# FASHI: A search for extragalactic OH megamasers with FAST

Chuan-Peng Zhang National Astronomical Observatories, Chinese Academy of
Sciences, Beijing 100101, China  Guizhou Radio Astronomical Observatory,
Guizhou University, Guiyang 550000, China  Cheng Cheng  Chinese Academy of
Sciences South America Center for Astronomy, National Astronomical
Observatories, CAS, Beijing 100101, China  Ming Zhu  Peng Jiang  National
Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
Guizhou Radio Astronomical Observatory, Guizhou University, Guiyang 550000,
China

###### Abstract

The FAST All Sky H I survey (FASHI) is broader in frequency band and deeper in
detection sensitivity than the Arecibo Legacy Fast ALFA survey (ALFALFA).
FASHI is designed to cover the entire sky observable by the Five-hundred-meter
Aperture Spherical radio Telescope (FAST). To efficiently expand the OH
megamaser (OHM) sample at the rest frequency of 1667.35903 MHz, we directly
matched the IRAS Point Source Catalog Redshift (PSCz) catalog with the
corresponding FASHI data cube. We then obtained 27 OHMs, including 9
previously known and 18 new ones, within a redshift range of $0.14314\lesssim
z_{\rm OH}\lesssim 0.27656$. We also measured the hyperfine ratio of nine OHMs
between the 1667 and 1665 MHz lines. The ratio ranges from 1.32 to 15.22, with
an average of $R_{1667:1665}=4.74$. To fit the $L_{\rm OH}$ and $L_{\rm FIR}$
relationship, we have ${\rm log}L_{\rm OH}=(1.58\pm 0.10){\rm log}L_{\rm
FIR}-(15.93\pm 1.20)$, which is almost the same as the previous observations.
All 27 OHMs have relatively high FIR luminosities, suggesting that the host
system has undergone a very recent and violent starburst. The multi-wavelength
SED fitting results also show that the OH host galaxies are massive
($M_{*}\simeq 10^{11}M_{\odot}$) galaxies with the SFR above the star-forming
main sequence. The high $A_{V}$ value of the OH galaxies from the SED fit is
consistent with the high IR luminosities. On the other hand, not all ULIRGs
have detectable OH emission, suggesting that the OH emission may be triggered
within a specific stage of the merger. In general, FAST, with its 19-beam
array and UWB receiver, will be a powerful tool for observing more OHMs and
unraveling their mystery in the future.

Radio telescopes (1360), Megamasers (1023), Hydroxyl masers (771), Redshift
surveys (1378), Radio sources (1358)

##  1 Introduction

OH megamasers (OHMs) at rest frequencies of 1667 and 1665 MHz in extragalactic
systems are valuable indicators of galaxy interactions. These megamasers are
thought to originate from the starburst nuclei of merging gas-rich galaxy
systems, based on both high-resolution interferometer observations (Lo, 2005)
and statistical analysis of luminosity functions (Darling & Giovanelli, 2002,
2006; Giovanelli & Haynes, 2015). OHMs thus offer a distinctive approach to
measuring the occurrence of galaxy mergers at specific evolutionary stages.
(Lo, 2005). The masing emission or absorption lines are usually broad, with a
line width ranging from 10 to $10^{3}\,{\rm km~{}s}^{-1}$, and exhibit an
isotropic luminosity in the range of $10-10^{4}\,L_{\odot}$ (Darling &
Giovanelli, 2002). OHMs are connected to high-density molecular gas ($n(\rm
H_{2})\sim 10^{4}\,cm^{-3}$) and strong far-infrared radiation. They would
offer potential insights into extreme star formation and galactic evolution,
particularly high-redshift OHMs (Darling, 2007; Lockett & Elitzur, 2008;
Roberts et al., 2021; Glowacki et al., 2022; Jarvis et al., 2023). Therefore,
investigating OHMs is a meaningful pursuit.

