The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

https://doi.org/10.3847/1538-4365/aad1ef© 2018. The American Astronomical Society. All rights reserved.

The 7-year MAXI/GSC X-Ray Source Catalog in the High Galactic Latitude Sky(3MAXI)
T. Kawamuro1,13 , Y. Ueda2 , M. Shidatsu3, T. Hori2 , M. Morii4, S. Nakahira3, N. Isobe5, N. Kawai6 , T. Mihara3,
M. Matsuoka3, T. Morita2, M. Nakajima7, H. Negoro8, S. Oda2, T. Sakamoto9, M. Serino9, M. Sugizaki3, A. Tanimoto2 ,H. Tomida5, Y. Tsuboi10 , H. Tsunemi11, S. Ueno5, K. Yamaoka12, S. Yamada2, A. Yoshida9, W. Iwakiri3, Y. Kawakubo9,
Y. Sugawara5 , S. Sugita6, Y. Tachibana6, and T. Yoshii6
1

National Astronomical Observatory of Japan, Osawa, Mitaka, Tokyo 181-8588, Japan; taiki.kawamuro@nao.ac.jp
2
Department of Astronomy, Kyoto University, Kitashirakawa-Oiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan
3
MAXI team, RIKEN, 2-1, Hirosawa, Wako-shi, Saitama 351-0198, Japan
4
The Institute of Statistical Mathematics, 10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan
5
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 3-1-1 Yoshinodai, Chuo, Sagamihara, Kanagawa 252-5210, Japan
6
Department of Physics, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8551, Japan
7
School of Dentistry at Matsudo, Nihon University, 2-870-1, Sakaecho-nishi, Matsudo, 271-8587, Chiba, Japan
8
Department of Physics, Nihon University, 1-8 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-8308, Japan
9
College of Science and Engineering, Department of Physics and Mathematics, Aoyama Gakuin University,
5-10-1 Fuchinobe, Chuo-ku, Sagamihara, Kanagawa 252-5258, Japan10
Department of Physics, Faculty of Science & Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo, Tokyo 112-8551, Japan
11
Department of Earth and Space Science, Graduate School of Science, Osaka University, 1-1 Machikaneyama-cho, Toyonaka, Osaka 560-0043, Japan
12
Institute for Space-Earth Environmental Research (ISEE), Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601, Japan
Received 2018 April 22; revised 2018 June 22; accepted 2018 June 29; published 2018 October 15

Abstract
We present the third MAXI/GSC catalog in the high Galactic latitude sky (∣b∣ > 10) based on the 7-year
data from 2009 August 13 to 2016 July 31, complementary to that in the low Galactic latitude sky (∣b∣ < 10)(Hori et al. 2018). We compile 682 sources detected at signiﬁcances of sD,4–10 keV 6.5 in the 4–10 keV band.
A two-dimensional image ﬁt based on the Poisson likelihood algorithm (C-statistics) is adopted for the detections
and constraints on their ﬂuxes and positions. The 4–10 keV sensitivity reaches ≈0.48 mCrab, or ≈5.9×10−12 erg
cm−2 s−1, over half of the survey area. Compared with the 37-month Hiroi et al. (2013) catalog, which adopted athreshold of sD,4–10 keV 7, the source number increases by a factor of ∼1.4. The ﬂuxes in the 3–4 keV and
10–20 keV bands are further estimated, and hardness ratios (HRs) are calculated using the 3–4 keV, 4–10 keV,
3–10 keV, and 10–20 keV band ﬂuxes. We also make the 4–10 keV light curves in 1-year bins for all the sources
and characterize their variabilities with an index based on a likelihood function and the excess variance. Possible
counterparts are found from ﬁve major X-ray survey catalogs by Swift, Uhuru, RXTE, XMM-Newton, and ROSAT,
as well as an X-ray galaxy cluster catalog (MCXC). Our catalog provides the ﬂuxes, positions, detection
signiﬁcances, HRs, 1-year bin light curves, variability indices, and counterpart candidates.
Key words: catalogs – galaxies: active – galaxies: clusters: general – surveys – X-rays: galaxies
Supporting material: ﬁgure set, machine-readable tables, tar.gz ﬁlesbiased against the absorption than the ROSAT catalogs. Also,
this energy band has an advantage in detecting sources with
“soft” spectra above 4 keV (e.g., a steep power law), comparedwith hard X-rays above 10 keV. Thus, the MAXI/GSC survey iscomplementary to other X-ray surveys conducted in different
energy bands.
A variety of X-ray sources have been detected by accumulating the MAXI/GSC data on different timescales. The MAXI
Alert system automatically informs us of variabilities within a
few days (Negoro et al. 2012, 2016). As a result, a numberof new X-ray transients have been discovered (e.g., Morii
et al. 2013; Serino et al. 2015; Shidatsu et al. 2017a), andrecurrent activities of known sources have been captured (e.g.,
Isobe et al. 2015). Most of them are Galactic objects. Also,
systematic surveys focusing on a few-month variability provided
unique samples including objects undetected in shorteror longer-timescale surveys (e.g., tidal disruption events;
Kawamuro et al. 2016a). To extract the best sensitivities formost sources, high and low Galactic latitude sky catalogs were
produced by integrating all the MAXI/GSC data available then
(7 months to 7 years; Hiroi et al. 2011, 2013; Hori et al. 2018).

1. Introduction
The Monitor of All-sky X-ray Image (MAXI; Matsuoka
et al. 2009) on board the International Space Station (ISS) has
been successfully monitoring the X-ray sky since its launch in2009 August. The Gas Slit Camera (GSC) on the MAXI
(Mihara et al. 2011), covering the 2–30 keV band, surveys thesky with two instantaneous ﬁelds of view of 3°. 0×160°
separated by 84°. Rotating its ﬁelds of view with a period of
92 minutes according to the orbital motion of the ISS, the GSC
eventually covers a large fraction of the sky (95%) in 1 day(Sugizaki et al. 2011).
As an all-sky X-ray survey mission, the MAXI/GSC has
achieved the best sensitivity in the 4–10 keV band, which is notcovered by the ROSAT all-sky survey (<2 keV; Truemper 1982)
and hard X-ray (>10 keV) surveys performed with the Swift/
BAT (Gehrels et al. 2004) and INTEGRAL/IBIS (Winkler et al.
2003). The 4–10 keV X-rays have good penetrating power up toa column density of log NH cm-2 ~ 23, providing samples less
13

JSPS fellow (PD).

