At the Simons Foundation's Flatiron Institute, a team of physicists just solved a quantum physics problem on a laptop—a feat that quantum computing researchers had claimed was impossible for classical computers. The breakthrough, published in Science, challenges the narrative that quantum supremacy requires actual quantum computers, and it centers on an elegant mathematical tool called tensor networks that acts like a "zip file for the wave function."
The problem itself required simulating the dynamics of hundreds of interacting qubits—the quantum computing equivalent of classical bits—arranged in intricate square, cubic, and diamond lattices. This task seems impossible for ordinary computers because qubits exist in superposition, and quantum entanglement means they cannot be treated individually, even when separated. The wave function describing such a system balloons exponentially as more particles are added, becoming too massive to store directly on conventional hardware. It's a fundamental challenge in quantum physics research, especially for predicting properties of quantum materials like superconductors.
In March 2025, researchers using an actual quantum computer published their own solution to this same problem in Science, claiming that classical computers could never achieve the same feat. The team at the Center for Computational Quantum Physics—Joseph Tindall, Miles Stoudenmire, and collaborators at Boston University—took that claim as a challenge. "Whenever we at the CCQ see these kinds of claims, we're always a bit skeptical," Tindall says. "Like, 'Did you try this? Did you try that?'" Rather than pursuing an arbitrary target, they decided to test their tensor network tools against this high-profile claim.
Tensor networks accomplish what seemed impossible through radical compression. Rather than storing the entire wave function, tensor networks compress it into interconnected tables of numbers—Tindall describes it as "a zip file for the wave function where you've taken all this information, and you've compressed it into this mathematical data structure full of these small tables of numbers that are interconnected to each other." The team developed new tools based on this approach, then implemented them using ITensor, a high-performance tensor network software library developed at the CCQ. Tindall performed many of the initial calculations using nothing more than a personal laptop.
The simulations capture three-dimensional quantum dynamics using a 3D tensor network, work that Stoudenmire calls "a frontier, because working with these objects—especially in three dimensions—is very untrodden." The team also revived belief propagation, an older algorithm from the 1980s, for new quantum physics applications, demonstrating that sophisticated mathematics doesn't always require cutting-edge hardware—just creative thinking.
The implications ripple across quantum physics research. By squeezing extra problem-solving power from classical computers, this methodology opens new pathways for studying quantum dynamics and may prove useful for solving optimization problems where many feasible solutions exist. The work suggests that quantum supremacy claims deserve scrutiny, and that the gap between quantum and classical computing may be narrower than previously thought.