As of now, approximately 135 OHMs have been discovered, for instance, in
studies of Darling & Giovanelli (2002); Willett (2012); Haynes et al. (2018);
Suess et al. (2016); Hess et al. (2021); Roberts et al. (2021); Glowacki et
al. (2022); Jarvis et al. (2023). The Arecibo Sky Survey exhibits the most
successful tracking or single-point observation to date, detecting
approximately 17% of OHMs (Darling & Giovanelli, 2000). All OHMs known to date
are exclusively associated with (ultra)luminous infrared galaxies ([U]LIRGs),
even those with $L_{\rm FIR}\gtrsim 10^{12}L_{\odot}$ (Baan, 1991). However,
only about 20% of [U]LIRGs are detected with OMH emission, as shown by studies
conducted by Baan (1991); Baan et al. (1992); Darling & Giovanelli (2000,
2001, 2002). The production of OHMs may be a transient phenomenon in the
evolution of a galaxy, from starburst nucleus to an AGN (Wiggins et al.,
2016), or has beaming and orientation effects, as suggested in Darling (2007).

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) All Sky H I
survey (FASHI) aims to cover the entire sky visible to FAST, between
declinations of $-14^{\circ}$ and $+66^{\circ}$, within a frequency range of
$1.0-1.5$ GHz (Nan et al., 2011; Jiang et al., 2019, 2020). The survey
currently has a typical map rms of $\sim$0.76 ${\rm mJy~{}beam}^{-1}$ with a
velocity resolution of 6.4 ${\rm km~{}s}^{-1}$ within a redshift range of
$0.11-0.66$ for OHMs (Zhang et al., 2024), while the Arecibo Legacy Fast ALFA
Survey (ALFALFA) has a lower detection sensitivity of $\sim$1.86 ${\rm
mJy~{}beam}^{-1}$ after smoothing to a velocity resolution of 10 ${\rm
km~{}s}^{-1}$ (Haynes et al., 2018). This suggests that the FASHI could detect
more OHMs than the ALFALFA. Furthermore, the Ultra-Wide Bandwidth (UWB)
receiver on FAST can simultaneously cover a frequency range of 500-3300 MHz
(or $z<2.33$), making FAST a powerful instrument for observing the OHMs in
extragalactic objects (Zhang et al., 2023).

In this paper, we mainly report 18 new and 9 old OHMs detected by FAST.
Section 2 shows the FAST observations and source identification. Section 3
presents the characterization of the detected OHMs and lists four OHM-related
catalogs. Section 4 discusses the hyperfine ratio, host galaxy properties,
$L_{\rm OH}$ and $L_{\rm FIR}$ relationship, and FAST OHM detectability.
Section 5 is a summary. Throughout this paper, we assume a $\Lambda$CDM
cosmology with $H_{0}$ = 75 ${\rm km~{}s}^{-1}$ Mpc-1, $\Omega_{\rm M}=0.3$,
and $\Omega_{\rm\Lambda}=0.7$.

##  2 Data and identification

###  2.1 Observational data

The observational spectral data are from the FASHI project by Zhang et al.
(2024), using the FAST 19-beam receiver to efficiently cover the FAST sky. The
aperture of FAST is 500 m and the effective aperture is about 300 m, resulting
in a beam size of $\sim$2.9′ at 1.4 GHz. The full broadband of 500 MHz in the
spectral line backend has a frequency coverage of 1000 to 1500 MHz with a
total of 64k channels. The corresponding frequency resolution is 7.63 kHz or
1.6 ${\rm km~{}s}^{-1}$ at 1.4 GHz. The FASHI data are reduced using the FAST
spectral data reduction pipeline HiFAST111https://hifast.readthedocs.io/. The
HiFAST pipeline combines data reduction packages including antenna temperature
correction, baseline correction, RFI mitigation, standing wave correction,
gridding, flux correction, and fit cube generation. The data has been smoothed
to 6.4 ${\rm km~{}s}^{-1}$ spectral resolution per channel and the fit cubes
are gridded to a pixel scale of 1′. A heliocentric velocity correction was
applied to the data due to the Doppler effect. A detailed observational setup
and data reduction procedure is presented in the FASHI paper by Zhang et al.
(2024).