1

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 OctoberParticularly, the high-latitude catalogs have been used as abasis to study extragalactic objects, mainly active galactic
nuclei (AGNs; e.g., Ueda et al. 2011, 2014; Terashima et al.
2015; Inoue & Tanaka 2016; Isobe et al. 2016; Abeysekara
et al. 2017).
In this paper, we present the third MAXI/GSC X-ray source
catalog in the high Galactic latitude sky (∣b∣ > 10) constructedfrom the ﬁrst 7-year data. This is an extension of the 7-monthand 37-month catalogs (Hiroi et al. 2011, 2013) and iscomplementary to the 7-year low Galactic latitude catalog(Hori et al. 2018). The catalog consists of sources detected in
the 4–10 keV data, to be consistent with the previous works.
We also estimate the ﬂuxes in the 3–4 keV and 10–20 keVbands of each source and calculate the hardness ratios (HRs)among the four bands (3–4 keV, 4–10 keV, 3–10 keV, and10–20 keV) to obtain spectral information. The 10–20 keVband ﬂux is new information that was unavailable in theprevious high Galactic latitude catalogs. Also, by analyzingtime-sliced images, we make the 4–10 keV light curves in
1-year bins for all the detected sources. Transiently brightenedsources undetected in the 7-year image are found in these timesliced data, which are summarized as a transient event catalog
in the Appendix.
This paper is organized as follows. Section 2 describes
analysis procedures from data reduction to source detection andprovides the source catalog. In Section 3 we make the 1-year
bin light curves and search for transient events. Cross-matchingwith other X-ray catalogs is performed in Section 4.1. Then, we
discuss the statistical properties of the cataloged sources in
Section 5 based on the ﬂuxes, HRs, and the time variability
index. The logN–logS relation is also shown in Section 5.3.
We summarize our work in Section 6.

Kawamuro et al.

the cosmic X-ray background) and the point-spread function(PSF), as detailed in Hori et al. (2018). These are key components
in our image analysis (Section 2.2.1). It was found thatthe background event rates well correlate with the rates ofsimultaneous events in the carbon-anode cells and the tungstenanode cells for particle veto (i.e., VC-counts; Mihara et al. 2011;
Sugizaki et al. 2011). This correlation was already used toreproduce the background events in Hiroi et al. (2013). In the new
background model, we also take into account the direction of
movement of the ISS with respect to the Earth (to the north or
south), on which the background-to-VC-count correlation is foundto largely depend (see Figure2 of Shidatsu et al. 2017b; Horiet al. 2018). In return, the 10–20 keV data can now be reliably
utilized, which were not analyzed in the previous work. Also, an
updated PSF database as a function of energy and detector
position of each counter (see the Appendix of Hori et al. 2018)is implemented to the MAXI event simulator, “maxisim”(Eguchi et al. 2009).
2.2. Image Analysis
Here we brieﬂy describe the image analysis for source
detection, which is essentially the same as that adopted in Hiroi
et al. (2013). In the event ﬁles, each photon has information ofsky position (RA and decl.), which is converted from anestimated position in the detector along the anode direction andthe pointed direction of the collimator at the detected time. We
ﬁrst divide the all-sky image into 768 tangentially projected
images of 14°. 0×14°. 0 size (binned by 0°. 1 × 0°. 1), whose
central coordinates are determined by the HEALPix system(Górski et al. 2005). Then, we apply the processes described in
the following subsections to each projected image. Thisconsists of two steps: (1) making a tentative source-candidate
list based on simple photon statistics, and (2) determining theﬂux, signiﬁcance, and position by image ﬁtting with a modelcomposed of the background and PSFs. To model thebackground image, we produce simulated background events
that have 10 times more counts than those of real data, using
the MAXI/GSC background generator (Eguchi et al. 2009).

2. Catalog Construction
2.1. Overview of the MAXI/GSC Data
We analyze the MAXI/GSC event data from 2009 August 13
to 2016 July 31 provided by RIKEN (rev. 1.8),14 focusing on
those at high Galactic latitudes (∣b∣ > 10). The same datascreening criteria as adopted by Hori et al. (2018; see their
Section 2) are applied. We exclude the data taken with four GSCs
(GSC3, GSC6, GSC9, and GSCa) out of all 12 GSCs from theanalysis. GSC6, GSC9, and GSCa were operated only for <1 yr,
which is too short to establish a reliable background model (seebelow). The GSC3 data are highly contaminated by backgroundcounts owing to defects of the veto counters (Sugizaki et al.
2011), and they are also subject to large calibration uncertainties
in the position determination. Apart from them, the GSC0 data
since 2013 June 15 are not used because they are affected by gas
leakage. We select the 4–10 keV band for source detection byconsidering the high quantum efﬁciency and low background rate
(Mihara et al. 2011).
Here we summarize main differences of the third MAXI/GSC
high Galactic latitude catalog compared with the second one(Hiroi et al. 2013). A major advantage is the increased photon
statistics (37 months to 84 months). Others are improved
calibration of the background (the non-X-ray background plus

2.2.1. Source Finding

We ﬁrst make a source-candidate list to be used as the input
to the image-ﬁt process. Combining the real data (consisting ofsource and background events) and the simulated background data, we calculate “nominal signiﬁcances” as (real−
background counts)/ real counts , where those counts areintegrated within a radius of 1° around each image bin. From
this “signiﬁcance map,” we identify a bin showing the highest
signiﬁcance as the position of the ﬁrst source candidate. Aftermasking a 3° radius circular region centered on the sourcecandidate position, we again search for another candidate. This
is iterated until no peak is found with a signiﬁcance larger than15σ. Subsequently, to ﬁnd fainter sources, we adjust thenormalization of the background model so that the counts ofthe masked real and masked background data become identical,
assuming that the contribution from remaining fainter sources
to the observed counts is ignorable. Such ﬁne-tuning of the
background (typically by <5%) is required owing to systematic
uncertainties in the background model and ﬂuctuation of
the level of the cosmic X-ray background. Then, we repeat
the same source-ﬁnding procedures above by lowering thedetection threshold to 5.0σ. Merging the source-candidate lists

14
The ofﬁcial day of the MAXI ﬁrst light is 2009 August 15 (http://iss.jaxa.
jp/en/kiboexp/ef/maxi/maxi_ﬁrst_light.html), when both the GSCs andSolid-state Slit Cameras (Tomida et al. 2011) started the operation. However,
because the activation of all the GSCs was already completed on 2009 August
13, the GSC data taken earlier than the ﬁrst-light day are available.

2The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Figure 1. Histogram of the 4–10 keV ﬂux (left), that of the detection signiﬁcance (middle), and their correlation plot (right).

from all the images, we sometimes ﬁnd multiple sources within
1°, which is smaller than a typical size (FWHM) of the MAXI/
GSC PSF (∼1°. 5). This happens because there are some overlap
areas among the projected images. In such cases, we only leave
the source candidate located closest to the center of theanalyzed image.

that that would be expected from the Crab Nebula spectrum,
the ﬂux is given in “Crab” units.
2.2.3. Iteration of Source Finding and Image Fit

Some sources located near bright sources could be missed in
the ﬁrst source-candidate list because we masked out the 3°
circular region around each source candidate. To make oursource ﬁnding complete, we repeat the source-ﬁnding process(Section 2.2.1) by using a new signiﬁcance map (smoothed
residual map) where the best-ﬁt model (background plus PSFs)
obtained in the above image-ﬁt process (Section 2.2.2) is adopted
as the background. Then, including those new source candidates
detected with nominal signiﬁcances of 5.5σ, we perform theimage ﬁt again. This provides the ﬁnal source catalog.

