[PDF][PDF] Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
Quantum optimal control, a toolbox for devising and implementing the shapes of external
fields that accomplish given tasks in the operation of a quantum device in the best way …
fields that accomplish given tasks in the operation of a quantum device in the best way …
Machine learning for quantum matter
J Carrasquilla - Advances in Physics: X, 2020 - Taylor & Francis
Quantum matter, the research field studying phases of matter whose properties are
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
intrinsically quantum mechanical, draws from areas as diverse as hard condensed matter …
Entanglement devised barren plateau mitigation
Hybrid quantum-classical variational algorithms are one of the most propitious
implementations of quantum computing on near-term devices, offering classical machine …
implementations of quantum computing on near-term devices, offering classical machine …
Quantum machine learning for chemistry and physics
Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …
pertinent patterns within a given data set with the objective of subsequent generation of …
Quantum information processing with bosonic qubits in circuit QED
The unique features of quantum theory offer a powerful new paradigm for information
processing. Translating these mathematical abstractions into useful algorithms and …
processing. Translating these mathematical abstractions into useful algorithms and …
Guiding the design of heterogeneous electrode microstructures for Li‐ion batteries: microscopic imaging, predictive modeling, and machine learning
Electrochemical and mechanical properties of lithium‐ion battery materials are heavily
dependent on their 3D microstructure characteristics. A quantitative understanding of the …
dependent on their 3D microstructure characteristics. A quantitative understanding of the …
Experimental deep reinforcement learning for error-robust gate-set design on a superconducting quantum computer
Quantum computers promise tremendous impact across applications—and have shown
great strides in hardware engineering—but remain notoriously error prone. Careful design of …
great strides in hardware engineering—but remain notoriously error prone. Careful design of …
Model-free quantum control with reinforcement learning
Model bias is an inherent limitation of the current dominant approach to optimal quantum
control, which relies on a system simulation for optimization of control policies. To overcome …
control, which relies on a system simulation for optimization of control policies. To overcome …
Quantum architecture search via deep reinforcement learning
Recent advances in quantum computing have drawn considerable attention to building
realistic application for and using quantum computers. However, designing a suitable …
realistic application for and using quantum computers. However, designing a suitable …
[HTML][HTML] A tutorial on optimal control and reinforcement learning methods for quantum technologies
Abstract Quantum Optimal Control is an established field of research which is necessary for
the development of Quantum Technologies. In recent years, Machine Learning techniques …
the development of Quantum Technologies. In recent years, Machine Learning techniques …