Unknown

Dataset Information

0

Solving quantum ground-state problems with nuclear magnetic resonance.


ABSTRACT: Quantum ground-state problems are computationally hard problems for general many-body Hamiltonians; there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating the ground state is available, as often happens for many problems in physics and chemistry, a quantum computer could employ this trial wavefunction to project the ground state by means of the phase estimation algorithm (PEA). We performed an experimental realization of this idea by implementing a variational-wavefunction approach to solve the ground-state problem of the Heisenberg spin model with an NMR quantum simulator. Our iterative phase estimation procedure yields a high accuracy for the eigenenergies (to the 10?? decimal digit). The ground-state fidelity was distilled to be more than 80%, and the singlet-to-triplet switching near the critical field is reliably captured. This result shows that quantum simulators can better leverage classical trial wave functions than classical computers.

SUBMITTER: Li Z 

PROVIDER: S-EPMC3216574 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

altmetric image

Publications

Solving quantum ground-state problems with nuclear magnetic resonance.

Li Zhaokai Z   Yung Man-Hong MH   Chen Hongwei H   Lu Dawei D   Whitfield James D JD   Peng Xinhua X   Aspuru-Guzik Alán A   Du Jiangfeng J  

Scientific reports 20110909


Quantum ground-state problems are computationally hard problems for general many-body Hamiltonians; there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating the ground state is available, as often happens for many problems in physics and chemistry, a quantum computer could employ this trial wavefunction to project the ground state by means of the phase estimation algorithm (PEA). We performed an experimental realiz  ...[more]

Similar Datasets

| S-EPMC3460969 | biostudies-literature
| S-EPMC3323964 | biostudies-literature
| S-EPMC6641569 | biostudies-literature
| S-EPMC3565169 | biostudies-other
| S-EPMC11364692 | biostudies-literature
| S-EPMC6003724 | biostudies-literature
| S-EPMC6660203 | biostudies-literature
| S-EPMC4960298 | biostudies-literature
| S-EPMC7005697 | biostudies-literature
| S-EPMC7033176 | biostudies-literature