The classical-quantum divergence of complexity in modelling spin chains

被引:16
|
作者
Suen, Whei Yeap [1 ]
Thompson, Jayne [1 ]
Garner, Andrew J. P. [1 ]
Vedral, Vlatko [1 ,2 ,3 ]
Gu, Mile [1 ,4 ,5 ]
机构
[1] Natl Univ Singapore, Ctr Quantum Technol, 3 Sci Dr 2, Singapore 117543, Singapore
[2] Univ Oxford, Clarendon Lab, Atom & Laser Phys, Parks Rd, Oxford OX1 3PU, England
[3] Natl Univ Singapore, Dept Phys, 3 Sci Dr 2, Singapore 117543, Singapore
[4] Nanyang Technol Univ, Sch Math & Phys Scieces, Singapore, Singapore
[5] Nanyang Technol Univ, Complex Inst, Singapore, Singapore
来源
QUANTUM | 2017年 / 1卷
基金
新加坡国家研究基金会; 中国国家自然科学基金;
关键词
COMPUTATIONAL MECHANICS; STATISTICAL COMPLEXITY;
D O I
10.22331/q-2017-08-11-25
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The minimal memory required to model a given stochastic process known as the statistical complexity is a widely adopted quantifier of structure in complexity science. Here, we ask if quantum mechanics can fundamentally change the qualitative behaviour of this measure. We study this question in the context of the classical Ising spin chain. In this system, the statistical complexity is known to grow monotonically with temperature. We evaluate the spin chain's quantum mechanical statistical complexity by explicitly constructing its provably simplest quantum model, and demonstrate that this measure exhibits drastically different behaviour: it rises to a maximum at some finite temperature then tends back towards zero for higher temperatures. This demonstrates how complexity, as captured by the amount of memory required to model a process, can exhibit radically different behaviour when quantum processing is allowed.
引用
收藏
页数:9
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