Hamiltonian learning for 300 trapped ion qubits with long-range couplings

Fuente: arXiv
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Hauptverfasser: Guo, S. -A., Wu, Y. -K., Ye, J., Zhang, L., Wang, Y., Lian, W. -Q., Yao, R., Xu, Y. -L., Zhang, C., Xu, Y. -Z., Qi, B. -X., Hou, P. -Y., He, L., Zhou, Z. -C., Duan, L. -M.
Format: Preprint
Veröffentlicht: 2024
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author Guo, S. -A.
Wu, Y. -K.
Ye, J.
Zhang, L.
Wang, Y.
Lian, W. -Q.
Yao, R.
Xu, Y. -L.
Zhang, C.
Xu, Y. -Z.
Qi, B. -X.
Hou, P. -Y.
He, L.
Zhou, Z. -C.
Duan, L. -M.
author_facet Guo, S. -A.
Wu, Y. -K.
Ye, J.
Zhang, L.
Wang, Y.
Lian, W. -Q.
Yao, R.
Xu, Y. -L.
Zhang, C.
Xu, Y. -Z.
Qi, B. -X.
Hou, P. -Y.
He, L.
Zhou, Z. -C.
Duan, L. -M.
contents Quantum simulators with hundreds of qubits and engineerable Hamiltonians have the potential to explore quantum many-body models that are intractable for classical computers. However, learning the simulated Hamiltonian, a prerequisite for any applications of a quantum simulator, remains an outstanding challenge due to the fast increasing time cost with the qubit number and the lack of high-fidelity universal gate operations in the noisy intermediate-scale quantum era. Here we demonstrate the Hamiltonian learning of a two-dimensional ion trap quantum simulator with 300 qubits. We employ global manipulations and single-qubit-resolved state detection to efficiently learn the all-to-all-coupled Ising model Hamiltonian, with the required quantum resources scaling at most linearly with the qubit number. Our work paves the way for wide applications of large-scale ion trap quantum simulators.
format Preprint
id arxiv_https___arxiv_org_abs_2408_03801
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hamiltonian learning for 300 trapped ion qubits with long-range couplings
Guo, S. -A.
Wu, Y. -K.
Ye, J.
Zhang, L.
Wang, Y.
Lian, W. -Q.
Yao, R.
Xu, Y. -L.
Zhang, C.
Xu, Y. -Z.
Qi, B. -X.
Hou, P. -Y.
He, L.
Zhou, Z. -C.
Duan, L. -M.
Quantum Physics
Quantum simulators with hundreds of qubits and engineerable Hamiltonians have the potential to explore quantum many-body models that are intractable for classical computers. However, learning the simulated Hamiltonian, a prerequisite for any applications of a quantum simulator, remains an outstanding challenge due to the fast increasing time cost with the qubit number and the lack of high-fidelity universal gate operations in the noisy intermediate-scale quantum era. Here we demonstrate the Hamiltonian learning of a two-dimensional ion trap quantum simulator with 300 qubits. We employ global manipulations and single-qubit-resolved state detection to efficiently learn the all-to-all-coupled Ising model Hamiltonian, with the required quantum resources scaling at most linearly with the qubit number. Our work paves the way for wide applications of large-scale ion trap quantum simulators.
title Hamiltonian learning for 300 trapped ion qubits with long-range couplings
topic Quantum Physics
url https://arxiv.org/abs/2408.03801