Detector & Electronics Throughput

One of the most significant limitations of using NuSTAR for heliophysics observations is the τ = 2.5 ms dead-time window after a photon trigger that is a result of the throughput of the onboard electronics to process the event. After each photon trigger there is a 2.5 ms window in which no other photons incident in the focal plane trigger a detection. The onboard electronics therefore limit the maximum throughput of 400

counts s−1 telescope−1 (calculated as τ−1). Importantly, at the start of this window

there is an 8 µs readout time during which pile-up can also occur (§ 4.2.2.3).

For most astrophysical sources the incident count rate at NuSTAR is smaller than the maximum throughput rate. However, even for modest activity on the Sun, the count

4.2: NuSTAR Instrument 74

et al., 2016). The maximum throughput of the electronics can dramatically diminish

the hard X-ray sensitivity of NuSTAR if there are bright sources on disk. The high count rate leads to large dead-time windows, lost photons, and a limited dynamic range.

For example, the presence of very bright sources in the field-of-view leads the NuS- TAR detectors to assume a problem, as was seen with the engineering tests on Septem- ber 2014 when a large X-ray flare was observed a few hours prior to the start of the NuSTAR observations. Near the flare location the observations mimicked cosmic ray interactions (many photons co-temporally arriving at different spatial locations), such

that these observations were vetoed by the electronics (Grefenstette et al.,2016), which

led to a 0% livetime. With more modest levels of activity from within the field-of-view— those equivalent to GOES B-class—leads to livetimes of a few percent, which increases to tens-of-percent for GOES A-class. With decreasing activity, an active region free, quiet Sun observation will result in livetimes of up to 100%.

For livetimes < 100%, the effective exposure (calculated as the livetime fraction multiplied by the dwell time) is smaller than the dwell time, and these limited livetimes limit the spectral dynamic range as a steep drop-off to higher energies is expected.

Furthermore, because of ghost-rays (§4.2.1.2), pointing NuSTAR to a quieter region of

the Sun would lead to the brighter regions outside the field of view still being detected,

and could dominate the limited throughput (See Figure 4.7). Ideal observations with

NuSTAR will be obtained near solar minimum when there are minimal X-ray sources outside the field-of-view.

4.2.2.2 GRADE

For those events that are recorded, each photon event is given a GRADE—an integer between 0 and 31. The GRADE is based on the morphology of triggered pixels within a 3 × 3 grid centred on a pixel with the highest deposited energy. GRADE 0 indicates a single pixel hit, but higher grades mean the neighbouring pixels recorded a detection

within the 8 µs readout time. Figure 4.9 shows morphology of pixel interactions for

the most common grades that are assigned. Grades 21 − 24 give the clearest example of a second photon during this time, instead of a single photon being detected across multiple pixels, and so can be used to help determine the amount of pileup, as will be

4.2: NuSTAR Instrument 75

Figure 4.9: The 3 × 3 pixel morphology of GRADEs 0 − 26. These images are extracted from the NuSTAR User’s Guide at the HEASARC.

4.2.2.3 Pileup

With high (incident) count rates the effects of pileup on the observed spectra need to

be considered. The term “pileup” (Datlowe, 1975) refers to the phenomena of two (or

more) incident photons being read out as a single photon with an energy that is the sum of these photon energies. This generally occurs when photons are incident at a higher rate than the readout time. While pileup can still occur with pixellated detectors, it is less problematic than with previous methods of detection; for a discussion of pileup

with RHESSI’s nine RMCs, seeSmith et al.(2002). For NuSTAR observations, pileup

can occur as the result of two scenarios (as discussed in Grefenstette et al., 2016):

1. Two photons hit the same pixel and are assumed, by the on-board electronics, to be a single-pixel event.

2. Two photons hit adjacent pixels (GRADE > 0; see § 4.2.2.2), are identified as a

“split-pixel” event, and are combined in the post-processing.

In order to further understand the potential effects of pileup, specifically (1), on

solar observations,Grefenstette et al.(2016) analysed the NuSTAR spectra of Scorpius

X-1—a bright source with a steep thermal-type spectrum. During the observations with NuSTAR, Scorpius X-1 was observed to have count rates in its flaring state of

4.3: Data Processing 76

but these observations ledGrefenstette et al.(2016) to conclude that one would expect

< 0.05% of events to be piled up in observations of the Sun.

