Solar X-ray Monitor (XSM)

• Solar X-ray Monitor (XSM) is a soft X-ray spectrometer on Chandrayaan-2 that records disk-integrated solar spectra in the 1–15 keV band with high time and energy resolution for lunar elemental analysis and solar coronal studies.
• It employs a Silicon Drift Detector with Peltier cooling and automatic flux attenuation to maintain response stability across a wide solar dynamic range, even during intense flares.
• Data processed through the XSMDAS pipeline yield high-quality spectra and light curves, enabling precise plasma diagnostics, elemental-abundance studies, and detailed flare evolution analysis.

Solar X-ray Monitor (XSM) is the soft X-ray spectrometer on board the Chandrayaan-2 orbiter. It observes the Sun as a star and records disk-integrated solar spectra in the 1–15 keV band with 1 s cadence and energy resolution better than 180 eV at 5.9 keV. Its primary mission role is to provide the incident solar spectrum for the Chandrayaan-2 X-ray fluorescence experiment on the lunar surface, but the same measurements are also used for solar coronal spectroscopy, flare plasma diagnostics, microflare statistics, and elemental-abundance studies (Shanmugam et al., 2019, Mithun et al., 2020).

1. Mission role and instrument architecture

XSM was flown as part of the Chandrayaan-2 remote X-ray fluorescence experiment together with CLASS, the Chandrayaan-2 Large Area Soft X-ray Spectrometer. In that configuration, the solar spectrum measured by XSM provides the excitation input required to infer elemental abundances on the lunar surface from fluorescence lines. The solar data are also scientifically useful in their own right because the 1–15 keV band contains both continuum emission and diagnostically important line complexes from coronal plasma (Shanmugam et al., 2019).

The flight model consists of two mechanical units: a Sensor Package and a Processing Electronics Package. The Sensor Package houses the Silicon Drift Detector (SDD) with Peltier cooler, front-end electronics, high-voltage bias generator, and a three-position filter wheel. The Processing Electronics Package contains DC-DC converters, the Peltier controller, stepper-motor driver, and an FPGA board for event processing, ADC, data formatting, and spacecraft interface. The detector is a single-element SDD, operated with thermoelectric cooling, and the bore-sight is configured as a non-imaging, Sun-as-a-star view with a field of view of about $\pm 40^\circ$ (Shanmugam et al., 2019, Mithun et al., 2020).

The core performance parameters repeatedly reported for Chandrayaan-2 XSM are summarized below.

Parameter	Reported value	Source
Energy range	1–15 keV	(Shanmugam et al., 2019)
Spectral resolution	$\lesssim 180$ eV FWHM at 5.9 keV	(Mithun et al., 2020)
Spectrum cadence	1 s	(Shanmugam et al., 2019)
Light-curve cadence	100 ms in three bands	(Shanmugam et al., 2019)
Field of view	$\pm 40^\circ$	(Shanmugam et al., 2019)

The hardware was designed to maintain performance over a broad solar dynamic range. The instrument papers describe automatic flux attenuation with a Be filter during strong flares, together with on-board calibration capability using a $^{55}$Fe source. This design underpins the stated operating range from below GOES A-class levels up to intense flares without saturation (Shanmugam et al., 2019, Nama et al., 2023).

2. Calibration, response, and in-flight stability

XSM calibration is based on both ground characterization and in-flight verification. Ground calibration established the gain, offset, spectral redistribution, and effective area using radioactive lines, laboratory X-ray sources, and synchrotron beam-line measurements. The channel–energy relation was found to be linear, and the redistribution model includes a Gaussian core together with low-energy tails, escape features, and shelf components. The response used in analysis is factorized into an RMF and an ARF, following the standard forward-folding formalism (Mithun et al., 2020).

