A team of researchers has reached a major milestone in quantum computing by successfully simulating Google’s 53-qubit, 20-layer Sycamore quantum circuit. This was accomplished using 1,432 NVIDIA A100 GPUs and highly optimized parallel algorithms, opening new doors for simulating quantum systems on classical hardware. At the core of this achievement are advanced tensor network contraction techniques, which efficiently estimate the output probabilities of quantum circuits. To make the simulation feasible, the researchers used slicing strategies to break the full tensor network into smaller, more manageable parts. This significantly reduced memory demands while preserving computational efficiency — making it possible to simulate large quantum circuits with comparatively modest resources. The team also used a “top-k” sampling method, which selects the most probable bitstrings from the simulation output. By focusing only on these high-probability results, they improved the linear cross-entropy benchmark (XEB) — a key measure of how closely the simulation matches expected quantum behavior. This not only boosted simulation accuracy but also reduced the computational load, making the process faster and more scalable.

Full report : Researchers have achieved a major leap in quantum computing by simulating Google’s 53-qubit Sycamore circuit using over 1,400 GPUs and groundbreaking algorithmic techniques.