Quantum Chaos Simulation on 91-Qubit Processor Using Error Mitigation Breakthrough
Large-Scale Quantum Chaos Finally Within Reach of Near-Term Quantum Computers
The study of quantum chaos aims to translate chaotic classical dynamics into quantum terms, but practical simulations have been held back by limited computing power. Using advanced error mitigation and custom-designed circuits on a 91-qubit superconducting quantum processor, researchers have demonstrated a promising new approach. The work is reported in Nature Physics.
Error Mitigation Instead of Error Correction
Reliable quantum simulations demand the suppression of errors, yet full-scale quantum error correction comes at the cost of significant qubit and control overheads. Until now, researchers have largely sidestepped this challenge by focusing on smaller quantum many-body systems or on integrable models that exhibit limited chaos.
In the new study, the team adopted a different strategy. Rather than eliminating noise at the outset, they employed error mitigation—allowing to occur and correcting them afterwards—thereby conserving valuable computational resources.
"Our results rely on precisely characterizing noise across a large quantum processor, combined with the recently developed tensor-network error mitigation (TEM) approach," the authors note. "TEM performs error correction entirely during post-processing by implementing an inverted noise channel through tensor networks, exchanging increased classical computation and approximation bias for reduced sampling demands on the quantum hardware."
Dual-Unitary Circuits Enable Exact Predictions
The researchers successfully modelled many-body quantum chaos on a 91-qubit superconducting quantum processor using dual-unitary (DU) circuits.
Why Dual-Unitary Circuits Matter
These circuits employ gates that remain unitary across both time and space, making it possible to calculate certain system properties exactly—tasks that are normally computationally prohibitive. Despite their ability to mix information at exceptional speed, DU circuits still precise predictions for a select set of measurements.
Using DU circuits, the team simulated a kicked Ising model, a periodically driven quantum many-body system, by preparing well-defined initial quantum states. The error-mitigated results closely followed exact analytical predictions for autocorrelation decay across a range of system sizes.
Benchmarking Quantum Results Against Classical Models
The researchers also benchmarked their quantum simulations against both exact analytical results and advanced classical tensor-network calculations, examined in the Heisenberg and Schrödinger pictures.
For dual-unitary circuits that are analytically solvable, they observed that once the system moves away from perfectly solvable points, the quantum data continues to align closely with sophisticated tensor-network simulations—even at scales where brute-force classical approaches break down.
The team stresses, however, that beyond the reach of exact analytical solutions, such large-scale simulations can only be assessed against approximate classical methods.
Heisenberg vs Schrödinger Picture Performance
Commenting on the comparison between error-mitigated experiments and tensor-network models, the author notes that the experimental results show strong agreement with Heisenberg-picture simulations across a wide range of parameters, with some deviations appearing at larger circuit sizes, while displaying significant discrepancies when compared with Schrödinger-picture simulations.
The researchers note that simulations carried out in the Heisenberg picture converge significantly faster than those performed in the Schrödinger picture. While Heisenberg-picture dynamics appear to remain tractable on classical computers, achieving the same level of convergence in Schrö dinger-picture simulations quickly becomes computationally prohibitive at the scale explored in their experiments.
A Practical Path for Near-Term Quantum Advantage
Taken together, the findings outline a practical route for deploying near-term quantum computers to investigate:
- Quantum chaos
- Transport phenomena
- Localization in complex materials
The work also strengthens confidence in quantum computing as a reliable scientific instrument, even before full error correction is realized. According to the authors, this strategy may allow quantum simulations of many-body dynamics to outpace classical approaches well before fault-tolerant hardware becomes available.
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