# KW-Sun: The Konus-Wind Solar Flare Database in Hard X-ray and Soft Gamma-ray
Ranges

A. L. Lysenko  Ioffe Institute, Polytekhnicheskaya, 26, St. Petersburg, 194021
– Russian Federation<EMAIL_ADDRESS>M. V. Ulanov  Ioffe
Institute, Polytekhnicheskaya, 26, St. Petersburg, 194021 – Russian Federation
A. A. Kuznetsov  Institute of Solar-Terrestrial Physics (ISZF), Lermontov st.,
126a, Irkutsk, 664033 – Russian Federation  G. D. Fleishman  New Jersey
Institute of Technology, University Heights, Newark, NJ 07102-1982 – USA  D.
D. Frederiks  Ioffe Institute, Polytekhnicheskaya, 26, St. Petersburg, 194021
– Russian Federation  L. K. Kashapova  Institute of Solar-Terrestrial Physics
(ISZF), Lermontov st., 126a, Irkutsk, 664033 – Russian Federation  Z. Ya.
Sokolova  Ioffe Institute, Polytekhnicheskaya, 26, St. Petersburg, 194021 –
Russian Federation  D. S. Svinkin  Ioffe Institute, Polytekhnicheskaya, 26,
St. Petersburg, 194021 – Russian Federation  A. E. Tsvetkova  Ioffe Institute,
Polytekhnicheskaya, 26, St. Petersburg, 194021 – Russian Federation

###### Abstract

We present a database of solar flares registered by the Konus-Wind instrument
during more than 27 years of operation, from 1994 November to now (2022 June).
The constantly updated database (hereafter KW-Sun) contains over 1000 events
detected in the instrument’s triggered mode and is accessible online at
http://www.ioffe.ru/LEA/kwsun/. For each flare, the database provides time-
resolved energy spectra in energy range from $\sim$20 keV to $\sim$15 MeV in
FITS format along with count rate light curves in three wide energy bands G1
($\sim$20–80 keV), G2 ($\sim$80–300 keV), and G3 ($\sim$300–1200 keV) with
high time resolution (down to 16 ms) in ASCII and IDL SAV formats. This
article focuses on the instrument capabilities in the context of solar
observations, the structure of the KW-Sun data and their intended usage. The
presented homogeneous data set obtained in the broad energy range with the
high temporal resolution during more than two full solar cycles is beneficial
for both statistical and case studies as well as a source of context data for
solar flare research.

Sun: flares - Sun: X-rays, gamma rays

##  1  Introduction

Hard X-ray (HXR) and gamma-ray emissions play a primary role in the
diagnostics of electron and ion acceleration in solar flares. They provide
information about the spectrum, energetics and abundances of accelerated
particles along with acceleration timescales (Fletcher et al., 2011).
Therefore hard X-ray/gamma-ray data with high temporal and energy resolutions
are of particular interest. The main mechanism responsible for HXR emission of
solar flares is the bremsstrahlung emission of accelerated electrons (see,
e.g., Holman et al., 2011, and references therein). Protons and heavier ions
accelerated during a flare produce gamma-ray lines and a continuum due to
numerous nuclear reactions (see, e.g., Vilmer et al., 2011, and references
therein).

Spectral, temporal, and spatial characteristics of HXR and gamma-ray emission
in solar flares are very diverse. The range of flare energies emitted in HXR
and gamma-ray ranges extends over many orders of magnitude, from $\sim$1026
erg (Crosby et al., 1993) to $\sim$1032 erg for large eruptive flares (Emslie
et al., 2012). Energy spectra of the so-called microflares (see, e.g., Hannah
et al., 2008) barely reach ten keV, the majority of solar flares demonstrate
emission up to several tens of keV, and in some flares the spectra extend to
GeV energies (see, e.g., Vestrand et al., 1999; Share et al., 2018). The flare
durations range from a fraction of a second for short impulsive bursts to
hours for gradual flares (Dennis, 1985; Crosby et al., 1993).

Despite several decades of research, many questions in solar flare physics are
still under discussion and require further development of instrumentation and
theory (Fletcher et al., 2011). Among these questions are the particular
mechanism (mechanisms) responsible for particle acceleration during
reconnection; the cause of energy partitioning between different flare
components including cases of 100 % efficiency of the electron acceleration
(Fleishman et al., 2022); whether the same acceleration mechanism is involved
in both short and long-duration HXR bursts, etc.