2.2.2. Image Fit

The PSFs for the source candidates are constructed fromsimulated photon events produced by the MAXI simulator (Eguchi
et al. 2009) with exactly the same observing conditions as for thereal data. We assume a point source having the same spectrum as
the Crab Nebula. Throughout this paper, we assume that the Crab
Nebula has a power law with a photon index of 2.1 and anormalization of 10 photons cm−2 s−1 keV−1 at 1 keV, absorbedwith a hydrogen column density of 2.6×1021 cm−2. The ﬂuxes
are 3.96×10−9 erg cm−2 s−1, 1.21×10−8 erg cm−2 s−1,
8.51×10−9 erg cm−2 s−1, and 1.61×10−8 erg cm−2 s−1 inthe 3–4 keV, 4–10 keV, 10–20 keV, and 3–10 keV bands,
respectively, which correspond to “1 Crab.”
Then, we ﬁt the PSF and background models to the real
image. Here we restrict the ﬁtting region to an inner
11°. 0×11°. 0 area, because the outer region may be affectedby sources located just outside the edge of the 14°. 0×14°. 0
region. The ﬂuxes and peak positions of the PSFs and thenormalization of the background are left as free parameters. We
determine these parameters by the Poisson maximum likelihood (ML) algorithm (C-statistics), using the MINUIT
software package. The likelihood function is deﬁned as
C º 2 å  (i , j ) ,2.3. Catalog
We detect 682 sources with 4–10 keV detection signiﬁcances ofsD,4–10 keV 6.5 at high Galactic latitudes (∣b∣ > 10). Table 1
gives our source catalog. Considering the improved calibration of
the background and PSF models (Section 2.1), and following the
7-year “low” Galactic latitude catalog (Hori et al. 2018), we havedecided to lower the detection threshold from sD,4–10 keV 7,
which was adopted in the 37-month catalog (Hiroi et al. 2013), tosD,4–10 keV 6.5 in our new catalog. The number of the cataloged
sources increases by a factor of ≈1.4 compared with Hiroi et al.
(2013), where 500 sources were listed. If the same threshold ofsD,4–10 keV 7 as in Hiroi et al. (2013) is adopted, the source
number of our catalog becomes 615. The counterpart candidate islisted in Table 2, as detailed in Section 4.1. The sensitivity limit
achieved for 50% of the survey area is ∼0.48 mCrab, or∼5.9×10−12 erg cm−2 s−1 (Section 5.3). Figure 1 shows the
distribution of the ﬂux and detection signiﬁcance in the 4–10 keVband, as well as their correlation. Figure 2 plots the statisticalerrors in the position (1σstat) against the detection signiﬁcance.
The spatial distribution in the Galactic coordinates is shown in
Figure 3. The classiﬁcation of sources in this ﬁgure is detailed in
Section 4.1.

(1 )

i, j

where
 (i , j )⎧ M (i , j ) - D (i , j ) + D (i , j ){ln D (i , j ) - ln M (i , j )}⎪(Di, j > 0)=⎨
⎪ M (i , j )Di, j = 0).
(⎩

2.3.1. Spurious Source Fraction

The observed data and model at the (i, j) bin are denoted with D(i, j) and M(i, j), respectively. The 1σ statistical error of eachparameter is estimated by ﬁnding a value when the likelihood
function (C) is increased from its minimum by unity. The
detection signiﬁcance is deﬁned as (best-ﬁt ﬂux)/(its lowerside 1σ error). We conﬁrm that the lower- and upper-side errors
are generally consistent with each other. This is expected
because the number of counts is large enough to follow a
Gaussian distribution. Since we measure a relative count rate to

The detection threshold should be determined to maximize thenumber of detected sources while suppressing that of spurious
sources caused by statistical and/or systematic ﬂuctuations of thedata to an acceptable level. We estimate the number of spurious
sources in our catalog by counting that of negative signals withthe same detection threshold, assuming that their signiﬁcance
distribution is symmetrical in positive and negative sides aroundthe background level. We ﬁrst search the signiﬁcance maps
produced from the data and the best-ﬁt models for negative-signal
3

4

No.
(1)

3MAXI
(2)

R.A.
(3)

Decl.
(4)

σstat
(5)

sD,4–10keV(6)

f4–10keV(7)sD,3–4keV(8)

f3–4keV(9)sD,10–20keV(10)

f10–20keV(11)

f3–10keV
(12)

HR1
(13)

HR2
(14)

HR3
(15)

TSvar
(16)

s 2rms
(17)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

J0001−684
J0004−348
J0006+727
J0009+109
J0010+323
J0011−113
J0011−292
J0012−313
J0012−154
J0016−825
J0021+286
J0022−193
J0027+075
J0029+127
J0035−791
J0039+231
J0041−093
J0042+412
J0048+319
J0048−732

0.251
1.037
1.602
2.462
2.621
2.804
2.962
3.132
3.139
4.145
5.319
5.733
6.762
7.269
8.974
9.850
10.45510.66812.05112.057−68.463−34.89772.74210.93832.390−11.311−29.231−31.351−15.433−82.587
28.601−19.356
7.597
12.736−79.17823.117−9.31841.23831.900−73.205

0.215
0.161
0.097
0.146
0.177
0.089
0.137
0.235
0.177
0.171
0.119
0.150
0.193
0.206
0.121
0.170
0.026
0.044
0.057
0.094

11.1
7.8
12.5
9.5
7.3
12.7
9.6
7.6
7.2
7.2
10.1
10.6
7.4
7.7
13.0
6.6
54.1
31.6
20.4
14.6

7.74±0.70
7.36±0.94
10.39±0.83
8.53±0.90
7.63±1.04
10.24±0.81
8.02±0.84
6.46±0.85
5.60±0.78
5.29±0.73
9.92±0.98
8.25±0.78
6.51±0.88
7.09±0.93
8.83±0.68
6.02±0.92
46.94±0.87
36.63±1.16
21.47±1.05
17.22±1.92

9.8
11.2
16.1
7.9
8.4
10.7
12.1
5.5
9.7
3.4
8.9
10.5
2.9
5.6
13.4
4.3
54.2
32.4
7.9
13.9

2.19±0.23
2.87±0.26
4.36±0.27
2.10±0.27
2.58±0.31
2.48±0.23
2.93±0.24
1.32±0.24
2.16±0.22
0.82±0.24
2.58±0.29
2.39±0.23
0.74±0.25
1.50±0.27
3.03±0.23
1.21±0.27
15.02±0.28
11.97±0.37
2.42±0.31
3.71±0.27

1.2
2.0
1.8
4.5
L
L
2.1
2.6
1.5
2.2
2.0
3.7
L
2.8
3.8
2.4
7.2
4.6
6.0
3.9

3.00±2.60
6.67±3.41
5.94±3.25
15.75±3.48
0.39(<4.49)
0.58(<3.69)
6.83±3.28
8.49±3.29
4.60±3.06
5.49±2.48
7.94±3.92
11.66±3.12
1.00(<4.30)
10.05±3.58
9.19±2.38
8.45±3.55
22.56±3.12
19.84±4.30
24.01±4.04
11.07±2.83

9.93±0.74
10.23±0.98
14.75±0.87
10.63±0.94
10.21±1.09
12.72±0.84
10.95±0.87
7.78±0.88
7.76±0.81
6.11±0.77
12.50±1.02
10.64±0.81
7.25±0.91
8.59±0.97
11.86±0.72
7.23±0.96
61.96±0.91
48.60±1.22
23.89±1.09
20.93±1.94