The instrument response is expressed in the form

$$C(E_{\rm obs})=\int A(E_{\rm true},\theta,\phi)\,R(E_{\rm obs},E_{\rm true})\,F_\odot(E_{\rm true})\,dE_{\rm true}+B(E_{\rm obs}),$$

where $A$ is the effective area, $R$ is the spectral redistribution, $F_\odot$ is the incident solar photon flux, and $B$ is the background. This same structure appears in later science analyses, where the measured count spectrum is unfolded through the RMF and ARF to recover plasma properties (Mithun et al., 2020, Nama et al., 2023).

In-flight performance was reported to match ground spectral performance. Six months of on-board $^{55}$Fe source measurements showed $\lesssim 180$0 eV constant and peak energy stable within $\lesssim 180$1 eV. Background measurements obtained when the Sun is occulted or outside the field of view are low enough that even sub-A1 solar fluxes remain well above background. XSM’s effective area also required an in-flight refinement: quiescent-Sun observations at varying Sun angles revealed an additional quadrant-dependent absorption in quadrant 3, modeled empirically as extra Be absorption; after correction, the residual uncertainty on relative $\lesssim 180$2 was reported as $\lesssim 180$3 (Mithun et al., 2020).

This calibration architecture is significant because the principal XSM science cases depend on small spectral differences: continuum slope for temperature, continuum normalization for emission measure, and line-to-continuum ratios for abundance work. The instrument papers and subsequent solar analyses therefore treat gain stability, background characterization, and response generation as essential rather than ancillary components of the measurement chain (Mithun et al., 2020, Mithun et al., 2020).

3. Data products and processing pipeline

The XSM ground segment is built around the XSM Data Analysis Software, XSMDAS. Raw Level-0 spacecraft packets are converted into Level-1 and then Level-2 FITS products, with associated PDS4 metadata. Level-2 outputs include gain-corrected spectra, light curves, Good Time Intervals (GTIs), and response files. The standard software modules include xsml1gen, xsmhkextract, xsmcalsa, xsmgtigen, xsmgenspec, xsmgenlc, xsmpds4gen, and xsmaddspec (Mithun et al., 2020).

Operationally, Level-1 event lists store detector pulse heights versus time. GTIs exclude intervals affected by occultation, Sun-off conditions, and instrument or geometry constraints. xsmgenspec produces the background-subtracted count spectrum, the ARF, and the RMF for each GTI, while xsmgenlc extracts count rates in user-defined energy bands. The resulting PHA, ARF, and RMF files are designed for use in XSPEC, ISIS, or OSPEX (Mithun et al., 2020, Nama et al., 2023).

For broad-band light curves, the daily 1–15 keV count rate is corrected by $\lesssim 180$4 to yield a disk-integrated photon rate. For spectral analysis, the count-to-photon relation is retained in forward-folded form rather than inverted directly. This is particularly important because XSM science cases often depend on weak line complexes in the 1.3–2.5 keV range and on multi-thermal continua extending toward higher energies (Nama et al., 2023, Mithun et al., 2022).

The pipeline structure also reflects the limitations of a disk-integrated instrument. Since XSM has no imaging capability, source isolation is frequently imposed through GTI selection and through contemporaneous contextual imaging from missions such as SDO/AIA, Hinode/XRT, and Hinode/EIS. That coupling between full-Sun spectroscopy and imaging recurs throughout the scientific literature using XSM data (Zanna et al., 2022, Vadawale et al., 2021).

4. Spectral modeling and plasma diagnostics

XSM spectral analysis is generally performed in XSPEC using custom CHIANTI-based thermal plasma models. Several studies use the local model chisoth, based on CHIANTI v10, while quiet-Sun and some flare analyses use CHIANTI v9.0.1. The photon model includes free-free, free-bound, two-photon continuum, and line emission from optically thin plasma; the model spectrum is then convolved with the instrument response (Nama et al., 2023, Vadawale et al., 2021).

