8. Resolve Observations of Bright Sources

Bright sources, here defined as those that produce $\gtrsim 100$ counts s $^{-1}$ in the Resolve bandpass, are important XRISM targets because the high count rate enables precise measurements of variability in emission and absorption lines, as well as detecting weak features at high significance. The X-ray flux that produces a count rate exceeding 100 counts s $^{-1}$ depends on the spectrum, with softer spectra producing greater count rates at a fixed energy, but as a rule of thumb this chapter applies to source fluxes exceeding $0.3-10$

keV $F_{\rm X} > 5\times 10^{-9}$ erg s $^{-1}$ cm $^{-2}$ . This flux is equivalent to about 500 mCrab, where the Crab Nebula X-ray flux is defined as $2-10$

keV $F_{\rm X} = 2.4\times 10^{-8}$ erg s $^{-1}$ cm $^{-2}$ (Willingale et al., 2001). With the gate valve closed, only sources with $F_{\rm X} > 10^{-8}$ erg s $^{-1}$ cm $^{-2}$ are expected to require mitigation at the proposal stage. Almost all persistent “bright” sources are well-known Galactic compact objects (see https://heasarc.gsfc.nasa.gov/docs/heasarc/headates/brightest.html).

Above this flux, the number of source events (especially high-resolution events) no longer depends linearly on the source flux and exposure time. High count rates can make low-resolution events dominant, saturate the onboard event processor, degrade the energy resolution due to electrical cross-talk, and change the gain (Mizumoto et al. , 2025a). The net impact is fewer clean, high-resolution events than expected for the exposure time. In this chapter, we briefly introduce the challenges posed by very bright sources, then describe observing strategies to maximize the high-resolution event rate, and conclude with general advice on proposing and analyzing such sources. Since the Crab Nebula is the only current extended source with a count rate that falls in this regime, observing strategies assume point-like sources.

Any source that can produce $\gtrsim 100$ counts s $^{-1}$ in Resolve will be extremely piled-up in Xtend, for which a “bright” source is about thirty times dimmer ( $0.3-10$

keV $F_X \sim 5\times 10^{-11}$ erg s $^{-1}$ cm $^{-2}$ ). Chapter 6 describes the impact of high count rates on event detection (pile-up and out-of-time events) and the observing modes available to mitigate issues. For almost any bright source, the optimal Xtend observing mode is a windowed burst mode.

8.1 Challenge: High-Resolution Event Rates

Observing proposals typically require a certain signal-to-noise ratio to carry out the proposed measurements. Given a source flux, this translates to a required exposure time. While bright sources have, by definition, large fluxes, when the flux is too high the high-resolution yield is small (which we denote as Hp+Mp events following the convention of Section 5.3.3). Section 5.3 describes how events are detected, and Section 5.3.3 describes how the Hp+Mp yield in a single pixel depends on the count rate. The Hp+Mp rate increases with count rate until the average time delay between arriving photons becomes shorter than the length of the high-resolution optimal filtering template. At higher count rates, the fraction of Hp+Mp events monotonically decreases. Almost all bright sources are point-like, so the events are distributed unevenly across pixels. The total array Hp+Mp rate, $S_{\text{arr,Hp+Mp}}$ , depends on the total source flux, the shape of the PSF and pointing center relative to the center of the Resolve array, and the source spectrum. $S_{\text{arr,Hp+Mp}}$ reaches a maximum of $\approx$ 100 counts s $^{-1}$ for an on-axis point source with a Hitomi-like PSF (half-power diameter of 1.2 $^{\prime}$ ) at a total incident rate of 1000 counts s $^{-1}$ on the array, but this theoretical maximum far exceeds the ability to process events (see next section).

8.2 Challenge: Event Loss

While the maximum Hp+Mp rate for a point source occurs at a total count rate of $\sim$ 1000 counts s $^{-1}$ , the Pulse-Shape Processor (PSP) can only process about 200 counts s $^{-1}$ for an on-axis source (Mizumoto et al. , 2025a). The PSP houses four CPUs, one for each quadrant of the Resolve array, so the limit is actually 50 counts s $^{-1}$ per quadrant, with the 200 counts s $^{-1}$ assuming an even distribution of counts between the quadrants. Above this rate, some events are not processed by the PSP and are instead recorded as “lost.”

