Physicists have found a way to simulate quantum chaos on modern quantum computers without waiting for a complete fix to appear. The team performed complex quantum dynamics simulations on a 91-qubit superconducting processor using error suppression techniques during the data processing stage. The work was published in the journal Nature Physics. Quantum chaos studies how chaotic classical systems behave in the quantum world. Such problems are important for understanding the properties of materials, energy, and information transfer, but their modeling quickly runs into computational limitations. Quantum error correction can completely solve the problem, but it requires too many qubits and complex controls. Instead, researchers rely on so-called error mitigation – error prevention. This approach allows noise to exist in a quantum device and then corrects for its effects after the computation is performed. An important tool is the recently proposed tensor mesh error suppression technique, which allows you to “reverse” the effects of noise at the classical data post-processing level. For the simulation, scientists used a special type of quantum circuit – a dual unitary circuit. Their special feature is that the quantum gates in them are unique in both time and space. Such circuits mix quantum information extremely rapidly, causing the system to become chaotic but at the same time maintaining the ability to accurately calculate certain physical quantities. These circuits implement a quantum version of the “periodically excited” Ising model, a standard example of a quantum many-body system. The experimental results were obtained on a high-precision quantum processor with advanced analytical predictions and classical calculations in regimes where they are still possible. Most importantly, at scales beyond direct classical simulation, error-limited quantum processors continue to produce physically meaningful results. At the same time, modeling methods in the so-called Heisenberg representation turned out to be much more efficient than classical methods compared to calculations in the Schrödinger representation, which quickly became computationally expensive. The authors emphasize that their work paves the way for the use of “precalibrated” quantum computers to study quantum disorder, transport and localization in materials. This is an important step towards ensuring that quantum computing becomes a reliable scientific tool at this stage of technological development – long before the emergence of fully fault-tolerant quantum machines.