Due to the opacity of the Earth’s atmosphere to X-rays and gamma-rays, the
solar observations in these ranges became possible only with the beginning of
the exoatmospheric astronomy. Important results were obtained by low Earth
orbit space observatories, among them are OSO-5 (1969–1983), OSO-7
(1971-1974), Hinotori (1981-1991), Solar Maximum Mission (SMM, 1980-1989),
Yokhoh (Ogawara et al., 1991; Acton et al., 1992, 1991-2001), Reuven Ramaty
High Energy Solar Spectroscopic Imager (RHESSI, Lin et al., 2002, 2002-2018).
Since 1975 space telescopes on board the Geostationary Operational
Environmental Satellite (GOES) spacecraft series continuously monitor solar
soft X-ray emission in two broad energy channels providing the commonly
accepted X-ray classification of solar flares (classes A, B, C, M, and X)
according to their power. In 2020 February Solar Orbiter (SolO, Müller et al.,
2020) was launched into a heliocentric orbit with the purpose of investigating
solar and heliospheric physics using a payload of instruments designed for
both remote and in situ sensing. Among them is the Spectrometer/Telescope for
Imaging X-rays (STIX, Krucker et al., 2020) which allows solar imaging in a
4–150 keV range from an off-ecliptical positions. Although now there are no
solar-dedicated HXR and gamma-ray instruments operating in the near-Earth
space, several high-energy detectors provide solar spectra and light curves in
these ranges; e. g., Fermi-GBM (Meegan et al., 2009) and Fermi-LAT (Atwood et
al., 2009; Ajello et al., 2021) at low Earth orbit, which have operated since
2008, and Konus-Wind (Aptekar et al., 1995), which was launched in 1994 and
operates in interplanetary space. Solar data from these instruments are freely
accessible via the SolarSoft package111https://www.lmsal.com/solarsoft/,
Virtual Solar Observatory222 https://sdac.virtualsolar.org/cgi/search,
Interactive Multi-Instrument Database of Solar Flares and
Helioportal333https://sun.njit.edu/About/IMIDSFH.html, and other resources.

Here we present KW-Sun, a database of Konus-Wind solar flare observations that
cover more than two full solar cycles, from 1994 to nowadays. The main
objectives of Konus-Wind are the studies of high-energy transient emission
from distant astrophysical sources, such as cosmological gamma-ray bursts and
soft gamma-repeater (magnetar) flares. Although the systematic use of the
Konus-Wind data for solar physics applications began only recently, it has
already yielded important results (see a review by Lysenko et al., 2020). The
KW-Sun database has been developing since 2016, and many improvements in data
analysis and presentation have been made over the past few years.

Konus-Wind has a number of advantages for solar flare studies compared to
other instruments. Among them are: high temporal resolution in the triggered
mode, which allows one to reconstruct accelerated electron properties and
obtain constraints on the acceleration mechanism (Altyntsev et al., 2019;
Glesener & Fleishman, 2018); wide energy range that covers emission from
accelerated electrons and a good fraction of emission from nuclear reactions
of accelerated ions (eg., Lysenko et al., 2019, and references therein); and
last but not least the instrument location in the interplanetary space that
allows observations of the Sun in stable background conditions during
$\gtrsim$90 % of the time.

##  2 Konus-Wind

(a)

(b)

Figure 1:  Konus-Wind: (a) the location of Konus detectors S1 and S2 on the
spacecraft, ‘‘N’’ and ‘‘S’’ are the directions to the ecliptic poles and the
circular arrow indicates the spin direction of the spacecraft; (b) a scheme of
the Konus detector. The green arrow indicates the direction of solar emission.

Figure 2:  Temporal evolutions of Konus-Wind low-energy boundaries (left) and
high-energy boundaries (right) for detectors S1 and S2.

The Konus-Wind spectrometer was launched on board the NASA Wind spacecraft in
1994, November and operates till the present time (Wilson et al., 2021). Wind
is a spin stabilized spacecraft with spin axis aligned with ecliptic south and
a spin period of $\sim$3 s.444The deviation of the spacecraft spin axis from
the ecliptic north-south axis does not exceed 1∘ and the spin period varies
gradually in the interval 3.0-3.2 s. Since 2004, July, the spacecraft has been
in orbit around Lagrange point L1 at $\sim$5 light seconds from the Earth.
Operating in the interplanetary space the instrument sees the Sun 24 hours a
day and being far from the Earth radiation belts it has an exceptionally
stable background. The total fraction of time when the Konus-Wind data are
unavailable or contaminated by a high solar particle background does not
exceed 10 %.555Detailed information on the availability of Konus-Wind data for
a particular time can be obtained from the authors on request.

