Classical computers achieve quantum-level accuracy for FeMoco energy

Researchers have used conventional supercomputers to calculate the ground-state energy of FeMoco, a crucial molecule in nitrogen fixation, with the precision long thought exclusive to quantum computers. This breakthrough challenges claims of quantum advantage for such chemical simulations. The finding could accelerate efforts to understand and replicate nitrogen fixation for more efficient fertilizers.

Nitrogen fixation, the process by which microbes convert atmospheric nitrogen into usable ammonia, is essential for life on Earth. At its core lies FeMoco, a complex molecule whose exact workings remain elusive. Understanding FeMoco could enable industrial-scale replication, slashing the energy costs of fertilizer production and potentially increasing crop yields.

Computing FeMoco's ground-state energy has been notoriously difficult due to its many electrons behaving in quantum wave-like patterns across multiple orbitals. While quantum computers have been mathematically proven capable of exact solutions without approximations, classical methods have lagged, relying on less accurate estimates.

Now, a team led by Garnet Kin-Lic Chan at the California Institute of Technology has developed a classical approach that matches 'chemical accuracy'—the precision needed for reliable chemical predictions. By analyzing properties of FeMoco's higher-energy quantum states, such as electron symmetries, the researchers calculated upper bounds on the ground-state energy and extrapolated to a precise value. Their method reportedly completes the task in under a minute on a supercomputer, compared to an estimated eight hours on a quantum device under ideal conditions.

However, the advance does not fully unravel FeMoco's role in nitrogen fixation. Questions persist about which molecular parts interact with nitrogen and what intermediates form during the process.

David Reichmann at Columbia University noted, “The work doesn’t really tell us much about the FeMoco system in terms of its function, but as a model to show quantum advantage, it does place the bar even higher for quantum approaches.”

Dominic Berry at Macquarie University added, “This does challenge the argument for using quantum computers for problems like this, but for more complicated systems, it is expected that the computation time for classical methods will increase much faster than that for quantum algorithms.” Berry emphasized that upcoming fault-tolerant quantum computers could still offer broader solutions for such molecules.

The research appears in a preprint on arXiv (DOI: 10.48550/arXiv.2601.04621).

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