Researchers at the Flatiron Institute’s Center for Computational Quantum Physics (CCQ) have discovered why a classical computer was able to outperform a quantum computer on a challenging task.
Their findings, published in Physical Review Letters, reveal that the problem they tackled exhibited a special phenomenon called “confinement,” which unexpectedly made it easier for a classical computer to solve.
The task involved simulating a two-dimensional system of tiny magnets that could flip directions, creating complex patterns of interactions.
Normally, quantum computers are better suited for these kinds of simulations because they use “qubits” that can represent multiple states at once, giving them the potential for vastly superior processing power compared to classical computers.
However, quantum computers are still in the early stages of development, and researchers are working to identify the problems where these computers truly excel.
In June 2023, IBM researchers claimed that their quantum computer had successfully solved this difficult problem involving flipping magnets, which they believed was beyond the reach of classical computers.
They argued that only a quantum computer could handle the rapid “entanglement” that occurs when the magnets influence each other’s behavior. Entanglement refers to the quantum linking of particles, which makes their states interdependent and often complicates the simulation.
After hearing about IBM’s results, Joseph Tindall, a research fellow at CCQ, decided to take on the challenge with a classical computer.
Tindall and his team have been working on advanced algorithms for solving quantum problems with classical methods.
To everyone’s surprise, Tindall was able to solve the problem using a classical computer in just two weeks, without needing much computing power—it could even run on a smartphone.
Tindall explained that his team did not use cutting-edge technology but instead combined existing ideas in a smart way to create a solution. Their method relied on well-written software and clever mathematical approaches that had been overlooked.
Tindall and his colleague Dries Sels from New York University wanted to understand why their classical solution worked so well.
They noticed that the system’s behavior matched a concept called “confinement.” Confinement is a phenomenon where only small clusters of particles can flip their state due to limited energy, preventing large-scale entanglement from taking over.
To grasp the concept, imagine a setup where all the tiny magnets initially point in the same direction.
When a small magnetic field is applied, some magnets begin to flip, and these flips can influence nearby magnets. In a typical open system, these interactions could quickly lead to widespread entanglement.
However, in a closed system with limited energy, only small groups of magnets could flip at a time. This natural limitation kept the entanglement in check and made the problem easier for classical computers to handle.
The researchers showed through simulations that the confinement in this system kept the magnets from becoming completely disordered. Instead, they tended to oscillate around their original states, even over long periods of time.
This discovery has broader implications for understanding the limits of quantum and classical computers.
Tindall explained that their results clarify when and why entanglement grows in certain quantum systems and when it doesn’t. They developed a simple mathematical model that explains the observed behavior, offering insights into other two-dimensional quantum systems where confinement might also occur.
The researchers believe that confinement could appear in a range of two-dimensional quantum systems.
Their findings not only help distinguish where classical computers can excel, but also provide a tool for scientists to test and refine quantum simulations.
Overall, the study shows that despite the rapid advancements in quantum computing, classical methods still have much to offer. Understanding the boundaries between what quantum and classical computers can do will be key as we continue to explore the potential of quantum technology.
