## 2. **Breadboard Design and Implementation**
### Sensor Characterisation  
The charge conversion efficiency (CCE), readout noise, and sensor's dark current were characterized. The CCE is related to the electrons' number converted into digital counts. Therefore, CCE can be calculated using a homogeneous and monochromatic light source. The CCE calculation is done by plotting the images' variance and mean counts of the light source for several integration times until it reaches saturation. A helium-neon gas laser beam was used as the source of light, which assures a monochromatic light source.  
The measurements were done in an integration sphere, ensuring the sensor received a homogeneous light. The used integration sphere had three orifices where any instrument could be installed. The laser used was assembled in one cavity, the sensor in another, and the remaining was closed.  
Ten frames were taken, varying from the minimal integration time of 6.31 us up to the completely saturated value, 71.43 ms. Then, each frame variance and mean counts were extracted. The region where these two values have an approximate linear behaviour was chosen. The variance-versus-mean-counts linear relation for several images extracted by the MT9J001 with the laser beam switched on are shown in Figure 3. The CCE result is taken from the slope of the data's linear fit. Therefore, a value of 5.22 \(\frac{e^{-}}{ADU}\) was found, where the Analog-Digital Units (ADU) represent the pixel reading value.  
by the subtraction of both frames, resulting in a value with the standard deviation of the counts of \(\sigma=3.24\) ADU. The readout noise \(N_{RN}\) is then given by: \[N_{RN}=\frac{CCE\ \sigma}{\sqrt{2}}\] (4) Substituting the results of \(\sigma\) and CCE in (4) gives a \(N_{RN}=11.97\ e^{-}\).
* Dark noise The dark noise is computed through the dark current, which is measured by taking dark frames, images taken in the dark with the shutter closed, at a controlled temperature. The dark frame uses an integration time that is different from the minimal value, diverging from the bias frame in this aspect. The dark current was measured in the integration sphere with the aforementioned configuration at a constant temperature of 24 \({}^{\circ}\)C. Ten dark frames with several integration times were taken until the sensor reached a moderated level of saturated pixels. Afterwards, a mean of the ten measurements for the different integration times was computed. The mean values obtained for each integration time are shown in Figure 4.  
In Figure 4, the slope of the linear fit indicates the dark current: 0.2098 ADU/s. This value can be converted to electrons/s, giving 1.095 e\({}^{-}\)/s. The dark noise \(N_{DN}\) is then given by: \[N_{DN}=\sqrt{i_{DC}t}\] (5) In (5), \(i_{DC}\) is the dark current, and \(t\) is the integration time.
* Focus and FWHM of the optical system The optical system focus and the full width at half maximum (FWHM) of the signal of a point source were found using an interferometer. The interferometer sends a light beam representing a light source at an infinite distance to the camera. The best configuration for the focus is achieved when the light beam occupies the minimum value of pixels in the sensor, i.e., the minimum FWHM. Figure 5 shows the camera in the interferometer (a) and the image of the focused light beam (b).  
Figure 4: Mean values of each set of measurements in different integration times.  
After achieving the best result, as seen in Figure 5b, the software ThorCan and SAOImageDS9 were used to determine the number of pixels the light beam signal occupies. A value of 16 pixels was found, also representing the number of pixels an A0-type star occupies in the sensor.