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The European Quantum Technologies Roadmap
Antonio Acín, Immanuel Bloch, Harry Buhrman, Tommaso Calarco, Christopher Eichler, Jens Eisert, Daniel Esteve, Nicolas Gisin, Steffen J. Glaser, Fedor Jelezko, Stefan Kuhr, Maciej Lewenstein, Max F. Riedel, Piet O. Schmidt, Rob Thew, Andreas Wallraff, Ian Walmsley, Frank K. Wilhelm
TL;DR
Quantum computation has demonstrated elementary algorithms and protocols, but building a fully featured machine remains constrained by scalability, error correction, and implementation-specific challenges. This roadmap summary organizes current capabilities and future directions, including error-corrected logical qubits, fault-tolerant gates, scalable control, and quantum software limitations.
Problem
Building a fully featured quantum computer requires integrating many qubits and correcting quantum errors, while quantum algorithms do not provide an advantage for every problem.
Method
The paper surveys quantum-computing implementations, their current capabilities and challenges, and cross-cutting software and control requirements.
Results
The roadmap anticipates error-corrected logical qubits and fault-tolerant gates within five years, followed in five to ten years by universal quantum algorithms operating on logical qubits.
Takeaways & Limitations
Progress toward large-scale quantum computation depends on improving qubit coherence and gate fidelities while realizing scalable classical control and tune-up routines.
Takeaways & Limitations
Miniaturized ion traps face increased electric-field noise near trap surfaces, requiring cryogenic operation and/or in-situ surface cleaning to address motional heating.
Abstract
from arXiv · showhide
Within the last two decades, Quantum Technologies (QT) have made tremendous progress, moving from Noble Prize award-winning experiments on quantum physics into a cross-disciplinary field of applied research. Technologies are being developed now that explicitly address individual quantum states and make use of the 'strange' quantum properties, such as superposition and entanglement. The field comprises four domains: Quantum Communication, Quantum Simulation, Quantum Computation, and Quantum Sensing and Metrology. One success factor for the rapid advancement of QT is a well-aligned global research community with a common understanding of the challenges and goals. In Europe, this community has profited from several coordination projects, which have orchestrated the creation of a 150-page QT Roadmap. This article presents an updated summary of this roadmap. Besides sections on the four domains of QT, we have included sections on Quantum Theory and Software, and on Quantum Control, as both are important areas of research that cut across all four domains. Each section, after a short introduction to the domain, gives an overview on its current status and main challenges and then describes the advances in science and technology foreseen for the next ten years and beyond.
7 Quantum Computation
Quantum computation has demonstrated elementary algorithms and high-fidelity operations across several physical platforms, but scaling remains constrained by integrating many qubits, correcting errors, and controlling complex hardware. The roadmap therefore emphasizes fault-tolerant architectures, platform-specific engineering, and improved interfaces for larger systems.
- Overview: Quantum processors have demonstrated elementary algorithms, while fully featured systems still face scalability challenges from integrating many qubits and correcting quantum errors.Different fault-tolerant architectures are being proposed to address these challenges.
- Scalable architectures: Controlling and error-correcting about 100 logical qubits is identified as a major milestone for overcoming classical processors on selected tasks such as quantum chemistry and simulation.Realizing logical qubits requires encoding them in larger numbers of physical qubits within viable architectures.
- Trapped ions: Ion systems have demonstrated gate errors of ~10^-6 for single-qubit control and ~10^-3 for two-qubit gates, but scalability remains their most significant challenge.Microfabricated traps, photonic interconnects, cryogenic operation, and in-situ cleaning are among the approaches under development.
- Superconducting circuits: Superconducting processors with 4-17 qubits have demonstrated universal gates exceeding 99.9% fidelity for single qubits and 99.5% for two-qubit gates.Single-shot, nondemolition measurements exceed 99% fidelity, while larger circuits remain difficult because of crosstalk, fabrication variability, and sub-50 mK operation.
- Quantum dots: Quantum-dot circuits have reached single-qubit gate fidelities above 99%, initialization fidelity of 99.9%, and coherence times up to T2 (T2*) = 500 (0.2) ms in enriched 28Si.A central remaining challenge is developing high-fidelity two-qubit gates, particularly for donor spins.
- Roadmap goals: Across implementations, near-term goals include error-corrected logical qubits, fault-tolerant gates, scalable classical control, and quantum interfaces connecting computing modules.Large-scale quantum computation is pursued on a ten-year-and-beyond timescale.
12 Quantum Simulation
Quantum simulation uses highly controlled quantum systems to mimic complex many-body systems, targeting problems that are difficult for classical computers. The roadmap distinguishes several simulator types while emphasizing validation, verification, and the unresolved scope of quantum advantage.
- Introduction: Classical simulation can require exponentially large resources as the underlying Hilbert space grows exponentially with system size.Quantum simulation was proposed to efficiently study interacting quantum systems beyond standard classical methods.
- Introduction: Quantum simulators use controlled quantum systems to mimic interacting systems with many degrees of freedom or encode hard constrained optimization problems.The simulated models should be challenging, potentially classically intractable, and controllable across preparation, manipulation, and measurement.
