過去研究中半導體雷射互相注入耦合系統產生低頻波動動態已經被應用在機器學習中的強化學習去做機器決策，但是研究中通常都假設兩雷射的操作條件相同且不考慮雷射自發輻射所造成的雜訊。但在實際的情況中，兩雷射的條件不對稱可能會影響到機器決策的結果。因此本論文將用模擬的方式，並改變雷射操作條件，例如:雷射注入強度、兩雷射之間的頻率差、兩雷射之間的延遲時間和雜訊來觀察機器決策的結果。從模擬的結果我們發現雷射注入強度、雷射的頻率差和雷射自發輻射所造成的雜訊對決策結果的影響有限，但兩雷射之間的延遲時間不對稱卻會讓結果出現非常大的變化。綜合以上結果，我們可以找出用在現實中用本論文的系統做機器決策實驗時需要注意的操作條件誤差避免影響決策結果。

Low-frequency fluctuations (LFF) of two mutually delay-coupled semiconductor lasers has been used for doing decision making for machine learning. In general, the asymmetric operating conditions of two lasers and laser spontaneous emission noise are ignored in previous studies. In actual experiment, these asymmetric operating conditions of two lasers and laser spontaneous emission noise might affect the results of decision making. In this study, we adjust the operating conditions of two lasers like injection strength, detuning frequency, delay time between two lasers and spontaneous emission noise by simulation and observe the performance. According to the results, we find injection strength, detuning frequency and spontaneous emission noise hardly affect the performance, but the asymmetric of delay time between two lasers has a significant effect. Summarize these results, we can find a suitable operating condition when we use mutually delay-coupled semiconductor lasers system for doing decision making in experiment.

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