0.07±0.07−0.09±0.08−0.12±0.05
0.14±0.08−0.02±0.09
0.15±0.06−0.06±0.07
0.23±0.11−0.08±0.09
0.36±0.14
0.11±0.07
0.06±0.07
0.48±0.14
0.21±0.11−0.02±0.05
0.24±0.13
0.01±0.01
0.00±0.02
0.49±0.05
0.21±0.06−0.29±0.40
0.13±0.26−0.10±0.27
0.45±0.10−0.86±1.33−0.85±0.74
0.10±0.24
0.30±0.19
0.08±0.34
0.19±0.23
0.07±0.25
0.34±0.13−0.64±0.97
0.34±0.17
0.19±0.13
0.33±0.20−0.19±0.07−0.13±0.11
0.23±0.08−0.04±0.14−0.27±0.40
0.10±0.26−0.14±0.27
0.47±0.09−0.86±1.32−0.84±0.78
0.08±0.24
0.35±0.18
0.06±0.34
0.26±0.22
0.09±0.25
0.35±0.12−0.59±1.08
0.38±0.16
0.19±0.13
0.38±0.19−0.18±0.07−0.13±0.11
0.31±0.08−0.00±0.14

2.29
4.98
10.26
14.78
5.64
8.93
9.36
6.98
6.81
5.02
10.20
5.37
9.65
4.48
24.40
3.41
7.99
6.38
15.54
47.97

−0.045±0.037−0.047±0.059
0.043±0.054
0.067±0.069−0.071±0.080
0.009±0.030
0.034±0.066−0.020±0.061−0.038±0.097−0.072±0.087
0.076±0.075−0.034±0.041
0.024±0.098−0.059±0.075
0.092±0.057−0.090±0.089−0.000±0.002−0.004±0.005
0.009±0.014
0.227±0.096

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 OctoberTable 1
X-Ray Properties of Sources in the Third MAXI/GSC Catalog

Note. Column (1): source number. Column (2): MAXI name determined from the source coordinates. Columns (3)–(4): R.A. and decl. in units of degrees. Column (5): 1σ statistical error of the position in units ofdegrees. Note that the systematic error is not taken into consideration. Columns (6)–(7), (8)–(9), and (10)–(11): detection signiﬁcance and 7-year averaged ﬂux in units of 10−12 erg cm−2 s−1 for each energy band. Whena 1σ error is larger than the best-ﬁt value, the 1σ upper limit is represented. The conversion factor from Crab units into erg cm−2 s−1 units in the 4–10 keV, 3–4 keV, and 10–20 keV bands is 1.21×10−11 erg cm−2 s−1
mCrab−1, 3.96×10−12 erg cm−2 s−1 mCrab−1, and 8.51×10−12 erg cm−2 s−1 mCrab−1, respectively. Column (12): the ﬂux in the 3–10 keV band. Note that the factor of 1.61×10−11 erg cm−2 s−1 mCrab−1 isusable for the conversion. Column (13): hardness ratios calculated from the ﬂuxes in the 3–4 keV and 4–10 keV bands. Note that they are derived from the ﬂux in units of Crab. Columns (14)–(15): same as Column (13),but for the 4–10 keV and 10–20 keV bands and the 3–10 keV and 10–20 keV bands. Column (16): time variability index (see the text for the deﬁnition). The hypothesis that the ﬂux does not vary can be ruled out forTSvar>18.48 at the 99% conﬁdence level. Column (17): excess variance.
(This table is available in its entirety in machine-readable form.)

Kawamuro et al.

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Table 2
Possible Counterparts of the Third MAXI/GSC SourcesCounterpart

No.
(1)

MAXI
3MAXI
(2)

Name
(3)

R.A.
(4)

Decl.
(5)

z
(6)

Type
(7)

Flag
(8)

Note
(9)

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

J0001−684
J0004−348
J0006+727
J0009+109
J0010+323
J0011−113
J0011−292
J0012−313
J0012−154
J0016−825
J0021+286
J0022−193
J0027+075
J0029+127
J0035−791
J0039+231
J0041−093
J0042+412
J0048+319
J0048−732

L
L
L
Mrk 1501
RXC J0011.7+3225
1RXS J001124.6−112843
L
L
MACS J0011.7−1523
L
RXC J0020.6+2840
L
L
L
2MASX J00341665−7905204
L
ABELL 85
SWIFT J0042.7+4111
Mrk 348
L

L
L
L
2.629
2.935
2.853
L
L
2.928
L
5.17
L
L
L
8.57
L
10.40810.66812.196
L

L
L
L
10.97532.417−11.479L
L−15.389
L
28.675
L
L
L−79.089L−9.342
41.2
31.957
L

L
L
L
0.08930.1073
L
L
L
0.378
L
0.094
L
L
L
0.074
L
0.0555
L
0.015
L

L
L
L
BlazarGalaxy Cluster
Dwarf Nova
L
L
Galaxy Cluster
L
Galaxy Cluster
L
L
L
Sy1
L
Galaxy Cluster
confused source
Blazar
L

L
L
L
BR
MR
R
L
L
M
L
MR
L
L
L
BR
L
BMR
B
BX
L

L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L
L

Note. Column (1): source number. Column (2): MAXI name. Columns (3)–(7): available information of the counterpart (name, R.A., and decl. in units of degrees,
redshift, and source type). Column (8): cross-matching ﬂag: B, U, X, M, N, and R represents that the source has more than one counterpart in BAT105, 4U,
XTEASMLONG, MCXC, XMMSL2, and 1RXS, respectively. The counterpart name listed in Column (3) is quoted from the catalog expressed by the leftmost letterin this column. Column (9): note related to the identiﬁcation of the counterpart. (A) The auto-matching identiﬁes a galaxy cluster, but this is likely inconsistent withthe signiﬁcant variability (TSvar = 87). Then, we select a star as a plausible candidate of the counterpart. (B) We automatically ﬁnd an obscured AGN from BAT105 as
the counterpart, but the very soft property is not so common to such objects. Then, we ﬁnd a bright object, CXO J092418.2−314217, in a Swift/XRT soft X-ray
image. According to a study by Tomsick et al. (2017), it can be classiﬁed as an LMXB or a CV, and here we representatively adopt the LMXB. (C) One of thebrightest galaxies is selected for the most plausible counterpart.
(This table is available in its entirety in machine-readable form.)candidates. Then, we create their PSF models through simulationand perform image ﬁtting by allowing their normalizations to be
negative. We ﬁnd that our catalog may contain 26 spurious
sources with sD,4–10 keV 6.5, which corresponds to 4% of thetotal 682 sources. If we adopt sD,4–10 keV 6 as the threshold, thenumber of spurious sources drastically increases to 58 sources, 8%of the total 766 sources. Thus, we select sD,4–10 keV=6.5 as thethreshold. Depending on the scientiﬁc purpose, catalog users canchoose a more conservative threshold; the estimated fraction of
spurious sources becomes 3% (17/615) for sD,4–10 keV 7 and
0.6% (3/477) for sD,4–10 keV 8.
2.3.2. Hardness Ratios

To calculate HRs of the detected sources, we determine theﬂuxes in the 3–4 keV and 10–20 keV bands in the following way.
Tangentially projected images in these bands are produced fromthe event ﬁles. We prepare the input source list for the image ﬁt
from our catalog produced above. For completeness, here we also
include the source candidates whose detection signiﬁcances wereless than 6.5σ in the 4–10 keV band. We then perform an image
ﬁt to the image in the 3–4 keV or 10–20 keV band using thissource list. During the ﬁtting process, the positions are ﬁxed atthose determined in the 4–10 keV band. This process is repeatedby adding new source candidates found in the smoothed residual
map with nominal signiﬁcances (see Section 2.2.1) above 5.5σ.
Eventually, we ﬁnd no new sources detected with signiﬁcances
above 6.5σ in the 3–4 keV or 10–20 keV band but not included in
the above catalog based on the 4–10 keV band survey. The

Figure 2. Positional error (1σstat) as a function of the 4–10 keV detection
signiﬁcance (sD,4–10keV).

