# The Tarantula–Revealed by X-rays (T-ReX)

Leisa K. Townsley Deceased. This paper is part of a collection publishing
posthumously the unfinished work of Leisa K. Townsley. Her coauthors completed
the manuscript based on her initial draft, written notes and private
communications.  Department of Astronomy & Astrophysics, 525 Davey Laboratory,
Pennsylvania State University, University Park, PA 16802 USA  Patrick S. Broos
Department of Astronomy & Astrophysics, 525 Davey Laboratory, Pennsylvania
State University, University Park, PA 16802 USA  Matthew S. Povich Department
of Physics & Astronomy, California State Polytechnic University, 3801 West
Temple Ave, Pomona, CA 91768 USA Matthew S. Povich<EMAIL_ADDRESS>
(Received March 21, 2024; Accepted 15 April 2024)

###### Abstract

The Tarantula Nebula (30 Doradus) is the most important star-forming complex
in the Local Group, offering a microscope on starburst astrophysics. At its
heart lies the exceptionally rich young stellar cluster R136, containing the
most massive stars known. Stellar winds and supernovae have carved 30 Dor into
an amazing display of arcs, pillars, and bubbles. We present first results and
advanced data processing products from the 2-Ms Chandra X-ray Visionary
Project, “The Tarantula – Revealed by X-rays” (T-ReX). The 3615 point sources
in the T-ReX catalog include massive stars, compact objects, binaries, bright
pre-main-sequence stars and compact young stellar (sub)clusters in 30 Dor.
After removing point sources and excluding the exceptionally bright supernova
remnant N157B (30 Dor B), the global diffuse X-ray maps reveal hot plasma
structures resolved at 1–10 pc scales, with an absorption-corrected total-band
(0.5–7 keV) X-ray luminosity of $2.110\times 10^{37}$ erg s-1. Spatially-
resolved spectral modeling provides evidence for emission lines enhanced by
charge-exchange processes at the interfaces. We identify a candidate for the
oldest X-ray pulsar detected to date in 30 Dor, PSR J0538-6902, inside a
newly-resolved arctuate X-ray wind nebula, the Manta Ray. The long time
baseline of T-ReX monitored dozens of massive stars, several showing periodic
variability tied to binary orbital periods, and captured strong flares from at
least three low-mass Galactic foreground stars.

H II regions (694), High energy astrophysics (739), Early-type stars (430),
Star formation (1569), Interstellar medium (847), Superbubbles (1656)

††journal: ApJS††facilities: CXO (ACIS), Gaia, ESO:VISTA (VIRCAM), VLT:Kueyen
(FLAMES-ARGUS), HST (WFC3, ACS), Spitzer (IRAC, MIPS), WISE Herschel
(SPIRE)††software:  ACIS Extract (Broos et al., 2010, 2012; Broos & Townsley,
2016), CIAO (Fruscione et al., 2006), DS9 (Joye & Mandel, 2003), MARX (Davis
et al., 2012) XSPEC (Arnaud, 1996).

##  1 30 Doradus: A Field of Superlatives

The Tarantula Nebula (30 Doradus, or 30 Dor), located in the Large Magellanic
Cloud (LMC), is the most powerful massive star-forming region (MSFR) in the
Local Group of galaxies. 30 Dor is unlike any Galactic MSFR; with no
differential galactic rotation to rip the complex apart, it persists and grows
at the confluence of two supergiant shells (Meaburn, 1980) that have provided
it with the fuel to power massive star formation for at least 25 Myr (Cignoni
et al., 2015), reaching starburst proportions. Today it is dominated by its
1–2 Myr-old central massive cluster R136, containing the richest young stellar
population in the Local Group, including the most massive stars known. Also in
contrast to Galactic MSFRs, the location of 30 Dor in the LMC offers us a
nearly face-on, low-metallicity starburst laboratory with low intervening
absorption and a well-known distance. Pietrzyński et al. (2019) refined the
distance to the LMC to 49.5 kpc, but we assume a 50 kpc distance to 30 Dor to
facilitate comparison with other recent studies (e.g., Sabbi et al., 2013;
Cheng et al., 2021; Chen et al., 2023). At this distance, the spatial scale is
0.24 pc/arcsec.

R136 produces ${\sim}1000$ times the ionizing radiation of Orion (Conti et
al., 2012) from at least five times as many early O-type stars as Carina
(Evans et al., 2011). It contains several of the most massive stars known
(Crowther et al., 2010) and the full complement of massive binaries, including
WR–WR, WR–O, and O–O systems (Crowther & Dessart, 1998). In the wider 30 Dor
field, the presence of $\sim$25 Myr-old evolved supergiants and embedded
massive young stellar objects shows that 30 Dor is the product of multiple
epochs of star formation (Walborn & Blades, 1997; Whitney et al., 2008); the
newest generation of embedded stars may represent triggered collapse from the
effects of R136 (Walborn et al., 2013).

We present the 2 Ms Chandra X-ray Visionary Project, “The Tarantula—Revealed
by X-rays” (T-ReX), an intensive imaging study of 30 Dor with the Advanced CCD
Imaging Spectrometer (ACIS) instrument (Garmire et al., 2003) of the Chandra
X-ray Observatory. Before T-ReX, Chandra had invested just 114 ks in this
iconic target, revealing only the most massive stars and large-scale diffuse
structures (Townsley et al., 2006a, b, 2014). T-ReX leverages the unparalleled
X-ray spatial resolution of Chandra, a unique resource that will remain
unmatched for another decade, revealing the X-ray properties of dozens of low-
metallicity massive stars (see Crowther et al., 2022, hereafter C22) and
parsec-scale shocks from winds and supernovae that are shredding its
interstellar medium (ISM; the main science focus of this contribution, but see
also Cheng et al., 2021; Chen et al., 2023). This definitive Chandra
characterization of 30 Dor was motivated by the fundamental need to understand
the complex machinery of a starburst. Massive stars, their remnants, and the
lower-mass populations that accompany them exert a profound influence on dense
molecular clouds through radiation and mechanical feedback, which both
perpetuates and quenches star formation. T-ReX unveils the detailed spatial
and spectral morphology of hot plasmas permeating the complex cold ISM
structures, ionization fronts, and photon-dominated regions seen in optical
and infrared (IR) images.

This paper is organized as follows: Section 2 describes the T-ReX observations
and data processing, culminating in the publicly-available point-source
catalog and other advanced data products. High-level descriptions and
interpretation of the T-ReX images and point-source populations are presented
in Sections 3 and 4, respectively. Section 5 presents our deeper dive into
spatially-resolved spectral fitting analysis of the T-ReX diffuse emission and
its physical properties. A brief summary of the anticipated legacy value of
T-ReX is included in Section 6. Finally, two Appendices present more detailed
analysis of select point-sources: Appendix A details the challenges of
matching T-ReX point-sources to optical/IR source catalogs and presents tables
of high-reliability matching results. Appendix B presents light-curves and
basic properties of notable X-ray variable sources, including massive stellar
systems with periodic variability and low-mass stars exhibiting strong X-ray
flares.

##  2 Chandra Observations and Data Analysis

###  2.1 Observations

T-ReX obtained 51 Chandra imaging observations, using the 4 ACIS-I detectors
plus the two central ACIS-S detectors, with an aimpoint near R136 over the
period 2014 May 3 through 2016 January 22 (Table 1). The extreme ecliptic
latitude ($-87\arcdeg$) of 30 Dor limited T-ReX to 2 Ms due to spacecraft
thermal constraints. Including three archival observations of 30 Dor from 2006
January brings the total exposure time to 2.05 Ms. The exposure map for all 54
observations, with detected point sources overlaid (see Section 2.3), is
presented in Figure 1. Due to the various, arbitrary roll angles among the
observations, the final exposure map resembles a daisy flower, with the two
S-array detectors arranged like petals around a central disk created by
rotating the four ACIS-I detectors. Both the greatest exposure time and on-
axis point-source sensitivity are hence obtained within the central portions
of ACIS-I (Figure 1b).

Table 1:  Log of Chandra Observations

| ObsID | Start Date | ExposureaaSource “labels” identify each source during data analysis, as the source position (and thus the Name) is subject to change. | On-axis PositionbbACIS ObsIDs are shifted to align with our astrometric reference catalog, composed of 20 stars chosen from the VISTA Magellanic Survey (Cioni et al., 2011, VMC) and Two Micron All Sky Survey (2MASS, Skrutskie et al., 2006). | Roll |  |  |  | TGAINccThe suffixes “_t”, “_s”, “_h”, and “_v” on source validation p-values (“ProbNoSrc_*”) designate the 0.5–7 keV, 0.5–2 keV, 2–7 keV, and 4–7 keV energy bands. |  | ShiftddDue to dithering over inactive portions of the focal plane, a Chandrasource often is not observed during some fraction of the nominal exposure time (http://cxc.harvard.edu/ciao/why/dither.html). We report here the CIAO quantity “FRACEXPO” produced by the tool mkarf.
---|---|---|---|---|---|---|---|---|---|---|---
|  | (UT) | (s) | $\alpha_{\rm J2000}$ | $\delta_{\rm J2000}$ | (°) |  |  |  |  |  | (SKY pixel)
| 10.25574/05906 (catalog 5906) | 2006-01-21 | 12317 | 05:38:43.92 | -69:06:16.3 | 323 |  |  |  | 2005-11-01N6 |  | (-0.285, -0.315)
| 10.25574/07263 (catalog 7263) | 2006-01-22 | 42528 | 05:38:43.96 | -69:06:16.4 | 323 |  |  |  | 2005-11-01N6 |  | (-0.120, -0.254)
| 10.25574/07264 (catalog 7264) | 2006-01-30 | 37593 | 05:38:43.54 | -69:06:17.4 | 314 |  |  |  | 2005-11-01N6 |  | (-0.076, -0.417)
| 10.25574/16192 (catalog 16192) | 2014-05-03 | 93761 | 05:38:39.69 | -69:06:28.1 | 222 |  |  |  | 2014-05-01N6_revA |  | (+0.305, -1.001)
| 10.25574/16193 (catalog 16193) | 2014-05-08 | 75993 | 05:38:39.31 | -69:06:26.8 | 218 |  |  |  | 2014-05-01N6_revA |  | (+0.119, -0.957)
| 10.25574/16612 (catalog 16612) | 2014-05-11 | 22672 | 05:38:39.31 | -69:06:26.8 | 218 |  |  |  | 2014-05-01N6_revA |  | (-0.048, -0.662)
| 10.25574/16194 (catalog 16194) | 2014-05-12 | 31333 | 05:38:38.87 | -69:06:24.9 | 212 |  |  |  | 2014-05-01N6_revA |  | (+0.480, -1.665)
| 10.25574/16615 (catalog 16615) | 2014-05-15 | 45170 | 05:38:38.86 | -69:06:25.0 | 212 |  |  |  | 2014-05-01N6_revA |  | (-0.193, -0.727)
| 10.25574/16195 (catalog 16195) | 2014-05-24 | 44405 | 05:38:38.20 | -69:06:21.4 | 202 |  |  |  | 2014-05-01N6_revA |  | (+0.928, -1.448)
| 10.25574/16196 (catalog 16196) | 2014-05-30 | 67109 | 05:38:38.19 | -69:06:21.4 | 202 |  |  |  | 2014-05-01N6_revA |  | (+0.323, -0.942)
| 10.25574/16617 (catalog 16617) | 2014-05-31 | 58860 | 05:38:38.19 | -69:06:21.3 | 202 |  |  |  | 2014-05-01N6_revA |  | (+1.063, -1.710)
| 10.25574/16616 (catalog 16616) | 2014-06-03 | 34530 | 05:38:38.19 | -69:06:21.3 | 202 |  |  |  | 2014-05-01N6_revA |  | (+0.008, -0.746)
| 10.25574/16197 (catalog 16197) | 2014-06-06 | 67790 | 05:38:38.19 | -69:06:21.3 | 202 |  |  |  | 2014-05-01N6_revA |  | (+0.911, -1.483)
| 10.25574/16198 (catalog 16198) | 2014-06-11 | 39465 | 05:38:37.45 | -69:06:14.9 | 187 |  |  |  | 2014-05-01N6_revA |  | (+1.397, -1.247)
| 10.25574/16621 (catalog 16621) | 2014-06-14 | 44400 | 05:38:37.44 | -69:06:14.9 | 187 |  |  |  | 2014-05-01N6_revA |  | (+1.211, -1.110)
| 10.25574/16200 (catalog 16200) | 2014-06-26 | 27360 | 05:38:37.01 | -69:06:06.8 | 170 |  |  |  | 2014-05-01N6_revA |  | (+1.720, -0.801)
| 10.25574/16201 (catalog 16201) | 2014-07-21 | 58390 | 05:38:37.14 | -69:05:54.0 | 145 |  |  |  | 2014-05-01N6_revA |  | (+0.158, -0.038)
| 10.25574/16640 (catalog 16640) | 2014-07-24 | 61679 | 05:38:37.15 | -69:05:54.0 | 145 |  |  |  | 2014-05-01N6_revA |  | (+0.594, -0.135)
| 10.25574/16202 (catalog 16202) | 2014-08-19 | 65128 | 05:38:38.53 | -69:05:41.8 | 117 |  |  |  | 2014-08-01N6_revA |  | (+0.561, +0.312)
| 10.25574/17312 (catalog 17312) | 2014-08-22 | 44895 | 05:38:38.53 | -69:05:41.8 | 117 |  |  |  | 2014-08-01N6_revA |  | (+0.481, +0.346)
| 10.25574/16203 (catalog 16203) | 2014-09-02 | 41422 | 05:38:39.63 | -69:05:37.4 | 102 |  |  |  | 2014-08-01N6_revA |  | (+0.243, +0.248)
| 10.25574/17413 (catalog 17413) | 2014-09-08 | 24650 | 05:38:39.63 | -69:05:37.3 | 102 |  |  |  | 2014-08-01N6_revA |  | (+0.718, +0.789)
| 10.25574/17414 (catalog 17414) | 2014-09-13 | 17317 | 05:38:40.32 | -69:05:35.5 | 94 |  |  |  | 2014-08-01N6_revA |  | (+0.356, -0.146)
| 10.25574/16442 (catalog 16442) | 2014-10-25 | 48350 | 05:38:44.49 | -69:05:35.6 | 50 |  |  |  | 2014-08-01N6_revA |  | (-0.138, -0.336)
| 10.25574/17545 (catalog 17545) | 2014-10-28 | 34530 | 05:38:44.50 | -69:05:35.5 | 50 |  |  |  | 2014-08-01N6_revA |  | (-0.071, -0.008)
| 10.25574/17544 (catalog 17544) | 2014-11-01 | 25642 | 05:38:44.49 | -69:05:35.7 | 50 |  |  |  | 2014-11-01N6 |  | (+0.015, -0.032)
| 10.25574/16443 (catalog 16443) | 2014-11-14 | 34530 | 05:38:45.51 | -69:05:38.5 | 38 |  |  |  | 2014-11-01N6 |  | (-0.014, +0.069)
| 10.25574/17486 (catalog 17486) | 2014-12-04 | 33541 | 05:38:47.19 | -69:05:48.3 | 12 |  |  |  | 2014-11-01N6 |  | (+0.257, -0.702)
| 10.25574/17555 (catalog 17555) | 2014-12-06 | 55246 | 05:38:47.18 | -69:05:48.3 | 12 |  |  |  | 2014-11-01N6 |  | (+0.557, -0.761)
| 10.25574/17561 (catalog 17561) | 2014-12-20 | 54567 | 05:38:47.86 | -69:05:58.9 | 350 |  |  |  | 2014-11-01N6 |  | (+0.707, -0.514)
| 10.25574/17562 (catalog 17562) | 2014-12-25 | 42031 | 05:38:47.85 | -69:05:58.9 | 350 |  |  |  | 2014-11-01N6 |  | (+0.602, -0.204)
| 10.25574/16444 (catalog 16444) | 2014-12-27 | 41440 | 05:38:47.85 | -69:05:58.9 | 350 |  |  |  | 2014-11-01N6 |  | (+0.270, -0.188)
| 10.25574/16448 (catalog 16448) | 2015-02-14 | 34599 | 05:38:46.12 | -69:06:24.6 | 295 |  |  |  | 2015-02-01N6 |  | (+0.722, -0.198)
| 10.25574/17602 (catalog 17602) | 2015-02-19 | 51705 | 05:38:46.12 | -69:06:24.5 | 295 |  |  |  | 2015-02-01N6 |  | (+1.587, +0.330)
| 10.25574/16447 (catalog 16447) | 2015-03-26 | 26868 | 05:38:43.31 | -69:06:31.8 | 262 |  |  |  | 2015-02-01N6 |  | (+0.243, +0.421)
| 10.25574/16199 (catalog 16199) | 2015-03-27 | 39461 | 05:38:43.31 | -69:06:31.9 | 262 |  |  |  | 2015-02-01N6 |  | (+0.287, +0.669)
| 10.25574/17640 (catalog 17640) | 2015-03-31 | 26318 | 05:38:43.31 | -69:06:31.9 | 262 |  |  |  | 2015-02-01N6 |  | (+0.326, +0.421)
| 10.25574/17641 (catalog 17641) | 2015-04-04 | 24638 | 05:38:43.32 | -69:06:31.9 | 262 |  |  |  | 2015-02-01N6 |  | (+0.969, +1.656)
| 10.25574/16445 (catalog 16445) | 2015-05-27 | 49310 | 05:38:37.81 | -69:06:19.1 | 196 |  |  |  | 2015-05-01N6 |  | (+0.286, +0.166)
| 10.25574/17660 (catalog 17660) | 2015-05-29 | 38956 | 05:38:37.81 | -69:06:19.1 | 196 |  |  |  | 2015-05-01N6 |  | (-0.023, +0.124)
| 10.25574/16446 (catalog 16446) | 2015-06-02 | 47547 | 05:38:37.68 | -69:06:18.1 | 193 |  |  |  | 2015-05-01N6 |  | (+0.117, +0.072)
| 10.25574/17642 (catalog 17642) | 2015-06-08 | 34438 | 05:38:37.44 | -69:06:15.6 | 188 |  |  |  | 2015-05-01N6 |  | (+0.182, -0.065)
| 10.25574/16449 (catalog 16449) | 2015-09-28 | 24628 | 05:38:41.66 | -69:05:33.6 | 80 |  |  |  | 2015-08-01N6 |  | (-1.468, -0.353)
| 10.25574/18672 (catalog 18672) | 2015-11-08 | 30574 | 05:38:45.82 | -69:05:39.8 | 34 |  |  |  | 2015-11-01N6 |  | (-0.480, -1.424)
| 10.25574/18706 (catalog 18706) | 2015-11-10 | 14776 | 05:38:45.80 | -69:05:39.7 | 34 |  |  |  | 2015-11-01N6 |  | (-0.889, -1.345)
| 10.25574/18720 (catalog 18720) | 2015-12-02 | 9832 | 05:38:45.30 | -69:05:58.0 | 357 |  |  |  | 2015-11-01N6 |  | (-0.563, -1.301)
| 10.25574/18721 (catalog 18721) | 2015-12-08 | 25598 | 05:38:44.95 | -69:05:54.0 | 12 |  |  |  | 2015-11-01N6 |  | (+0.040, -1.745)
| 10.25574/17603 (catalog 17603) | 2015-12-09 | 13778 | 05:38:45.02 | -69:05:55.1 | 8 |  |  |  | 2015-11-01N6 |  | (+0.155, -1.927)
| 10.25574/18722 (catalog 18722) | 2015-12-11 | 9826 | 05:38:45.16 | -69:05:56.0 | 3 |  |  |  | 2015-11-01N6 |  | (-0.510, -1.237)
| 10.25574/18671 (catalog 18671) | 2015-12-13 | 25617 | 05:38:45.17 | -69:05:56.1 | 3 |  |  |  | 2015-11-01N6 |  | (-0.465, -1.112)
| 10.25574/18729 (catalog 18729) | 2015-12-21 | 16742 | 05:38:45.18 | -69:05:56.1 | 3 |  |  |  | 2015-11-01N6 |  | (+0.500, -1.643)
| 10.25574/18750 (catalog 18750) | 2016-01-20 | 48318 | 05:38:45.44 | -69:06:07.5 | 324 |  |  |  | 2015-11-01N6 |  | (+1.496, -0.875)
| 10.25574/18670 (catalog 18670) | 2016-01-21 | 14565 | 05:38:45.43 | -69:06:07.5 | 324 |  |  |  | 2015-11-01N6 |  | (+0.905, -0.902)
| 10.25574/18749 (catalog 18749) | 2016-01-22 | 22153 | 05:38:45.42 | -69:06:07.4 | 324 |  |  |  | 2015-11-01N6 |  | (+0.730, -1.058)
|  |  |  |  |  |  |  |  |  |  |

