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Results for “Quantum optimization”
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Characterization of control noise effects in optimal quantum unitary dynamics
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Nearly Optimal Quantum Algorithm for Estimating Multiple Expectation Values
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Threshold-Based Quantum Optimization
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Using Reinforcement Learning to Optimize Quantum Circuits in the Presence of Noise
As we move towards devices which utilize more qubits, it becomes increasing more important to map quantum circuits in a way that uses resources efficiently as well as maximizes the reliability of the results of that circuit. To this end, we will need to rely on heuristic algorithms, specifically reinforcement learning (RL) as a method of building quantum circuits based on observations of the noise characteristics in its environment.
Optimizing Quantum Circuit Layout Using Reinforcement Learning
Presentation slides for Summer Internships in Science and Technology (SIST) End of Term Activities 2020.
Lyapunov control-inspired protocol for quantum optimization.
Abstract not provided.
Optimal Quantum Transfer from Input Flying Qubit to Lossy Memory.
Abstract not provided.
Tradeoffs in hybrid quantum-classical algorithms for designing quantum optimal controls
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Hybrid quantum-classical algorithms for quantum optimal control
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The Role of the Global Phase in Optimal Quantum Control to Implement Partial Isometries.
Abstract not provided.
Searching for quantum optimal controls in the presence of singular critical points.
Abstract not provided.