Comment Section for Quantinuum and Microsoft achieve breakthrough that unlocks a new era of reliable quantum computing

This webpage announces a significant breakthrough in quantum computing achieved by Quantinuum and Microsoft. The two companies successfully used Quantinuum's System Model H2 quantum computer and Microsoft's qubit-virtualization system to generate the most reliable logical qubits ever recorded. This achievement has broad implications for the quantum computing industry, as it accelerates progress and challenges current assumptions about the timeline toward large scale reliable quantum computing. The collaboration between Microsoft and Quantinuum resulted in logical circuit error rates 800 times lower than the corresponding physical circuit error rates. This achievement is not only significant for the two companies but also for the entire quantum ecosystem, marking a crucial milestone towards building a hybrid supercomputing system. Quantinuum's System Model H2 has become the first quantum computer to reach Microsoft's Level 2 - Resilient phase of quantum computing. Using Microsoft's qubit-virtualization system, the teams managed to perform 14,000 individual instances of a quantum circuit with no errors. Microsoft also demonstrated multiple rounds of active syndrome extraction, an essential error correction capability. The webpage highlights the critical role of fault-tolerance in quantum computing, explaining the challenges and the solutions involved. Looking forward, in 2025, Quantinuum plans to introduce a new H-Series quantum computer, Helios, which will improve both physical qubit count and physical fidelity. This new model is expected to support at least 10 highly reliable logical qubits. In the long term, Quantinuum aims to unlock significant real-world economic value by developing systems capable of supporting ~1,000 reliable logical qubits. These systems will be used to tackle some of the most important problems facing humanity, such as modeling materials used in batteries and hydrogen fuel cells, and accelerating the development of meaning-aware AI language models.