a  Exposure times are the net usable times after various filtering steps are
applied in the data reduction process. No exposure time needed to be removed
during periods of high instrumental background. The time variability of the
ACIS background is discussed in Section 6.16.3 of the Chandra Proposers’
Observatory Guide (http://asc.harvard.edu/proposer/POG/) and in the ACIS
Background Memos at http://asc.harvard.edu/cal/Acis/Cal_prods/bkgrnd/current/.

b  The On-axis Position is the time-averaged location of the optical axis
(CIAO parameters RA_PNT,DEC_PNT)
(http://cxc.harvard.edu/ciao/faq/nomtargpnt.html). Units of right ascension
($\alpha$) are hours, minutes, and seconds; units of declination ($\delta$)
are degrees, arcminutes, and arcseconds.

c  Abbreviated name of the ACIS Time-Dependent Gain file used for calibration
of event energies, e.g. “2002-02-01N6” = “acisD2002-02-01t_gainN0006.fits”.

d  The shift (in RA and Dec) applied to the ObsID’s aspect file (via the CIAO
tool wcs_update) to achieve astrometric alignment, expressed as (dx,dy) in the
Chandra “SKY” coordinate system
(http://asc.harvard.edu/ciao/ahelp/coords.html); 1 SKY pixel = 0.492
arcsecond. Note that astrometric shifts are correlated in time.

Figure 1: ACIS exposure map with 2743 brighter ($\geq$5 net counts) ACIS point
sources overlaid; colors denote median energy for each source. (a) The full
T-ReX field. (b) A zoom of (a) showing the central $\sim$10$\arcmin$ of the
ACIS field.

###  2.2 Data Analysis

####  2.2.1 Methods, software, and procedures

The algorithms, procedures, and tools used for data reduction, astrometric
alignment of observations, point source detection and validation, point source
extraction, point source masking, construction of smoothed diffuse emission
images, diffuse region extraction, and point source spectral fitting were the
same as those used in the second and third installments of our Massive star-
forming regions Omnibus X-ray Catalog (MOXC2 and MOXC3, Townsley et al., 2018,
2019). Please see those papers (and their references) for explanations of our
data analysis methods. Even though all T-ReX observations have similar
aimpoints, we followed our usual practice of extracting point sources and
diffuse regions from each observation, and then combining those extractions
and calibration products.

We employ a variety of standard and custom X-ray analysis software packages in
our workflows. ACIS data are manipulated and calibrated using the Chandra data
analysis system, CIAO111http://cxc.harvard.edu/ciao/ (Fruscione et al., 2006),
and the MARX222http://space.mit.edu/ASC/marx observatory simulator (Davis et
al., 2012). Throughout our workflow, data products are visually reviewed using
the SAOImage DS9333http://ds9.si.edu tool (Joye & Mandel, 2003) and
TOPCAT444http://www.star.bris.ac.uk/~mbt/topcat/ (Taylor, 2005). Models are
fit to extracted spectra using the
XSPEC555https://heasarc.gsfc.nasa.gov/xanadu/xspec/ tool (Arnaud, 1996). The
algorithms and scripts driving these standard tools are implemented in the
ACIS Extract (AE, Broos et al., 2010, 2012; Broos & Townsley, 2016) software
package666 The ACIS Extract software package and User’s Guide are publicly
available from the Astrophysics Source Code Library, from Zenodo, and at
http://personal.psu.edu/psb6/TARA/ae_users_guide.html.  and in a set of
detailed procedures we developed. AE and most other custom software we use are
written in the Interactive Data
Language777www.harrisgeospatial.com/ProductsandTechnology/Software/IDL.aspx
(IDL).

####  2.2.2 Alignment of Observations

When Chandra observations overlap, many data reduction tasks (e.g. source
detection, position estimation, source extraction) are compromised if the
misalignments among those observations are large (compared to the on-axis
PSF). Thus, our standard data analysis includes iterative re-alignment of the
observations to each other, and to an astrometric reference catalog. The
astrometric reference catalog chosen for T-ReX consists of 20 sources888 X-ray
sources p1_1194, p1_1234, p1_296, p1_1256, p1_1186, p1_611, p1_830, p1_995,
p1_682, p1_1033, p1_441, p1_639, p1_450, p1_1391, p1_1317, p1_686 have likely
counterparts in VMC. X-ray sources p1_711, p1_812, p1_911, p1_924 have likely
counterparts in 2MASS.  from the VMC and 2MASS catalogs that are likely
counterparts to bright and un-crowded X-ray sources observed less than 5′ off-
axis. The final shifts we applied to each observation, expressed in the
Chandra SKY coordinate system999https://cxc.harvard.edu/ciao/ahelp/coords.html
are reported in Table 1. We estimate remaining misalignment among the ObsIDs
to be approximately 0.02″.

###  2.3 Point Source Catalog

Extraction apertures for the 3615 point sources in the T-ReX catalog are
overlaid on an image of the full T-ReX event data in Figure 2. The catalog is
published as an electronic table accompanying this article, and its columns
are summarized in Table 2. The variation in both resolution and sensitivity as
a function of increasing off-axis angle $\theta$ are evident in the aperture
sizes (increasing) and point-source density (decreasing). Both event data and
point-source density decrease further in the S-array detectors farther off-
axis where the exposure time is unevenly reduced compared to the field center,
due to arbitrary roll angles (Figure 1).

The extraction aperture for each observation of a point source is usually a
contour of the local point spread function (PSF), chosen to enclose $\sim$90%
of the PSF for uncrowded observations or a reduced fraction to handle crowding
(Broos et al., 2010). We manually increased aperture sizes for the following
very bright sources: VFTS399 (Clark et al., 2015, source Label p1_610), Mk34
(Pollock et al., 2018, p1_995), R140a1/a2 (p1_752), Mk39 (p1_698), R144
(p1_1194), 053844.33-690554.7 (p1_1000), 053844.12-690556.6 (p1_979), SN1987A
(c73). Two bright and severely crowded sources, R136a (p1_832) and R136c
(p1_893), required hand-drawn apertures (see Fig. 1 of C22, and related
discussion of these sources as blends of multiple unresolved massive stars).

Table 2: T-ReX X-ray Source Properties

Column Label | Units | Description
---|---|---
Source identifiers
Name | $\cdots$ |  X-ray source name in IAU format; prefix is CXOU J
Label | $\cdots$ |  X-ray source name used within the projectaaSource “labels” identify each source during data analysis, as the source position (and thus the Name) is subject to change.
Source position, derived from the set of ObsIDs that minimized position
uncertainty (Broos et al., 2010, Section 6.2 and 7)
RAdeg | deg |  right ascension (ICRS)bbACIS ObsIDs are shifted to align with our astrometric reference catalog, composed of 20 stars chosen from the VISTA Magellanic Survey (Cioni et al., 2011, VMC) and Two Micron All Sky Survey (2MASS, Skrutskie et al., 2006).
DEdeg | deg |  declination (ICRS)bbACIS ObsIDs are shifted to align with our astrometric reference catalog, composed of 20 stars chosen from the VISTA Magellanic Survey (Cioni et al., 2011, VMC) and Two Micron All Sky Survey (2MASS, Skrutskie et al., 2006).
PosErr | arcsec |  1-$\sigma$ error circle around (RAdeg,DEdeg)
PosType | $\cdots$ |  algorithm used to estimate position (Broos et al., 2010, Section 7.1)
Validity metrics, derived from a pre-defined set of ObsID combinations
(Townsley et al., 2018, Section 2.2.3)
ProbNoSrc_MostValid | $\cdots$ |  smallest of ProbNoSrc_t, ProbNoSrc_s, ProbNoSrc_h, ProbNoSrc_v (Broos et al., 2010, Section 4.3 and Weisskopf et al., 2007, Appendix A2)ccThe suffixes “_t”, “_s”, “_h”, and “_v” on source validation p-values (“ProbNoSrc_*”) designate the 0.5–7 keV, 0.5–2 keV, 2–7 keV, and 4–7 keV energy bands.
ProbNoSrc_t | $\cdots$ |  smallest p-value under the no-source (0.5–7 keV) null hypothesis among validation merges
ProbNoSrc_s | $\cdots$ |  smallest p-value under the no-source (0.5–2 keV) null hypothesis among validation merges
ProbNoSrc_h | $\cdots$ |  smallest p-value under the no-source (2–7 keV) null hypothesis among validation merges
ProbNoSrc_v | $\cdots$ |  smallest p-value under the no-source (4–7 keV) null hypothesis among validation merges
IsOccasional | boolean |  flag indicating that source validation failed in all multi-ObsID merges; source validation comes from a single ObsID (Townsley et al., 2019, Section 3.1).
Variability indicators, derived from all ObsIDs
ProbKS_single | $\cdots$ |  $\min(P_{1},P_{2},\ldots P_{N\\_KS\\_single})$, where each $P_{i}$ is the p-value arising from a Kolmogorov–Smirnov test of event arrive times under the null hypothesis of no variability within a single observation
N_KS_single | observations |  number of p-values compared to produce ProbKS_single
ProbKS_merge | $\cdots$ |  p-value from a Kolmogorov–Smirnov test on the combined events from all observations; the null hypothesis is no variability on any time scale
ProbChisq_PhotonFlux | $\cdots$ |  p-value from a $\chi^{2}$ test on the single-ObsID measurements of PhotonFlux_t; the null hypothesis is no inter-ObsID variability
Observation details and photometric quantities, derived from all observations
of the source
ExposureTimeNominal | s |  total exposure time in merged ObsIDs
ExposureFraction | $\cdots$ |  fraction of ExposureTimeNominal that source was observedddDue to dithering over inactive portions of the focal plane, a Chandrasource often is not observed during some fraction of the nominal exposure time (http://cxc.harvard.edu/ciao/why/dither.html). We report here the CIAO quantity “FRACEXPO” produced by the tool mkarf.
RateIn3x3Cell | count/frame |  0.5:8 keV, in 3$\times$3 CCD pixel cellee Source properties in this table are not corrected for pile-up effects. RateIn3x3Cell is an estimate of the observed count rate falling on an event detection cell of size 3$\times$3 ACIS pixels, centered on the source position. When RateIn3x3Cell $>0.05$ (count/frame), the reported source properties may be biased by pile-up effects. See Section 2.6 for a list of source extractions confirmed to have significant pile-up.
NumObsIDs | observations |  total number of ObsIDs extracted
NumMerged | observations |  number of ObsIDs merged to estimate photometry properties
MergeBias | $\cdots$ |  fraction of exposure discarded in merge
Theta_Lo | arcmin |  smallest off-axis angle for merged ObsIDs
Theta | arcmin |  average off-axis angle for merged ObsIDs
Theta_Hi | arcmin |  largest off-axis angle for merged ObsIDs
PsfFraction | $\cdots$ |  average PSF fraction (at 1.5 keV) for merged ObsIDs
SrcArea | (0.492 arcsec)2 |  average aperture area for merged ObsIDs
AfterglowFraction | $\cdots$ |  suspected afterglow fractionffSome background events arising from an instrumental effect known as “afterglow” (http://cxc.harvard.edu/ciao/why/afterglow.html) may contaminate source extractions. After extraction, we attempt to identify afterglow events using the AE tool ae_afterglow_report, and report the fraction of extracted events attributed to afterglow; see the AE manual.
SrcCounts_t | count |  observed counts (0.5–8 keV) in merged apertures
SrcCounts_s | count |  observed counts (0.5–2 keV) in merged apertures
SrcCounts_h | count |  observed counts (2–8 keV) in merged apertures
BkgScaling | $\cdots$ |  scaling of the background extraction (Broos et al., 2010, Section 5.4)
BkgCounts_t | count |  observed counts (0.5–8 keV) in merged background regions
BkgCounts_s | count |  observed counts (0.5–2 keV) in merged background regions
BkgCounts_h | count |  observed counts (2–8 keV) in merged background regions
NetCounts_t | count |  net counts (0.5–8 keV) in merged apertures
NetCounts_s | count |  net counts (0.5–2 keV) in merged apertures
NetCounts_h | count |  net counts (2–8 keV) in merged apertures
NetCounts_Lo_t | count |  1-$\sigma$ lower bound on NetCounts_tggConfidence intervals (68%) for NetCounts quantities are estimated by the CIAO tool aprates (http://asc.harvard.edu/ciao/ahelp/aprates.html).
NetCounts_Hi_t | count |  1-$\sigma$ upper bound on NetCounts_tggConfidence intervals (68%) for NetCounts quantities are estimated by the CIAO tool aprates (http://asc.harvard.edu/ciao/ahelp/aprates.html).
NetCounts_Lo_s | count |  1-$\sigma$ lower bound on NetCounts_sggConfidence intervals (68%) for NetCounts quantities are estimated by the CIAO tool aprates (http://asc.harvard.edu/ciao/ahelp/aprates.html).
NetCounts_Hi_s | count |  1-$\sigma$ upper bound on NetCounts_sggConfidence intervals (68%) for NetCounts quantities are estimated by the CIAO tool aprates (http://asc.harvard.edu/ciao/ahelp/aprates.html).
NetCounts_Lo_h | count |  1-$\sigma$ lower bound on NetCounts_hggConfidence intervals (68%) for NetCounts quantities are estimated by the CIAO tool aprates (http://asc.harvard.edu/ciao/ahelp/aprates.html).
NetCounts_Hi_h | count |  1-$\sigma$ upper bound on NetCounts_hggConfidence intervals (68%) for NetCounts quantities are estimated by the CIAO tool aprates (http://asc.harvard.edu/ciao/ahelp/aprates.html).
MeanEffectiveArea_t | cm2 count photon-1 |  mean ARF value (0.5–8 keV)hhThe Ancillary Response File (ARF) in ACIS data analysis represents both the effective area of the Observatory and the fraction of the observation time for which data were actually collected for the source (column ExposureFraction).
MeanEffectiveArea_s | cm2 count photon-1 |  mean ARF value (0.5–2 keV)hhThe Ancillary Response File (ARF) in ACIS data analysis represents both the effective area of the Observatory and the fraction of the observation time for which data were actually collected for the source (column ExposureFraction).
MeanEffectiveArea_h | cm2 count photon-1 |  mean ARF value (2–8 keV)hhThe Ancillary Response File (ARF) in ACIS data analysis represents both the effective area of the Observatory and the fraction of the observation time for which data were actually collected for the source (column ExposureFraction).
MedianEnergy_t | keV |  median energy, observed spectrum (0.5–8 keV)iiMedianEnergy is the median energy of extracted events, corrected for background but dependent on the shape of the Effective Area curves for the extractions of the source(Broos et al., 2010, Section 7.3).
MedianEnergy_s | keV |  median energy, observed spectrum (0.5–2 keV)iiMedianEnergy is the median energy of extracted events, corrected for background but dependent on the shape of the Effective Area curves for the extractions of the source(Broos et al., 2010, Section 7.3).
MedianEnergy_h | keV |  median energy, observed spectrum (2–8 keV)iiMedianEnergy is the median energy of extracted events, corrected for background but dependent on the shape of the Effective Area curves for the extractions of the source(Broos et al., 2010, Section 7.3).
PhotonFlux_t | photon cm-2 s-1 |  apparent photon flux (0.5–8 keV)jjPhotonFlux = (NetCounts / MeanEffectiveArea / ExposureTimeNominal) (Broos et al., 2010, Section 7.4). EnergyFlux = $1.602\times 10^{-9}{\rm(erg/keV)}\times$ PhotonFlux $\times$ MedianEnergy (Getman et al., 2010, Section 2.2). Because MeanEffectiveArea depends on the shape of the Effective Area curves for the extractions of the source, PhotonFlux and EnergyFlux exhibit source-dependent calibration errors.
PhotonFlux_s | photon cm-2 s-1 |  apparent photon flux (0.5–2 keV)jjPhotonFlux = (NetCounts / MeanEffectiveArea / ExposureTimeNominal) (Broos et al., 2010, Section 7.4). EnergyFlux = $1.602\times 10^{-9}{\rm(erg/keV)}\times$ PhotonFlux $\times$ MedianEnergy (Getman et al., 2010, Section 2.2). Because MeanEffectiveArea depends on the shape of the Effective Area curves for the extractions of the source, PhotonFlux and EnergyFlux exhibit source-dependent calibration errors.
PhotonFlux_h | photon cm-2 s-1 |  apparent photon flux (2–8 keV)jjPhotonFlux = (NetCounts / MeanEffectiveArea / ExposureTimeNominal) (Broos et al., 2010, Section 7.4). EnergyFlux = $1.602\times 10^{-9}{\rm(erg/keV)}\times$ PhotonFlux $\times$ MedianEnergy (Getman et al., 2010, Section 2.2). Because MeanEffectiveArea depends on the shape of the Effective Area curves for the extractions of the source, PhotonFlux and EnergyFlux exhibit source-dependent calibration errors.
EnergyFlux_t | erg cm-2 s-1 |  max(EnergyFlux_s,0) + max(EnergyFlux_h,0)
EnergyFlux_s | erg cm-2 s-1 |  apparent energy flux (0.5–2 keV)jjPhotonFlux = (NetCounts / MeanEffectiveArea / ExposureTimeNominal) (Broos et al., 2010, Section 7.4). EnergyFlux = $1.602\times 10^{-9}{\rm(erg/keV)}\times$ PhotonFlux $\times$ MedianEnergy (Getman et al., 2010, Section 2.2). Because MeanEffectiveArea depends on the shape of the Effective Area curves for the extractions of the source, PhotonFlux and EnergyFlux exhibit source-dependent calibration errors.
EnergyFlux_h | erg cm-2 s-1 |  apparent energy flux (0.5–2 keV)jjPhotonFlux = (NetCounts / MeanEffectiveArea / ExposureTimeNominal) (Broos et al., 2010, Section 7.4). EnergyFlux = $1.602\times 10^{-9}{\rm(erg/keV)}\times$ PhotonFlux $\times$ MedianEnergy (Getman et al., 2010, Section 2.2). Because MeanEffectiveArea depends on the shape of the Effective Area curves for the extractions of the source, PhotonFlux and EnergyFlux exhibit source-dependent calibration errors.

