1. Quantum Engineering & Control
Quantum Technologies Flagship
Quantum Engineering & Control

2. Quantum Technologies Flagship
Communication:
Devices & Systems
Quantum
Sensing &
Metrology
Quantum Computers:
Hardware & Software
Quantum
Simulators
Engineering
Quantum
& Control
Enabling
Science
Algorithms
& Protocols
Theory,

3. Quantum Engineering vs Enabling Science
Communication:
Devices & Systems
Quantum
Sensing &
Metrology
Quantum Computers:
Hardware & Software
Quantum
Simulators
Engineering
Quantum
& Control
Enabling
Science
Quantum Engineering (inc. applied science): Combining or refining technologies and concepts from enabling science, to realise more complex devices or systems that address or demonstrate applications.
Enabling Science (inc. both quantum and classical): Develop the tools, components, materials, processes, etc. - that will enable the mission-driven objectives to be realised.

4. Cross-Cutting Challenges
Grand Challenges
Quantum Engineering (inc. applied science): combining or refining technologies and concepts from enabling science, to realise more complex device or systems that address or demonstrate applications.
Quantum Computers: Hardware & Software
Demonstrations of quantum algorithms operating on logical qubits in a universal quantum computer.
Few-qubit test-beds and quantum information transport between three or more networked systems.
Quantum Communication: Devices & Systems
Create a quantum-safe secure backbone and access networks connecting major cities in Europe, exploiting trusted-node technologies.
Demonstration of practical, autonomous, systems capable of performing continuous secure key distribution > Mbps rates, e.g. over metropolitan distances.
Cross-Cutting Challenges
Quantum Simulators
Realise quantum simulators that show superior performance compared to classical simulators.
Already 100 “good” physical qubits could enable us to simulate systems that are hard to simulate classically
Quantum Sensing & Metrology
Demonstrate ultra-high-precision spectroscopy and microscopy, positioning systems, clocks, gravitational, electrical and magnetic field sensors, and optical resolution beyond the wavelength limit.
A pan-European optical fibre network for time and frequency comparison and dissemination.
Quantum sensors networks
… Networking?

5. Quantum control for Quantum Technologies
Emerged from quantum control roadmap (includes chemistry, NMR ...)
Emerged from QUAINT coordination action ( )
Focus on optimal control, theory and experiment
Definition:
The general goal of quantum control is
to actively manipulate dynamical processes
of quantum systems, typically by means of
external electromagnetic fields or forces.

6. Mathematical foundation
Controllability: What states and operations are reachable for given hardware?
Full mathematical theory for closed systems
Partial insights for open systems, new goal
Analytical control principles – simple insights
Based on the Pontryagin maximum principle
Few, powerful examples
Special area of shortcuts to adiabaticity
Numerical packages
Different methods: Fast Gradient-based (GRAPE, Krotov), or robust gradient-free (CRAB, AdHOC)
Various versatile numerical packages are available (DYNAMO, Spinach)

7. AMO / NMR tradition
Not quite part of Quantum Technologies 2.0 – but important source and context
NMR: Optimal control used for design of pulse sequence
Used for different aims: Fidelity, Robustness, speed, sensitivity
Parts of spectrometers (commercial!) used in hospitals, biochemistry ...
Ideas transfer, e.g., to spin-based quantum sensing
Control of chemical reactions
Pioneering application of quantum control
Aims at control of chemical reactions, breaking and welding of bonds
New frontier: Cold molecules
Includes open systems control / reservoir engineering for cooling molecules

8. Quantum computing and simulation
Achieved:
Resilient gates in ion traps
Leakage-avoidance in superconducting qubits
Control of large electro-nuclear system in neutral atoms
Proposals for cluster states, high-fidelity gates etc.
Improved loading of atoms into optical lattice
Fidelity limits after decoherence
Jones polynomial shortcuts
Aims:
Bring theory and experiment together much more closely, deepen development of automatic tuneup
Advance debugging of pulses
Improve gate robutness
Develop quantum compiler for complex gates
Make control and error correction compatible
Fast generation of entangled states fors simulation

9. Quantum sensing and communication
Achieved:
Proposals for state transport and transport of ions and photons
Spectroscopy and imaging sequences for diamond sensing
Nonclassical BEC states
Optimal preparation of squeezed and other special states for sensing
Aims:
Optimal intercoversion between stationary and flying qubits
Hybrid quantum-classical error correction
Further enhance sensitivity of diamond through noise-adapted control
Demonstrate usefulness of nonclassical states for sensing
Advance adaptive sensing techniques

10. Quantum feedback control
Closed loop control. Processing measured data, use quantum trajectories – or use feedback method to design coherent controllers
Mathematically rigorous framework, initial experiments
Goals:
Efficiently simulate larger network
Non-Markovian feedback networks
Integrate with experiments
Develop quantum design language

11. Consultation feedback categories
Merge quantum control with hard- and software development, quantum-classcal interface, talk more about electronics: Cross-cutting control and engineering challenge
Emphasize chemistry more Needs to be integrated with applications
Why does it have its own section? Needs to be integrated with non-existing engineering section
Quantum control opens new platforms, such as plasmonics We could not agree more, but new platforms need to prove their relevance for applications