QuoUSKWe

The problem

Quantum computing holds the potential to revolutionise computing across multiple domains, driven by rapid advancements in hardware. That progress is not yet matched by the development of system software, which remains fragmented and low-level, creating significant barriers for developers seeking to access quantum resources and implement complex algorithms. To accelerate adoption, the field urgently needs compelling “killer applications” that justify investment and demonstrate practical utility — and trained developers capable of navigating the emerging landscape.

What QuoUSKWe does

QuoUSKWe — pronounced kwo-us-kwe, echoing the Latin quousque, “up to which limit” — explores the boundaries of quantum computing’s promises and assesses how far they can be realised in the near future.

Through European Union–Republic of Korea collaboration, the project develops a technology-agnostic quantum programming model and compiler infrastructure, alongside a suite of high-impact applications validated on real quantum hardware. It integrates the Qrisp high-level programming framework with MLIR-based compiler infrastructures, supporting multiple source languages and target architectures, and develops quantum-aware intermediate representations, optimisation passes and backend-specific lowering strategies.

Objectives

1. A high-level, technology-agnostic programming model. Extend Qrisp with real-time hybrid features, formalise its meta-model, and integrate it with MLIR through the Jaspr intermediate representation.
2. A layered, open compiler infrastructure. Build MLIR dialects that support progressive lowering from high-level constructs to gate-level instructions across diverse quantum hardware.
3. Optimisation that matters on real devices. Implement dead code elimination, common subexpression elimination, Hermitian gate cancellation and in-place XOR rewriting to reduce qubit usage and circuit depth.
4. Killer applications, validated on hardware. Quantum cryptanalysis of lattice- and code-based post-quantum cryptosystems, simulation of strongly correlated systems via QPE, VQE and QITE, and Quantum AI for 6G threat detection in AI-native RAN environments.
5. Standardisation and community. Contribute to CEN/CENELEC and the Eclipse Foundation, and build capacity through joint EU–ROK training and workshops.

Approach

Applications are benchmarked on real quantum hardware — including the systems provided by IQM — with performance measured through fidelity, gate count and circuit depth across use cases. This integrated approach establishes a feedback loop between algorithm design, hardware constraints and application needs, unlocking scalable, accessible and sustainable quantum computing for both academic and industrial stakeholders.