Konus-Wind consists of two cylindrical NaI(Tl) detectors S1 and S2 mounted on
the opposite sides of the rotationally stabilized spacecraft so that they
point to the southern and the northern ecliptical poles, respectively.
Consequently, the solar emission enters the detectors from the lateral side,
at an incident angle of $(90\pm 1)^{\circ}$ to the axis, and is registered in
both S1 and S2 (Figure 1). Due to Wind rotation, Konus-Wind suffers from
occultations from other instruments and the spacecraft structures that is
important for studies of flare time histories on millisecond timescales (see
details in Section 3.1).

The instrument operates in two modes: waiting and triggered. In the waiting
mode, the count rates in three wide energy bands G1 ($\sim$20–80 keV), G2
($\sim$80–300 keV), G3 ($\sim$300–1200 keV) are available with time resolution
of 2.944 s along with the count rate at energies $\gtrsim$10 MeV (the Z
channel). As the gamma-ray flux at the higher energies is low as compared to
the charged particle background, the Z-channel data can be used to monitor
flux variations of high-energy electrons and ions.

When the count rate in G2 exceeds a $\sim$9$\sigma$ threshold above the
background on one of two fixed timescales, 1 s or 140 ms, the instrument
switches into the triggered mode. Thus, rather spiky and spectrally hard (with
a significant emission above $\sim$80 keV) flares are recorded in the
triggered mode, while more gradual and soft events are typically registered in
the waiting mode only.

In the triggered mode, the count rate curves in G1, G2, and G3 are recorded
with high time resolution during an interval of 229 s. The time resolution
constitutes 2 ms for the time period from 0.512 s before the trigger to 0.512
s after the trigger time, 16 ms from 0.512 to 33.280 s after the trigger, 64
ms from 33.280 to 98.816 s after the trigger and 256 ms for the remaining
triggered time history. In the KW-Sun database we merge adjacent 2 ms bins
into 16 ms bins. Along with the high resolution triggered mode light curves,
the waiting mode record continues until $\sim$250 s after the trigger time.

Starting from the trigger time, 64 energy spectra are accumulated, over
pseudologarithmic energy scales, in two partially overlapping energy ranges
PHA1 (63 channels, $\sim$20–1200 keV) and PHA2 (60 channels, $\sim$0.35–15
MeV). For the first four spectra the accumulation time is fixed at 64 ms and
for the last eight spectra at 8.192 s. For spectra from 5 to 56, the
accumulation time varies between 256 ms and 8.192 s according to the count
rate in G2: with the intensity increase the accumulation time decreases. Thus,
the spectra may cover a time interval with the total duration varying from
79.104 s for very bright flares to 492 s for less intense events. After the
end of the trigger record, the measurements are stopped for $\sim$1 hour due
to the data readout, and only count rate in G2 is available with the time
resolution of 3.68 s.

As the triggered mode record is limited in time ($\sim$250 s for the time
profiles and $\leq$492 s for multichannel spectra) the record can stop before
the actual end of the flare for long-duration events.

For each flare, the instrument energy scale is calibrated using the 1460 keV
line of 40K. Temporal evolution of energy boundaries for S1 and S2 is shown in
Figure 2.

The energy resolution (FWHM/E=$\Delta$E/E) of Konus-Wind depends on energy and
constitute $\sim$20 % at 20 keV and $\sim$5 % at 2 MeV. The spectral
resolution of the detectors did not change significantly during the mission,
and the corresponding resolution loss is less than a factor of 1.5 as compared
to the ground-based calibrations (Svinkin et al., 2016).

For most flares, a standard Konus-Wind dead-time (DT) correction procedure
(i.e., a simple non-paralyzable dead-time correction in each of the
measurement bands, with a DT of a few microseconds for light curves and
$\sim$42 $\mu$s for multichannel spectra) provides a robust flux estimate.
Details of DT corrections for very intense flares are given in Section 3.3.2.

##  3 KW-Sun Database

Figure 3:  Annual rate of solar flares registered by Konus-Wind in the
triggered mode categorized by the GOES classes. Figure 4:  KW-Sun web
interface to the data for a specific flare, which displays the flare light
curves in G1, G2, G3 and provides links to the data. Horizontal dashed lines
represent background levels, and vertical dotted lines in the plot indicate
time intervals of multichannel spectrum accumulation.

By the time of writing, 2022 June, Konus-Wind registered $\sim$13,000 solar
flares in the waiting mode, 1065 flares in the triggered mode, and, among
them, 93 flares with emission at high, >1 MeV, energies. Annual statistics of
the triggered solar flares categorized according to their GOES classes is
presented in Figure 3.

