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• W3136455697 abstract "The Quantum Fisher Information (QFI) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution. Computing the full QFI matrix for a model with $d$ parameters, however, is computationally expensive and generally requires $mathcal{O}(d^2)$ function evaluations. To remedy these increasing costs in high-dimensional parameter spaces, we propose using simultaneous perturbation stochastic approximation techniques to approximate the QFI at a constant cost. We present the resulting algorithm and successfully apply it to prepare Hamiltonian ground states and train Variational Quantum Boltzmann Machines." @default.
• W3136455697 created "2021-03-29" @default.
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• W3136455697 date "2021-03-15" @default.
• W3136455697 modified "2023-10-01" @default.
• W3136455697 title "Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information" @default.
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