###  2.2 Source identification

The extragalactic H I and OHM lines have a similar spectral profile at
different redshifts. Spectroscopic redshift information is needed to
distinguish them (Hess et al., 2021). The IRAS Point Source Catalog Redshift
(PSCz) survey consists of spectroscopic redshifts, infrared and optical
photometry, and miscellaneous information for 18351 IRAS sources, mostly
selected from the Point Source Catalog (Saunders et al., 2000). The survey
covers almost all galaxies with flux brighter than 0.595 Jy at 60 microns,
over the 84% of the sky. It is well known that most previously known OHM have
associated IRAS sources (e.g., Darling & Giovanelli, 2000, 2001, 2002). To
efficiently expand the OHM sample, we could directly cross-check the PSCz
catalog (Saunders et al., 2000) with the corresponding FASHI data cube to see
if there are any emission lines within a beam size of 2.9′ and a velocity
range of $\sim$600 ${\rm km~{}s}^{-1}$. The FASHI data covers around 10000
deg2 within $0^{h}\lesssim{\rm RA}\lesssim 17^{h}$, $22^{h}\lesssim{\rm
RA}\lesssim 24^{h}$, $6^{\circ}\lesssim{\rm DEC}\lesssim 0^{\circ}$, and
$18^{\circ}\lesssim{\rm DEC}\lesssim 64^{\circ}$ with a typical spectral
detection sensitivity of $\sim$1.50 mJy with a velocity resolution of
$\sim$6.4 ${\rm km~{}s}^{-1}$ at 1.4 GHz. Because the FASHI project can only
operate in schedule-filler mode, parts of the above region are not fully
covered. Within the region we found that there are a total of 145 PSCz sources
covered by the current FASHI data with the spectroscopic redshifts in the
frequency range from 1304 to 1461 MHz. Using the FAST spectral data and the
moment 0, 1, 2 images, we check the 145 sources one by one, including the
redshift, coordinate, flux density, and the $g$, $r$, and $z$ bands of the
SDSS data, and then discard the probable H I source. In the end, we discovered
and conformed 27 OHMs, 18 of which were first found by FAST. Detailed
information on these sources is presented in the following sections.

##  3 Detection Results and Analysis

###  3.1 OHM locations

Figure 1: Locations for a total of 154 OHMs, including all previously known
(Darling & Giovanelli, 2002, 2006; Willett, 2012; Suess et al., 2016; Hess et
al., 2021; Glowacki et al., 2022; Jarvis et al., 2023) and newly discovered
OHMs in this work. The triangles with blue IRAS names are the 18 OHMs first
discovered by FAST, while the red ones are 9 known OHMs recovered by FAST. The
black dots are previously discovered OHMs by others.

In Figure 1 we show all the OHM locations, including 18 new OHMs found by FAST
and 135 known ones found by others. From the Figure 1 we can see that the
previously known OHMs are mostly located at $0^{\circ}\lesssim{\rm
DEC}\lesssim 30^{\circ}$, covered by the Arecibo observations. It is
expectable that the FAST observation will be able to fill the gap of ${\rm
DEC}\gtrsim 30^{\circ}$ and ${\rm DEC}\lesssim 0^{\circ}$. Currently, the area
covered by FAST has reached $\sim$10000 deg2. We have discovered and
identified 27 OHMs, which is 20% of all known OHMs, and including 18 newly
found OHMs, which is 12.4% of all known OHMs. The 27 OHMs are selected and
identified from the 145 PSCz sources, already covered by the current FAST
observation. This means that the FAST OHM detection rate is 18.6%, which is
close to the 17% detection rate of the Arecibo OHM Survey (Darling &
Giovanelli, 2000). All information and parameters of the OHMs found by FAST
are presented in the following sections.

###  3.2 Individual sources

Figure 2: OHM IRAS 08201+2801. Left: FAST detected OH emission spectrum. The
1667 MHz OH redshift measured by FAST (in black) and a spectroscopic redshift
(in red) are presented above and below the spectrum with text and
corresponding colored arrows, respectively. The velocity position of the
expected 1665 MHz OH line is indicated by a shorter arrow. Middle: Gray
contours indicate the OH integrated intensity distribution by FAST with a beam
size of $\sim$2.9′. The first three contour levels from inner to outer are
shown in the image. The background shows an RGB image of the $g$, $r$, and $z$
bands of the SDSS data. The white square indicates the optical counterpart
(OC) of the OHM. Right: The zoomed-in RGB image of the OC within the white
square in the middle panel. The figures for the other 26 OHMs are shown in the
Appendix.