To identify a detected event as a solar flare we check if (i) the net count
rates in both Konus detectors are close to each other, and, (ii) there is a
corresponding flare in the GOES event list666GOES event list is available via
https://hesperia.gsfc.nasa.gov/goes/ or a simultaneous flux increase in the
GOES soft X-ray sensor data in the 1–8 Å and 0.5–4.0 Å bands. In controversial
cases, we analyze spatial information from other telescopes.

As Konus-Wind doesn’t have an anticoincidence shield to filter out charged
particles we use either count rate curve in the Z-channel or data from 3DP
instrument (Lin et al., 1995) located at Wind spacecraft that provides
information on the fluxes of electrons in the 27–517 keV energy band and
protons in the 71–6800 keV energy band. The total fraction of the Konus-Wind
observation time contaminated by solar energetic particles is $\lesssim$8 %;
data obtained during these intervals are not included to the database.

Table 1:  Data types presented in KW-Sun repository.  Data type | Energy range | Time resolution | Record | Format
---|---|---|---|---
|  |  | durationaaAfter trigger time. |
Light curves | Three channels G1,G2,G3 | 16, 64, 256 msbbTriggered mode., |  $\sim$250 s | ASCII, IDL SAV
|  $\sim$20–1200 keV | 2.944 sccWaiting mode. |  |
Multichannel | First range: 63 channels, | 64 ms–8.192 s |  $\leq$492 s | FITS, OGIP standard
spectra | 20-1200 keV |  |  | PHA Type-II – spectral files
| Second range: 60 channels, |  |  | PHA Type-I – background files
| 350 keV–15 MeV |  |  | RMF, ARF – response files

Currently, the KW-Sun database contains light curves in the G1, G2, and G3
channels, multichannel spectra and detector response matrices for the flares
registered in the triggered mode. The data are described in the following
sections and summarized in Table 1. A detailed data description is also
available at the KW-Sun website777http://www.ioffe.ru/LEA/kwsun/kw-info.html.
An example of a web interface to the data for a specific flare is given in
Figure 4.

As Wind is located at distances up to $\sim$6 light seconds from Earth, for
every flare in addition to the Konus-Wind trigger time (UT) we provide the
trigger time corrected for the light propagation time from Wind to the Earth
center (geocenter time) – in order to compare Konus-Wind observations with
observations made by Earth-based or Earth-orbiting instruments. It should be
noted that the geocenter times may differ from UT at near-Earth spacecraft or
ground-based locations by up to $\sim$20 ms.

###  3.1 Light Curves

Figure 5:  Occultations in the Konus-Wind solar flare time profiles for S1
(left) and S2 (right) detectors. Gray shaded regions mark time intervals when
the Sun was occulted partially or fully by other instruments or the spacecraft
(S/C) structures. These intervals are removed from the KW-Sun light curves.

Light curves in the KW-Sun database are available in two formats: ASCII and
IDL SAV named as KWYYYYMMDD_TSSSSS.txt and KWYYYYMMDD_TSSSSS.sav respectively,
where YYYYMMDD is the flare date and SSSSS is the trigger time in seconds UT.
The data description is available at the top of the ASCII file and in the
‘‘description’’ section of the SAV file.

For each flare, the description contains the Konus-Wind trigger time ($t\\_kw$
variable in the IDL SAV file), the corresponding geocenter time ($t\\_earth$
variable in the IDL SAV file) and the calibrated energy boundaries of the G1,
G2 and G3 channels ($channels$ variable in the IDL SAV file).

The light curve data are stored in 11 columns in the ASCII file and in four
variables in the IDL SAV file: the start and end times of the time bin
(columns $t1$ and $t2$ in the ASCII file and $tkw$ variable in the IDL SAV),
relative to the trigger time; dead-time corrected count rates in G1, G2 and G3
(columns $G1$, $G2$, $G3$ in the ASCII file and $lc$ variable in the IDL SAV
file); the background-subtracted and dead-time corrected count rates (columns
$G1bgsub$, $G2bgsub$, $G3bgsub$ in the ASCII file and $lc\\_bgsub$ variable in
the IDL SAV file); and the count rate uncertanties at 1 $\sigma$ level
(columns $eG1$, $eG2$, $eG3$ in the ASCII file and $lc\\_err$ variable in the
IDL SAV file). The time history stored in the database includes several
hundred seconds of waiting mode data measured before the trigger time, which,
for gradually-rising flares, cover the beginning of the event (see Table 1).

