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Thermal state preparation of the SYK model using a variational quantum algorithm
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abstract
We study the preparation of thermal states of the dense and sparse Sachdev-Ye-Kitaev (SYK) model using a variational quantum algorithm for $6 \le N \le 12$ Majorana fermions over a wide range of temperatures. Utilizing IBM's 127-qubit quantum processor, we perform benchmark computations for the dense SYK model with $N = 6$, showing good agreement with exact results. The preparation of thermal states of a non-local random Hamiltonian with all-to-all coupling using the simulator and quantum hardware represents a significant step toward future computations of thermal out-of-time order correlators in quantum many-body systems.
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Improving thermal state preparation of Sachdev-Ye-Kitaev model with reinforcement learning on quantum hardware
Reinforcement learning with a 3D convolutional network designs low-CNOT circuits for variational thermal state preparation of the SYK model up to 14 Majorana fermions, but training uses the exact free energy and fidel...
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