dundant access is obtained by using thelogmeinservice.2 Data are periodically transferred to sarasvarti, the main NuSTAR server.
Figure 3.8. XRG beam profile with a knife edge scan in the X (left panel) and Y directions (right panel). The blue lines show the differential count rate measured by moving the knife edge in steps of 5 µm, normalized such that the peak response is unity. The dashed error bars show Poisson uncertainties in fluxes. The physical coordinates are set to be 0 at the peak intensity of the beam. The measured beam FWHM (∆) from multiple knife edge scans is ∆X≈50µmand ∆Y≈70µm.
3.4.2 Rate Stability
The rate stability of the XRG was tested in two ways: first, with aSidetector and a scalar, and then with NuSTAR detectors.
I set up the X-ray generator (XRG) with a 50 × 70 µm slit, which generates a spot size of 100 × 100 µm at the detector. I used aMotube, operated at 45 kV, 20 mA. Data were acquired using the Amptex Si detector and a scalar. The background rate for this detector is negligible: ∼0.03 counts/s. I aligned the Si detector to the XRG beam using the MCA for quick readout. The detector position was adjusted to achieve maximum count rate. Then I swapped the MCA with the scalar. The measurements were done by manually starting and stopping the scalar acquisition as per a stopwatch. The time recorded on the stopwatch (≃10 s) was used to calculate count rates. The RMS scatter in the time intervals is 0.1 s. I took 50 readings for the XRG, at a count rate of about 400 counts per second.
For comparison, I also obtained 20 readings with an 241Am source, with distance adjusted to get a similar count rate.
Figure 3.9. XRG stability measurements. The red curve is a histogram of counts per second obtained in a 22 hour integration. The mean of the histogram is sensitive to the input count rate, while the width depends on the dead-time per event. The dashed blue histogram shows a simulated distribution adjusted for the input count rate, using 2.5 ms dead-time per event. The residuals (green histogram) demonstrate the good quality of the fit.
The measured counts for the241Amhave a mean of 440 counts/s. The scatter in readings is 6.6 counts/s—consistent with a Poisson distribution. This test shows that theSidetector and scalar combination gives a reliable measurement of the count rate. For the XRG, the mean count rate is 412 counts/s, with a standard deviation of 6.4 counts/s. This is consistent with the expected scatter for a Poisson distribution.
Next, I conducted a stability measurement using the NuSTAR detectors themselves. I set up the XRG at 20 kV, 2 mA, and placed H78 in a the cold box to intercept the beam.
The stages were manually adjusted so that the beam was placed close to the center of a pixel. I measured a count rate of about 333 counts/s. Data were acquired for ∼22 h, yielding about 79,000 one-second count rate measurements. It was observed that the count measured by the detector was constant over the entire run. Due to the dead-time interval
associated with reading out each event, the count-rate distribution is a modified Poisson process (Figure 3.9). The observed data are in excellent agreement with a simulated count rate distribution for an incident beam with constant flux. The mean of this distribution is sensitive to the total count rate, while the width depends on the dead-time per event.
Using this data set, I verified that the dead-time per event is 2.50 ms.
3.4.3 Radioactive Source Fluence
As explained in Section 3.2.4, the quantum efficiency measurements consist of shining a radioactive source with a known count rate on a part of the detector, and calculating the QE from the measured count rate. A prerequisite for this is knowing the source flux well.
We accomplished this by measuring the source count rate with good statistics, using a Ge detector. We have a detailed model for the response of the Ge detector from previous work. We placed each radioactive source in turn in the beam tube with the QE mask, and placed it such that the distance from the Ge detector was same as the distance from the CZT detector during calibrations. The calibration Mylar window covering the cold box was also added in the beam path. In this configuration, the Ge detector intercepts the entire beam coming from the QE mask. During calibration, the source and detector were both inside the purge box, in a nitrogen environment. In the ≈2.5 in gap between the source and detector, air absorbs about 15% radiation at 6 keV, whileN2 absorbs only about 12%:
a significant difference. Ambient humidity further increases the absorption in air. So, we placed the entire setup in a nitrogen bag. We then took long integrations to beat down Poission noise, and measured source fluxes with high precision. The count rate of the55Fe (∼40,000 counts/s) is too high for the Ge readout electronics. We could not revert to the AmptexSidetector since its active area there is too small to intercept the full beam. Hence, we decided to insert an attenuator to reduce the count rate onGeto about 180 counts/s. In turn, we would calibrate the attenuator itself using theSidetector, by simply taking anI/I0 pair of measurements with and without the attenuator respectively. With a combination of these steps, we calculated the final fluence of the 3 calibration sources through the QE mask to be ≈150 counts/sfor 155Eu, ≈60 counts/sfor 241Am, and ≈30,000 counts/sfor 55Fe. The uncertainties in these measurements were propagated through to the uncertainty in-flight detector quantum efficiency measurements.