Konus-Wind occultations by other instruments and the spacecraft parts appear
on millisecond timescales as dips in the light curves with a period of $\sim$3
s. Figure 5 illustrates occultation influence on flare time profiles. The
total durations of the dips per rotation period constitute $\sim$200 ms for S2
and $\sim$600 ms for S1. The occultation positions are calculated based on the
spacecraft spin phase data, and the appropriate time intervals are removed
from the light curves to ensure data reliability.

An example plot of Konus-Wind time profile in G1, G2 and G3 is shown in Figure
4 for the M5.5 class flare of 2022-01-20.

###  3.2 Multichannel Energy Spectra

For each flare, KW-Sun provides multichannel energy spectra in the two energy
ranges as PHA Type-II (PHA-II) FITS files, which contain multiple spectrum
datasets. The corresponding background spectra (see below) are available as
PHA Type-I (PHA-I) FITS files with a single dataset. The spectra are
complemented with detector response matrices (in RMF format) and an ancillary
response file (in ARF format). All these data conform OGIP
specifications888https://heasarc.gsfc.nasa.gov/docs/heasarc/ofwg/ofwg_intro.html.
The detailed description of spectral and response files can be found in
Appendix A. The response matrices are calculated using the Geant4 toolkit
(Agostinelli et al., 2003), for a parallel beam entering the detector at the
incident angle of 90∘ to its axis. The energy channel boundaries of the matrix
are adjusted to match the appropriate detector calibration.

Spectra for the first energy range ($\sim$20–1200 keV) are measured by two
redundant analyzers PHA1 and PHA3. By default KW-Sun contains data from PHA1
(the FITS files are named as KWYYYYMMDD_TSSSSS_1.pha), but in the cases of
data gaps in PHA1, we provide the data from PHA3 (files named as
KWYYYYMMDD_TSSSSS_3.pha). Data for the second energy range ($\sim$0.35–15 MeV)
are stored in files named as KWYYYYMMDD_TSSSSS_2.pha (see Table 1). Background
spectrum files for the first energy range are named as
KWYYYYMMDD_TSSSSS_1_bg.pha (or KWYYYYMMDD_TSSSSS_3_bg.pha if PHA3 is used, see
above) and for the second energy range as KWYYYYMMDD_TSSSSS_2_bg.pha. Response
matrices for the first energy range are named KWYYYYMMDD_TSSSSS_1.rmf
(KWYYYYMMDD_TSSSSS_3.rmf if PHA3 is used), for the second energy range –
KWYYYYMMDD_TSSSSS_2.rmf and an ancillary response file is named as
KWYYYYMMDD_TSSSSS.arf.

An example of the multichannel spectrum in the first (PHA1) and the second
(PHA2) energy ranges is plotted in Figure 6 for the X9.3 class flare that
occurred on 2017-09-06 and described in Lysenko et al. (2019).

For most solar flares ($\sim$90 %) data from the second, hard Konus-Wind
energy range do not contain useful information on the emission. However, when
data from both first (PHA1 or PHA3) and second (PHA2) ranges are used in the
analysis, it is necessary to exclude the spectral channels of the first band
in the overlapping range of energies (i.e. ignore channels 42-63 of PHA1 or
PHA3) due to two reasons. First, in this range PHA1 (PHA3) and PHA2 measure
the signals produced by the same detected photons (yet the PHA2 low-energy
discriminator is set at a 10x higher level), and, second, for a typical
steeply falling spectrum a smaller dead time fraction in PHA2 leads to better
signal-to-noise ratio of the counts in the overlapping energy range (see
Figure 6).

For short-duration solar flares, that end before the accumulation of the
multichannel spectra has finished, the background spectra are selected as
measured at the end of the trigger record. For the flares that last longer
than the triggered record the background is taken from a nearby triggered
event with similar background levels and close calibrations, and appropriate
uncertanties are added in quadrature to the Poisson errors of the background
counts (see Appendix. A)

A table containing time intervals covered by multichannel spectra for all
flares registered in the triggered mode is available at
http://www.ioffe.ru/LEA/kwsun/KW_spectrum_times.txt.

The KW-Sun spectral data are suitable for analysis with standard tools for
X-ray and gamma-ray spectral fitting, e.g., XSPEC (Arnaud, 1996) and OSPEX
(Schwartz et al., 2002; Tolbert & Schwartz, 2020), the latter is the part of
the SolarSoftWare package. We provide a Unix utility
SumKonusSpectra999http://www.ioffe.ru/LEA/kwsun/kw-info.html that extracts
(and merges, if needed) individual Konus-Wind spectra from the PHA-II format
files, which contain multiple multichannel spectra, to PHA-I format files
which contain data on a single spectrum. We recommend to use this utility when
working with XSPEC. The OSPEX package accepts input in PHA-II and allows
searching for flares in the KW-Sun database, downloading Konus-Wind spectral
data automatically and analyzing them using its common routines. Both XSPEC
and OSPEX load appropriate background and response files automatically when a
spectral PHA file is selected for the analysis.