3–10 keV ﬂuxes are also calculated from the 3–4 keV and
4–10 keV ﬂuxes obtained above by assuming the Crab-like
spectrum. We deﬁne the HR as
HR =fH - fS,
fH + fS(2 )where fH and fS correspond to the hard- and soft-band ﬂuxes,
respectively, in Crab units. The catalog lists three HRs: HR1
5

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Figure 3. Spatial distribution of the detected 682 X-ray sources in Galactic coordinates. The center corresponds to (l, b)=(0°. 0, 0°. 0). The radii of the circles areproportional to the logarithm of the 4–10 keV ﬂux. According to the results of catalog cross-matching (Section 4.1), a color is assigned to each source type:unidentiﬁed X-ray sources in BAT105 (black), galaxies (cyan), galaxy clusters (green), Seyfert galaxies (blue), blazars (purple), cataclysmic variables/stars (magenta),
X-ray binaries (red), pulsars (pink), confused sources (orange), and sources without any counterparts in the reference catalogs (gray).

(3–4 keV, 4–10 keV), HR2 (4–10 keV, 10–20 keV), and HR3(3–10 keV, 10–20 keV).
To deduce the spectral shape from the HRs, we calculate therelation between the HRs and spectra parameters by assuming anabsorbed power-law model. The parameters are a photon index(Γ) and an intrinsic hydrogen column density (NH). We also take
into account a representative Galactic absorption of NHGal = 2.5 ´
10 20 cm−2 in addition to the intrinsic one. This column density
roughly corresponds to the minimum value over the high Galactic
latitude sky (∣b∣ > 10; Daltabuit & Meyer 1972) and should beconsidered as a lower limit for extragalactic objects. We
conﬁrmed, however, that the spatial variation in the total Galactic
column (NHGal < 2 ´ 10 21 cm−2 for ∣b∣ > 10) has little effecton the following results. The source redshift is not considered forsimplicity. We generate, through the MAXI on-demand tool,15
the 7-year averaged MAXI/GSC response ﬁle and calculate thepredicted count rates in these bands for given spectral parameters.
We consider two cases: a power-law model with and without
an intrinsic absorption. The Galactic absorption is taken into
account in both cases. In the former case, we ﬁx Γ=1.8 and varylogNH/cm−2 in a range of 20–24, whereas in the latter case, we
ﬁx NH=0 and vary Γ in a range of 1–3. The results are plotted in
the left panels of Figure 4. We also calculate the conversion
factors from the ﬂux in Crab units to that in the CGS system (ergcm−2 s−1), which are presented in the right panels of Figure 4. For
an unabsorbed power law with Γ=1.8, HR1= 0.0749, HR2=
0.115, and HR3= 0.136, and the conversion factors are 4.00×10−12 erg cm−2 s−1 mCrab−1, 1.24×10−11 erg cm−2 s−1
mCrab−1, 1.65×10−11 erg cm−2 s−1 mCrab−1, and 8.74×10−12 erg cm−2 s−1mCrab−1 in the 3–4 keV, 4–10 keV,
10–20 keV, and 3–10 keV bands, respectively.
15

3. Time-sliced Image Analysis
3.1. 4–10 keV Light Curves
Flux variability provides us with a key to deduce the natureof X-ray sources; for example, we can use the fact thatmany compact objects (e.g., X-ray binaries and AGNs) aretransients, whereas extended sources like galaxy clusters are
more persistent.
Here we produce the 4–10 keV light curves in 1-year binning.
We split the real, background, and PSF data used in the catalog
construction into each year and perform image ﬁtting for eachtime-sliced data set. We adopt the same observation period as
those in the catalog construction, and therefore the time bins in2009 and 2016 have smaller sizes than the other bins. In addition
to the cataloged sources, there may be transient sources that canbe detected at signiﬁcances above 6.5σ in a 1-year image but notin the 7-year accumulated data. Thus, we systematically search forsuch sources (see Section 3.2) and incorporate their PSFs in theimage ﬁtting. The positions of the cataloged sources are ﬁxed atthose determined from the whole 7-year data, while the positionsof the newly detected transients are at those determined in the time
bin where their detection signiﬁcances are the highest. Then, weconstruct the light curves of the individual sources by ﬁtting thenormalizations of their PSFs and the background model.
In addition to the statistical ﬂux errors, we derive the systematic
error, which may remain because we do not consider possible
time variation of the PSF proﬁle in our PSF database. We simply
determine the systematic error so that the Crab light curve isconsistent with 1 Crab over the 7 years. This is a conservative
way to estimate the systematic errors, since the X-ray ﬂux of Crabis not perfectly constant (Wilson-Hodge et al. 2011) and its
variability is included in the estimation. As shown in the left panelof Figure 5, adding 1.4% error is found to be sufﬁcient. This value
is taken into account in all the light curves as the systematic
errors. This systematic uncertainty is comparable to that derived

http://maxi.riken.jp/mxondem/

6

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Figure 4. Top left: relation between photon index and HRs: HR1 (3–4 keV, 4–10 keV), HR2 (4–10 keV, 10–20 keV), and HR3 (3–10 keV, 10–20 keV). No
absorption other than the Galactic one (NHGal = 2.5 ´ 10 20 cm−2) is considered. Top right: conversion factor in units of 10−11 erg cm−2 s−1mCrab−1 as a function ofphoton index. Bottom left: relation between hydrogen column density and HRs for an absorbed power-law model with a photon index of 1.8. Bottom right: conversion
factor in units of 10−11 erg cm−2 s−1mCrab−1 as a function of hydrogen column density.

