IBM has set an ambitious goal to develop the world´s first large-scale, fault-tolerant quantum supercomputer, targeting operational readiness by 2029. The project, dubbed IBM Quantum Starling, will reside in a purpose-built Quantum Data Center in Poughkeepsie, New York. At its core, the system will harness 200 logical qubits, enabling it to reliably perform up to 100 million quantum operations. This level of capability places Starling roughly 20,000 times ahead of today’s most advanced quantum processors, unlocking practical quantum computing for complex algorithmic workloads.
The key to Starling’s leap lies in error correction and efficient resource management. Unlike physical qubits, which are susceptible to frequent errors, logical qubits aggregate multiple physical qubits and continuously monitor for errors, drastically reducing failure rates. IBM aims to further optimize this process by employing quantum low-density parity-check (qLDPC) error-correcting codes. Compared to conventional surface codes, qLDPC allows for up to 90 percent fewer physical qubits per logical qubit, dramatically lowering the hardware and infrastructure demands. Real-time sequencing, operation control, and decoding of qubit states will be handled via conventional electronics, including FPGAs and ASICs, ensuring the seamless integration of quantum and classical technologies.
IBM’s Quantum Roadmap outlines intermediate milestones en route to Starling’s debut. The Quantum Loon processor, scheduled for 2025, will be the first to test long-range ‘C-coupler’ interconnects and critical qLDPC technology. In 2026, the modular Kookaburra chip is set to combine quantum memory with logical processing, enhancing system flexibility and scale. By 2027, the Cockatoo processor will interlink multiple modules using ‘L-couplers’, effectively simulating the distributed nodes of a complete, modular quantum system. Collectively, these stages exemplify IBM’s methodical approach, laying the foundation needed to bring reliable quantum computing into practical realms such as drug discovery, advanced materials, chemistry simulation, and large-scale optimization.