Under the isothermal approximation, the emitted spectrum is written as

$\lesssim 180$5

with

$\lesssim 180$6

or, in related formulations,

$\lesssim 180$7

In practice, the continuum slope around 3–10 keV constrains $\lesssim 180$8, while the continuum normalization constrains $\lesssim 180$9. Absolute abundances are derived from resolved line complexes, principally Mg XI–XII, Al XIII, Si XIII–XIV, and S XV–XVI in the 1.3–8 keV range; at higher flare intensities, Fe line complexes also contribute (Nama et al., 2023, Mithun et al., 2022, Mondal et al., 2021).

The abundance analyses define the First Ionization Potential bias as

$\pm 40^\circ$0

Photospheric reference abundances are taken from Asplund et al. (2009), while other elements may be fixed to reference coronal values when they are not directly constrained by XSM. Statistical errors on fitted abundances are reported as typically 10–30%, with additional systematic errors from response functions and atomic data at the $\pm 40^\circ$1–20% level (Nama et al., 2023).

XSM observations also motivated departures from the isothermal approximation. For A-class flares, a single-temperature component was reported to suffice in one study, whereas for the impulsive phases of stronger C-class events, isothermal fits were inconsistent with the observed spectra and double-peaked DEM distributions were required. The DEM formalism was implemented with isothermal, two-temperature, Gaussian, and double-Gaussian parameterizations, solved by $\pm 40^\circ$2 minimization or MCMC depending on the study (Nama et al., 2023, Mithun et al., 2022).

5. Quiet Sun, active regions, and flare physics

During the exceptionally quiet 2019–20 solar minimum, XSM enabled direct spectroscopy of the quiescent corona in the absence of active regions. One analysis selected 73 days of quiet-Sun integrations and found a nearly constant temperature of about 2 MK and an emission measure of about $\pm 40^\circ$3. The abundances of Mg, Al, and Si corresponded to a FIP bias of $\pm 40^\circ$4, lower than the usual active-region value, and the paper interpreted the emission as dominated by X-ray Bright Points (Vadawale et al., 2021).

The same low-background capability extended into the microflare regime. Over 76 days of the deep solar minimum, XSM detected 98 microflares with peak flux below GOES A-level. For the 74 events with EUV counterparts in AIA 94 Å, fitted temperatures ranged from 3 MK to 7.5 MK, emission measures from $\pm 40^\circ$5 to $\pm 40^\circ$6, and thermal energies from $\pm 40^\circ$7 to $\pm 40^\circ$8 erg. Their differential frequency distribution followed a power law with $\pm 40^\circ$9 above the detection threshold (Vadawale et al., 2021).

In active-region cores, XSM abundance measurements showed persistent low-FIP enhancement. For three active regions observed under conditions where a single AR dominated the full-disk signal, the average values of temperature and emission measure were $^{55}$0 MK and $^{55}$1, respectively. The abstract reports average FIP bias of $^{55}$2 for Mg and Si, $^{55}$3 for S, and higher than 3 for Al, with the FIP bias established within $^{55}$4 hours of emergence and remaining almost constant thereafter (Mondal et al., 2023). A coordinated XSM–EIS–AIA–XRT study of AR 12759 similarly found that the quiescent AR core emission and abundances did not change significantly over time, and that frequent microflares did not affect the abundances of the quiescent AR core (Zanna et al., 2022).

Flare spectroscopy with XSM emphasized both thermal structure and composition evolution. In nine isolated B-class flares, the abundances of Mg, Al, Si, and S were found to decrease toward their photospheric values during the peak phase and to return quickly to pre-flare coronal values during decay; the proposed interpretation was chromospheric evaporation followed by rapid restoration of coronal FIP bias (Mondal et al., 2021). A-class flares showed a related pattern: lower A-flares exhibited an intermediate FIP bias, higher A-flares had FIP bias near unity, and time-resolved fits showed abundances dropping from coronal to photospheric values in the impulsive phase before rapidly returning in decay (Nama et al., 2023). For representative C-class flares, XSM spectra during the impulsive phase required double-peaked DEMs, with a cooler component at $^{55}$5–8 MK and a hotter component at $^{55}$6–18 MK; the associated abundance evolution again moved from near-coronal toward near-photospheric values during rise and back to coronal values in decay (Mithun et al., 2022).