Figure 5. Left: 1-year-bin light curve of the Crab Nebula in the 4–10 keV band. The dashed line denotes the 7-year-averaged Crab ﬂux, which is deﬁned as 1 Crab.
Right: same as the left panel, but for NGC 1365 (AGN) in units of mCrab. The counterpart information (name, type, and redshift) is listed in the legend. Both light
curves take account of a systematic ﬂux error of 1.4% (see the text).

in Hori et al. (2018), 1.6%, and much reduced compared with thatin the 37-month data (∼10%; Hiroi et al. 2013; Kawamuro et al.
2016a). This improvement can be ascribed to the sophisticated
PSF model. Among the light curves (Figure 6), we present, as aninteresting case, the NGC 1365 (AGN) one in the right panel of
Figure 5, which shows the strong variability by a factor of ∼5within the 7-year. Individual light-curve plots and full light-curve
data are published in an online tar.gz supplement.
We characterize the light curves in two steps. First, tostatistically examine whether a light curve is constant or varies,

we adopt a likelihood-based method as used in Nolan et al.
(2012). This is more appropriate than the simple leastchi-squared method when the photon statistics follow the
Poisson distribution, and therefore it can be used for faintsources as well as for bright ones. We calculate a test statistic
deﬁned as
TSvar = 2 åiDFi2[log ¢i (Fi ) - log ¢i (Fconst )] ,2
DFi2 + f 2 Fconst(3 )7The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Figure 6. Light curves in the 4–10 keV band during the 7 years in units of mCrab. The blue dashed line denotes the 7-year averaged ﬂux. The counterpart information(name, type, and redshift if available) is denoted in each ﬁgure. Individual plots and data for the light curves are available from the online supplementary tar.gz ﬁle.
The complete ﬁgure set (86 images) is available in the online journal.
(The complete ﬁgure set (86 images) is available.)

8

MAXI

Counterpart

9

No.
(1)

3MAXIt
(2)

R.A.
(3)

Decl.
(4)

σstat
(5)

sD,4–10keV(6)

f4–10keV
(7)

TSvar
(8)

s 2rms
(9)

Name
(10)

R.A.
(11)

Decl.
(12)

z
(13)

1
2
3
4

J0051−735
J0912−649
J1257+014
J1357−095

12.954138.047
194.471209.257−73.562−64.9111.489−9.509

0.080
0.060
0.118
0.139

11.7
20.8
9.4
13.6

48.4±2.872.3±3.5
18.6±1.925.5±1.81721.87
3486.07367.453758.6315.395±0.782
5.652±0.329
3.253±0.849
5.708±0.835

RX J0052.1−7319
MAXI J0911−655
NGC 4845
Swift J1357.2−0933

13.058138.010194.505
209.320−73.322−64.868
1.576−9.544L
L
0.004110
L

Type
(14)
HMXB
millisecond X-ray pulsar
Sy2/tidal disruption event
LMXB

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 OctoberTable 3
Properties of Transient Events

Note. Column (1): source number. Column (2): MAXI transient source name. Columns (3)–(4): R.A. and decl. in units of degrees. Column (5): 1σ statistical error of the position in units of degrees. Note that thesystematic error is not taken into consideration. Columns (6)–(7): detection signiﬁcance and ﬂux in units of 10−12 erg cm−2 s−1. Column (8): time variability index (see the text for the deﬁnition). Column (9): excess
variance. Columns (10)–(14): available information of the counterpart (name, R.A. and decl. in units of degrees, redshift, and source type), which is based on the Swift/BAT Hard X-ray Transient Monitor catalog(https://swift.gsfc.nasa.gov/results/transients/). The data ﬁle of the light curves is available from the online supplementary tar.gz ﬁle.

Kawamuro et al.

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Figure 7. Light curves of the transient sources in the 4–10 keV band. The counterpart information (name, type, and redshift if available) is denoted in each ﬁgure. The
data ﬁle of the light curves is available from the online supplementary tar.gz ﬁle.

Vaughan et al. (2003), or Equations(3) and (4) in Hori et al.
(2018), to investigate the strength of ﬂux variations. TSvar andσrms are listed in Table 1.
3.2. Transient Event Search
We systematically search for transient events that are
missed in the catalog based on the 7-year integrated images.
First, we create the signiﬁcance maps in the individual years
in the same manner as described in Section 2.2.1, using thebest-ﬁt model only including the cataloged sources. We thenidentify residuals with nominal signiﬁcances above 5.5σ as
the candidates of transients. Then, we perform the image
ﬁtting by including their PSFs in the model in addition to
those of the catalog sources. Four transient sources are foundto show signiﬁcances of sD,4–10 keV 6.5 in a time bin.
Table 3 and Figure 7 present their X-ray properties and thelight curves, respectively. Their coordinates are estimatedfrom a period where the source shows the highest signiﬁcanceamong all the time bins. Note that circular regions with a 3°
radius around the very bright sources Sco X-1, Cyg X-2,
and the Crab Nebula are excluded from this analysis to
avoid fake source detection due to systematic errors in the
PSF calibration.

Figure 8. Correlation between the detection signiﬁcance (sD,4–10keV) and the
90% conﬁdence limit of the separation angles between the MAXI sources andtheir possible counterparts. The data (black crosses) can be described as(A s D,4 – 10 keV ) B + C 2 (blue solid line), where A=2.27±0.05, B=
1.74±0.02, and C=0.047±0.001.

where Fi, ΔFi, Fconst, and f denote the best-ﬁt ﬂux, statisticaluncertainty, 7-year averaged ﬂux, and systematic error (i.e.,1.4%), respectively, at the ith time bin. TSvar follows thechi-squared distribution when the number of bins is large. IfTSvar>18.48, we can reject the null hypothesis that the ﬂux
is constant at the 99% conﬁdence level for 7 degrees of
freedom. Next, we derive the excess variance (s 2rms) following

4. Counterparts of Detected X-Ray Sources
4.1. Positional Cross-matching with Other X-Ray Catalogs
Identiﬁcation of the X-ray sources is an important task for thestatistical use of the catalog. To ﬁnd possible counterparts of our

10The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

Kawamuro et al.

Figure 9. Histograms of the HRs. Here the MAXI sources are categorized into four types: AGN (blue), galaxy cluster (green), Galactic/SMC/LMC source (red), andothers (gray).

Table 4
Numbers of MAXI Sources Positionally Matched with Other Catalogs
Catalog Name

BAT1054U

XTEASMLONGMCXCXMMSL2

1RXS

One Catalog Onlya

BAT1054U
XTEASMLONGMCXCXMMSL2
1RXS

239(243)b
L
L
L
L
L

10
17(17)b
L
L
L
L

77
12
94(95)b
L
L
L

10
4
1
152(164)b
L
L

97
8
43
16
198(226)b
L

133
11
61
66
98
250(251)b

75
2
5
82
77
48

Notes. The numbers of MAXI sources matched with both catalogs given in the ﬁrst column and ﬁrst row are listed.
a
Numbers of the MAXI sources matched only with one catalog given in the ﬁrst column.
b
Numbers in parentheses represent those of total matched sources in each catalog.