Here we summarize the PSP operation that leads to event loss. The signal from each pixel is digitized and events are identified as pulses in a field-programmable gate array (FPGA) board. When an event is detected, the time series containing the event data (whose length depends on the event grade; Section 5.3.3) is stored in a memory buffer and the record of the event is passed to one of the PSP computers, which maintains a list of events waiting to be processed. Events are processed by retrieving the event data from the buffer and applying optimal filtering (cross correlation with an optimal template) to measure the event energy and search recursively for secondary events. The pulse height, arrival time, and other data are then sent to the data recorder, the buffer memory occupied by that event is freed, and the computer retrieves the next event. When events fill the buffer faster than the PSP can process them, to make space for new events the entire buffer is cleared and those events are recorded as lost. Because the events are detected before they are sent to the PSP, the events are not totally lost, but their energies are not measured by the PSP, and the FPGA count rate is a lower limit (as no secondary event search is performed for lost events). Event loss is independent of event energy or grade.

We note that Resolve does not “pile up” in the same way as CCD imaging spectrometers, but an analogous effect occurs when two events arrive within 2 ms of each other and are erroneously treated as a single event. Most such events are identifiable via anomalous RISE_TIME and SLOPE_DIFFER behavior and are screened out, but some will be misidentified as clean events. At high count rates, several percent of the events can be lost this way with the gate valve closed (Mizumoto et al. , 2025a).

8.3 Challenge: Minimizing Cross-talk

Electrical cross-talk can degrade the energy resolution (Section 5.3.6). Cross-talk occurs because of capacitative coupling between adjacent wires such that a voltage pulse in one wire (the “parent”) induces a smaller “child” pulse in neighboring wires (there is also thermal cross-talk, but it is an order of magnitude weaker). The amplitude of child pulses is 0.6% of the parent for neighboring wires and $<$

0.1% for next-nearest wires. Due to the wiring map of the array, child pulses are not necessarily induced in physically adjacent pixels (Figure 8.1). Most pixels produce two child pulses per parent, and several produce only one.

Because of their small amplitude relative to the event detection threshold, most child pulses are not identified as events. Instead, they distort the signal. If a cross-talk child pulse coincides (within about 10 ms) with the pulse from a real X-ray, this distortion leads to an error in the energy measured via optimal filtering. Such unhappy coincidences increase with count rate, and since the errors can be positive or negative cross-talk effectively degrades (broadens) the energy resolution. The magnitude of the broadening varies from pixel to pixel, so the effective full-array broadening is a weighted average.

The impact of cross-talk on scientific analysis depends on the spectrum and the goal. A hard spectrum at a very high count rate will produce child pulses with larger average amplitudes than a soft spectrum at the same rate, leading to larger errors on the energy. Likewise, if a line of interest falls at 1 keV the fractional error in the velocity resolution will be worse than at 6 keV. The effect can be calculated exactly as a function of count rate for a monochromatic source, but for a more physically motivated spectrum we must calculate it statistically. Figure 8.2 shows the impact of cross-talk for a 4 Crab (2-10 keV $F_X \sim 10^{-7}$ erg s $^{-1}$ cm $^{-2}$ ), on-axis point source with a Crab-like spectrum with no filters. The left panel shows the broadening and centroid shift resulting from increased cross-talk contamination for an example Fe K $\alpha$ line. The right panel shows the average energy resolution (starting from a fiducial 5 eV resolution) in each pixel for this source (note that the most strongly affected pixels are at the array edge but are electrical neighbors of the central four). More examples of the impact of cross-talk on energy resolution are given for simulated spectra in Mizumoto et al. (2025a).

With the gate valve closed, cross-talk contamination can be mitigated (nearly eliminated) by ignoring events in electrically neighboring pixels that occur within a coincidence window. The Resolve pipeline software automatically flags (but does not exclude) such events, allowing users to filter the spectrum by STATUS flags. At very high count rates, this filtering can exclude a large fraction of events (although users may only need to apply the filtering to a small subset of pixels), so proposers should consider mitigation strategies prior to observing. With the gate valve closed, very few sources are bright enough for filtering to remove a large fraction of events.

Finally, it is worth noting that in bursty sources (i.e., those with sharp variations within a single observation) the spectral resolution may degrade during a particularly bright burst. Observers interpreting line shifts and broadening during a burst must account for cross-talk.

Note: The quantitative estimates of cross-talk degradation presented here are based on a representative pair of pixels from the Hitomi Soft X-ray Spectrometer and Resolve ground testing. Cross-talk impact can be non-uniform, as it depends on the size of the parent pulse in volts per eV, the strength of the coupling, the interaction of the cross-talk pulse shape with the unique digital filter of the parent pixel, and the gain scale of the parent pixel. Modeling using in-flight Resolve data is ongoing.