Note. — These X-ray columns are produced by the ACIS Extract (AE, Broos et
al., 2010, 2012; Broos & Townsley, 2016) software package. Similar column
labels were previously published by the CCCP (Broos et al., 2011), MOXC1,
MOXC2, and MOXC3. AE and its User’s Guide are publicly available from the
Astrophysics Source Code Library, from Zenodo, and at
http://personal.psu.edu/psb6/TARA/ae_users_guide.html.

Figure 2: The T-ReX event data for the full T-ReX field. Events are binned by
4 sky pixels ($2\arcsec$). Soft events (0.5–2 keV) are shown in red, hard
events (2–7 keV) in green. Regular point sources are outlined by blue
polygons, “occasional” sources by white polygons. Red polygons outline sources
exhibiting significant pile-up. These polygons are examples of event
extraction regions, usually based on 90% encircled energy PSF contours.
Notable off-axis sources discussed in the text are labeled in yellow.

Source identifiers and position quantities (Name, RAdeg, DEdeg, PosErr,
PosType) are computed using a subset of extractions for each source chosen to
minimize the position uncertainty (Broos et al., 2010, Section 6.2 and 7.1).
Source significance quantities in each energy band (ProbNoSrc_*) are computed
using a pre-defined set of ObsID combinations which do not depend on the data
observed (Townsley et al., 2018, Section 2.2.3). Because T-ReX observations
have similar aimpoints, source significance ends up being calculated for each
individual observation and for the combination of all observations. Source
detection used our standard significance threshold (${<}1\%$ chance that the
source is a random background fluctuation in the combination of extraction and
energy band generating the highest detection significance), corresponding to
ProbNoSrc_MostValid$<0.01$. Of course, identifying a multiwavelength
counterpart to a faint X-ray point source (Appendix A) generally increases
confidence that the detection is an astrophysical object.

Variability indices (ProbKS_single, ProbKS_merge, and ProbChisq_PhotonFlux;
see Section 2.5 below) are computed using all observations. Quantities in the
remaining columns of Table 2 are computed using a subset of ObsIDs, chosen
independently for each source, to balance the conflicting goals of minimizing
photometric uncertainty and of avoiding photometric bias (Broos et al., 2010,
Section 6.2 and 7).

As with many ACIS studies, the (up to 54) extractions of a specific source in
T-ReX do not share identical calibrations. Even observations taken on the same
CCD detector in the same configuration suffer from time-dependent Effective
Area curves due to time-varying contamination on the ACIS Optical Blocking
Filters101010http://cxc.harvard.edu/ciao/why/acisqecontamN0010.html. These
calibration variations among source extractions introduce biases into certain
uncalibrated source properties (e.g., MedianEnergy_*) and introduce source-
dependent calibration errors into other source properties (e.g., PhotonFlux,
EnergyFlux, ProbKS_merge, and ProbChisq_PhotonFlux). Spectral fitting is
needed to account for these calibration differences and to establish actual
flux changes in sources that might be variable.

###  2.4 Sources Flagged as “Occasional”

Nearly half ($1744/3615=48\%$) of sources in the catalog have the Boolean flag
IsOccasional set (Table 2); these sources are also identified in Figure 2 and
subsequent figures displaying point sources overlaid on various images. The
“occasional” flag, defined in Townsley et al. (2019, MOXC3; Section 3.1), is
set when “source validation failed in all attempted multi-ObsID extraction
combinations, but succeeded in one or more single-ObsID extractions.” Since
T-ReX observations have similar aimpoints, occasional sources are those that
failed validation when all observations were combined, but passed validation
in one or more single-ObsID extractions. By contrast, we denote sources
validated in multi-ObsID extractions as “regular.”

In the MOXC3 catalog, 14% of sources were flagged as occasional, a much lower
fraction than in T-ReX. But T-ReX differs from our previous MOXC catalogs in
the large number of OBsIDs targeting a single area on the sky, which increases
the chances that a spurious source could be valid in a given single ObsID.
This probably explains the much larger fraction of occasional sources in
T-ReX.

It is important to emphasize that flagging a source IsOccasional is not a
claim of variability, indeed, as Townsley et al. (2019) noted, most occasional
sources are too faint to assess X-ray variability. The majority of occasional
sources in the T-ReX catalog have ${\lesssim}12$ NetCounts_t, while the large
majority of regular sources exceed this value. Occasional sources also appear
marginally softer than regular sources (e.g., in the MedianEnergy_t
distributions). As a test, we stacked the spectra of occasional sources in
T-ReX and found that their total (gross) spectrum, local background spectrum,
and net spectrum look very similar to each other and similar to the gross
global diffuse spectrum (Section 5). It is hence plausible that many
occasional sources could be knots of diffuse emission, but they could also
include faint astrophysical sources at the detection limit.

We choose to include occasional sources in the catalog because (1) some of
them may represent real X-ray counterparts to astrophysical objects detected
at other wavelengths, and (2) they are subject to the source masking process
in our diffuse emission work flow. We hence regard the 1871 “regular” sources
as the more-reliable subset of the T-ReX catalog and those with the
“occasional” property as a more complete set of candidate point sources.

###  2.5 Variability Metrics

The point source catalog (Table 2) reports information that can help identify
source variability on two timescales. Short-term variability is assessed
within each observation of a source. AE calculates a p-value for the observed
arrival times of extracted (point source + background) in-band events from
that observation, under the null hypothesis of a constant event rate, using a
one-sample Kolmogorov-Smirnov (K–S) hypothesis test (Broos et al., 2010,
Section 7.6). If we reported all of those p-values (up to 54 in T-ReX), then
variable sources within a specific observation could be identified by applying
a threshold to the p-values from that observation. However, observers are more
typically interested in sources that show evidence for variability in any of
the observations. This is a classic multiple comparisons
problem111111https://en.wikipedia.org/wiki/Multiple_comparisons_problem,
wherein any one of multiple observations can produce the “discovery” of short-
term variability.

Every extraction that produces four or more X-ray events is tested for
variability. Instead of reporting p-values from each of those tests, we choose
to report the smallest p-value produced by each source, as ProbKS_single in
Table 2. Note that the statistic ProbKS_single $=\min(P_{1},P_{2},\ldots
P_{\rm N\\_KS\\_single})$ is not uniformly distributed under the null
hypothesis, and is thus not a p-value. However, a proper p-value can be
calculated via

$p=1-(1-\texttt{ProbKS\\_single})^{\texttt{N\\_KS\\_single}}.$ (1)

If a set of $N$ sources is screened for variability by thresholding this
p-value (e.g. “variable” $\Leftrightarrow p<0.005)$, then the number of false
positives expected would be approximately $N$ multiplied by the threshold
(e.g. $N\times 0.005$). 121212If instead variability were determined by
thresholding the statistic ProbKS_single (e.g. “variable” $\Leftrightarrow$
ProbKS_single$<0.005)$, then the number of false positives expected would be
approximately the total number of K–S tests performed in that set of sources,
multiplied by the threshold (e.g. $\sum_{i=1}^{N}$N_KS_single${}_{i}\times
0.005$). Such an approach would produce a much higher false-positive rate for
variability, given the large number of OBsIDs in T-ReX. This intra-ObsID
variability testing requires no calibration information, because instrument
response is not expected to vary during an observation.

To assess variability over longer timescales than a single exposure (typically
15–60 ks, Table 1) one must consider all observations of a source. We assess
Inter-ObsID variability using a K–S test (ProbKS_merge) that combines all the
observations of the source (Broos et al., 2010, Section 7.6) and also by
employing a standard $\chi^{2}$ test (ProbChisq_PhotonFlux) on the single-
ObsID measurements of PhotonFlux_t. Computation of both metrics requires
calibration information. The instrument response for a given source will
always vary across observations, due to both chromatic effects (aperture
correction, mirror response, ACIS Optical Blocking Filter transmission, CCD
response) and achromatic effects (dead time, exposure lost to inactive CCD
pixels). The combined energy-dependent effect of these calibration factors is
represented by the Ancillary Response File (ARF) calculated for each source
extraction. For all multi-ObsID projects, the accuracy of the two long-term
variability metrics produced by AE (ProbKS_merge and ProbChisq_PhotonFlux) is
limited by their assumption that the single-ObsID ARFs have the same shape
(i.e. differ only in normalization). In T-ReX the calibration factor that most
strongly invalidates this assumption is the time-dependent variation in the
ACIS Optical Blocking Filter transmission.

Thus in T-ReX and many previous projects (Broos et al., 2011; Townsley et al.,
2014, 2018, 2019) thresholding ProbKS_merge or ProbChisq_PhotonFlux should be
viewed as a screening test for possible variability, rather than as a
calibrated null hypothesis test using an accurate p-value; false-positives are
expected. The only accurate method for measuring source variability across all
observations would be simultaneous fitting of all single-ObsID spectra, which
is beyond the scope of this paper.

We do not attempt to flag all candidate variable sources in the T-ReX point
source catalog, but in Appendix B we discuss seven examples of high-quality
periodic X-ray variables and two large X-ray flares associated with foreground
Galactic stars in the T-ReX field.

###  2.6 Sources Suffering Photon Pile-up

Three point sources (Mk34, R140a, PSR J0537-6910) have extractions that are
significantly impacted by an instrumental non-linearity known as photon pile-
up131313http://cxc.harvard.edu/ciao/why/pileup_intro.html, which is described
in the three MOXC papers (Townsley et al., 2014, 2018, 2019, and references
therein). When possible, we model the piled-up spectra in these extractions
(Broos et al., 2011) and use that model to estimate a “reconstructed” ACIS
spectrum free from pile-up effects. The metric we choose to describe the
severity of pile-up is the ratio of the pile-up-free count rate to the
observed (piled-up) count rate in the total (0.5–8 keV) energy band, which we
call the Rate Correction.

Rate Corrections for the colliding-wind Wolf-Rayet binary system Mk34
(053844.25-690605.9 = p1_995, VFTS 770) range from 1.176 when the count rate
was highest (ObsID 17312) to 1.0 (no pile-up) when the count rate was lowest.
Pollock et al. (2018, Figure 6) compare spectral fits to the piled and
corrected spectra.

The nearly constant colliding-wind Wolf-Rayet binary system R140a
(053841.59-690513.4 = p1_752, see C22) produced moderate Rate Corrections
($\sim$1.07) in all observations.

Although the pulsar PSR J0537-6910 (053747.40-691020.2 = p1_255) has count
rates about 5 times larger than Mk34 and R140a, it has similarly moderate Rate
Corrections because its photons were distributed over a much larger PSF (6′
off-axis).