catalog sources including the transients (hereafter we call them“the third MAXI sources”), we spatially cross-match them tothose in other X-ray catalogs in the following order: the Swift/
BAT 105-month catalog (BAT105; Oh et al. 2018), the Uhuru
fourth catalog (4U; Forman et al. 1978), the RXTE All-Sky
Monitor long-term observed source table (XTEASMLONG16),
Meta-Catalog of X-Ray Detected Clusters of Galaxies (MCXC;
Piffaretti et al. 2011), the XMM-Newton slew survey catalog(XMMSL217), and the ROSAT all-sky survey bright source
catalog (1RXS; Voges et al. 1999). To reduce false identiﬁcations, we only take account of XMMSL2 and 1RXS sourcesbrighter than >1.0×10−12 erg cm−1 s−1 and >0.30 countss−1,
respectively. This is a ﬂux corresponding to 0.3 mCrab when the
Crab spectrum is assumed. The statistical positional errors of thethird MAXI sources (σstat) are evaluated as dx 2 + dy 2 , where dx
and dy are one-dimensional spatial errors in perpendicular
directions at the 1σ level. A systematic error (σsys) is further
22+ s sys
added to the statistical ones as spos = s stat
. We adopt
σsys=0°. 03, determined to self-consistently match the crossmatching result (see Section 4.3 and Figure 8). Here, we identify acounterpart if its position falls within 2.5σpos of a third MAXI
source. Using several representative sources, we have veriﬁed thatthe radius of 2.5σstat typically corresponds to that of the 95%
conﬁdence contour for the source positions where the C value inEquation (1) is increased from the best value by 6.0. The positional
errors in the reference catalogs are ignored. Note that if we ﬁnd
more than one source as counterpart candidates, we list the object
nearest to the MAXI position. The cross-matching result issummarized in Table 2, and the numbers of the positionallymatched MAXI sources are listed in Table 4. The breakdown of
16
17

Table 5
Numbers of Sources in Each Category
Category

Number of Sources

Unknowna
Galaxy clusters
Galaxies
Seyfert galaxies
Blazars
Cataclysmic variables/stars
Pulsars
X-ray binaries
Confused
Unmatchedb

14
135
2
142
48
54
2
24
1
260

Total

682

Notes.
a
Sources that have possible counterparts in at least one of the cross-matchedcatalogs but have no classiﬁcation.
b
Sources that have no counterparts in the cross-matched catalogs.

the source types is seen in Table 5. The counterparts of thetransients (Section 3.2) are also identiﬁed from the Swift/BAT
Hard X-ray Transient Monitor catalog18 in the same manner, butwith the 3.0σ positional errors, because the probability of false
matching is much lower than in the other cases (see Section 4.2).
In some cases, we suspect that a matched counterpart is
likely incorrect, judging from the X-ray properties (i.e., thetime variability, HRs, and observed ﬂuxes). Also, some brightgalaxy clusters are not identiﬁed from the automatic crossmatching. This could be because our PSF model is developed
so that it reproduces a point source and would not properly ﬁt

https://heasarc.gsfc.nasa.gov/W3Browse/xte/xteasmlong.html
https://www.cosmos.esa.int/web/xmm-newton/xmmsl2-ug

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Kawamuro et al.

Figure 10. Scatter plots between the HRs and the 4–10 keV ﬂux. The color deﬁnition is the same as in Figure 3.

Figure 11. X-ray color–color plots among the three HRs. The ﬁlled stars and dot-dashed lines illustrate the HR track for a power-law model without intrinsic
absorption. The stars from upper right to lower left correspond to photon indices from 1.0 to 3.0 with a step of 0.5. The open stars and dashed lines present the track for
an absorbed power-law model with a photon index of 1.8. The open stars from lower left to upper right correspond to logNH/cm−2 from 20.0 to 24.0 with a step of
1.0 The color deﬁnition is the same as those in Figure 3.

we ﬁt the data with the same equation as that in Hiroi et al.
(2013), (A sD,4 – 10 keV ) B + C 2 . The best-ﬁt parameters areA=2.27±0.05, B=1.74±0.02, and C=0.047±0.001,
suggesting the systematic error at a 90% conﬁdence limit of≈0°. 047. The corresponding 1σ error is ∼0°. 03. The systematic
error is successfully reduced from the previous works (≈0°. 05;
Hiroi et al. 2011, 2013).

such extended sources. More plausible counterparts for them
are listed in the catalog, with the associated comments in
Column (9).
4.2. Probability of Chance Coincidence
The above cross-matching is based only on the separation
angles between the MAXI and other reference sources, and somecounterparts are incorrectly identiﬁed because they just coincidentally fall within the positional error of a third MAXI source.
We derive the expected number of such events by combining
integrated positional errors of the MAXI sources used for eachcross-matching and source number densities (i.e., source number
divided by our survey area) of the reference catalogs. We ﬁnd that10, 1, 2, 11, 11, and 7 MAXI sources may be misidentiﬁed inreferring to BAT105, 4U, XTEASMLONG, MCXC, XMMSL2,
and 1RXS, respectively. Note that due to the incomplete all-sky
survey of XMMSL2, its derived value should be regarded as alower limit. If we use only MCXC and Swift/BAT 105-monthcatalogs, similarly to the case of Hiroi et al. (2013), who used
MCXC and the Swift/BAT 70-month catalog (Baumgartner
et al. 2013), the expected fraction of the false identiﬁcation is∼0.03. This remains at the same level as in the 37-month catalog,in spite of the increased source number in the 7-year MAXI and
Swift/BAT 105-month catalogs. This small value is likely because
the systematic errors of the PSF model are reduced in our catalog.

5. Statistical Properties of Our Catalog
5.1. Correlations among X-Ray Properties
In this section, we describe basic properties of our catalog
based on the parameters constrained so far: the ﬂuxes, the HRs,
and the time variability index (TSvar). Here, we simply
categorize the third MAXI sources into four types: AGN(i.e., Seyfert galaxies and blazars), galaxy cluster, Galactic/
Small/Large Magellanic Cloud (SMC/LMC) source (i.e.,
cataclysmic variables/stars, X-ray binaries, and pulsars), andthe others. The HR distributions are shown in Figure 9, and thescatter plots between the HRs and the 4–10 keV ﬂuxes areshown in Figure 10. A noticeable point is that the HRs of
AGNs are typically harder than those of the galaxy clusters.
The difference is more clearly seen in the HRs using the
10–20 keV band. This is likely to be a natural consequence ofthe difference in their typical spectra; galaxy clusters are brightin soft X-ray bands by optically thin thermal emission, whereas
AGNs exhibit harder spectral proﬁles, roughly described with apower-law component with a photon index of ∼1.4–2.4 (e.g.,
Ueda et al. 2014; Kawamuro et al. 2016b). Strong absorption,
often seen in AGNs, hardens their spectrum even more, andthereby higher HRs are expected. A more detailed view can beobtained from X-ray color–color plots in Figure 11, which

4.3. Systematic Positional Error
Using the results in Section 4.1, we examine the separation
angles between the MAXI sources and their possible counterparts as a function of the detection signiﬁcance (sD,4–10 keV).
Figure 8 plots the 90% conﬁdence limit of the separation
angles, estimated in each signiﬁcance bin. For consistency,
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Kawamuro et al.

Figure 12. Left: histogram of the time variability index (TSvar). The color deﬁnition is the same as that in Figure 9. Right: scatter plot between the 4–10 keV ﬂux andTSvar. The colors are the same as in Figure 3. In both ﬁgures, variable sources are located in the area of TSvar>18.48 (dashed line), corresponding to a 99%
conﬁdence limit.