**Figure 8.1:** Electrical cross-talk “child” pulses occur in electrically adjacent pixels, so the cross-talk distribution does not follow the shape of the PSF. Left: Resolve pixel map showing electrically neighboring pixels. A parent pulse in pixel 18 (blue) will produce a child pulse in pixel 19 (light blue), but not in pixel 17 because it is in a different and electrically isolated quadrant. Likewise, a parent pulse in pixel 31 (orange) will produce child pulses in both pixels 30 and 32. Right: Cross-talk pulses (blue) have a shape based on the time derivative of the parent pulse (red) and a much smaller signal, with a peak amplitude of 0.6% of the pulse height. The child pulses are superimposed on the data stream in their pixels; when a child pulse in pixel 19, induced by a parent pulse in pixel 18, occurs around the same time as a parent pulse in pixel 19, the pulse shape is distorted. This leads to an erroneous energy measurement.
$\begin{figure}\centering \includegraphics[width=1\textwidth]{Figures_Bright_Source/crosstalk1.pdf} \end{figure}$

**Figure 8.2:** Left: Increasing contamination by cross-talk child pulses both broadens lines and shifts their centroids. At high count rates, this can significantly alter the energy resolution in individual pixels, as shown here for an example Fe K $\alpha$ line. Right: As an example, this Resolve pixel map shows the energy resolution (i.e., broadening) in each pixel when starting from $\Delta E$ = 5 eV and observing a source four times brighter than the Crab Nebula at the array center. The four exterior pixels with the worst resolution are electrically adjacent to the central four pixels. Note that the map is not weighted by the event rate or grade: despite the better energy resolution in the central pixels, there are hardly any Hp+Mp events from those pixels.
$\begin{figure}\centering \includegraphics[width=1\textwidth]{Figures_Bright_Source/crosstalk2_gvc.pdf} \end{figure}$

8.4 Challenge: Energy scale shift

Energy flux from bright sources can lead to a systematic negative shift ( $\sim$ 1 eV) in the measured energy of incident X-rays (Mizumoto et al. , 2025a). The gain, used to define the energy scale for measured pulse heights, is a function of pixel temperature (which changes with time) and is tracked during Resolve observations. The detector frame, which serves as a heat sink for the detector pixels, is locally heated by incoming photons. For large energy flux, the pixel temperatures depart from the fiducial value used to calculate the energy scale so that photon energies measured from these pixels will have a negative energy offset.

Figure 8.3 shows the energy offset as a function of the total incoming X-ray energy, defined as the product of the incoming rate and the average photon energy. The plot includes results from both ground-based tests (Mizumoto et al. , 2025a) and in-flight measurements using the Crab Nebula (Mizumoto et al. , 2025b). Although there is considerable scatter in the data, these measurements can be used to estimate the energy shift. For an incoming rate of 10–15 counts s $^{-1}$ pix $^{-1}$ and an average photon energy of 5.3 keV (as observed in the central four pixels from the GX 13 $+$

1 observation during the Performance Verification phase), the energy flux is $\sim$ 50–80 keV s $^{-1}$ pix $^{-1}$ and we expect an offset of about $-1$

eV. Because of the PSF pattern, the energy shift varies across the array.

**Figure 8.3:** Energy offset versus incoming count rate times the average photon energy (Mizumoto et al. , 2025b). As the horizontal axis increases, the thermal input from the incoming photons gets larger. The different color show different offset positions of the Crab nebula observation, while the gray shows the ground test results (Mizumoto et al. , 2025a).
$\begin{figure}\centering \includegraphics[clip, trim=1cm 8cm 1cm 7cm, width=1\textwidth]{Figures_Bright_Source/cr_offset_compare.pdf} \end{figure}$

8.5 Observing Strategies: Filters and Off-Axis Pointing

Typically, observers should aim to maximize the “clean” Hp+Mp rate (i.e., events minimally affected by cross-talk or gain shift), although the extent to which these effects matter depends on the science goals. In the following section we briefly discuss analysis strategies following an observation. Degradation of energy resolution due to electrical cross-talk becomes relevant above 0.3-10 keV $F_{\rm X} \gtrsim 5\times 10^{-9}$ erg s $^{-1}$ cm $^{-2}$ (gate-valve closed). Event loss begins to occur around the same time and becomes important above $F_{\rm X} \gtrsim 2\times 10^{-8}$ erg s $^{-1}$ cm $^{-2}$ .

Above these thresholds, maximizing the clean Hp+Mp rate is achieved by reducing the incident count rate relative to an on-axis point source by observing through a filter (Figure 8.4), off-axis pointing, or both. The neutral density filter reduces the count rate at every energy by a factor of about four, while the Be filter removes most photons below $E < 2$

keV. The Be filter is not useful with the gate valve closed, as the gate valve has a beryllium window thicker than the Be filter.

