Google’s 67-Qubit Sycamore Quantum Computer Could Beat Top Supercomputers: Study

Google's Sycamore chip shows unprecedented capabilities, outpacing supercomputers in performance.

Highlights

• Google's Sycamore chip surpasses supercomputers in benchmark tests
• Quantum research reveals a new "weak noise phase" for calculations
• Significant step towards practical applications of quantum computing

Recent advancements in quantum computing have revealed that Google's 67-qubit Sycamore processor can outperform the fastest classical supercomputers. This breakthrough, detailed in a study published in Nature on October 9, 2024, indicates a new phase in quantum computation known as the "weak noise phase."

Understanding the Weak Noise Phase

The research, spearheaded by Alexis Morvan at Google Quantum AI, demonstrates how quantum processors can enter this stable computationally complex phase. During this phase, the Sycamore chip is capable of executing calculations that exceed the performance capabilities of traditional supercomputers. According to Google representatives, this discovery represents a significant step towards real-world applications for quantum technology that cannot be replicated by classical computers.

The Role of Qubits in Quantum Computing

Quantum computers leverage qubits, which harness the principles of quantum mechanics to perform calculations in parallel. This contrasts sharply with classical computing, where bits process information sequentially. The exponential power of qubits allows quantum machines to solve problems in seconds that would take classical computers thousands of years. However, qubits are highly sensitive to interference, leading to a higher failure rate; for instance, around 1 in 100 qubits may fail, compared to an incredibly low failure rate of 1 in a billion billion bits in classical systems.

Overcoming Challenges: Noise and Error Correction

Despite the potential, quantum computing faces significant challenges, primarily the noise that affects qubit performance. To achieve "quantum supremacy," effective error correction methods are necessary, especially as the number of qubits increases, as per a LiveScience report. Currently, the largest quantum machines have around 1,000 qubits, and scaling up presents complex technical hurdles.

The Experiment: Random Circuit Sampling

In the recent experiment, Google researchers employed a technique called random circuit sampling (RCS) to evaluate the performance of a two-dimensional grid of superconducting qubits. RCS serves as a benchmark to compare the capabilities of quantum computers against classical supercomputers and is regarded as one of the most challenging benchmarks in quantum computing.

The findings indicated that by manipulating noise levels and controlling quantum correlations, the researchers could transition qubits into the "weak noise phase." In this state, the computations became sufficiently complex, demonstrating that the Sycamore chip could outperform classical systems.