###  2.7 Archive of Reduced Data Products

The Zenodo archive (Townsley & Broos,
2023)141414https://zenodo.org/doi/10.5281/zenodo.8372420 contains data
products and plots that may be of use to other investigators who wish to use
the T-ReX data set; see the file README.TXT there for details.

##  3 An Imaging Tour of T-ReX

To emphasize various morphological features of the T-ReX diffuse X-ray
emission, we present in this section several visualizations of the imaging
data with no overlays. Soft diffuse emission, divided into three energy bands,
across the full T-ReX field is shown in Figure 3. This field is
$40\arcmin\approx 580$ pc in diameter. The image has been smoothed to achieve
a roughly constant SNR and showcases the dramatic improvement in spatial
resolution afforded by the increased SNR of the 2 Ms T-ReX exposure compared
to previously published images (Townsley et al., 2006a, 2011c).

Figure 3: T-ReX diffuse emission in three soft X-ray bands, smoothed with
adaptive kernels to achieve SNR = 15. All 3615 point sources (seen in Figure 2
above) were excised before smoothing. Axes are in celestial (J2000)
coordinates.

Based on earlier, shallower and hence blurrier images, 30 Dor appeared to
exhibit at least five plasma-filled superbubbles (Townsley et al., 2006a),
products of strong OB winds and multiple supernovae. Because of their
proximity and the low absorbing column to the LMC, they provide the best
opportunity to study the X-ray spectrum and structure of any superbubble
system. Chandra has already shown (Townsley et al., 2011c; Lopez et al., 2011;
Pellegrini et al., 2011) that they are spatially complex X-ray structures with
a range of X-ray plasma temperatures, ionization timescales, absorptions, and
luminosities. The T-ReX images reveal that the ISM in 30 Dor, as in Carina and
other MSFRs, forms a complex labyrinth of low-density cells and channels
filled with hot plasma, surrounded by walls of colder material. The boundaries
apparently separating the superbubble lobes are much less distinct in the
deeper observations that more effectively penetrate absorbing columns of the
cold, dense ISM walls, shells, and filaments.

Figure 4:  T-ReX diffuse emission in the Spitzer context. Spitzer images are
from the Surveying the Agents of Galaxy Evolution (SAGE) survey (Meixner et
al., 2006).

The outer regions of the T-ReX field are suffused with fainter, softer (red-
green in in Figure 3) emission that also shows rich spatial structure. Much of
this spatial complexity could be explained by the imprint of spatially-varying
absorption (see Figure 4) on background of X-ray emission that is
intrinsically softer than 30 Dor itself. Some of this emission could be hot
plasma leaking from the 30 Dor superbubbles.

Figure 5:  Light and shadow: zoomed and rescaled regions from Figure 4. These
images illustrate the complex interfaces between the hot and cold ISM of 30
Dor. With respect to R136, these regions are located: (a) northeast; (b)
northwest; (c) southeast; (d) southwest.

Three neighboring structures, labeled in Figure 2, stand out in the 1.1–2.3
keV band against the softer background. The ${\sim}5$-Myr-old star-forming
region NGC 2060 (Sabbi et al., 2016), located ${\sim}6\arcmin$ southwest of
R136, is dominated by the young SNR N157B (also known as 30 Dor B), containing
the 16-ms PSR J0537-6910 (Chen et al., 2006, 2023). N157B and its prominent
cometary pulsar wind nebula contributed over half of the total X-ray counts in
prior Chandra studies of 30 Dor (Townsley et al., 2006a). West of N157B lies
the 30 Dor C superbubble, a large shell of non-thermal X-ray emission, which
appears as an elongated, broken blue ring surrounding (in projection) a
compact, softer source that has been identified as MCSNR J0536–6913 (Kavanagh
et al., 2015). A hard-edged artifact produced by smoothing over the mask for
the exceptionally bright PSR B0540-69 appears in the S-array mosaic SE of 30
Dor. Enhanced hard diffuse emission in the vicinity is likely associated with
the young, oxygen-rich SNR reported by Park et al. (2010) using on-axis
Chandra observations.

In Figures 4 and 5 we highlight the complex morphological interplay between
the hot X-ray emitting plasma, and the cool, dusty ISM revealed in Spitzer
images.151515Our T-ReX diffuse map, combined with JWST images of the central
portions of 30 Dor, was released publicly
by the Chandra X-Ray Center in 2022 October, see
https://chandra.si.edu/photo/2023/30dor/index.html. In these images, the
Spitzer/IRAC 8 $\mu$m band (green) shows primarily emission from polycyclic
aromatic hydrocarbons (PAHs) that produce a strong 7.7 $\mu$m fluorescence
feature when exposed to UV irradiation (Povich et al., 2007), making it an
excellent tracer of locations where the surfaces of cold, molecular clouds are
exposed to ionizing radiation. The Spitzer/MIPS 24 $\mu$m band (red) traces
warm dust, which emits most strongly where dust grains are intermixed with
ionized plasma and becomes stochastically heated by the hard radiation field
(Watson et al., 2008; Everett & Churchwell, 2010). The full ACIS 0.5–7 keV
emission (blue) tends to fill in the cavities and voids in the mid-IR nebula.
Regions where the diffuse X-rays are especially faint, notably a broad region
bordering the East-Southeast half of 30 Dor (Figure 3), tend to be filled in
by mid-IR cloud structures (Figure 4), indicating that the cold clouds are
located in front of the hot plasma in these locations and absorb the soft
X-rays. In other regions, diffuse X-rays appear to surround or pass in front
of bright mid-IR filaments (many examples are evident in Figure 5, especially
panels c and d), revealing interfaces between the hot and cold ISM.

##  4 Point Sources

In this and the following section we focus on the central region of the T-ReX
field containing 30 Dor itself, imaged by the ACIS I-array (Figure 6). Point
sources in the T-ReX catalog are distributed widely throughout this field,
except in the vicinity of N157B, where bright diffuse emission prevented
detection of point sources associated with NGC 2060 other than the
extraordinarily bright, piled source PSR J0537–69 (source p1_255 with
$3.4\times 10^{5}$ net counts). The field center contains the R136 cluster,
and we zoom in on this region in Figure 7 to better display its dense
concentration of X-ray events and cluster of detected point-sources. The
spatial distribution of regular sources exhibits more structure compared to
occasional sources; besides R136 there are several smaller clusters of X-ray
sources that appear to be associated with embedded subclusters (Walborn et
al., 2013; Sabbi et al., 2016) in the molecular cloud to the north and west.

After the pulsar, most of the brightest point sources in the 30 Dor field are
massive stars studied in detail by C22, including two Wolf-Rayet systems (Mk
34 and R140a) and the candidate high mass X-ray binary VFTS 399 (Clark et al.,
2015). We present the cross-matching of T-ReX point sources with massive
stellar counterpart catalogs in Appendix A; these matching lists, including
blended sources in R136 (Figure 7) that could represent multiple OB stars,
were used to construct the C22 sample. C22 found that the majority of Wolf-
Rayet and Of/WN systems in 30 Dor were detected in X-rays (70.0% and 85.7%,
respectively), but for O-type stars in general a similar majority went
undetected, and the fraction of detected B-type stars was very low. The
absorption-corrected X-ray luminosity ($L_{X}$) from spectral fitting of
detected massive stars and upper limits on undetected massive stars indicate
that the T-ReX massive star sample is highly incomplete for
$\log{L_{X}}<32~{}{\rm ergs}^{-1}$.

We can also estimate the sensitivity of T-ReX to lower-mass, pre-main sequence
stars. Among the regular sources in the T-ReX catalog, 1501/1871 (80%) were
detected with ${>}12$ net counts. Assuming a typical T-Tauri X-ray spectrum
and absorption equivalent to $A_{V}=0.5$ mag, 12 counts on-axis corresponds to
$\log{L_{X}}>31.5~{}{\rm ergs}^{-1}$. A calculation using the absorption-
corrected surface brightness of the global diffuse emission (see Section 5
below) yields a very similar luminosity for a circular region of diffuse
background emission enclosed by an on-axis point-source extraction aperture.
Diffuse X-ray emission limits point-source sensitivity throughout the T-ReX
field, not only in the brightest regions. This luminosity threshold suggests
that T Tauri stars detected in T-ReX are likely to be in a mega-flaring state
(Getman & Feigelson, 2021). The Chandra Carina Complex Project (CCCP, Townsley
et al., 2011a) provides a useful comparison to put this source luminosity in
context, as it is a Galactic starburst region containing multiple stellar
clusters with different ages, similar to 30 Dor (Cignoni et al., 2015; Povich
et al., 2019). Nuñez et al. (2021) performed X-ray spectral fitting on 370
bright CCCP stellar sources that were not associated with OB stars. Imposing
the T-ReX luminosity cut on the CCCP sample would exclude all but a small
number (${\lesssim}20$) of flaring, low-mass T Tauri stars ($M<2~{}M_{\sun}$).
About one-third of intermediate-mass, pre-main sequence stars (IMPS; 2–4
$M_{\sun}$) in CCCP would be detectable in T-ReX, but with the caveat that
their X-ray luminosity fades rapidly after ${\sim}1$ Myr (Gregory et al.,
2016; Nuñez et al., 2021). X-ray activity for pre-main sequence stars of all
masses decays after ${\sim}7$ Myr (Getman et al., 2022).

Considering the above arguments, T-ReX is sensitive primarily to early O stars
and convective (flaring) IMPS, tracing the youngest stellar populations in 30
Dor, primarily R136. This explains why the older cluster Hodge 301 (20 Myr;
Sabbi et al., 2016) is not detected in T-ReX. The great density of R136 itself
means that the cluster core is not resolvable by ACIS, and (probably hundreds)
of unresolved stellar sources contribute to elevated diffuse X-ray backgrounds
that further reduce point-source sensitivity in the vicinity (Figure 7). R136
contains the majority of stellar sources that should be detectable in
principle, based on X-ray luminosity, but in reality this cluster also
exhibits extreme source crowding and elevated diffuse background levels that
dramatically reduced point-source sensitivity compared to the T-ReX field
overall.

Beyond R136 and the neighboring smaller, embedded clusters, the point source
population in the wider T-ReX field appears broadly consistent with a
population of AGN and other background extragalactic sources, as indicated by
the general lack of spatial clustering and the dearth of multiwavelength
counterparts to T-ReX sources (see Appendix A). Using the 95% completeness
limits of the 2-Ms Chandra Deep Field North catalog (CDF-N Alexander et al.,
2003; Kim et al., 2004)161616The CDF-S 2 Ms catalog (Luo et al., 2008) would
yield very similar numbers. as a control for the T-ReX field if the LMC were
removed, we would predict 720 sources with soft-band (0.5–2 keV) flux
${>}8\times 10^{-17}$ erg s-1 cm-2 and 480 sources with hard-band (2–8 keV)
flux ${>}4\times 10^{-16}$ erg s-1 cm-2. Assuming an average absorbing column
through 30 Dor of $N_{H}=2\times 10^{22}$ cm-2 and a characteristic photon
index of 1.7, PIMMS171717https://cxc.harvard.edu/toolkit/pimms.jsp shows that
the limiting observed fluxes would be reduced to ${\sim}1.2\times 10^{-17}$
erg s-1 cm-2 in the soft band. The T-ReX catalog contains ${\sim}1600$ regular
sources above this soft-band limit, more than double the expected background
contamination rate. By contrast, T-ReX contains only 525 hard-band sources
brighter than the CDF-N 95% completeness limit (with absorption producing a
negligible correction), hence the large majority of T-ReX sources detected in
the hard band are consistent with background contaminants.

Figure 6: The T-ReX event data with point source extraction apertures
overlaid, as in Figure 2, now zooming in on 30 Dor itself. Events are binned
by 2 sky pixels.  Figure 7: T-ReX event data (as in Figures 2 and 6) zoomed in
to show the inner ${\sim}35\arcsec=8.4$ pc of the field, centered on the T-ReX
aimpoint (R136). Events are binned by 0.5 sky pixels. Source positions are
shown as blue diamonds for occasional sources and as white crosses for regular
sources, with their ACIS source labels (Table 2; regular source labels in the
most crowded central region are shown in black, with reduced size, for
clarity). The piled-up WR star Mk34 (p1_995) is noted in red.

##  5 Diffuse X-ray Emission

30 Dor offers us a microscope on starburst astrophysics, having endured 25 Myr
of the birth and death of the most massive stars known. Across its 250-pc
extent, stellar winds and supernovae have carved the ISM within 30 Dor into an
amazing display of arcs, pillars, and bubbles (Figures 4 and 5). For over 40
years, we have also known that 30 Dor is a bright X-ray emitter, so its
familiar stars and cold ISM structures suffer irradiation by multi-million-
degree plasmas. Here we focus on the diffuse X-ray emission revealed by T-ReX,
highlighting hot/cold interfaces (Figure 5) and other hot plasma structures
resolved to 1–10 pc scales across the entire 30 Dor complex (Figures 3 and 8).
Massive star winds and cavity supernovae over the millenia have contributed to
a broad mix of X-ray-emitting plasmas and absorbing columns, and the hot ISM
within 30 Dor exhibits similar complexity as seen at colder temperatures.

Figure 8: 30 Dor diffuse emission in three soft X-ray bands. This is a zoom of
Figure 3, cropped to a similar field as shown in Figure 6.

In Figure 8 we present a square approximately the size of the ACIS I-array
($17\arcmin=245$ pc on a side), where the sensitivity and spatial resolution
are maximized. In this section we present spectral fitting of the diffuse
emission using extraction regions from within this image.

Townsley et al. (2011b, c) provided a detailed description of our general
spectral modeling strategy as applied to the Carina Nebula, other Galactic
massive star-forming complexes, and the 30 Dor observations predating T-ReX.
The spectral model consists of three shocked thermal plasma components
implemented in XSPEC (vpshock). Components 1 and 2 consist of cooler plasmas
($0.25~{}{\rm keV}\lesssim kT\lesssim 0.35$ keV) with different cooling
timescales; the high timescales for component 2 (e.g.
$\log{(\rm\tau)}=13.7/[{\rm s~{}cm}^{-3}$]) imply collisional ionization
equilibrium (CIE) while the lower timescales for component 1 suggest the
presence of non-equilibrium ionization (NEI) plasma. Component 3 consists of
hotter plasmas ($0.7~{}{\rm keV}\lesssim kT\lesssim 1.3$ keV) exhibiting a
mixture of CIE and NEI. Each spectral fit plot presented below (Figures 9–11)
labels the vpshock parameters for the various employed components: absorbing
column $N_{H}$ is labeled as NH[123], plasma temperature $kT$ as kT[123],
timescale $\tau$ as tau[123] and absorption-corrected surface brightness as
SB[123].

We assumed that absorbing material in both the LMC and foreground Milky Way
have relative abundances equal to those of the Sun, but that the LMC
abundances are scaled down from the Milky Way (by about 50%). Thus in XSPEC we
chose to model total absorption with a single TBabs model that uses solar
abundances. Abundances for most elements in the vpshock models were frozen at
$0.4Z_{\odot}$, appropriate for the low-metallicity environment of the LMC
(Russell & Dopita, 1990), but we found that enhanced abundances of Ne
($0.59Z_{\odot}$), Mg $1.06Z_{\odot}$, and Si ($0.75Z_{\odot}$) were needed to
account for other line features in the spectrum. The NH[123] values labeled in
Figures 9–11 may be doubled to correct for LMC abundances.

Dotted Gaussians representing unmodeled lines were added because they
substantially improve the fit (Townsley et al., 2011b, c). The central line
energies, widths, and normalizations were all free parameters, and yet, as we
demonstrate below, the multiple Gaussian components typically land on or near
the energies of real X-ray emission lines. They may represent charge exchange
(CX, see Gu & Shah, 2023, for a recent review) or some other physics not
captured by the current plasma models.

We also allow a contribution from unresolved pre-MS stars (2-temperature apec
model for collisionally-ionized thermal plasma) and an absorbed power law to
account for a hard tail in the spectrum due to a background of unresolved AGN
and/or nonthermal emission in 30 Dor.

###  5.1 N157B SNR and Pulsar Wind Nebula

The N157B SNR (also known as 30 Dor B) and the associated wind nebula produced
by its pulsar, PSR J0537 (Marshall et al., 1998; Wang et al., 2001), produce
the brightest diffuse X-ray emission by far in the T-ReX field, with
(absorption-corrected) surface brightnesses exceeding the typical values of 30
Dor itself by one to two orders of magnitude. It was therefore critical to
remove these diffuse sources prior to modeling the global diffuse emission of
30 Dor.

