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首页> 外文期刊>Journal of Applied Physics >Time resolved gain and excess noise properties of InGaAs/InAlAs avalanche photodiodes with cascaded discrete gain layer multiplication regions
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Time resolved gain and excess noise properties of InGaAs/InAlAs avalanche photodiodes with cascaded discrete gain layer multiplication regions

机译：具有级联离散增益层倍增区域的InGaAs / InAlAs雪崩光电二极管的时间分辨增益和超额噪声特性

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摘要

To predict pulse detection performance when implemented in high speed photoreceivers, temporally resolved measurements of a 10-stage InAlAs/InGaAs single carrier multiplication (SCM) avalanche photodiode (APD)'s avalanche response to short multi-photon laser pulses were explained using instantaneous (time resolved) pulse height statistics of the device's impulse response. Numeric models of the junction carrier populations as a function of the time following injection of a primary photo-electron were used to create the probability density functions (pdfs) of the instances of the avalanche buildup process. The numeric pdfs were used to generate low frequency gain and excess noise models, which were in good agreement with analytic models of multiple discrete low-gain-stage APDs and with measured excess noise data. The numeric models were then used to generate the instantaneous and cumulative instantaneous low order statistics of the instances of the impulse response. It is shown that during the early times of the impulse response, the SCM APDs have lower excess noise than the pseudo-DC measurements and the common APD models used to describe them. The methods of determining the time resolved low order statistics of APDs are described and the importance of using time-resolved models of APD gain and noise is discussed.
机译：为了预测在高速光接收器中实施时的脉冲检测性能，使用瞬时时间（）解释了10阶InAlAs / InGaAs单载流子乘积（SCM）雪崩光电二极管（APD）对短多光子激光脉冲的雪崩响应的时间分辨测量结果时间分辨）设备脉冲响应的脉冲高度统计信息。注入初级光电子后，作为时间函数的结载流子种群的数值模型用于创建雪崩累积过程实例的概率密度函数（pdfs）。数字pdf用于生成低频增益和过量噪声模型，这与多个离散的低增益级APD的分析模型以及测得的过量噪声数据非常吻合。然后使用数值模型来生成脉冲响应实例的瞬时和累积瞬时低阶统计量。结果表明，在脉冲响应的早期，SCM APD的过剩噪声比伪DC测量和用于描述它们的通用APD模型要低。描述了确定APD的时间分辨低阶统计量的方法，并讨论了使用APD增益和噪声的时间分辨模型的重要性。

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