- Current Status: Simulators are classified as static, annealing, or dynamical, and as digital circuit-based or analogue systems reconstructing controlled quantum dynamics.Analogue platforms can address many constituents with architectures available using present technology.
- Current Status: Quantum simulation spans platforms including ultracold gases, trapped ions, polariton condensates, cavity-QED systems, quantum dots, superconducting circuits, and photonics.These platforms differ in maturity and experimental implementation.
- Challenges: A central challenge is verifying that a simulator performed correctly when its target task is inaccessible to efficient classical tracking.Validation can use parameter regimes with classical reference results, but certification need not always rely on efficient classical simulation.
- Challenges: Without error correction and fault tolerance, the extent to which verified simulators and annealers outperform classical computers remains unclear.Ground-state energy approximation can remain difficult even for a presumed quantum computer, while long-time many-body dynamics may offer quantum advantage.
- Future Outlook: Analogue simulators are expected within five to ten years to explore interacting many-particle systems and optimization problems beyond classical reach, with larger simulations targeted longer term.The roadmap anticipates applications in physics, materials science, and quantum chemistry.
Current status
Quantum sensing already spans photonic, atomic, spin-based, and optomechanical platforms, demonstrating precision measurements across fields and applications. Its next advances depend on overcoming losses, noise, integration, fabrication, and nanoscale functionalization constraints.
- Photonic sensors: Photonic sensors use engineered quantum states and measurements for multi-photon interferometry beyond the classical limit.
- Atomic sensors: Atomic interferometers harness quantum superposition for precise sensing of gravity, rotation, magnetic fields, and time, with applications including geophysics and climate research.
- Spin-qubit-based sensing: Spin sensors measure quantum phase accumulated by a qubit under external perturbations, targeting sensitivity, spatial resolution, and spectral or temporal resolution.Coherent control, including dynamical decoupling, is crucial for performance; diamond spins can retain millisecond coherence under ambient conditions.
- Optomechanical sensors: Optomechanical devices now support quantum-level measurement and control, including squeezed states, QND measurements, entanglement, photon-phonon interfaces, and quantum feedback.These platforms are being explored for electromagnetic-field conversion, sensing, and measurement across radio, microwave, and terahertz frequencies.
- Future challenges: Demonstrating sensing beyond standard quantum or interferometric limits in lossy systems remains an unresolved challenge across atomic and photonic platforms.Loss, dephasing, probe-state preparation, atomic motion, and the need for chip-scale integration constrain future sensor development.
- Applications: Quantum sensing has broad potential across measurements of time, space, rotation, gravitational, electrical, and magnetic fields in physics, chemistry, biology, medicine, and data processing.
23 Quantum Control
Quantum control converts quantum-system knowledge into implementable pulse sequences and control strategies for computing, simulation, communication, metrology, and sensing. The field has mature numerical methods but must improve scalability, platform coverage, experimental convergence, and benchmarking.
- Introduction: Quantum control designs external-field pulses or pulse sequences that drive a quantum system toward a specified task.
- Current status: Control theory addresses which targets are accessible and how to reach them through open-loop or measurement-aware closed-loop design.
- Current status: Numerical methods including gradient, Quasi-Newton, Newton, Krotov, and CRAB approaches have achieved reasonable maturity, but their performance can still improve.Important challenges include faster algorithms and broader controllability research across more platforms.
- Current status: Quantum optimal control supports decoherence avoidance, cooling, open-system control, coherence preservation, and engineering tasks across quantum technologies.
- Future challenges: Reliable scaled quantum technologies require control for preparation or reset, desired evolution, readout, and benchmarking of control success.
- Applications: Applications include feedback-stabilized quantum networks, robust gates and measurements, improved simulation loading and entangled-state preparation, and validation under noise.
- Conclusion: The long-term goal is a software layer that enhances quantum hardware performance beyond classical capabilities across computing, simulation, communication, metrology, and sensing.
27 Quantum Software and Theory
Quantum software and theory provide the algorithms, protocols, resource frameworks, and certification methods needed to exploit and assess quantum information processing. Near-term work targets small processors and practical protocols while addressing algorithmic limits, errors, security, and distributed computation.
- Quantum software for computing: Quantum software extracts useful computation from superposition, supporting algorithms for factoring, search, sorting, and quantum simulation.
- Quantum software for networks: Quantum communication can reduce transmitted bit resources for distributed problems, while quantum networks support protocols and certification of entanglement or channel security.
- Future challenges: A central challenge is finding quantum algorithms that outperform classical methods while understanding where quantum advantage does not apply.
- Future challenges: Near-future research must assess errors, design error-correction and fault-tolerance schemes for realistic noise, and understand errors in quantum simulation.
- Future challenges: Network research must develop distributed protocols, characterize entanglement-assisted communication, and advance device-independent QKD against hacking attacks.
- Quantum information theory: Quantum information theory develops laws, limits, resource theories, and scalable methods for estimating, detecting, and certifying quantum properties.
- Conclusion: Over the next 5-10 years, work will focus on small quantum processors, classically infeasible computation protocols, unprecedentedly secure protocols, and their eventual convergence with ultimate information-processing limits.