We present spectral fits to N157B and the pulsar wind nebula in Figure 9.
N157B required a complex model consisting of three thermal plasma components
plus a power law of comparable brightness. The two thermal plasma components
used to model the soft end of the diffuse spectrum have $kT1\approx kT2=0.25$
keV, and Chen et al. (2023) recently concluded that the combination of the
soft X-ray plasma and the physical extent of N157B require at least one more
supernova preceded the one, 5000 years ago, that created PSR J0537.

Our model also includes 10 Gaussian line components, many of which correspond
to energies of emission lines that show CX enhancement in the Cygnus Loop SNR
(Katsuda et al., 2011; Uchida et al., 2019) or starburst galaxies (Ranalli et
al., 2008; Liu et al., 2012; Zhang et al., 2022). The O VII triplet falls near
0.53 keV, while O VIII can produce lines near 0.61 keV and 0.75 keV. Highly-
ionized iron can produce the lines near 0.88 keV (Fe XVII or Fe XVIII) and
0.94 keV (Fe XIX), but the latter could also be Ne IX. Other ionized neon
and/or magnesium lines could produce the components at 1.07 keV (Ne X), 1.17
keV (Ne X or Mg), 1.35 keV (Mg XI), and 1.60 keV (possibly Mg).

The two components attributable to magnesium CX lines also appear in the
modeled spectrum of the pulsar wind nebula, which otherwise presents a
comparatively simple, power-law spectrum requiring only one additional NEI
plasma component to model the soft tail of the spectrum. This model resembles
that of the combined ACIS-S spectrum of N157B and the pulsar wind nebula
presented by Chen et al. (2006).

Unique among the T-ReX diffuse spectra modeled thus far, the fit to the hard
tail of the N157B was significantly improved by the addition of a Gaussian
component at 6.38 keV corresponding to the Fe K$\alpha$ fluorescence line.
This is a common feature in AGN and some X-ray binaries, arising in dense
accretion disks at high temperature. It is unlikely that this emission arises
in the low-density SNR, but it could be produced by massive, colliding-wind
binaries present in the massive NGC 2060 stellar cluster that hosted the
supernova progenitor (see, e.g., Walborn et al., 2014). This line is obvious
in the X-ray spectrum of the $\eta$ Car system, for example (Kashi et al.,
2021). The average X-ray luminosity of the strongly variable $\eta$ Car is
$6.33\times 10^{34}$ erg s-1, which would rank it among the brightest T-ReX
point sources but still an order of magnitude fainter than PSR J0537-69, the
sole point source detected in the central regions of N157B.

Figure 9: Diffuse X-ray spectra of N157B. (a) The N157B SNR spectrum with the
central PWN removed. (b) The J0537 PWN spectrum with the PSR J0537 point
source removed. In these and other plots of spectral fitting presented below,
the following parameters of various numbered models components are labeled:
$N_{H}$ (absorbing hydrogen column density), $kT$ (plasma temperature), tau
(timescale), and SB (surface brightness, corrected for absorption NH).

###  5.2 Spectral Fits to Global Diffuse Emission

Figure 10: The global diffuse X-ray spectrum of 30 Dor, with the N157B SNR and
its PWN removed. The “Global” diffuse region is defined in Figure 11 below.

The spectrum “Global $-$ N157B” presented in Figure 10 includes everything
inside the outer tessellate boundary (red outline with the approximate shape
of the state of Texas) shown in Figure 11, but excluding the very bright N157B
supernova remnant and its pulsar wind nebula (see the previous subsection).
The global boundary was chosen based on a constant level of soft-band,
smoothed photon flux that enclosed the brightest diffuse emission associated
with 30 Dor. This integrated diffuse X-ray emission spectrum has $1.7\times
10^{6}$ net counts.

The 8 brightest T-ReX point sources (those with NetCounts_t$>10^{4}$ in Table
2) total $2.55\times 10^{6}$ X-ray counts, however most of this contribution
comes from outside the area enclosed by the global boundary, in the off-axis
regions and PSR J0537. The fainter point sources in the 30 Dor field provide
an order of magnitude fewer aggregate net counts, $2.2\times 10^{5}$, or 13%
of the global diffuse counts.181818T-ReX has enabled a significant improvement
in faint point-source extraction compared to our early analysis of the first,
shallow observations of 30 Dor, for which extracted point sources represented
9% of the integrated diffuse emission (Townsley et al., 2006a, b). The
spectral model component representing unresolved T Tauri stars represents
${<}1\%$ of the diffuse emission (Figure 10).

The fits to the global spectrum in Figure 10 included 8 Gaussians with
energies between 0.5 and 2 keV, some of which could plausibly represent CX-
enhanced line emission and several of which were also used in the fit to the
spectrum of N157B (see Figure 9). Absent from the global spectrum are Gaussian
components at the energies of the magnesium lines, seen in both the SNR and
pulsar wind nebula spectrum. One new Gaussian component appears at 1.90 keV
and could represent the Si XIII emission observed in starburst galaxies
(Ranalli et al., 2008; Katsuda et al., 2011).

###  5.3 Sample Tessellate Spectral Fits

Figure 11: Tesselation used for spatially-resolved spectral fitting analysis
of the ACIS diffuse emission. Spectral fits to 11 sample extractions
representing a range of locations and regions of interest (labeled in red and
yellow in the soft diffuse image) illustrate the spectral complexity and
diversity of the diffuse X-ray emission in 30 Dor. The outer boundary defines
the “global” diffuse spectrum (Figure 10), plotted in the upper-left panel to
facilitate comparison with the smaller extraction regions. Global and the
other named regions outlined in red are based on surface brightness contours:
N157B and PWN (Figure 9), Manta Ray, Comet, and SE Ridge. The 308 tessellates
(in green and yellow) come from the WVT Binning code by Diehl & Statler
(2006).

Employing the strategy developed for CCCP (Townsley et al., 2011b), we
subdivided the 30 Dor diffuse emission into tessellates using the WVT binning
algorithm (Diehl & Statler, 2006). This method allows for higher spatial
resolution in regions of brighter emission while maintaining a constant SNR
across all extracted spectra. Using SNR=70, we needed 308 tessellates to tile
the field enclosed by the “Global” contour (Figure 11). The starting point for
spectral fits to each extracted tessellate spectrum was the global model with
no Gaussian components. Unneeded components were then removed, fits optimized,
and Gaussians added last if they improved the fit.

Many tessellates (e.g. 188, and, with the addition of Gaussian lines, 305,
293, 92, 21, and SE Ridge) can be modeled with just vpshock2, a soft CIE
plasma that usually dominates the surface brightness, and vpshock3, a harder
plasma that may be NEI or CIE. Of course the absorptions, temperatures, and
timescales of these plasmas vary across the complex, creating 30 Dor’s rich
X-ray appearance.

The soft vpshock1 component usually has the same temperature as vpshock2 but a
much shorter ionization timescale, implying an NEI plasma. Thus tessellates
requiring vpshock1 may indicate the presence of a plasma transitioning from
NEI to CIE. This component is needed only in tesselates 189 and 239, which
have the lowest apparent surface brightnesses of all sample tessellates due to
high absorption north of R136. Tesselate 189 additionally required the
brightest unresolved TTS components among the sample tesselates, representing
the embedded stellar population north of R136 (Sabbi et al., 2016).

Tesselate 131 provides a sample of the diffuse plasma nearest to R136.
Unsurprisingly, it includes relatively strong components modeling the
unresolved T Tauri population. The absorption to all components is higher than
the Global average, and the diffuse spectrum here is significantly harder,
requiring both a CIE thermal plasma with $kT3=1.3$ keV and an hard tail.
Tesselates 21 and 189, the other two samples of the central regions of 30 Dor
(Figure 11), have hot thermal plasma components with the same temperature but
shorter timescales, implying NEI.

Comet and SE Ridge are names given to two hand-drawn tesselate boundaries
encircling areas of unusually bright, apparently hard diffuse emission. Comet
was the only sample tessellate fit with single CIE plasma component, while SE
Ridge required two CIE plasmas and several Gaussian lines. The hotter
$kT3=0.69$ keV component dominates SE Ridge more than in most other regions.
Both tesselates show higher absorption than the Global average, suggesting
regions where hot plasma encounters cold gas at the western edge of the 30 Dor
superbubble.

If Comet and SE Ridge represent regions of plasma confinement and possible
mixing with the cold ISM, sample tesselates 305 and 92 appear to sample
regions at the northern and southern extremes, respectively, where there could
be champagne flows of diffuse plasma leaking from 30 Dor. The X-ray flux
appears softer in these lobes (Figures 8 and 11), and indeed the absorption is
lower here compared to central regions and to the Global average. Figures 5a
and b show that the X-ray plasma in these regions fills cavities outlined by
PAH emission.

Figure 12: HTTP F160W image (Sabbi et al., 2013) showing the stellar content
in the region of the Manta Ray diffuse extraction tesselate (blue outline).
Three stellar overdensities are visible along the trailing edges of the Manta
Ray “wings;” the one at lower-right also shows NIR nebulosity suggesting an
embedded cluster associated with the T-ReX point source c5160. The candidate
X-ray pulsar (PSR J0538-6902 = T-ReX catalog source p1_799) is marked with a
blue + sign enclosed by red-blue ellipse showing mask used to exclude the
source from the diffuse emission. OB stars from VFTS (Walborn et al., 2014;
Evans et al., 2015) are marked with red + symbols with spectral types labeled;
the majority are evolved massive stars. Extraction apertures for regular T-ReX
catalog sources are outlined with blue polygons (occasional sources are
omitted).

###  5.4 The Manta Ray: A New Candidate Pulsar Wind Nebula

The Manta Ray (named for its morphological resemblance to the large, flat-
bodied, winged fish that “flies” under the sea) is an unusually hard, extended
X-ray source located 4′ north of R136. This feature is visible as a green “V”
shape in the event data displayed in Figure 6. It required a custom, hand-
drawn aperture to extract its diffuse emission. We fit the spectrum of the
Manta Ray using a similar model as with N157B and its PWN (see Figure 9) and
found that it needed only two components (Figure 11). The soft portion of the
spectrum was fit with a CIE plasma with $kT=0.30$, $\log{N_{H}/{\rm
cm^{-2}}}=21.7$, and $\log{\rm SB/(erg~{}s^{-1}~{}pc^{-2})}=33.61$. The hard
spectrum required a power-law with $\alpha_{\rm PWN}=1.77$, $\log{N_{H}/{\rm
cm^{-2}}}=21.8$, and $\log{\rm SB/(erg~{}s^{-1}~{}pc^{-2})}=32.30$.

We used a power-law with LMC absorption (TBvarabs*pow) to fit the spectrum of
the T-ReX point source p1_799 (585 net counts), which is located near the
center of the Manta Ray but has no apparent counterpart at visible/NIR
wavelengths (Figure 12). The spectral fits returned
$N_{H}=2.71_{-0.9}^{+1.1}\times 10^{22}$ cm-2 (for $Z=0.4$), power-law index
$\alpha_{\rm PSR}=1.5\pm 0.3$, and $\log{L_{tc}}=33.42$ (0.5–8 keV total-band
luminosity). Comparing the power-law indices of the Manta Ray diffuse emission
($\alpha_{\rm PWN}$) with its point source ($\alpha_{\rm PSR}$) reveals very
good agreement with the empirical relationship between the spectra of young
X-ray pulsars and their wind nebulae derived by Gotthelf (2003). These
$\alpha$ values imply a spin-down luminosity of $L_{\rm sd}\sim
0.8$–$1.5\times 10^{37}$ erg s-1 for the driving pulsar. Based on the broad
correlation between $L_{X}$ and $L_{\rm SD}$ reported by Possenti et al.
(2002, their Fig. 2), we would expect $L_{X}\sim 5\times 10^{33}$ erg s-1 for
the pulsar, in very good agreement with the absorption-corrected $L_{tc}$ for
p1_799. We therefore propose that p1_799 be designated PSR J0538-6902, the
candidate pulsar responsible for generating the Manta Ray PWN.

Additional lines of circumstantial evidence also support the conclusion that
the Manta Ray is a PWN. Since the diffuse absorption was modeled assuming
solar metallicity using TBabs, doubling its value yields $N_{H}=1.26\times
10^{22}$ cm-2 for the power-law nebular component at LMC metallicity, which is
similar to the absorption of the point source PSR J0538-6902. There are
several evolved, massive stars and three compact star clusters in the vicinity
of the Manta Ray (Figure 12), which could trace a massive stellar association
that hosted the progenitor of the pulsar. The arc-shaped morphology of the PWN
suggests a bow shock resulting from a high space velocity for the pulsar in an
easterly direction. Assuming, for example, that the progenitor resided in the
nearest HTTP cluster (${\sim}15\arcsec=3.6$ pc away), and also assuming a
typical neutron star birth velocity of ${\sim}200$ km/s (Sartore et al.,
2010), PSR J0538-6902 could have reached its present-day location
${\sim}20,000$ yr post-supernova. An age of a few $\times 10^{4}$ would be
consistent with the X-ray luminosity of PSR J0538-6902 (Possenti et al.,
2002), making it ${\sim}10$ times older and hence ${\sim}1000$ times less
luminous than PSR J0537-6910 in N157B (Chen et al., 2006).

###  5.5 Physical Properties of the Global Diffuse X-ray Emission in 30 Dor

Table 3: Physical Properties of the Diffuse Plasma Components

Parameter |  Scale factor | T-ReX “Global” Region
---|---|---
|  | vpshock1 | vpshock2 | vpshock3
Observed X-ray properties
median $kT_{x}$ (keV) |  $\cdots$ | 0.28 | 0.29 | 0.94
$L_{tc}$ (erg s-1) |  $\cdots$ | $6.2\times 10^{36}$ | $12.9\times 10^{36}$ | $2.2\times 10^{36}$
$V_{x}$ (cm3) | $\eta$ | $5.5\times 10^{61}$ | $5.5\times 10^{61}$ | $5.5\times 10^{61}$
Derived X-ray plasma properties
$T_{x}$ (K) |  $\cdots$ | $3.2\times 10^{6}$ | $3.4\times 10^{6}$ | $10.9\times 10^{6}$
$n_{e,x}$ (cm-3) | $\eta^{-1/2}$ | 0.05 | 0.07 | 0.03
$P_{x}/k$ (K cm-3) | $\eta^{-1/2}$ | $3.4\times 10^{5}$ | $5.1\times 10^{5}$ | $6.8\times 10^{5}$
$E_{x}$ (erg) | $\eta^{1/2}$ | $3.9\times 10^{51}$ | $5.8\times 10^{51}$ | $7.7\times 10^{51}$
$\tau_{cool}$ (Myr) | $\eta^{1/2}$ | 20 | 14 | 111
$M_{x}$ (M⊙) | $\eta^{1/2}$ | 1358 | 1964 | 809

Note. — Equations detailing how the derived properties were obtained from the
observed properties are given in Townsley et al. (2003). The volume is assumed
to be the area of the “Global” diffuse region multiplied by a depth of 50 pc.
The quantity $\eta$ is a “filling factor,” $0<\eta<1$, accounting for partial
filling of the “Global” volume with the X-ray-emitting plasmas. The parameters
in the table should be multiplied by the appropriate scale factor (Column 2)
to account for this filling factor. Derived plasma properties are proportional
to $\eta^{1/2}$ and are thus only weakly sensitive to this correction.

To estimate the physical conditions of the diffuse X-ray plasma within 30 Dor,
we follow the approach used in previous work for M17 (Townsley et al., 2003)
and the Carina (Townsley et al., 2011b) to produce Table 3. These three
massive star-forming complexes span more than an order of magnitude in
bolometric luminosity and physical size. Both 30 Dor and Carina clearly host
multiple generations of massive star formation over the past ${\sim}10$ Myr
(Povich et al., 2019; Cignoni et al., 2015). M17 is the least luminous and
most compact of the three, with the youngest rich cluster, the 0.5-Myr-old NGC
6618—but here, too there is evidence for a more evolved and spatially
distributed massive stellar population (Povich et al., 2009; Getman et al.,
2014).

Compared to previous work on much shallower Chandra observations, our Global
model now includes a softer (0.28 keV) NEI component in 30 Dor, similar to
both M17 and Carina (Townsley et al., 2011c). The hardest, $kT3$ component is
hotter in 30 Dor (0.94 keV) than in M17 or Carina (both 0.6 keV). Both 30 Dor
and Carina have similar X-ray plasma densities ($n_{e,x}\sim 10^{-2}$ cm-3)
and pressures ($P_{x}/k\sim 10^{5}$ K cm-3), while the corresponding densities
and pressures in M17 are higher by an order of magnitude. This difference
seems to indicate that the hot plasma is more confined in M17 compared to the
two larger, more evolved complexes.