These results define one of the central physical themes in the XSM literature: direct tracking of the coupling between thermal evolution, chromospheric evaporation, and elemental fractionation in weak-to-moderate flares. At the same time, the rapid abundance recovery after impulsive phases is repeatedly identified as difficult to explain, so the observational result is robust while the mechanism remains open (Nama et al., 2023, Mondal et al., 2021).

6. Statistical products, interpretation, and limitations

A three-year XSM flare catalog extended the instrument’s role from case studies to uniform flare statistics. Using Level-2 light curves in 1.55–12.4 keV between 2019 September 12 and 2022 November 4, the catalog identified 6266 solar flares, including 1469 type A flares, 213 sub-A flares, and 1330 A-class flares. The background-subtracted peak-flux distribution yielded $^{55}$7 for all flares, $^{55}$8 for type B, and $^{55}$9 for type A. The catalog also found a clear bimodality in the ratio $$C(E_{\rm obs})=\int A(E_{\rm true},\theta,\phi)\,R(E_{\rm obs},E_{\rm true})\,F_\odot(E_{\rm true})\,dE_{\rm true}+B(E_{\rm obs}),$$0, with a valley at $$C(E_{\rm obs})=\int A(E_{\rm true},\theta,\phi)\,R(E_{\rm obs},E_{\rm true})\,F_\odot(E_{\rm true})\,dE_{\rm true}+B(E_{\rm obs}),$$1, separating gradual type A from impulsive type B morphology (Valluvan et al., 2023).

XSM data have also been used for statistical coronal-heating inference. A two-step inversion applied to quiet-Sun light curves in three soft-X-ray passbands found impulsive events at a frequency of approximately 25 events per minute with a typical lifetime of approximately 10 minutes. The inferred event energies lay in the range $$C(E_{\rm obs})=\int A(E_{\rm true},\theta,\phi)\,R(E_{\rm obs},E_{\rm true})\,F_\odot(E_{\rm true})\,dE_{\rm true}+B(E_{\rm obs}),$$2–$$C(E_{\rm obs})=\int A(E_{\rm true},\theta,\phi)\,R(E_{\rm obs},E_{\rm true})\,F_\odot(E_{\rm true})\,dE_{\rm true}+B(E_{\rm obs}),$$3 erg, with a typical radiative loss of about $$C(E_{\rm obs})=\int A(E_{\rm true},\theta,\phi)\,R(E_{\rm obs},E_{\rm true})\,F_\odot(E_{\rm true})\,dE_{\rm true}+B(E_{\rm obs}),$$4 in 1–2.3 keV (Upendran et al., 2022). This suggests that XSM’s cadence and background stability are sufficient not only for individual flare diagnostics but also for unresolved-event statistics.

Several methodological caveats recur in the literature. XSM is non-imaging, so localization, volume estimation, and separation of simultaneous structures require contextual EUV or X-ray imaging. One multi-wavelength study showed that simple XRT filter-ratio isothermal diagnostics can underestimate peak temperatures in multi-thermal plasma, whereas forward modeling from AIA DEMs reproduced the observed XSM spectrum with residuals below 10% (Zanna et al., 2022). Instrument papers also note that spectra below about 1.3 keV were often excluded because of response uncertainties, and that background modeling during geomagnetic-tail passages and high latitudes required further work (Mithun et al., 2020).

Future directions identified in the XSM literature include extension of low-energy response below 1 keV for direct oxygen abundance work, cross-calibration with MaGIXS, DAXSS on INSPIRESat-1, and SoLEXS on Aditya-L1, and joint campaigns with Solar Orbiter/STIX and Aditya-L1/HEL1OS for broader-band spectroscopy (Mondal et al., 2023, Mithun et al., 2020). In that sense, XSM occupies a dual role: an operational irradiance monitor for lunar X-ray fluorescence and a precision solar spectrometer for coronal composition, thermal structure, and flare evolution.