In terms of case (2), the solution is straight forward to implement. As will be

discussed in Chapter 5, events assigned with GRADE > 0 are ignored.

4.2.3

Astrometric Alignment

Usually, where NuSTAR is pointing in the sky is determined by the instrument star

tracker (Camera Head Unit 4, CHU 4), mounted on the optics bench (see Figure 4.1)

in the direction of pointing. However, due to the bright Sun, this star tracker is

unusable and NuSTAR solar observations are obtained using the spacecraft science

mode (SCIENCE_SC, mode 06) (Grefenstette et al.,2016). The SCIENCE_SC mode

uses combinations of the other orthogonal star trackers located on the spacecraft bus (CHUs 1 − 3) to determine the pointing of the spacecraft, and source of a photon on the sky.

The combination of CHUs 1-3 are automatically determined given the orbital po- sition of the spacecraft and this varies over an observation. Although the pointing of the spacecraft is stable, the X-ray source location can be offset from its true location

by up to about 10. This is why mode 6 is not usually recommended for imaging of

astrophysical objects (Walton et al.,2016).

With solar observations there is no choice but to use this mode, but the true source locations can be found later by alignment to observations at other wavelengths, such as

Soft X-rays from Hinode/XRT or EUV from SDO/AIA (as performed inWright et al.,

2017, Chapter 5).

4.3

Data Processing

4.3.1

NuSTARDAS

The NuSTAR Data Analysis Software (NuSTARDAS4) as a part of HEASOFT is a

collection of modules dedicated to process the NuSTAR data to a scientific data product that can consist of energy spectra, event files, images, exposure maps, light curves, and

4

For more details see NuSTAR User’s Guide at the HEASARC, https://heasarc.gsfc.nasa. gov/docs/nustar/

4.3: Data Processing 77

response files. The NuSTARDAS processing routine, nupipeline, allows the user to run the relevant processing routines on Level-1 data in order and is organised in to three stages, as follows:

1. Data Calibration: This stage uses the calibration database (CALDB) to cali- brate the science event files. First, the relative alignment of the optics and focal

plane modules (separated by the 10 m mast, Figures 4.1, 4.2) is realised using

the laser meteorology system. Next, the attitude data obtained from the com-

binations of CHUs (§ 4.2.3) is processed, bad pixels and hot pixels are flagged,

and a GRADE (§ 4.2.2.2) is calculated for each 3 × 3 photon event. After energy

and gain correction, an interaction depth threshold is applied, and the detector

co-ordinates of each event are converted to sky co-ordinates (see Harp et al.,

2010, for details on the pointing reconstruction). The result of data calibration

is a Level-1a event file: a fits file of a list of detected X-rays with a variety of properties (such as energy channel, position on detector, GRADE, etc.)

2. Data Screening: screens the calibrated event files (1) to account for attitude, or- bital, and instrument parameters and event properties, returning Level 2 cleaned event files. This includes the removal of bad pixels, events with GRADE > 0, and data obtained during Earth occultation, slewing, and South Atlantic Anomaly passages, to name a few.

3. Product Extraction: The final stage is the calculation of high-level scientific products (e.g. energy spectra, response files, images, exposure maps). The energy spectra and response files for the chosen observation and configuration (e.g. time range, specific spatial region) can then be inputted to data analysis programs

such as XSPEC (Arnaud, 1996) and OSPEX (Schwartz et al., 2002) for X-ray

spectral fitting.

An additional step for solar observations is the conversion of the co-ordinates from right ascension and declination (R.A./Dec.) to helioprojective co-ordinates using

NASA’s Jet Propulsion Lab Horizons online ephemeris tool (Giorgini et al., 1996) as

described in (Grefenstette et al., 2016). This processing of the eventlist files can be

performed in Python or SSWIDL. These resulting eventlists can be spatially binned to produce images (again software in both Python and SSWIDL) so that they can be compared to solar observations at other wavelengths. These images can then be