Figure 6:  Example of background-subtracted multichannel energy spectrum for
the X9.3 class solar flare 2017-09-06 in the first energy range (PHA1, black)
and the second energy range (PHA2, red). The gray shaded area marks the
PHA1/PHA2 ovverlapping range.

###  3.3 Instrumental effects at high intensities

####  3.3.1 Integer overflows in low energy spectral channels

At high incident photon fluxes, integer overflows in low-energy channels of
PHA1 (PHA3) ($\leq$40 keV) may occur that result in underestimation of the
total count number, DT, and flux; and also in the spectrum distortion. We use
a special algorithm for the overflow corrections, but, for some very intense
flares, incorrect values in the first channels of PHA1 (PHA3) can appear
anyway. Thus, in the cases of bad fit residuals in the low-energy channels, it
is recommended to exclude these channels from the analysis.

####  3.3.2 Circuit saturation and pulse pileup effects101010The detailed
description of pile-up corrections for Konus-Wind data is given in Appendix of
Lysenko et al. (2019).

For intense events, the standard Konus-Wind dead-time correction procedure
(see Section 2) results in flux underestimation due to saturations in the
instrument’s signal shaper and counter logic circuits. Such saturations are
not negligible in PHA1 (PHA3) at incident photon rates per detector area $n$
exceeding $\sim$2$\times$104 photon s-1, and in the G1, G2, and G3 channel
counters at $n\gtrsim 2.5\times$105 photon s-1. At considerably higher photon
rates, the shape of the spectrum can also be distorted due to the pulse pileup
effect. We studied the influence of the pileup effect using Monte-Carlo
modeling and found that it becomes significant for PHA1 (PHA3) at $n\gtrsim
5\times$104 photon s-1.

For the events of moderate intensity (2$\times$104 photon s-1 < $n$ < 5
$\times$104 photon s-1, $\sim$15 % of all triggered flares) the flux in PHA1
(PHA3) can be underestimated, but this uncertainty does not exceed $\sim$10 %,
thus no additional corrections are needed. For high intensity events ($n$ >
5$\times$104 photon s-1, $\sim$8 % of all triggered flares) the corrections
are applied for both spectral shape and flux. In practice, the saturation
correction to PHA1 (PHA3) count rate can be estimated using dead-time
corrected counts in the overlapping PHA1/PHA2 energy range (see Section 3.2).
For the cases of additional dead-time corrections applied for high intensity
flares two columns with count and exposure uncertanties are added to the PHA
files. These systematic errors are taken into account automatically both in
XSPEC and OSPEX (see Appendix A). As the pileup correction procedure is time
consuming, corrected PHA1 (PHA3) data are available only for a subset of
intense flares, while for other flares spectral data for the 1st energy range
are not available from the database and the appropriate note is added to the
web page of the flare. In the latter case, we encourage the user to contact
the KW-Sun team by e-mail for pileup-corrected spectra of the event they are
interested in.

####  3.3.3 Uncertanties with energy calibration

One more issue for high-intensity events is the calibration uncertainties
resulting from the fact that the lines used in the calibration are faintly
distinguishable above the continuum. Although these uncertainties do not
exceed a few per cent, they may be important in the gamma-ray emission line
studies.

##  4 Summary and Conclusion

In this paper, we presented KW-Sun – the online catalog of solar flares
registered by Konus-Wind experiment in hard X-ray and soft gamma-ray ranges
during more than two full solar cycles. The database contains light curves
with high (down to 16 ms) time resolution and multichannel spectra in the wide
energy range ($\sim$20 keV–15 MeV) for more than a thousand solar flares
detected by the instrument in the triggered mode.

The main area of application of the Konus-Wind data for Solar physics is the
study of the emission from accelerated electrons and ions. The high time
resolution in the triggered mode allows to examine properties of nonthermal
electrons on a subsecond timescales which is crucial for the research of the
acceleration mechanisms during magnetic reconnection. Other advantages of
Konus-Wind for solar flare stuies are the absence of the Earth occultations
and extremely stable background conditions due to its location in the
interplanetary space. The presented homogeneous data set can be used for both
statistical and case studies of solar flares. Now with the beginning of a new
solar cycle, this may be especially in demand as there is no solar-dedicated
instrument in hard X-ray range near the Earth.