Because both the three-dimensional geometry and filling factor of the X-ray
emitting plasma are unknown, we introduce a correction factor $\eta$ that can
range from zero to unity that applies to all physical quantities related to
the volume of the hot plasma (see Table 3). The assumed volume ($\eta V_{x}$)
of the hot plasma region in 30 Dor is about 50 times greater than that of
Carina, while the total-band, absorption-corrected luminosity ($L_{tc}$) is
${\sim}120$ times greater (Townsley et al., 2011b). Both the total energy and
mass ($E_{x}$ and $M_{x}$) of the hot plasma scale as $(L_{tc}\eta
V_{x})^{1/2}$. From Townsley et al. (2003), $L_{tc}=\Lambda n_{e,x}^{2}\eta
V_{x}$, where $\Lambda=5\times 10^{-23}$ erg cm3 s-1 is the bolometric X-ray
emissivity (Landi & Landini, 1999). Then the total thermal energy can be
written as

$E_{x}=\frac{3}{2}P_{x}\eta V_{x}\propto n_{e,x}T_{x}\eta
V_{x}\propto\left(\frac{L_{tc}}{\Lambda\eta V_{x}}\right)^{1/2}\eta
V_{x}T_{x}=(L_{tc}\eta V_{x}/\Lambda)^{1/2}T_{x}.$ (2)

The total mass $M_{x}=\mu_{x}m_{p}n_{e}\eta V_{x}$ (denoting the mean particle
mass as $\mu_{x}m_{p}$) has the same dependence on number density and emitting
volume as the total energy, and hence also scales with luminosity as shown in
Equation 2. Based on the above scaling relations and the very similar observed
plasma temperatures, we would expect the total energy and mass of X-ray
emitting plasam to be roughly 10 times greater in 30 Dor than in Carina, but
instead we find they are 65–75 times greater.

We can also compare the luminosity of the diffuse X-ray emission to the
combined bolometric lumnosity of the massive stars in each region. For 30 Dor,
$L_{\rm bol}=3\times 10^{41}$ (Lopez et al., 2011) yields $\log{L_{tc}/L_{\rm
bol}}=-4.15$. Adopting $L_{tc}$ from Townsley et al. (2011c) and $L_{\rm bol}$
from (Binder & Povich, 2018), we have $\log{L_{tc}/L_{\rm bol}}=-5.70$,
$-$5.52, and $-$6.04 for Carina, NGC 3603, and M17, respectively, in the Milky
Way.

Based on the above simple comparisons, the superlative mass, energy, and
luminosity of the X-ray-emitting plasma in 30 Dor require enhanced mass-loss
and high-energy feedback for this starburst region, exceeding expectations for
scaled-up versions of the Galactic regions.191919While a smaller filling
factor $\eta$ for the 30 Dor plasma compared to the Galactic regions is
plausible, its value would need to be vanishingly small to explain the
differences in mass and energy in these comparisons, and $\eta$ does not
factor into the luminosity calculation at all. Multiple supernova explosions
have likely contributed to the diffuse plasma. A SN shock propagating at
$v_{\rm shock}{>}100$ km s-1 (e.g., Chen et al., 2023) would cross the
diameter of the T-ReX field in ${<}0.5$ Myr, and we have already discussed the
abundance of evidence for recent SNe in the form of pulsars (+wind nebulae
such as the Manta Ray) associated with evolved massive clusters.

The brightest diffuse emission, however, is centered on R136, which is too
young to have experienced SNe. This points to a wind origin, driven by the
higher mass-loss rates of the numerous Wolf-Rayet and other supermassive stars
in this extraordinarily rich cluster (Nugis & Lamers, 2000; Vink & de Koter,
2005, C22). Example tesselates in outer regions of 30 Dor that could plausibly
be dominated by SN-driven bubbles (92, 293, and 305; see Figure 11) have
15%–25% the absorption-corrected surface brightness of tessellate 131, which
samples diffuse plasma closest to R136, hence 70–85% of the diffuse X-ray
luminosity in the central regions could be wind-generated.

##  6 Legacy Value of T–ReX

In this overview of the T-ReX project, we have provided numerous data
products, including a point-source catalog, diffuse emission images and
spatially-resolved spectra (Section 2.7). The analysis presented in this work
only scratches the surface of this unprecedentedly deep and rich X-ray
dataset. T-ReX provides our best opportunity to dissect the high-energy
emission from a starburst region. These galactic building blocks all emit
X-rays, but they blur together in distant starburst galaxies. With T-ReX, we
have quantified the relative contributions of the diverse sources that
constitute the X-ray emission of a starburst. The stars themselves (single
very massive stars, colliding-wind binaries, and lower-mass pre-MS stars) and
their stellar remnants (pulsars, X-ray binaries) are generally resolved and
hence can be separated from truly diffuse shock emission (from massive stellar
winds, individual young SNRs, thermalized cavity SNRs, and PWNe). T-ReX
provides the largest number of diffuse X-ray emission counts ever detected
from a massive star-forming region, surpassing Carina (Townsley et al., 2011c)
and Cygnus OB2 (Albacete-Colombo et al., 2023).

A rich history of multiwavelength studies leverages 30 Dor as a bridge from
Galactic to extragalactic studies. T-ReX emerges as a singularly powerful
dataset for study of diffuse emission and feedback, but it has also revealed
the limits of current X-ray instrumentation in studying resolved stellar
populations beyond the Milky Way. While point sources become fainter with
distance, X-ray surface brightness is a conserved quantity, and we have shown
that the exceptionally bright diffuse emission in 30 Dor adversely affects the
point-source sensitivity limits, which was not the case in Carina and other
Galactic GHIIR s (Townsley et al., 2011c). Even Chandra’s unmatched spatial
resolution is no match for the level of crowding and source confusion at the
center of the R136 cluster (see also C22).

T-ReX will remain the best dataset available for the foreseeable future for
the analysis of diffuse X-ray emission in active star-forming regions,
including evidence for charge exchange processes at hot/cold ISM interfaces.
Gratings spectroscopy with current instruments, while successfully applied to
young Galactic supernova remnants and more distant starburst galaxies, cannot
probe the lower surface brightness of plasmas generated by stellar winds and
cavity supernovae. There is need for still better spatial resolution to
resolve out contributions from bright point sources that outshine the diffuse
emission in more distant galaxies. Further analysis of the T-ReX data should
map the variations in X-ray absorption-corrected surface brightness, plasma
temperature, density, pressure, and metallicity across 30 Dor, better
quantifying the effects of feedback from massive stars on the evolution of
star-forming regions and their host galaxies.

We appreciate the time and effort donated by our anonymous referee to provide
helpful and supportive comments on this paper. We thank Breanna Binder and
Anna Rosen for helpful discussions, offering their perspectives as,
respectively, an extragalactic high-energy observer and a theoretician of
massive stellar feedback processes. This work was supported by the Chandra
X-ray Observatory Guest Observer grants GO5-6080X (PI: L. Townsley) and
GO4-15131X (PI: L. Townsley) and by the Penn State ACIS Instrument Team
Contract SV4-74018. Both of these were issued by the Chandra X-ray Center,
which is operated by the Smithsonian Astrophysical Observatory for and on
behalf of NASA under contract NAS8-03060. M. Povich acknowledges support from
the National Science Foundation under award AST-2108349 (RUI). The ACIS
Guaranteed Time Observations included here were selected by the ACIS
Instrument Principal Investigator, Gordon P. Garmire, of the Huntingdon
Institute for X-ray Astronomy, LLC, which is under contract to the Smithsonian
Astrophysical Observatory; Contract SV2-82024. This research used data
products from the Chandra Data Archive, software provided by the Chandra X-ray
Center in the application package CIAO, and the SAOImage DS9 software
developed by the Smithsonian Astrophysical Observatory. This research also
used data products from the Spitzer Space Telescope, operated by the Jet
Propulsion Laboratory (California Institute of Technology) under a contract
with NASA. This work used data products from the NASA/ESA Hubble Space
Telescope, obtained at the Space Telescope Science Institute, which is
operated by AURA Inc., under NASA contract NAS 5-26555. This work also used
data from the ESA mission Gaia (https://www.cosmos.esa.int/gaia), processed by
the Gaia Data Processing and Analysis Consortium (DPAC,
https://www.cosmos.esa.int/web/gaia/dpac/consortium); funding for the DPAC has
been provided by national institutions, in particular the institutions
participating in the Gaia Multilateral Agreement. This research has also made
use of NASA’s Astrophysics Data System Bibliographic Services, and the SIMBAD
and VizieR databases operated at the Centre de Données Astronomique de
Strasbourg. .

##  Appendix A Possible Optical/IR Counterparts to X-ray Point Sources

Identifying optical-infrared (OIR) counterparts to Chandra sources (“matching”
X-ray and OIR catalogs) is often a challenging task. The dynamic range of flux
sensitivity for any OIR catalog will typically be narrower than the apparent
OIR fluxes of the objects detected by Chandra. For example, when the absorbing
column and astrophysical classification of an X-ray source are unknown, its
apparent magnitude could span a range ${\gtrsim}15$ in $J$ (Getman et al.,
2011; Broos et al., 2013). The difference in spatial resolution of an OIR
catalog compared to the ${\sim}0.5\arcsec$ on-axis resolution of ACIS
complicates the notion of a simple, one-to-one match, as in cases of large
resolution departures (beyond a factor of 2) a single source in the lower-
resolution catalog will frequently overlap with multiple sources in the other.
The population of X-ray sources without detected OIR counterparts can
significantly degrade the reliability of most X-ray/OIR matching algorithms,
because every such X-ray source is an opportunity for generating a spurious
match declaration (arising from the random proximity of unrelated
astrophysical objects in the two catalogs).

When matching a Chandra catalog to an OIR catalog, we use simulations to
estimate the fraction of Chandra sources that have true counterparts and to
statistically characterize the performance of the matching run (Broos et al.,
2007, 2011). One useful product of those simulations is a quality metric for
the run—the fraction of declared matches expected to be spurious. That match
quality depends on the fraction of X-ray sources with true counterparts, on
the size of the Chandra and OIR position uncertainties, and on the density of
the catalogs.

We identified possible counterparts in the six OIR catalogs listed in Table 4:

  1. 1.

The Gaia catalog reports optical sources across the entire T-ReX field to a
limiting magnitude of $G<21$, with effective spatial resolution comparable to
ACIS (Gaia Collaboration, 2018).

  2. 2.

The VISTA Magellanic Cloud survey catalog(Irwin et al., 2004; Hambly et al.,
2008; Cross et al., 2012, VMC;) reports near-infrared sources across the
entire T-ReX field to limiting magnitudes of $Y=21.1$, $J=21.3$, and
$K_{S}=20.7$ with comparable spatial resolution to ACIS on-axis. We have used
data from the 3rd data release.

  3. 3.

The VLT-FLAMES Tarantula Survey (VFTS) catalog (Evans et al., 2011) is a list
of 930 candidate massive stars, many subsequently confirmed via spectroscopic
classification in the 30 Doradus region of the Large Magellanic Cloud (Walborn
et al., 2014; Evans et al., 2015).

  4. 4.

Doran et al. (2013) published a comprehensive list of known and candidate
massive stars in the 30 Doradus region, with cross-references to the VFTS
catalog.

  5. 5.

The Hubble Tarantula Treasury Project (HTTP) catalog reports point-source
photometry in eight visible through NIR filters for a subset of the T-ReX
field (Sabbi et al., 2016). Each filter reaches a sensitivity of 25th
magnitude or better, with bright-source limits ranging between magnitudes 15
and 17. The spatial resolution of HST is 5 to 10 times sharper than ACIS on-
axis.

  6. 6.

The Spitzer Surveying the Agents of Galaxy Evolution (SAGE Meixner et al.,
2006) program cataloged mid-infrared point sources (in five filters ranging
from 3/6 to 24 $\mu$m) across the LMC, including the entire T-ReX field.
Point-source sensitivity ranged from $[3.6]\lesssim 18$ to $[24]\lesssim 11$,
with saturation limiting the bright sources to ${\gtrsim}4$ to 6 magnitudes.
The angular resolution of Spitzer at 3.6 $\mu$m was about five times poorer
than ACIS on-axis.

We performed simple experiments by which we introduced small, random
positional offsets between the T-ReX catalog and OIR catalogs to assess the
fraction of longer-wavelength counterparts consistent with random chance.
These simulations demonstrated that within the T-ReX field the fraction of
Chandra sources with true, one-to-one counterparts in the OIR catalogs is very
low, hence producing a counterpart list with a high level of quality is very
challenging. We employed two important strategies for improving counterpart
quality.

The first strategy was to improve the published positions in the OIR catalogs.
As shown in Table 4, we shifted the coordinate frames of the VMC, SAGE, and
Chandra catalogs to match the Gaia frame.202020 Gaia positions were propagated
to the mean epoch of the Chandra data (Y2014.5) . Each subgroup of massive
star coordinates we obtained from Doran et al. (2013) was shifted to optimally
align with the Gaia frame. Individual source positions in the VFTS and HTTP
catalogs were significantly improved by constructing field distortion maps.
Single-axis ($\alpha,\delta$) position uncertainties (column PosErr in Table
4) were estimated for the VMC, VFTS, Doran, and HTTP catalogs by examining the
distribution of offsets along each coordinate axis between those catalogs and
Gaia.

The second counterpart quality improvement strategy was to reduce the density
of the HTTP and Chandra catalogs. Among the X-ray emitting objects likely to
be detected by HTTP, those of most interest to us are massive stars and
T-Tauri stars. Thus, we made two photometry selections designed to select
those objects: a magnitude cut ($F555<19$) to select massive stars, and a
color-magnitude selection in the F555W vs F555W-F775W diagram approximating
the locus of T-Tauri stars in Figure 20 of Ksoll et al. (2018). Those
selections reduced the size of the HTTP catalog from ${>}8\times 10^{5}$ to
29,445 rows.

We found that counterpart matching quality could also be significantly
improved by trimming the Chandra catalog using any of several X-ray
properties, including detection significance, position uncertainty, off-axis
angle, observed photon flux, and median energy of the extracted X-ray events.
We chose to trim the Chandra catalog independently for matching to each OIR
catalog, using the X-ray detection significance thresholds reported in
footnote $h$ of Table 4.