Figure 13. Scatter plots between the HRs and TSvar. The colors are the same as in Figure 3.

overplots HR tracks predicted from a single (absorbed) powerlaw model based on Figure 4.
Figure 12 shows the histogram of the time variability index(TSvar) and its scatter plot against the 4–10 keV ﬂux. Also,
Figure 13 plots the HRs with respect to TSvar. Most of thegalaxy clusters have no signiﬁcant ﬂux variation, withTSvar<18.48, but there are two exceptions showing moderate
TSvar values of ≈30. One is 3MAXI J1231+122, identiﬁed as
the Virgo Cluster, and this apparent variability may be due touncertainties associated with our PSF model, which assumes apoint source, and/or the presence of an AGN in M87 (Wonget al. 2017). The other source, 3MAXI J1702+339, is locatednear the bright, variable source Her X-1, and part of its ﬂux
could be contaminated by Her X-1, causing the fake variability.
Figure 14. Scatter plot between the 4–10 keV and 14–195 keV ﬂuxes for
MAXI sources having a single counterpart in the Swift/BAT 105-monthcatalog. The 4–10 keV ﬂuxes are calculated with a conversion factor of
1.21×10−11 erg cm−2 s−1 mCrab−1, while the 14–195 keV ones are retrieved
from the Swift/BAT 105-month catalog (Oh et al. 2018). Dashed lines present
the relations for an unabsorbed power-law spectrum with different photon
indices: Γ=2.5 (black), Γ=2.0 (red), and Γ=1.7 (blue).

5.2. Comparison with the Swift/BAT 105-month Catalog
Here we brieﬂy view the nature of the third MAXI sourcesthat have a single counterpart in the BAT105. Figure 14 plots
the correlation between the 4–10 keV and 14–195 keV ﬂuxes,
together with the ﬂux ratios predicted from unabsorbed powerlaw models with three different photon indices (Γ=1.7, 2.0,
and 2.5). Note that we use the 4–10 keV ﬂuxes estimatedthrough the conversion factor of 1.21×10−11 erg cm−2 s−1
mCrab−1, while the 14–195 keV ﬂuxes are retrieved from Oh
et al. (2018). As seen in Figure 14, most of the MAXI sources
have soft spectra, corresponding to photon indices larger
than 1.7.

5.3. logN–logS Relation
We present the logN–logS relation, the cumulative ﬂux
distributions of the sources detected at sD,4–10 keV 6.5. To
derive it, we estimate the sensitivity at every sky position by
combining the background counts and the effective exposure
map, given in Figure1 of Hori et al. (2018). The effective
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Kawamuro et al.

than that expected for sources uniformly distributed in astatic Euclidean universe (i.e., N (>S)∝S−1.5). This may bepartially caused by the Eddington bias (i.e., fainter sources
than the sensitivity limit emerge owing to statisticalﬂuctuation).
6. Summary
We have provided the third MAXI/GSC X-ray source
catalog in the high-latitude sky (b>10°) utilizing the ﬁrst
7-year (2009 August 13 to 2016 July 31) data in the 4–10 keVband. The catalog contains 682 X-ray sources detected atsD,4–10 keV 6.5. Over half of the survey area, the 4–10 keVband sensitivity reaches ∼5.9×10−12 erg cm−2 s−1, which is
the highest ever achieved as an all-sky X-ray survey in a similarenergy band. The source number has increased by a factor of≈1.4 compared with the 37-month MAXI/GSC catalog (Hiroi
et al. 2013), which adopted sD,4–10 keV 7 as the detection
threshold. We have cross-matched the cataloged sources withthose in the other X-ray catalogs (BAT105, 4U, XTEASMLONG, MCXC, XMMSL2, and 1RXS) and found thecounterparts of 422 sources.
In addition to the basic properties in the 4–10 keV band, we
provide the 7-year averaged ﬂuxes in the 3–4 keV, 10–20 keV,and 3–10 keV bands, as well as their HRs. The HRs,
particularly the ones using the 10–20 keV ﬂuxes, seem to be
the most helpful to discriminate between AGNs and galaxy
clusters. We have also built the database of the 1-year-bin
4–10 keV light curves, with their variability index (TSvar) andthe excess variance (σ2rms). We ﬁnd that the compact objects,
such as X-ray binaries and AGNs, show strong variability(TSvar>18.48), demonstrating that the variability is a key touncovering the nature of unidentiﬁed X-ray sources. Future
follow-up observations with a higher spatial and timing
resolution are encouraged to associate the unidentiﬁed sourcesin our catalog with those in other catalogs, for improving thecompleteness of the catalog so that it can be used in statisticalstudies.
We have searched the 1-year time-sliced data for transient
sources (Section 3.2) and found four objects that are notdetected from the 7-year accumulated data (Table 3). They areindeed classiﬁed as transient compact objects (i.e., X-ray
binary, pulsar, and AGN/tidal disruption event).

Figure 15. Top panel: survey area plotted against 4–10 keV ﬂux for the
MAXI/GSC 7-year survey at ∣b∣ > 10. Bottom panel: logN–logS relation in
the integral form.

We thank Kyuseok Oh for providing the Swift/BAT 105month catalog prior to the ofﬁcial publication. Part of this work
was ﬁnancially supported by the Grant-in-Aid for JSPS Fellows
for young researchers (T.K. and T.H.), for Scientiﬁc Research
17H06362 (Y.U., N.K., T.M., H.N., and A.Y.) and 17K05384(Y.U.), and for Young Scientists (B) 16K17672 (M.S.). M.S.
acknowledges support by the Special Postdoctoral Researchers
Program at RIKEN. This research has made use of MAXI data
provided by RIKEN, JAXA, and the MAXI team.

exposure map, in units of cm2 s, is estimated via simulation of
the cosmic X-ray background, with uniform brightness (seeHori et al. 2018, for more details). The survey area as afunction of the sensitivity (i.e., the area curve) is displayed in
the top panel of Figure 15. From this curve, we can ﬁnd that
our survey is complete, in half of the high Galactic latitude sky(∣b∣ > 10), down to 5.9×10−12 erg cm−2 s−1, superior to the
37-month catalog (i.e., 7.5 × 10−12 erg cm−2 s−1; Hiroi et al.
2013). The deepest sensitivity of ∼4×10−12 erg cm−2 s−1isconsistent with the lowest ﬂux among the actually detectedsources.
We divide the number of sources with ﬂuxes of S∼S+dS
by the survey area at S and obtain the logN–logS relation in
the differential form. By integrating it, we obtain the number
density N (>S) of total sources having ﬂuxes above S (bottom
panel of Figure 15). At ﬂuxes lower than 8×10−11 ergs
cm−2 s−1, the logN–logS relation has a slightly steeper slope

ORCID iDs
T. Kawamuro https://orcid.org/0000-0002-6808-2052
Y. Ueda https://orcid.org/0000-0001-7821-6715
T. Hori https://orcid.org/0000-0001-8204-790X
N. Kawai https://orcid.org/0000-0001-9656-0261
A. Tanimoto https://orcid.org/0000-0002-0114-5581
Y. Tsuboi https://orcid.org/0000-0001-9943-0024
Y. Sugawara https://orcid.org/0000-0001-6749-1199
14

The Astrophysical Journal Supplement Series, 238:32 (15pp), 2018 October

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