# Observing the ambiguity of simplicity via quantum simulations of an Ising spin chain. (arXiv:1711.03661v1 [quant-ph])

The modelling of stochastic processes is ubiquitous throughout the natural

and social sciences. An ideal model produces the correct statistical output

without any unnecessary complexity. This minimal-complexity criterion is

important conceptually, entailing the least number of causes of effects

(Occam's razor), and practically, entailing the least stored information in the

simulation. Here, we experimentally compare classical and quantum information

encodings in simulating an Ising spin chain, showing that quantum encodings

perform better and redefine our understanding of what is complex. We

experimentally observe a recently conjectured effect, the ambiguity of

simplicity. Specifically, we simulate Ising chains at different temperatures, A

and B, such that classical encodings require fewer resources to model A than B,

while quantum encodings are simpler for B than A. This challenges the

perspective that relative complexity is contained solely in the configuration

of the system being modelled. Our error-tolerant techniques account for

inevitable imperfections in realising quantum simulators, thus providing the

technological milestone needed to simulate increasingly complex stochastic

processes.