Classical Computers Just Beat A Quantum Annealer At Its Own Benchmark

[Rachel_72]

Researchers at the Flatiron Institute in New York have used a new classical tensor network technique to simulate Ising spin glass dynamics, and in many cases their method turned out to be more accurate than D-Wave's Advantage2 quantum annealer running the exact same problem. The work, led by Joseph Tindall and published in Science, directly challenges an earlier claim that classical computers could not match the annealer's results on this specific benchmark.

The Ising spin glass model describes spins on a lattice pointing in essentially random directions due to competing interactions between neighboring pairs, and its difficulty scales up sharply with system size, which makes it a genuinely useful benchmark for comparing classical and quantum performance head to head. Tensor networks represent the state of a many particle system using interconnected mathematical objects that can be thought of a bit like LEGO pieces snapping together, where widening the connections between them lets the network capture more correlation detail at the cost of more computation.

The real trick behind this specific result was a technique called belief propagation, where each tensor receives a compact summary of what the rest of the network effectively looks like from its own local perspective rather than accounting for every single contribution exactly. That approach let the team's classical simulation push forward in time far enough to actually reach the same regime the quantum annealer operates in, something conventional tensor network methods have historically struggled to do without the computational cost exploding.

Across cylindrical, diamond, and cubic lattice geometries, the classical method's error in measuring how spins at different points on the lattice relate to each other came in lower than the annealer's on two of the three geometries, and roughly matched it on the third. That is a meaningfully different outcome than simply matching performance across the board, since it suggests the classical technique is not just catching up but genuinely outperforming the quantum hardware on some specific versions of this problem.

The team plans to extend this same belief propagation approach to interacting electronic systems and finite temperature problems next, continuing what has become a fairly consistent pattern of classical algorithms closing gaps that earlier quantum advantage claims assumed were permanent

No quantum advantage (yet) in the world of tensor networks - Physics Worldphysicsworld.com