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Physicists have demonstrated that an ordinary computer can solve a quantum physics problem previously believed to require a quantum computer, challenging assumptions about the limits of classical computing. The breakthrough was achieved using advanced mathematical techniques and specialized software, with some of the calculations running on a standard personal laptop.
The research was led by scientists at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation’s Flatiron Institute, in collaboration with Boston University. Their work, published in Science, showed that carefully designed algorithms running on conventional hardware could accurately simulate the behavior of hundreds of interacting quantum bits, or qubits. The findings suggest classical computers may be capable of tackling a broader range of quantum problems than previously thought.
The team set out to test claims made in a 2025 Science paper, in which researchers used a quantum computer to simulate an especially complex qubit system and argued that the task was beyond the reach of classical machines. Instead of accepting that conclusion, the CCQ researchers applied new computational techniques to see how far conventional hardware could go.
One of the biggest challenges was modeling quantum entanglement, where the states of qubits remain interconnected and cannot be treated independently. To overcome this, the researchers relied on tensor networks, mathematical structures that compress the enormous wave functions describing quantum systems. Lead author Joseph Tindall compared the technique to creating a “zip file” for a wave function, dramatically reducing the computing resources needed.
Many of the simulations were performed using ITensor, a high-performance tensor network software library developed at the CCQ. The team also adapted belief propagation, an algorithm first introduced in the 1980s, to efficiently tackle complex three-dimensional quantum systems. Despite the modest hardware, the simulations matched theoretical predictions and agreed with results previously obtained using quantum computers.
Rather than viewing classical and quantum computing as rivals, the researchers say the two approaches complement each other. Classical simulations can help validate quantum hardware while advances in quantum computing continue to inspire better algorithms for conventional machines. The team is now developing methods to simulate mobile electrons in quantum materials, a significantly more difficult challenge that could deepen scientists’ understanding of superconductors and other advanced materials.