KW-Sun database is a work in progress, data on new flares are added as they
become available. The major ‘‘to do task’’ is to extend KW-Sun with numerous
solar flares registered in the waiting mode and to provide response matrices
for 3-channel time history data, which will allow spectral fitting of Konus-
Wind G1, G2, and G3 data with simple spectral models at fine time scales.
Future enhancements of KW-Sun will be available via the database web site at
Ioffe121212http://www.ioffe.ru/LEA/kwsun/.

We thank Prof. A. K. Tolbert for her help with incorporating Konus-Wind data
in OSPEX package. G.D.F. was supported in part by NSF grant AGS-2121632 and
NASA grant 80NSSC19K0068 to New Jersey Institute of Technology.

##  Appendix A  Structure of FITS files in OGIP stardard

PHA-II files contain EBOUNDS extension with boundaries of energy channels
(columns E_MIN and E_MAX) and SPECTRUM extension which includes start (column
TSTART), stop (column TSTOP) and exposure (column EXPOSURE) time of spectrum
accumulation and $N_{sp}$$\times$$N_{ch}$ matrix (COUNTS) with count number in
each of $N_{ch}$ channels for $N_{sp}$=64 multichannel spectra. The separate
file with background multichannel spectra in PHA-I format contains EBOUNDS
extension with energy boundaries equal to those of a flare spectrum and a
single spectrum in SPECTRUM extension with columns CHANNEL, RATE, STAT_ERR,
SYS_ERR, GROUPING and QUALITY.

Standard Konus-Wind dead time corrections (Section 2) are taken into account
in the EXPOSURE column for PHA-II files and in the RATE and STAT_ERR columns
of PHA-I files. Systematic errors associated with additional dead-time
corrections for very intense events (see Section 3.3.2) are added in
quadrature to the statistical errors in each channel, and the resulting errors
are written to the STAT_ERR column in the PHA files. This column (if exists)
is automatically used by XSPEC and OSPEX instead of Poisson errors for count
spectra. Exposure errors caused by these corrections are added, for the
information, to the EXPOSURE_ERR column in the PHA file.

RMF files consist of EBOUNDS extension and MATRIX extension. MATRIX includes
columns ENERG_LO and ENERG_HI with $N_{i}$=263 incident energies ${E_{i}}$ of
test quanta used for response modeling and $N_{i}$$\times$$N_{ch}$ matrix with
probabilities of registering gamma-quantum of energy $E_{i}$ in channel
$N_{i}$ compressed by a special algorithm131313Response matrix compression is
described in OGIP standard.. ARF files contain SPECRESP extension with
effective areas calculated for $N_{i}$=263 incident energies ${E_{i}}$ of test
quanta.

