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→SiPM Measurements
* T: 0-above room temp., in practice 3°C (to avoid growing snow) to 25°C
* T: 0-above room temp., in practice 3°C (to avoid growing snow) to 25°C
However, it was found that the peaks were very indistinct by at bias voltages below 20V and temperatures above 20°C. This was probably due to the narrowing of the peaks due to smaller gain or convolution of the additional dark counts detected. The solution to this was to abandon the manual location of pedestals, peak spacing etc. Instead, a model was created by Prof. Richard Jones based on which fitting of the histograms was performed.
However, it was found that the peaks were very indistinct by at bias voltages below 20V and temperatures above 20°C. This was probably due to the narrowing of the peaks due to smaller gain or convolution of the additional dark counts detected. The solution to this was to abandon the manual location of pedestals, peak spacing etc. Instead, a model was created by Prof. Richard Jones based on which fitting of the histograms was performed. It has the form:
<math>
<math>
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==== rest ====
<math>\lambda_{(p)}, \lambda_{(s)}, \sigma_0, \sigma_1, g, x_0 \quad</math> are the fit parameters. Not the absence of a vertical scale parameter. The vertical scale depends on the number of samples collected, whereas the equation in this model is normalized. Rescaling works as follows:
If <math>f(x)=T*f(q)</math>, where <math>T</math> is a vertical scaling parameter and since <math>dq=dx/g</math>,
<math>\int_{-\infty}^{\infty} f(x)\, dx = Tg \int_{-\infty}^{\infty} f(q)\, dq = Tg </math> implies that Tg is the number of events collected times the bin width (in Vs).
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