Fault-Tolerant Quantum Computing
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IBM Delivers New Quantum Processors, Software, and Algorithm Breakthroughs on Path to Advantage and Fault Tolerance
Prnewswireยท 2025-11-12 11:00
Core Insights - IBM announced significant advancements in quantum computing, aiming for quantum advantage by the end of 2026 and fault-tolerant quantum computing by 2029 [1][11]. Quantum Processor Development - IBM introduced the Quantum Nighthawk processor, designed to achieve quantum advantage by solving problems more efficiently than classical methods, with delivery expected by the end of 2025 [3]. - Future iterations of the Nighthawk processor are projected to support up to 7,500 gates by the end of 2026, increasing to 10,000 gates in 2027, and potentially 15,000 gates by 2028 [3][5]. Quantum Advantage Tracking - IBM, along with partners, is contributing to a community-led quantum advantage tracker to validate quantum advantage claims, with the first confirmed cases expected by the end of 2026 [4][6]. - The tracker currently supports three experiments focused on observable estimation, variational problems, and efficient classical verification [6]. Error Correction and Fault-Tolerant Computing - IBM's Quantum Loon processor demonstrates all necessary components for fault-tolerant quantum computing, achieving efficient quantum error correction with a ten-fold speedup over existing methods [12][13]. - The company has successfully used classical hardware for real-time error decoding in under 480 nanoseconds, a year ahead of schedule [13]. Fabrication and Development Speed - IBM is transitioning to a 300mm wafer fabrication facility to enhance the development speed of quantum processors, achieving a ten-fold increase in physical complexity [14][15]. - The new facility allows for faster learning and improvement of quantum processor capabilities, including increased qubit connectivity and performance [15]. Software Enhancements - IBM's Qiskit software has been enhanced to provide developers with greater control, achieving a 24% increase in accuracy and reducing the cost of accurate result extraction by over 100 times [8][9]. - Future plans for Qiskit include extending computational libraries for machine learning and optimization by 2027 [10].