## References

  * Acton et al. (1992) Acton, L., Tsuneta, S., Ogawara, Y., Bentley, R., Bruner, M., Canfield, R., Culhane, L., Doschek, G., Hiei, E., & Hirayama, T. 1992, Science, 258, 618
  * Agostinelli et al. (2003) Agostinelli, S., Allison, J., Amako, K., & et al. 2003, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 506, 250
  * Ajello et al. (2021) Ajello, M., Baldini, L., Bastieri, D., & et al. 2021, ApJS, 252, 13
  * Altyntsev et al. (2019) Altyntsev, A. T., Meshalkina, N. S., Lysenko, A. L., & Fleishman, G. D. 2019, ApJ, 883, 38
  * Aptekar et al. (1995) Aptekar, R. L., Frederiks, D. D., Golenetskii, S. V., Ilynskii, V. N., Mazets, E. P., Panov, V. N., Sokolova, Z. J., Terekhov, M. M., Sheshin, L. O., Cline, T. L., & Stilwell, D. E. 1995, Space Sci. Rev., 71, 265
  * Arnaud (1996) Arnaud, K. A. 1996, in Astronomical Society of the Pacific Conference Series, Vol. 101, Astronomical Data Analysis Software and Systems V, ed. G. H. Jacoby & J. Barnes, 17
  * Atwood et al. (2009) Atwood, W. B., Abdo, A. A., Ackermann, M., & et al. 2009, ApJ, 697, 1071
  * Crosby et al. (1993) Crosby, N. B., Aschwanden, M. J., & Dennis, B. R. 1993, Sol. Phys., 143, 275
  * Dennis (1985) Dennis, B. R. 1985, Sol. Phys., 100, 465
  * Emslie et al. (2012) Emslie, A. G., Dennis, B. R., Shih, A. Y., Chamberlin, P. C., Mewaldt, R. A., Moore, C. S., Share, G. H., Vourlidas, A., & Welsch, B. T. 2012, ApJ, 759, 71
  * Fleishman et al. (2022) Fleishman, G. D., Nita, G. M., Chen, B., Yu, S., & Gary, D. E. 2022, Nature
  * Fletcher et al. (2011) Fletcher, L., Dennis, B. R., Hudson, H. S., Krucker, S., Phillips, K., Veronig, A., Battaglia, M., Bone, L., Caspi, A., Chen, Q., Gallagher, P., Grigis, P. T., Ji, H., Liu, W., Milligan, R. O., & Temmer, M. 2011, Space Sci. Rev., 159, 19
  * Glesener & Fleishman (2018) Glesener, L. & Fleishman, G. D. 2018, ApJ, 867, 84
  * Hannah et al. (2008) Hannah, I. G., Christe, S., Krucker, S., Hurford, G. J., Hudson, H. S., & Lin, R. P. 2008, ApJ, 677, 704
  * Holman et al. (2011) Holman, G. D., Aschwanden, M. J., Aurass, H., Battaglia, M., Grigis, P. C., Kontar, E. P., Liu, W., Saint-Hilaire, P., & Zharkova, V. V. 2011, Space Sci. Rev., 159, 107
  * Krucker et al. (2020) Krucker, S., Hurford, G. J., Grimm, O., & et al. 2020, A&A, 642, A15
  * Lin et al. (1995) Lin, R. P., Anderson, K. A., Ashford, S., & et al. 1995, Space Sci. Rev., 71, 125
  * Lin et al. (2002) Lin, R. P., Dennis, B. R., Hurford, G. J., & et al. 2002, Sol. Phys., 210, 3
  * Lysenko et al. (2019) Lysenko, A. L., Anfinogentov, S. A., Svinkin, D. S., Frederiks, D. D., & Fleishman, G. D. 2019, ApJ, 877, 145
  * Lysenko et al. (2020) Lysenko, A. L., Frederiks, D. D., Fleishman, G. D., Aptekar, R. L., Altyntsev, A. T., Golenetskii, S. V., Svinkin, D. S., Ulanov, M., Tsvetkova, A. E., & Ridnaia, A. V. 2020, Physics Uspekhi, 63, 818
  * Meegan et al. (2009) Meegan, C., Lichti, G., Bhat, P. N., & et al. 2009, ApJ, 702, 791
  * Müller et al. (2020) Müller, D., St. Cyr, O. C., Zouganelis, I., & et al. 2020, A&A, 642, A1
  * Ogawara et al. (1991) Ogawara, Y., Takano, T., Kato, T., Kosugi, T., Tsuneta, S., Watanabe, T., Kondo, I., & Uchida, Y. 1991, Sol. Phys., 136, 1
  * Schwartz et al. (2002) Schwartz, R. A., Csillaghy, A., Tolbert, A. K., Hurford, G. J., McTiernan, J., & Zarro, D. 2002, Sol. Phys., 210, 165
  * Share et al. (2018) Share, G. H., Murphy, R. J., White, S. M., Tolbert, A. K., Dennis, B. R., Schwartz, R. A., Smart, D. F., & Shea, M. A. 2018, ApJ, 869, 182
  * Svinkin et al. (2016) Svinkin, D. S., Frederiks, D. D., Aptekar, R. L., Golenetskii, S. V., Pal’shin, V. D., Oleynik, P. P., Tsvetkova, A. E., Ulanov, M. V., Cline, T. L., & Hurley, K. 2016, ApJS, 224, 10
  * Tolbert & Schwartz (2020) Tolbert, K. & Schwartz, R. 2020, OSPEX: Object Spectral Executive, Astrophysics Source Code Library, record ascl:2007.018
  * Vestrand et al. (1999) Vestrand, W. T., Share, G. H., J. Murphy, R., Forrest, D. J., Rieger, E., Chupp, E. L., & Kanbach, G. 1999, ApJS, 120, 409
  * Vilmer et al. (2011) Vilmer, N., MacKinnon, A. L., & Hurford, G. J. 2011, Space Sci. Rev., 159, 167
  * Wilson et al. (2021) Wilson, Lynn B., I., Brosius, A. L., Gopalswamy, N., Nieves-Chinchilla, T., Szabo, A., Hurley, K., Phan, T., Kasper, J. C., Lugaz, N., Richardson, I. G., Chen, C. H. K., Verscharen, D., Wicks, R. T., & TenBarge, J. M. 2021, Reviews of Geophysics, 59, e2020RG000714