Off-axis pointing causes more focused X-rays to fall off the chip (thereby reducing the count rate) and can also be used to concentrate low-resolution events and their cross-talk signals in one sacrificial quadrant. Figure 8.5 shows the results for a Crab-like point source located at the quadrant opposite the calibration pixel (the quadrant with the calibration pixel should not be used so as not to lose $^{55}$ Fe signal). The upper right quadrant is dominated by low-resolution events and contributes about 10% of the Hp+Mp events, which also have average energy resolutions degraded by 0.1-2.5 eV. However, the other three quadrants yield 55 counts s $^{-1}$ with an expected energy resolution within 0.1 eV of the fiducial 5 eV value. Note: The PSF wings have sharp edges and the distribution of photons over pixels near the edges, based on a ray race incorporating ground measurements, is not precisely known. Figure 8.5 does not have high fidelity and is shown as an example.

Table 8.1 illustrates how the optimal configuration (in bold) changes with increasing count rate for a sample spectrum from a point source. With the gate valve closed, almost all sources can be observed on-axis without a filter. For sources brighter than 3 Crab, the ND filter becomes optimal; at 10 Crab, off-axis pointing is also necessary. The numbers in this table are only for the sake of illustration, but the basic strategy is to first try a filter and then, if necessary, consider pointing off-axis. We have summarized general recommendations as a function of source brightness in Table 8.2.

**Table 8.1:** Resolve Count Rates
Flux	No filter			ND Filter			ND+Off-axis
(0.3-10 keV $10^{-8}$	Total	Hp+Mp	Clean	Total	Hp+Mp	Clean	Total	Hp+Mp	Clean
erg s $^{-1}$ cm $^{-2}$ )	(ph s $^{-1}$ )			(ph s $^{-1}$ )			(ph s $^{-1}$ )
0.5	35	30	15	10	10	5	10	10	5
1.0	70	45	30	20	15	5	20	15	10
2.0	140	60	50	30	30	15	30	25	20
3.0	210	70	50	50	35	15	50	35	25
4.0	280	70	50	70	45	30	60	40	25
5.0	350	80	45	90	50	30	80	40	30
6.0	420	85	40	100	50	45	100	40	25
7.0	490	85	30	120	60	45	110	50	25
8.0	560	80	25	140	60	45	130	50	25
9.0	630	80	25	160	65	50	150	50	25
10.	700	80	10	170	70	55	160	50	30
20.	1410	70	1	340	80	40	330	65	30
50.	3520	30	0	860	80	5	810	65	35
All values assume an on-axis source except for the “off-axis” set at a fiducial offset of 0.5 arcmin offset in both DETX and DETY. “Clean” events are those H+Mp events whose average energy resolution is within 2% of a fiducial 5 eV resolution. Bold text indicates the optimal rate and thus observing configuration. The input spectrum is a $\Gamma=2$ power law with photoelectric absorption from $10^{21}$ cm $^{-2}$ of foreground atomic gas. Exact values are sensitive to the spectrum, structure in the PSF wings, etc. This table is for illustration only.

To estimate the count rate for different filters, proposers should use the spectral responses provided with a simulated spectrum (e.g., via WebPIMMS: https://heasarc.gsfc.nasa.gov/cgi-bin/Tools/w3pimms/w3pimms.pl). On-axis, point-source ARFs are sufficient for this purpose when proposing; there is a small ( $<10$

%) decline in effective area for off-axis pointing due to vignetting, but this does not change the optimal strategy. Note that the total “clean” Hp+Mp rate cannot be estimated from the spectral response alone but requires knowing the count rate in each pixel (e.g., from heasim) and also the incident spectrum (as spectral hardness affects cross-talk and the energy flux at a given count rate). Proposers should then estimate the sensitivity of their scientific goals to small changes in energy resolution or scale. In the examples above, we used information from ground and on-orbit measurements to estimate the impact of cross-talk or gain shift on the energy resolution and scale, but the true values depend on the incident spectrum and will not be known a priori. If the goal is to measure variable line shifts, broadening in the Fe-K lines at the tens of km s $^{-1}$ level, or velocity differences between barely resolved absorption lines, proposers should plan to apply the most aggressive event screening and other analysis techniques on the ground, and may wish to pursue more aggressive mitigation in the observing setup and/or request more exposure time to account for the screening. We note that measurements in this regime are also sensitive to calibration uncertainty. On the other hand, if an effective resolution of, for example, 5.2 eV does not threaten the science, proposers may wish to maximize the total Hp+Mp count rate and live with the impacts. Table 8.1 can be used as a guide for proposing to maximize the total Hp+Mp rate or the clean Hp+Mp rate.

