Quantum Engineering & Control Quantum Technologies Flagship Quantum Engineering & Control

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

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.

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 > 100 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?

Quantum control for Quantum Technologies Emerged from quantum control roadmap (includes chemistry, NMR ...) Emerged from QUAINT coordination action (2012-15) 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.

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)

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

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

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

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

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