Quantum technologies promise transformative advances in computing, communication, and sensing. Among these areas, quantum computing is progressing the fastest, driven by exponential increases in qubit counts, record-breaking hardware demonstrations, and major industrial investment from leading technology companies and start-ups.
Potential applications span simulating complex molecules for drug and catalyst discovery, solving optimisation problems beyond classical reach, and unlocking new machine-learning paradigms. These efforts ultimately aim at achieving quantum advantage, i.e. the point at which a quantum device can solve a problem that no classical supercomputer can solve in any reasonable amount of time.
Recent demonstrations illustrate how the field is shifting from laboratory to pre-commercial platforms. IBM’s 433-qubit Osprey (2022), Quantinuum’s trapped-ion H2 processor (2023), and Atom Computing’s >1000-qubit neutral-atom array (2023) exemplify these achievements. In October 2025, Google Quantum AI’s Willow processor achieved a verifiable quantum advantage benchmark via the Quantum Echoes experiment, demonstrating constructive interference effects beyond the reach of classical simulation. This momentum is highlighted by the exponential growth of qubit numbers across leading platforms such as superconducting circuits, trapped ions, and neutral atoms over the past three decades and enabled by major advances in fabrication, control electronics, and system integration.
However, this rapid growth in quantity has not been matched by growth in quality. Today’s qubits remain noisy, short-lived, and vulnerable to crosstalk and correlated errors. Quantum error correction (QEC) is the enabler of fault-tolerant quantum computing as it protects fragile quantum states by encoding many physical qubits into fewer high-fidelity logical qubits and correcting errors without disturbing the stored information. Without effective QEC, simply increasing the number of qubits does not translate into more useful computational power, as errors accumulate faster with system size.
Despite impressive hardware progress, state-of-the-art QEC codes and decoders remain far from efficient enough to make large-scale fault-tolerant quantum computing practical. Even flagship targets such as breaking RSA-2048, using Shor’s algorithm, require tens of thousands of logical qubits and billions of error-free gate operations. Under current physical error rates, this translates to hundreds of thousands to millions of physical qubits. Strong QEC is essential to convert exponential hardware growth into genuine computational capability, instead of hitting diminishing returns long before practical quantum advantage is achieved.
QuBriC – Bridging Quantum and Classical Error Correction for Scalable Fault-Tolerant Quantum Computing directly addresses this challenge. Building such integrated expertise is now a prerequisite for progress. Even the most advanced quantum processors cannot deliver stable quantum advantage unless noise modelling, code design, decoding, and hardware constraints are tackled holistically, a skillset that remains exceedingly rare and fragmented across different research communities. QuBriC provides the coordinated framework and training pipeline needed to bridge these communities and convert abstract QEC theory into real device capability. The urgency of this effort is now widely recognized.
Our mission
QuBriC’s mission is to integrate classical coding theory, quantum information science, and quantum hardware engineering within the first European research and training network dedicated to scalable, hardware-ready QEC. Its goal is to translate rigorous code-design principles into practical QEC implementations while training 15 doctoral candidates fluent across the full quantum stack and major qubit platforms.