**Figure 8.4:** Resolve effective area curves with the gate valve closed for no filter (black), the Be filter (red), and the neutral-density filter (blue). The neutral-density filter reduces the count rate by about a factor of four across the bandpass. For filter transmission curves see Figure 5.13. The Be filter is optimized for suppressing (continuum) events at low energy in favor of preserving high-resolution events in the Fe-K complex.
$\includegraphics[width=0.6\textwidth]{Figures_Resolve/resolve_effective_area_filters_xlog_CVC.pdf}$

**Figure 8.5:** These six plots show a mock image (top left), raw incident count rate (top center), processed Hp+Mp rate (top right), cross-talk child pulse rate (bottom left), effective spectral resolution (bottom center), and centroid shift (bottom right) in each pixel for a $10^{-7}$ erg s $^{-1}$ cm $^{-2}$ source observed no filters. The top right quadrant is sacrificed to maximize the Hp+Mp rate in the other three quadrants, as each quadrant is processed separately in the PSP.
$\begin{figure}\centering \includegraphics[width=0.95\textwidth]{Figures_Bright_Source/offaxis_gvc.pdf} \end{figure}$

8.6 After Observing

The challenges listed above, and several others, affect data analysis (for a primer on data analysis, see https://heasarc.gsfc.nasa.gov/docs/xrism/analysis/abc_guide/xrism_abc.pdf). It is beyond the scope of this document to provide analysis recipes for bright sources, but here we list effects to watch out for and briefly describe mitigation, if any.

Cross-talk and Energy Resolution

Gain Shift and Energy Scale

Pile-up

Spectral Responses

Secondly, when creating a response for Hp+Mp events the effective area is scaled by the fraction of such events (see Section 5.3.3). On-orbit calibration has found that, for most sources, low-resolution secondary events are not astronomical X-rays but instead background or additional signal produced by an already-detected X-ray. These events are thus ignored in calculating the effective area. However, this is not true for bright sources, where true X-ray events can dominate the other types. There is no definitive prescription to arrive at the correct effective area, but observers can bracket the flux by creating a response assuming all low-resolution secondary events are from the source and another assuming none of them are.

Thirdly, the electron-loss continuum can matter for bright sources. The response files encode the likelihood that an incident X-ray of a given energy is detected at that energy or any lower energy. If an X-ray is absorbed in the detector pixel but some of its energy is transferred to electrons that scatter out of the pixel, the measured energy will be lower. Since the scattering can remove anywhere from 0% to almost 100% of the X-ray energy, there is a low-level continuum. This continuum exists for all sources, but is most noticeable in bright sources: when using the “medium” or “large” redistribution matrix file for spectral fitting (see Data Reduction Guide), observers may notice that the soft energy band has poor residuals. The extra-large file that includes the electron-loss continuum makes spectral fitting take significantly longer and is primarily used as a final step to check or refine results rather than for initial fitting.

Fourthly, observations during the Performance Verification phase revealed that, in some point sources, the spectrum extracted from the outer ring of Resolve pixels has a modestly different broadband shape from the inner-ring spectrum. The difference does not appear to be explained by dust halos, nor is it clearly from an anomaly in the instrument. As with the other issues with response generation, until this issue is better understood users should expect systematic differences in flux between subarrays or in comparison with other X-ray instruments. This effect does not impact the measurement of line energy or broadening.

Dust Halos

8.7 Summary of Observing Recommendations

The optimal combination of offset pointing and/or filter depends on the source type and science goals. Here we provide basic guidelines for observing point sources of various fluxes with the goal of characterizing Fe K emission or absorption above 6 keV in a source otherwise characterized by an absorbed power law.

**Table 8.2:** Bright Source Observing Recommendations.
Flux	Recommendation	Clean Rate
(0.3-10 keV $10^{-8}$ erg s $^{-1}$ cm $^{-2}$ )		(ph s $^{-1}$ )
0.5-1	On axis, no filter	20-30
1-3	On-axis, no filter	40-55
3-10	On-axis, ND	40-60
10-30	On-axis (0-0.5 $^{\prime}$ ), ND	40-50
50	Off-axis (1.0 $^{\prime}$ ), ND	30
“Clean” events are those H+Mp events unaffected by cross-talk, gain shift, or pile-up. The input source is a point source with a a $\Gamma=2$ power law spectrum with photoelectric absorption from $10^{21}$ cm $^{-2}$ of foreground atomic gas. Exact values are sensitive to the spectrum, structure in the PSF wings, and off-axis position. At all fluxes, the appropriate Xtend mode is 1/8 windowburst, as the source always produces 500 counts s $^{-1}$ .