A new quantum-inspired algorithm is reshaping how scientists approach some of the most complex materials known, enabling rapid analysis of structures that were previously beyond computational reach. Quantum technologies, including quantum computers, rely on materials that display unusual quantum effects under specific conditions. Researchers have found that these properties can also be engineered by adjusting a material’s structure. For example, stacking and slightly twisting layers of graphene creates a moiré pattern that can transform the material into a superconductor. As scientists build increasingly intricate layered systems, they reach structures such as quasicrystals and super-moiré materials. The challenge is predicting which designs will be useful. Modeling these materials requires calculating vast amounts of data. In the case of quasicrystals, this can involve more than a quadrillion numbers, far exceeding the limits of even the most powerful supercomputers. A Quantum-Inspired Breakthrough Researchers at Aalto University’s Department of Applied Physics have introduced a quantum-inspired algorithm that can handle these massive, non-periodic systems with remarkable speed. According to Assistant Professor Jose Lado, this work also highlights a growing feedback loop in quantum technology. “Crucially, these new quantum algorithms can enable the development of new quantum materials to build new paradigms of quantum computers, creating a productive two-way feedback loop between quantum materials and quantum computers,” he explains. Tensor networks play a central role in this approach, as they can represent functions across extremely fine computational grids. This makes them well-suited for analyzing large-scale quantum materials. The findings could lead to dissipationless electronics, which may help reduce the heat generated by AI-driven data centers. The research team was led by Lado and included doctoral researcher Tiago Antão, the study’s lead author, along with QDOC doctoral researcher Yitao Sun and Academy Research Fellow Adolfo Fumega. Their results were published in Physical Review Letters as an Editor’s