Rescaling Interactions for Quantum Control
PHYSICAL REVIEW APPLIED 13:3 (2020) 34002
Abstract:
© 2020 American Physical Society. A powerful control method in experimental quantum computing is the use of spin echoes, employed to select a desired term in the system's internal Hamiltonian, while refocusing others. Here, we address a more general problem, describing a method to not only turn on and off particular interactions but also to rescale their strengths so that we can generate any desired effective internal Hamiltonian. We propose an algorithm based on linear programming for achieving time-optimal rescaling solutions in fully coupled systems of tens of qubits, which can be modified to obtain near-time-optimal solutions for rescaling systems with hundreds of qubits.Rescaling interactions for quantum control
Physical Review Applied American Physical Society 13:3 (2020) 034002
Abstract:
A powerful control method in experimental quantum computing is the use of spin echoes, employed to select a desired term in the system’s internal Hamiltonian, while refocusing others. Here, we address a more general problem, describing a method to not only turn on and off particular interactions but also to rescale their strengths so that we can generate any desired effective internal Hamiltonian. We propose an algorithm based on linear programming for achieving time-optimal rescaling solutions in fully coupled systems of tens of qubits, which can be modified to obtain near-time-optimal solutions for rescaling systems with hundreds of qubits.Cost function embedding and dataset encoding for machine learning with parameterized quantum circuits
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