Every time a computer flips a single digital bit, it burns energy — and multiplied across trillions of operations a second, that cost is becoming one of computing's biggest problems. A new framework built entirely from math, not new hardware, could shrink it dramatically.

  • 10x weaker magnetic pulses than standard switching methods, in simulations
  • 0.94 nanojoules — the switching energy achieved under test conditions
  • Compared against DRAM, STT-MRAM, and emerging SOT-MRAM memory technologies
  • Published in Advanced Materials, September 2026

A math problem, not a materials problem

AI models, data centers, and everyday cloud services all depend on magnetic memory to store and move digital information as switched magnetic states. Historically, making that switching more efficient has meant inventing new materials. Researchers at the University of Edinburgh took a different approach: they applied Optimal Control Theory, a mathematical method for finding the most efficient path to a specific goal, to redesign the shape of the magnetic-field pulse itself.

Computer simulations showed the resulting pulses were more than 10 times weaker than those used in conventional switching protocols, while still reliably flipping the bit. Under test conditions, the required switching energy dropped as low as 0.94 nanojoules — a level the team says could lower energy use by several orders of magnitude compared with memory technologies used or in development today, including DRAM, STT-MRAM and SOT-MRAM.

How close to the physical limit

The framework's real headline is how close it pushes toward the Landauer limit — the fundamental thermodynamic floor on the minimum energy required to process a single bit of information, a boundary set by physics itself rather than engineering. Approaching that limit, rather than merely improving on today's chips, is what makes the result notable to the broader memory industry.

Dr. Elton Santos of the University of Edinburgh's Institute for Condensed Matter Physics and Complex Systems, who led the research alongside Mohammad H. Badarneh and PeiYu Cai, published the full method in the journal Advanced Materials.

"Every digital operation has an energy cost, and that cost becomes increasingly important as AI and data-intensive technologies continue to expand. Our work shows that, by carefully designing how a magnetic field changes in time, magnetization can be switched far more efficiently than with conventional approaches."

Beyond magnetic fields

The team didn't stop at theory. The paper includes practical guidance for implementation, including device designs and methods for delivering the optimized magnetic fields, intended to help other researchers test the concept experimentally rather than leaving it purely on paper.

Santos said the underlying mathematics is not limited to magnetic-field pulses at all. "The same framework can be adapted to electrical currents and even ultrafast laser pulses, which are among the most cutting-edge technologies for future data storage," he said. "It seems that we may have just found the next best thing."

With global data center electricity demand climbing as AI adoption accelerates, a method that squeezes more efficiency out of existing memory architectures — without waiting on a new wonder material — could matter well beyond a single lab's test bench.