Time-dependent Hamiltonian simulation with L1-norm scaling

被引:54
|
作者
Berry, Dominic W. [1 ]
Childs, Andrew M. [2 ,3 ,4 ]
Su, Yuan [2 ,3 ,4 ]
Wang, Xin [3 ,4 ,5 ]
Wiebe, Nathan [6 ,7 ,8 ]
机构
[1] Macquarie Univ, Dept Phys & Astron, Sydney, NSW 2109, Australia
[2] Univ Maryland, Dept Comp Sci, College Pk, MD 20742 USA
[3] Univ Maryland, Inst Adv Comp Studies, College Pk, MD 20742 USA
[4] Univ Maryland, Joint Ctr Quantum Informat & Comp Sci, College Pk, MD 20742 USA
[5] Baidu Res, Inst Quantum Comp, Beijing 100193, Peoples R China
[6] Univ Washington, Dept Phys, Seattle, WA 98195 USA
[7] Pacific Northwest Natl Lab, Richland, WA 99354 USA
[8] Google Inc, Venice, CA 90291 USA
来源
QUANTUM | 2020年 / 4卷
基金
美国国家科学基金会; 澳大利亚研究理事会;
关键词
QUANTUM ALGORITHMS;
D O I
10.22331/q-2020-04-20-254
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The difficulty of simulating quantum dynamics depends on the norm of the Hamiltonian. When the Hamiltonian varies with time, the simulation complexity should only depend on this quantity instantaneously. We develop quantum simulation algorithms that exploit this intuition. For sparse Hamiltonian simulation, the gate complexity scales with the L-1 norm integral(t)(0) d tau parallel to H(tau)parallel to(max), whereas the best previous results scale with tau max(tau is an element of[0,t]) parallel to H(tau)parallel to(max). We also show analogous results for Hamiltonians that are linear combinations of unitaries. Our approaches thus provide an improvement over previous simulation algorithms that can be substantial when the Hamiltonian varies significantly. We introduce two new techniques: a classical sampler of time-dependent Hamiltonians and a rescaling principle for the Schrodinger equation. The rescaled Dyson-series algorithm is nearly optimal with respect to all parameters of interest, whereas the sampling-based approach is easier to realize for near-term simulation. These algorithms could potentially be applied to semi-classical simulations of scattering processes in quantum chemistry.
引用
收藏
页数:40
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