本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2014-04-10
摘要
Recently, a programmable 量子 annealing machine has been built that minimizes the cost function of hard optimization problems by, in principle, adiabatically quenching 量子 fluctuations. Tests performed by different research teams have shown that, indeed, the machine seems to exploit 量子 effects. However, experiments on a class of random-bond instances have not yet demonstrated an advantage over classical optimization algorithms on traditional computer hardware. Here, we present evidence as to why this might be the case. These engineered 量子 annealing machines effectively operate coupled to a decohering thermal bath. Therefore, we study the finite-temperature critical behavior of the standard benchmark problem used to assess the 計算 capabilities of these complex machines. We simulate both random-
※ 此為已發表論文，全文需透過期刊付費取得