-access memory (ReRAM) with stochastic magnetic tunnel junctions (SMTJs): ReRAM devices store the weighted connections describing how variables influence one another and can perform analog matrix operations where data are stored, while SMTJs represent the binary variables and fluctuate between states driven by thermal noise. The researchers control annealing by adjusting a single read voltage applied to the ReRAM array, so the hardware produces an annealing schedule through the direct interaction of its components. The proof-of-concept machine consistently reached the global optimum in a 24-vertex weighted MAX-CUT benchmark and a 10-vertex, three-color graph-coloring problem, operated at room temperature without an applied magnetic field, and the researchers emphasize that ReRAM, magnetic tunnel junctions and CMOS circuitry are compatible with back-end-of-line fabrication and vertical three-dimensional integration. The article notes this remains a small experimental prototype, not evidence of superiority over leading conventional solvers; updates are currently sequential, external feedback is still used for measurement, and comparative speed and energy benefits have not yet been quantified. The source does not state a cause (this is a technology development report, not a market movement).

Impact and signal

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Source and time

Source: SemiWiki · 10/28/2026 · View original source