Abstract
Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealing optimizers that contain hundreds of quantum bits. These optimizers, commonly referred to as ‘D-Wave’ chips, promise to solve practical optimization problems potentially faster than conventional ‘classical’ computers. Attempts to quantify the quantum nature of these chips have been met with both excitement and skepticism but have also brought up numerous fundamental questions pertaining to the distinguishability of experimental quantum annealers from their classical thermal counterparts. Inspired by recent results in spin-glass theory that recognize ‘temperature chaos’ as the underlying mechanism responsible for the computational intractability of hard optimization problems, we devise a general method to quantify the performance of quantum annealers on optimization problems suffering from varying degrees of temperature chaos: A superior performance of quantum annealers over classical algorithms on these may allude to the role that quantum effects play in providing speedup. We utilize our method to experimentally study the D-Wave Two chip on different temperature-chaotic problems and find, surprisingly, that its performance scales unfavorably as compared to several analogous classical algorithms. We detect, quantify and discuss several purely classical effects that possibly mask the quantum behavior of the chip.
Highlights
Recent advances in quantum technology have led to the development and manufacturing of experimental programmable quantum annealing optimizers that contain hundreds of quantum bits
Inspired by recent results in spinglass theory that recognize ‘temperature chaos’ as the underlying mechanism responsible for the computational intractability of hard optimization problems, we devise a general method to quantify the performance of quantum annealers on optimization problems suffering from varying degrees of temperature chaos: A superior performance of quantum annealers over classical algorithms on these may allude to the role that quantum effects play in providing speedup
We have devised a method for quantifying the susceptibility of quantum annealers to classical effects by studying their performance on sets of instances characterized by different degrees of thermal hardness, which we have defined for that purpose as the mixing time τ of classical thermal algorithms on these
Summary
Victor Martin-Mayor1,2 & Itay Hen[3,4] received: 08 March 2015 accepted: 22 September 2015. Since quantum annealers are meant to utilize an altogether different mechanism for solving optimization problems than traditional classical devices, methods for quantifying this difference are expected to serve as important theoretical tools while having vast practical implications. We propose a method that partly solves the above question by providing a technique to characterize and quantitatively measure how detrimental classical effects are to the performance of quantum annealers This is done by studying the algorithmic performance of quantum annealers on sets of optimization problems possessing quantifiable, varying degrees of “thermal” or “classical” hardness, which we define for this purpose. In the large N limit, these are the short-τ samples that become exponentially rare in N23,34 This provides further motivation for studying TC instances of optimization problems on moderately small experimental devices (even if these problems are rare).
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