Could a one-dimensional melting quantum magnet be described by the same equations that describe snow as it falls and clumps together? This was the question that a collaboration between Google Quantum AI and researchers at Princeton set out to ask in a study that was published in the journal Science on April 5.

The team explored a theory known as Kardar-Parisi-Zhang (KPZ) universality, which outlines the common rules governing very different kinds of physical phenomena, ranging from the growth of bacterial colonies to the pileup of snow. A 2019 discovery from researchers at the University of Ljubljana conjectured that this behavior might apply to the case of a melting one-dimensional magnet as well.

In their recent paper, the team investigated this hypothesis using Google’s quantum processor built of 46 superconducting qubits. Upon careful statistical analysis, they found that the behavior of the quantum magnet showed clear deviations from the predictions of the KPZ theory, demonstrating the value of direct quantum simulation in exploring novel physical phenomena and theoretically unanticipated regimes of quantum dynamics.

Among the team were Princeton theorists Rhine Samajdar, a Princeton Quantum Initiative postdoctoral fellow in the Department of Physics, and Sarang Gopalakrishnan, an assistant professor in the Department of Electrical and Computer Engineering.

“What we found is that if you only look at the average of certain quantities, the dynamics appear to be consistent with the KPZ conjecture of falling snow and melting magnets being in the same class,” Samajdar said. “However, if you look at higher moments of distribution functions—beyond simple averages—you start to see the striking discrepancies. This tells us that there is a new universality class that we don’t quite understand and is yet to be discovered.”

Subir Sachdev, a condensed matter theorist and Herchel Smith Professor of Physics at Harvard University, noted: “Quantum computers hold great promise in describing the quantum dynamics of many degrees of freedom in regimes which are inaccessible by classical computers. A deeper understanding of quantum dynamics is the key to many fundamental physics problems, some of technological importance, ranging from higher temperature superconductors to the interior of a black hole. In this paper, the team from Google Quantum AI and their collaborators have clearly demonstrated this utility of quantum computers, showing how a chain of 46 superconducting qubits has a new regime of quantum dynamics that had not been anticipated either by theory, or by classical computers.”