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Faster ground state preparation and high-precision ground energy estimation with fewer qubits
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We propose a general-purpose quantum algorithm for preparing ground states of quantum Hamiltonians from a given trial state. The algorithm is based on techniques recently developed in the context of solving the quantum linear systems problem [Childs,Kothari,Somma'15]. We show that, compared to algorithms based on phase estimation, the runtime of our algorithm is exponentially better as a function of the allowed error, and at least quadratically better as a function of the overlap with the trial state. We also show that our algorithm requires fewer ancilla qubits than existing algorithms, making it attractive for early applications of small quantum computers. Additionally, it can be used to determine an unknown ground energy faster than with phase estimation if a very high precision is required.
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Eigenstate Preparation on Quantum Computers
A dissertation presenting adiabatic evolution with optimal control, the Rodeo Algorithm, and a new Variational Rodeo Algorithm that uses Rodeo success probability as a variational cost function.
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