Table 4: Catalog Matching Summary

Catalog | Position $(\alpha,\delta)$ | Rows Retained | Matches
---|---|---|---
Name | Citation | Shift | Error | OIR | Chandra | Gross | Correct
|  | mas | mas |  |  | matches | % of gross
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8)
Gaia | Gaia Collaboration (2016, 2018) | aa Gaia positions were precessed to the mean epoch of the Chandra data (Y2014.5). | published | all | 497h,ih,ifootnotemark:  | 114kk Chandra sources were matched to the union of the Gaia and VMC catalogs, rather than to each independently.  | 78%kk Chandra sources were matched to the union of the Gaia and VMC catalogs, rather than to each independently.
VMC | Cioni et al. (2011) | (23,15) | (41,44) | all | 497h,ih,ifootnotemark:  | 114kk Chandra sources were matched to the union of the Gaia and VMC catalogs, rather than to each independently.  | 78% kk Chandra sources were matched to the union of the Gaia and VMC catalogs, rather than to each independently.
VFTS | Evans et al. (2011) | bb Field distortions in the coordinates reported by the HTTP and VFTS catalogs were reduced by constructing smooth field distortion maps derived from matching those catalogs to Gaia. The median (maximum) HTTP correction was 67 (1200) mas. The median (maximum) VFTS correction was 81 (160) mas. | (15,13) | all | 1910hh To achieve reasonable match quality (Column 8), matching used only high-significance X-ray detections defined by ProbNoSrc_MostValid $<1\times 10^{-5}$ for Gaia and VMC, ProbNoSrc_MostValid $<1\times 10^{-3}$ for VFTS and Doran, ProbNoSrc_MostValid $<4\times 10^{-4}$ for HTTP, ProbNoSrc_MostValid $<1.2\times 10^{-4}$ for SAGE.  |  $>$74 |  $\cdots$
Doran | Doran et al. (2013) | cc Each subgroup of massive star coordinates we obtained from Doran et al. (2013)—originally from the CTIO, Parker, Selman, WFI, Walborn, Zaritsky, and De Marchi catalogs—was shifted to optimally align with the Gaia catalog. | dd Position errors were estimated for each published catalog collated by Doran et al. (2013): 0.025″for dM, $\sim$0.1″for W, S, C, P catalogs.  | ff Excluded Doran sources with a published VFTS identification (Doran et al., 2013), and the following Doran sources that we believe are missing VFTS cross-identifications: VFTS416=Doran390, VFTS562=Doran778, VFTS1011=Doran533, VFTS1024=Doran683, VFTS641=Doran884, VFTS522=Doran578, VFTS468=Doran451.  | 1910hh To achieve reasonable match quality (Column 8), matching used only high-significance X-ray detections defined by ProbNoSrc_MostValid $<1\times 10^{-5}$ for Gaia and VMC, ProbNoSrc_MostValid $<1\times 10^{-3}$ for VFTS and Doran, ProbNoSrc_MostValid $<4\times 10^{-4}$ for HTTP, ProbNoSrc_MostValid $<1.2\times 10^{-4}$ for SAGE.  |  $>$32 |  $\cdots$
HTTP | Sabbi et al. (2016) | bb Field distortions in the coordinates reported by the HTTP and VFTS catalogs were reduced by constructing smooth field distortion maps derived from matching those catalogs to Gaia. The median (maximum) HTTP correction was 67 (1200) mas. The median (maximum) VFTS correction was 81 (160) mas. | (2.7,4.3) | gg For matching, we selected 29,445 candidate massive stars ($F555<19$ mag) and candidate T Tauri stars (a region of the F555W vs F555W-F775W color-magnitude diagram approximating the locus of T Tauri stars in Figure 20 of Ksoll et al. (2018)). | 1013h,i,jh,i,jfootnotemark:  | 124 | 63%
SAGE | Meixner et al. (2006) | (64,17) | (134,110) | all | 851h,ih,ifootnotemark:  | 79 | 90%
T-ReX |  $\cdots$ | (17,23) | ee For matching, a systematic error (0.08″) was added in quadrature to published Chandra position errors.  |  $\cdots$ |  $\cdots$ |  $\cdots$ |  $\cdots$

iifootnotetext:  Chandra sources declared to have VFTS/Doran counterparts were
excluded from automated matching with Gaia, VMC, HTTP, and SAGE (Table 7).

jjfootnotetext:  Chandra sources were cropped to the HTTP field of view.

Note. — Column “Shift” reports the shift applied to published coordinates to
align with Gaia.

“Rows Retained” reports the subset of the published catalog used for
counterpart identification.

Column “Gross” reports the number of possible counterparts declared.

Column “Correct” reports the fraction of gross counterpart declarations that
are likely to be true astrophysical counterparts, estimated via simulations.

###  A.1 Massive Stars

Our list of known and candidate massive stars in the T-ReX field consists of
the 930 bright stars in the VFTS catalog and the additional ${>}500$ massive
stars that Doran et al. (2013) collected from pre-existing catalogs. Due to
crowding in R136, we chose to identify X-ray counterparts in our list of known
and candidate massive stars via visual review and human judgement, rather than
by algorithmic catalog matching. In that visual review positions of OIR
sources (VFTS, Doran, and HTTP positions, corrected as described above) and
position error rectangles for our X-ray sources were displayed on an $HST$
image (Sabbi et al., 2016). In most cases, we were able to identify the
VFTS/Doran object in the Gaia catalog and make our counterpart decision using
the Gaia position for the massive star. The median separation between OIR
(often Gaia) and X-ray positions was 0.15 arcsec.

Table 5 lists the known and candidate massive stars that we judge to have been
detected as individual T-ReX point sources (with the significance cut shown in
Table 4, $ProbNoSrc\\_MostValid<1\times 10^{-3}$). Table 6 reports instances
of close pairs or multiples of massive stars that were judged to be detected
but unresolved by ACIS. These datasets were used by C22 for an in-depth study
of X-ray emission from early-type stars in 30 Dor.

An additional 37 Chandra sources are located within 1–2″ of a VFTS/Doran
source, making it tempting to believe that these massive stars were also
detected in X-rays. However, we judged that the separations between these
X-ray sources and the nearby massive stars were inconsistent with their
position uncertainties.

###  A.2 Additional Counterparts

Counterparts to X-ray sources that are not suspected to be massive stars were
identified via automated catalog matching, using the Gaia, VMC, trimmed HTTP,
and SAGE catalogs described above. The matching criterion is defined such
that, if the actual position uncertainties are as declared, then 99% of the
true counterparts will be identified. Table 4 reports the X-ray detection
significance thresholds used to trim the X-ray catalog for each matching
exercise, the gross number of matches declared, and the expected quality of
the declared matches (fraction of declared expected to be spurious) estimated
from simulations. Table 7 lists the declared matches.

=0.5in  X-ray Source VFTS/Doran ID, Adopted Coordinatesaa The coordinates
published in the VFTS and Doran catalogs were not directly used to assess
positional coincidence between X-ray sources and candidate/known massive
stars. When the star could be identified in the Gaia catalog (Src “G”), Gaia
coordinates (propagated to the mean epoch of the Chandra data, Y2014.5) and
uncertainties were adopted. Otherwise, when the star could be identified in
the VMC catalog (Src “V”), VMC coordinates were adopted and uncertainties were
estimated by the authors. Otherwise, pubished VFTS coordinates (“V+ ”) were
corrected using a field distortion map derived using Gaia and uncertainties
were estimated by the authors. Otherwise, published Doran coordinates (“D+ ”)
were corrected using frame shifts derived using Gaia and uncertainties were
estimated by the authors.
Other Counterpart Names Label NetCt PhotonFlux_t $E_{med}$ ID RA DEC Src
Sep.bb Separation between ACIS source and star’s Adopted Coordinates; median
is 0.15 arcsec.  Gaia VMC HTTPcc Source label in the HTTP catalog. Due to
space limitations, our corrected HTTP positions are not reported.  See alsodd
Modeling of the T-ReX spectrum is described by Crowther et al. (2022, C22),
Tehrani (2019, T19), Pollock et al. (2018, P18), Clark et al. (2015, C15).
Notes ct ph cm-2 s-1 keV ″ #46576 #55834 Declared Counterparts in VFTS Catalog
p1_610 22077 4.93E-5 3.2 399 05:38:33.413 -69:11:59.02 G 0.13 77456003693440
9048274 053833.417-691159.00 C22 C15 X-ray binary 1_698 7988 1.69E-5 1.6 482
05:38:40.221 -69:05:59.91 G 0.03 79659312960256 053840.214-690559.86 C22 T19
p1_830 1680 4.19E-6 1.4 527 05:38:42.359 -69:04:58.19 G 0.06 85564856502528
9019909 053842.351-690458.19 C22 p1_893 6955 1.69E-5 1.8 1025 05:38:42.903
-69:06:04.96 G 0.02 85534828237440 $\cdots$ C22 T19 p1_1088 693 1.74E-6 1.4
617 05:38:47.522 -69:00:25.28 G 0.23 87733851287040 8944472
053847.533-690025.23 C22 T19 p1_1256 784 1.87E-6 2.0 695 05:38:57.072
-69:06:05.65 G 0.06 85500468567040 9018590 053857.072-690605.58 C22 T19
Declared Counterparts in Doran13 Catalog p1_296 1174 2.80E-6 1.9 185
05:37:49.039 -69:05:08.21 G 0.12 92338057418624 8986916 053749.028-690508.33
C22 T19 p1_812 933 2.02E-6 1.5 580 05:38:42.112 -69:05:55.33 G 0.06
85534828234496 053842.104-690555.29 C22 3 other Doran srcs (573, 577, 587) in
ACIS aperture, but this is definitely the best match p1_867 522 1.61E-6 1.4
682 05:38:42.658 -69:06:02.91 D+ 0.02 $\cdots$ C22 Doran682 uses dM position
p1_979 2180 4.70E-6 1.4 765 05:38:44.129 -69:05:56.71 G 0.03 85534828260608
053844.123-690556.63 C22 p1_995 74445 1.48E-4 1.8 770 05:38:44.256
-69:06:06.00 G 0.04 85534828257792 9020003 053844.252-690605.93 C22 P18 ACIS
pile-up p1_1000 1865 4.09E-6 1.5 775 05:38:44.334 -69:05:54.72 G 0.02
85534828252672 053844.329-690554.66 C22 p1_1194 1233 2.90E-6 1.8 916
05:38:53.383 -69:02:00.88 G 0.1 86222022977920 8959289 053853.363-690200.88
C22 T19

Table 5: Candidate and Known Massive Stars with T-ReX Detections

Note. — Sources with ${>}500$ net counts are displayed above; the full table
is available in the online journal. Reported properties of ACIS sources
(NetCounts_t, PhotonFlux_t, MedianEnergy_t from Table 2) are derived by
combining all observations. In some cases the source detection is most
significant in a single observation. NetCounts suggests the quality of the
extracted spectrum, but is unsuitable for photometry. Apparent Photon Flux
(NetCounts / MeanEffectiveArea / ExposureTimeNominal) is a rough scaling of
NetCounts to account for source-to-source variations in exposure time,
effective area, and aperture size (Broos et al., 2010, Section 7.4).

=0.5in  X-ray Source VFTS/Doran Label NetCt PhotonFlux_t $E_{med}$ ID Src Sep.
See also Notes ct ph cm-2 s-1 keV p1_987 84 1.96E-7 1.2 V1034aa We suspect
that the identifiers VFTS1034 and Doran769 refer to the same star.  G 0.2 C22
Both could contribute to ACIS light D772 D+ 0.3 p1_866 62 1.50E-7 1.4 D685 G
0.25 C22 Both could contribute to ACIS light D671 D+ 0.5 p1_832 4452 1.15E-5
1.5 D633 D+ C22 T19 Mushroom aperture at ACIS aimpoint; hopelessly confused at
R136 core D630 D+ D642 D+ D638 D+ p1_766 31 9.70E-8 1.6 V513bb We suspect that
the identifiers VFTS513 and Doran558 refer to the same star.  G 0.2 C22 Both
could contribute to ACIS light V515 V+ 0.4 cc4970 496 2.39E-6 1.7 D613 D+ C22
T19 $\sim$8 Doran srcs in ACIS aperture D621 D+ c7182 258 6.18E-7 1.4 D657 D+
C22 Many Doran sources in ACIS aperture D652 D+ D649 D+ D659 D+ c7157 345
8.16E-7 1.3 D648 D+ C22 Many Doran sources in ACIS aperture D624 D+ c7018 45
2.20E-7 1.5 D589 D+ C22 Many Doran sources in ACIS aperture D583 D+

Table 6: Candidate and Known Massive Stars Associated with ACIS Source Blends
In R136

Note. — See footnotes to Table 5.

=0.5in  X-ray Source Gaia+VMC HTTPaa Column “ID” is the published label for a
detection in the HTTP catalog. Column “Correction” reports the shift we
applied to the published position.  SAGE Label PosErr Dist.bb Separation
between ACIS source and Adopted Coordinates.  Gaia ID VMC ID K Dist.bb
Separation between ACIS source and Adopted Coordinates.  ID Shift F555 Dist.bb
Separation between ACIS source and Adopted Coordinates.  SAGE ID 3.6µm
SIMBADcc Identifiers reported by SIMBAD.  ″ ″ #4657 #55834 mag ″ mas mag ″ mag
p1_255dd Using our judgement, we assert two associations that were not found
by automated methods: Pulsar PSR J0537-6910 == T-Rex 053747.40-691020.2
(p1_255); the low-mass star HD 269921 == T-ReX 053834.66-685306.1 (pass52_4).
Pulsar (PSR J0537-6910) pass52_4dd Using our judgement, we assert two
associations that were not found by automated methods: Pulsar PSR J0537-6910
== T-Rex 053747.40-691020.2 (p1_255); the low-mass star HD 269921 == T-ReX
053834.66-685306.1 (pass52_4).  0.47 783116463742336 8880341 10 Rotationally
variable Star (HD 269921) p1_1548 0.2 0.4 9712401 19 0.2 053955.602-690846.62
130,688 25 p1_1529 0.2 0.1 684980764259456 8944793 16 0.2 J053939.44-690029.7
14 AGN ([GC2009] J053939.48-690030.0) c11125 0.3 0.2 8919503 15 0.1
J053938.25-685740.2 14 YSO (2MASS J05393821-6857404) p1_1521 0.1 0.2
682923488239360 9014587 13 0.3 053935.478-690438.90 204,381 17 0.4
J053935.50-690438.6 12 p1_1517 0.2 0.3 9778551 20 0.5 J053933.97-691130.4 16
c10740 0.3 0.5 9713682 18 0.2 053925.779-691031.35 -28,-54 23 c10422 0.2 0.2
9768044 18 0.2 J053915.91-685752.2 17 p1_1420 0.2 0.3 8939594 16 0.6
J053915.91-685950.0 15 c10393 0.2 0.1 679281354744320 9023693 14 0.1
053914.961-690923.81 -20,-139 19 0.1 J053914.96-690923.7 14 Long-period
variable star (2MASS J05391496-6909238) c10370 0.2 0.1 9767609 19 0.1
J053913.96-685728.6 17 c10266 0.1 0.2 679384433817472 9014737 0.2
053910.764-690756.78 10,-129 18 0.4 J053910.79-690756.7 15 p1_1368 0.1 0.1
9706871 18 0.1 J053908.45-685958.6 16 p1_1317 0.0 0.0 9774684 21 0.0
053903.176-690703.87 24,-125 24 c9590 0.2 0.3 8938310 18 0.4
J053859.69-685949.3 17 c9506 0.4 0.3 8849680 17 0.3 J053859.31-684959.5 15
p1_1246 0.2 0.4 688416745861760 8912946 17 0.3 J053856.83-685636.3 15 c9209
0.1 0.1 8978864 0.1 053856.710-690426.29 42,-84 22 c8790 0.1 0.2 9707745 18
0.2 J053852.25-690126.9 17 cc5713 0.1 0.4 053848.720-690715.56 27,-94 23 0.4
J053848.73-690715.6 15 c8315 0.1 0.3 9770921 18 0.4 J053848.05-690210.8 16
c8216 0.1 0.2 053846.871-690505.58 38,-73 24 0.2 J053846.84-690505.4 10
p1_1056 0.2 0.2 8921036 18 0.5 J053845.63-685759.7 c7568 0.1 0.1 8996929 17
0.2 053843.546-690628.82 33,-69 18 0.4 J053843.50-690629.0 14 YSO (OGLE LMC-
ECL-21448) c6236 0.1 0.2 9774528 17 0.2 053839.963-690652.52 33,-54 26 c6150
0.1 0.0 685534828103552 0.0 053839.633-690532.25 39,-48 17 c5995 0.1 0.2
679659312977664 0.2 053838.549-690612.85 35,-45 17 c5836 0.3 0.5 9705089 17
0.7 J053837.20-685655.0 16 p1_641 0.2 0.2 9767536 19 0.3 J053836.65-685725.9
18 p1_639 0.1 0.2 9038525 0.2 053836.577-691056.66 -14,-38 22 p1_609 0.3 0.7
8923829 18 0.3 J053833.49-685817.9 17 c5204 0.2 0.0 8968459 0.1
053832.322-690314.89 14,-9 22 p1_574 0.1 0.2 9707046 18 0.4
J053826.21-690012.9 16 c4405 0.4 0.7 783490104306304 8855976 10 0.9
J053821.25-685034.0 10 c3916 0.2 0.3 686698750750848 8976411 0.3
053810.121-690224.70 14,80 19 p1_464 0.2 0.3 688863422482304 8912592 16 0.2
J053809.91-685657.7 15 c3775 0.2 0.6 053806.273-691310.00 -37,46 24 0.8
J053806.27-691310.1 15 c3766 0.2 0.2 679968549406848 9021508 13 0.2
053805.644-690909.77 13,70 19 0.3 J053805.61-690909.6 11 YSO (2MASS6X
J05380564-6909098) p1_450 0.0 0.1 9708672 19 0.1 053802.741-690259.15 24,105
22 0.1 J053802.73-690258.9 16 c3526 0.2 0.6 8872736 17 0.7 J053757.84-685238.2
16 p1_410 0.1 0.3 9710167 16 0.2 053754.561-690516.57 23,107 26 p1_406 0.1 0.1
9771021 20 0.0 J053754.32-690222.1 17 c2202 0.5 0.5 701198560089088 8877930 17
0.5 J053745.77-685311.3 15 AGN (MQS J053745.77-685311.4) c1348 0.5 0.6 9705614
16 0.5 J053738.09-685753.1 15 c1167 0.2 0.5 692024485433088 8982580 16 0.2
J053729.61-690451.8 16 p1_11 0.2 0.2 9711726 17 0.2 053725.617-690738.37
-12,29 25 0.4 J053725.55-690738.2 16 c1042 0.3 0.3 053721.382-690621.28 -13,11
26 0.6 J053721.45-690621.4 17 c979 1.1 1.9 663849561921024 9131446 1.5
J053714.70-692021.0 17 c919 0.3 0.2 690001595436160 9033573 15 0.2
053710.840-691025.19 49,51 18 0.4 J053710.87-691025.1 14 p1_5 0.3 0.4
690070295111040 9025732 18 0.5 J053703.80-690942.6 17 c749 0.4 0.7
693433288582784 8962789 16 0.6 J053658.57-690234.2 16 pass53_1 0.2 0.3
666323458738560 9061522 15 0.3 053657.042-691328.57 309,290 21 0.1
J053657.12-691328.2 14 c373 0.9 0.8 702989558190336 8894623 14 0.8
J053612.44-685455.9 14 c73 0.2 0.5 9090770 15 SNR 1987A

Table 7: Counterparts To X-ray Sources Beyond the Massive Stellar Population

Note. — A portion of this table, highlighting sources with counterparts in
more than one optical/IR catalog, is provided here to illustrate format and
content. The full table is available in the online journal.

