Aalto University researchers have developed a quantum-inspired algorithm that simulates complex materials at an unprecedented scale, paving the way for dissipationless electronics and more stable quantum computers.
In the pursuit of the next generation of computing, the bottleneck has long been the sheer mathematical complexity of the materials required to move beyond silicon. This week, a research team at Aalto University’s Department of Applied Physics announced a breakthrough that could bypass this hurdle entirely. By utilizing a quantum-inspired algorithm, scientists have successfully simulated the behavior of “quasicrystals”—exotic materials with non-repeating patterns—at a scale previously considered impossible for conventional supercomputers.
Published in Physical Review Letters as an Editor’s Suggestion, the study led by Assistant Professor Jose Lado and doctoral researcher Tiago Antão addresses the immense computational load required to map quantum excitations within non-periodic structures. These excitations are the key to developing “topological qubits,” the building blocks of a more stable, error-resistant quantum computer. Until now, simulating these structures was a task of staggering proportions, often requiring the processing of over a quadrillion numbers. Such a scale is far beyond the reach of today’s most powerful traditional hardware, which struggles to maintain accuracy when patterns do not repeat predictably.
The team’s solution involves the use of tensor networks, a sophisticated mathematical family of algorithms that encodes computational spaces in a manner similar to how a quantum computer operates. By reformulating the challenge and treating the material simulation as a quantum many-body system, the researchers were able to compute a quasicrystal with over 268 million sites. This represents a leap of several orders of magnitude over previous capabilities, allowing for the design of “super-moiré” materials—structures created by twisting and stacking layers of atoms, such as graphene, to unlock entirely new physical properties like unconventional superconductivity.
Beyond the realm of abstract physics, this discovery has tangible implications for national infrastructure and energy sovereignty. One of the primary goals of the research, supported by the ULTRATWISTROICS grant and the Center of Excellence in Quantum Materials (QMAT), is the development of dissipationless electronics. Current silicon-based systems generate massive amounts of heat due to electrical resistance, leading to the staggering energy demands of modern AI-driven data centers. Materials designed through this new algorithm could theoretically conduct electricity without energy loss, drastically reducing the carbon footprint and the cooling requirements of the digital age.
The researchers focused specifically on topological quasicrystals because they host unconventional quantum excitations that are naturally protected from disruptive noise and interference. However, because these excitations are distributed unevenly throughout the material, they are notoriously difficult to track. The new tensor network method allows scientists to pinpoint these excitations almost instantly, providing a blueprint for materials that can maintain quantum coherence in the face of external environmental pressure.
While the work is currently theoretical and based on simulations, the path to physical implementation is already coming into view. Professor Lado noted that the algorithm is designed to eventually run on actual quantum hardware, such as the AaltoQ20 and the broader Finnish Quantum Computing Infrastructure, once those systems reach sufficient maturity and fidelity. This creates a productive “two-way feedback loop” where quantum-inspired mathematics builds the very materials needed to construct the next generation of quantum computers.
This advancement reinforces a critical trend in modern science: the shift toward decentralized, high-efficiency innovation that prioritizes hardware resilience. By mastering the topological properties of matter, researchers are moving closer to a future where computing is not limited by the physical heat of its own processing. For the American observer, this marks a vital step toward a future where technological leadership is grounded in efficient, sovereign, and revolutionary engineering that protects the integrity of data and the stability of the power grid alike.