##  Appendix B High-Quality Variable Sources

In this Appendix we briefly highlight several striking, high-quality variable
sources. This is by no means an exhaustive list, and we would expect the T-ReX
catalog to provide a resource for various future variability studies.

###  B.1 Periodic Variation

Binary stellar systems can exhibit periodic modulation of the unresolved X-ray
emission from the system, due to time-varying accretion, eclipses, or time-
variation in the physical state of colliding winds. The long-baseline T-ReX
observations (Table 1) provide several high-quality examples of periodic
variation.

The multipanel figure sets below (Figures 13, 15, and 16) depict X-ray
lightcurves (representing a 68% confidence interval versus phase), phase-
folded median X-ray energy, and periodograms. The phase-folded folded
lightcurves were constructed for the specified period by converting X-ray
event timestamps (with barycentric correction) to phase values, calculating
the phase distribution of those phased events, calculating the phase
distribution of all the time periods in which the source was observed (using
CIAO’s Good Time Interval data product), and then adaptively smoothing the
event and exposure distributions to achieve a signal-to-noise goal. The result
is a smooth estimate of gross (star plus background) photon flux (in units of
photon s${}^{-1}~{}$cm-2) with uncertainties. The median energy time-series
were constructed by simply binning the phased events, calculating the median
energy of the events in each bin, and estimating uncertainties (employing a
binomial distribution).

The periodograms plot $p$-values for the Kuiper statistic, under the null
hypothesis of a constant flux, computed on the phased event distribution and
the phased exposure distribution (Paltani, 2004) for a large number of trial
periods. Sharp local minima in the periodogram suggest periodic variability,
however interpretation requires caution because interactions between the
observational sampling and aperiodic variability of the source can also
produce small $p$-values.

R144
The binary Wolf-Rayet star R144 (053853.36-690200.9, p1_1194, Doran 916) has a
published optical period of 74.2074 day (Shenar et al., 2021), which is
consistent with the period we estimate from the T-ReX data ($\sim$74.4 day,
Fig. 13). When folded on that optical period, R144 exhibits $\sim$50% X-ray
flux modulation (Shenar et al., 2021, Fig. 17) and clear modulation of the
apparent spectral hardness (Fig. 13).

Figure 13: Phase-dependent X-ray flux (top left) and median X-ray event energy
(top right) for R144 (053853.36-690200.9, p1_1194, Doran 916). Phase is
calculated for a published optical period (74.2074 day) and T0 (periastron,
MJD 58268.98; Shenar et al., 2021). A similar period estimate ($\sim$74.4 day)
was obtained from the X-ray data (bottom).

Before modeling the phase-resolved X-ray spectrum of R144, we first identified
a reasonable model for the complete spectrum (full ${\sim}2$ Ms exposure),
consisting of two thermal plasmas with independent absorbers (in XSPEC, the
model tbvarabs1*vapec1 + tbvarabs2*vapec2). That fit indicated plasma
temperatures of 0.74 and 2.1 keV. One possible interpretation of this model
would be a soft plasma produced by each of the stars plus a hard plasma
produced by a colliding wind shock.

We then fit spectra obtained from ten groups of observations with similar
phase (Table 8). Each group contains 3–10 ObsIDs. We investigated the simple
hypothesis that the observed variation was dominated by only one phase-
dependent parameter, the absorption ($N_{H2}$) of the colliding wind shock
emission ($kT_{2}$). Specifically, each of the ten phase-resolved spectra was
fit with $kT_{1}$,$kT_{2}$ and $N_{H1}$ frozen to the values obstained from
the models of the complete spectrum. $N_{H2}$ and the plasma normalizations
remained free parameters. Most of the phase-interval spectra were well-fit by
this model (see $\chi_{\nu}^{2}$ in Table 8). Under these model assumptions,
the phase modulations of $N_{H2}$ and the absorption-corrected luminosities
are plotted in Figure 14.

Figure 14: Phase modulation of the hot plasma absorption (left) and absorption-corrected luminosity (right) in a model of the R144 spectrum.  Table 8: R144 ACIS X-ray Spectroscopy for Ten Phase Intervals  phaseaaPhase groups are labeled, for example, with “p36” representing the spectrum obtained by merging a group of observations with phase $\sim$0.36. | Spectral Fitbb All fits used the thermal plasma model tbvarabs*vapec+tbvarabs*vapec with abundances for both absorption and plasma components as adopted by Tehrani (2019). Best-fit values for the extinction are shown both as a column density and as $A_{V}=N_{H}/6.5\times 10^{21}$ cm-2. Quantities marked with an asterisk (*) were frozen in the fit. Uncertainties represent 90% confidence intervals. Uncertainties are missing when XSPEC was unable to compute them or when their values were so large that the parameter is effectively unconstrained.  | X-ray Luminositiescc X-ray luminosities in the total ($t$) band (0.5–8 keV) are derived from the model spectrum, assuming a distance of 50 kpc. Absorption-corrected luminosities are subscripted with a $c$. Model luminosities may underestimate the true X-ray luminosity for sources with high absorption because an additional soft thermal plasma could be present but unmeasurable in the X-ray spectrum.  |  |
---|---|---|---|---
|  |  |  |  |  | $\chi_{\nu}^{2}$ | $N_{H1}$ | $A_{V1}$ | $kT_{1}$ | $EM1$ | $N_{H2}$ | $A_{V2}$ | $kT_{2}$ | $EM2$ |  |  |  |  |  |  | $L_{1t}$ | $L_{1tc}$ | $L_{2t}$ | $L_{2tc}$ | $L_{t}$ | $L_{tc}$ |  |
|  |  |  |  |  |  | ($10^{22}$cm-2) | (mag) | (keV) | (log cm-3) | ($10^{22}$cm-2) | (mag) | (keV) | (log cm-3) |  | (log erg s-1) |  |
|  |  | R144, D=50.0 kpc |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
|  |  | p00 |  |  | 1.11 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.1\phantom{.}_{-0.3}^{+0.2}$ | $7.1\phantom{.}_{-3.4}^{+4.7}$ | 10.9 | $2.1\phantom{.}\\!*$ | $56.7\phantom{.}_{-0.2}^{+0.2}$ |  |  |  |  |  |  | 32.73 | 32.98 | 33.14 | 33.65 | 33.28 | 33.73 |  |
|  |  | p08 |  |  | 1.59 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.1\phantom{.}_{-0.2}^{+0.1}$ | $9.4\phantom{.}_{-3.9}^{+8.8}$ | 14.4 | $2.1\phantom{.}\\!*$ | $56.6\phantom{.}_{-0.2}^{+0.2}$ |  |  |  |  |  |  | 32.80 | 33.05 | 32.95 | 33.53 | 33.18 | 33.65 |  |
|  |  | p18 |  |  | 0.58 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.2\phantom{.}_{-0.2}^{+0.1}$ | $5.4\phantom{.}_{-3.1}^{+4.9}$ | 8.4 | $2.1\phantom{.}\\!*$ | $56.6\phantom{.}_{-0.2}^{+0.2}$ |  |  |  |  |  |  | 32.81 | 33.06 | 33.08 | 33.55 | 33.27 | 33.67 |  |
|  |  | p28 |  |  | 1.04 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.0\phantom{.}_{-0.5}^{+0.2}$ | $2.3\phantom{.}_{-1.0}^{+1.5}$ | 3.5 | $2.1\phantom{.}\\!*$ | $56.6\phantom{.}_{-0.1}^{+0.1}$ |  |  |  |  |  |  | 32.63 | 32.89 | 33.15 | 33.47 | 33.27 | 33.57 |  |
|  |  | p36 |  |  | 0.40 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.0\phantom{.}_{-0.3}^{+0.2}$ | $3.1\phantom{.}_{-0.9}^{+1.1}$ | 4.7 | $2.1\phantom{.}\\!*$ | $56.8\phantom{.}_{-0.09}^{+0.08}$ |  |  |  |  |  |  | 32.66 | 32.91 | 33.32 | 33.68 | 33.40 | 33.75 |  |
|  |  | p44 |  |  | 1.15 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.0\phantom{.}_{-0.6}^{+0.2}$ | $3.8\phantom{.}_{-1.3}^{+1.6}$ | 5.8 | $2.1\phantom{.}\\!*$ | $56.9\phantom{.}_{-0.11}^{+0.09}$ |  |  |  |  |  |  | 32.68 | 32.93 | 33.45 | 33.85 | 33.52 | 33.90 |  |
|  |  | p54 |  |  | 1.23 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $55.9\phantom{.}_{\cdots}^{+0.3}$ | $3.3\phantom{.}_{-1.5}^{+2.0}$ | 5.1 | $2.1\phantom{.}\\!*$ | $56.9\phantom{.}_{-0.1}^{+0.1}$ |  |  |  |  |  |  | 32.55 | 32.81 | 33.42 | 33.80 | 33.48 | 33.84 |  |
|  |  | p70 |  |  | 0.86 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $55.8\phantom{.}_{\cdots}^{+0.4}$ | $1.9\phantom{.}_{-1.3}^{+2.2}$ | 2.9 | $2.1\phantom{.}\\!*$ | $56.8\phantom{.}_{-0.2}^{+0.2}$ |  |  |  |  |  |  | 32.43 | 32.69 | 33.39 | 33.68 | 33.44 | 33.72 |  |
|  |  | p83 |  |  | 1.15 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.2\phantom{.}_{-0.2}^{+0.1}$ | $8.5\phantom{.}_{-4.4}^{+7.2}$ | 13.1 | $2.1\phantom{.}\\!*$ | $57.0\phantom{.}_{\cdots}^{+0.2}$ |  |  |  |  |  |  | 32.88 | 33.14 | 33.36 | 33.91 | 33.49 | 33.98 |  |
|  |  | p90 |  |  | 0.94 | $0.452\phantom{.}\\!*$ | 0.7 | $0.74\phantom{.}\\!*$ |  $56.1\phantom{.}_{-0.2}^{+0.1}$ | $9.2\phantom{.}_{-3.4}^{+5.2}$ | 14.2 | $2.1\phantom{.}\\!*$ | $56.8\phantom{.}_{-0.2}^{+0.1}$ |  |  |  |  |  |  | 32.71 | 32.97 | 33.18 | 33.75 | 33.31 | 33.82 |  |
|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |

R145
The binary Wolf-Rayet star R145 (053857.06-690605.6, p1_1256, VFTS 695) has a
published optical period of 158.76 day (Schnurr et al., 2009; Shenar et al.,
2017), which is consistent with the T-ReX data (Tehrani, 2019). When folded on
that period, we find that R145 exhibits $\sim$80% X-ray flux modulation and
clear modulation of the apparent spectral hardness (Fig. 15).

Figure 15: Phase-dependent X-ray flux (left) and median X-ray event energy
(right) for R145 (053857.06-690605.6, p1_1256, VFTS 695). Phase is calculated
for a published optical period (158.76 day) and T0 (MJD 56022.6) (Schnurr et
al., 2009; Shenar et al., 2017).

Figure 16: Phase-dependent X-ray flux (left) and median X-ray event energy
(right) for R139 (053842.34-690458.1, p1_830, VFTS 527). Phase is calculated
for the period we estimate from the T-ReX data ($\sim$153.0 day, bottom). T0
is derived from optical data (MJD 56041.3125, Hugues Sana, private
communication).

R139
The T-ReX data for the O6.5I+O6I binary R139 (053842.34-690458.1, p1_830, VFTS
527) exhibit $\sim$65% X-ray flux modulation and clear modulation of the
apparent spectrum when folded on the period we estimate from the T-ReX data
($\sim$153.0 day, Fig. 16). This period is very similar to the 153.90–day
period derived from optical radial velocity measurements (Taylor et al.,
2011).

Mk33Na
Periodic variation of the O3If (Massey & Hunter, 1998) star Mk33Na
(053844.33-690554.7, p1_1000, Doran 775, Hunter 16, MUSE 1943) has been
detected in both the T-ReX data (P$\sim$18.3 day) and in optical spectra
obtained over a short baseline (P=$18.32\pm 0.14$ day Bestenlehner et al.,
2022). When folded on that period, the T-ReX data exhibit flux modulation of
$\sim$50% and modulation of the apparent spectrum consistent with a phase-
dependent absorbing column density (Bestenlehner et al., 2022).

VFTS 399
Clark et al. (2015) discovered that the massive (O9) star VFTS 399
(053833.43-691159.0, p1_610) probably has an accreting neutron star companion,
based in part on the $\sim$2567 s periodic modulation found in its T-ReX
lightcurve.

Mk34
Pollock et al. (2018) find that Mk34 (053844.25-690605.9, p1_995, VFTS 770) is
an eccentric colliding-wind Wolf-Rayet binary system with a period of
$\sim$155 days, based on its remarkable T-ReX lightcurve.

Mk39
Tehrani (2019, Chapter 4) estimate the period ($\sim$640 day) of the binary
Wolf-Rayet star Mk39 (053840.22-690559.8, p1_698, VFTS 482) using the T-ReX
data.

###  B.2 “Flares”

Fast-rise, slow-decay “flares” were seen in at least two foreground stars. The
low-mass star HD 269921212121 94 pc, Gaia DR2 4657783116463742336
(0.47″separation)  (053834.66-685306.1, pass52_4) shows variability by a
factor of $\sim$100 (Figure 17). Moór et al. (2013) report a spectral type of
G7V, and assert membership in the Columba moving group. These data (85,000
X-ray events) should allow time-resolved spectroscopy of the two complete
“flare” events observed, which exhibit spectral hardening (red curve).

Figure 17: HD 269921 (053834.66-685306.1, pass52_4) lightcurve (blue, with
grouped events in black) and median energy timeseries (red). Two complete
“flare” events exhibit spectral hardening. Vertical dotted lines mark the
boundaries of individual ObsIDs.

The foreground star VFTS 2077 222222 220 pc, Gaia DR2 4657682923488239360
(0.2″separation)  (053935.54-690438.2 , p1_1521) shows dramatic variability in
two of its 54 observations (Figure 18). The peak count rate at the end of
ObsID 16446 (0.038 ct/s = 29 counts in a 770 s interval) is 460 times the mean
count rate ($8\times 10^{-5}$ ct/s = 169 net counts in 2 Ms).

Figure 18: Flares within two single ObsIDs of foreground source
053935.54-690438.2 (p1_1521). Black + symbols depict the arrival time and
energy of individual events, while the red curves give the cumulative
distributions of arrival times. The p-values for the null hypothesis (constant
flux) are $1\times 10^{-5}$ and $3\times 10^{-21}$ for ObsIDs 16202 and 16446,
respectively.

Finally, the foreground low-mass star CAL 6923232353 pc, Gaia DR3
4657651793560005632 (1.33″separation at large off-axis angle)
(053816.28-692331.1, c4107) is an early M dwarf (Riaz et al., 2006) exhibiting
complex, frequent flaring activity (Figure 19). Obtaining this long-baseline
lightcurve for this star was serendipitous, as it happened to fall within the
extreme southern portion of the T-ReX field (Figure 2). X-ray activity in low-
mass stars provides an important constraint on exoplanet habitability models.

Figure 19: CAL 69 (053816.28-692331.1, c4107) lightcurve, plotted with symbols
and axes as in Figure 17. Frequent, low-amplitude flares are observed, with
evidence for spectral hardening.

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