####  3.2.1 IRAS 00256-0208

IRAS 00256-0208 was first found and identified as an OHM by the FASHI survey
(see Figures 2). The radio redshift ($z_{\rm OH}=0.27654$) is in good
agreement with the optical observation ($z_{\rm OC}=0.27630$) (Saunders et
al., 2000), and their spatial offset is less than 1.5′. This OHM has the third
highest redshift among all known OHMs in the main 1667 MHz OH emission lines,
the highest being J095903.22+025356.1 with a redshift of $z_{\rm OH}\sim
0.7092$, recently discovered by Jarvis et al. (2023). In addition, the OH
spectrum of this OHM has a wider linewidth of $W_{50}=279.6\,{\rm
km~{}s}^{-1}$ due to its intrinsic multiple velocity components, and its 1667
MHz line is mixed with the 1665 MHz line. This can be a strong indication of
merging activity, as could also be seen in the optical RGB image, as evidenced
by the tidal tail.

####  3.2.2 IRAS 01562+2527

IRAS 01562+2527 has been confirmed as an OHM by the Arecibo OHM Survey
(Darling & Giovanelli, 2002). The FAST observed spectral profile is consistent
with that of Darling & Giovanelli (2002). The only difference is that Darling
& Giovanelli (2002) identified it as the name of IRAS 01562+2528, which is not
listed in the PSCz catalog compiled by Saunders et al. (2000). The optical RGB
image shows two compact cores, one of which has a spiral tidal tail structure
(see Figures 6). This may indicate a merging system.

####  3.2.3 IRAS 02524+2046

This OHM was first confirmed by the Arecibo OHM Survey (Darling & Giovanelli,
2002), which detected an extremely strong peak reaching 40 mJy. However, the
peak detected by FAST is $21.78\pm 1.83$ mJy. This is probably because the OH
flux density is time variable. The emission lines are strong and narrow and
show an extremely good correspondence between the 1667 and 1665 MHz lines.
This allows us to measure the hyperﬁne line ratio of the both. The measured
line ratio is $R_{1667:1665}=2.93\pm 0.23$ (see Tables 2), which is slightly
lower than the measured result (Darling & Giovanelli, 2002), probably due to
the flux variation. The optical RGB image shows a compact nucleus with an
elongated tidal tail surrounding the central nuclei (see Figure 7).

####  3.2.4 IRAS 03111-0244

The OHM IRAS 03111-0244 was first found and identified by the FASHI survey
(see Figures 8). Its measured OH redshift is 0.18956, while the optically
observed redshift is 0.18833 (Saunders et al., 2000) (see Tables 1 and 3). The
velocity difference is $\sim$400 ${\rm km~{}s}^{-1}$, and the spatial peak
offset is 1.5′ between the two. A careful search for other optical objects
shows that there is no possible match to the radio observation. Therefore this
source is probably an OHM corresponding to IRAS 03111-0244. The optical RGB
image shows a typical merging system with elongated tidal tails surrounding
the central nucleus.

####  3.2.5 IRAS 06487+2208

This OHM was first found and reported by the Arecibo OHM Surveys (Darling &
Giovanelli, 2000). The 1667 MHz peak flux density observed by FAST is
consistent with that of (Darling & Giovanelli, 2000). The strong corresponding
1665 MHz line is also visible. The measured line ratio is
$R_{1667:1665}=3.27\pm 0.63$ (see Tables 2). This source has been proposed as
a composite of H II and LINER features based on the Osterbrock spectral line
ratio classification method (Osterbrock, 1989; Veilleux et al., 1995). The
optical RGB image is unresolved, but there may be another nucleus or tidal
tail to the north of the main nucleus.

####  3.2.6 IRAS 08201+2801

IRAS 08201+2801 has been confirmed as an OHM by the Arecibo OHM Surveys
(Darling & Giovanelli, 2001). This object was also detected by the FASHI
survey. The coordinates and redshift are very close between the two
observations, but the OH line profile observed by FAST is consistent with that
of Darling & Giovanelli (2001). The measured OH and infrared parameters are
listed in Tables 1 and 3. The FIR luminosity of this object is 1011.98±0.03
$L_{\odot}$ and it belongs to a LIRG galaxy. Kim et al. (1998) classified the
nucleus of this LIRG as a starburst. The OH spectrum of 08201+2801 shows
multiple velocity components with $W_{50}=242.3\,{\rm km~{}s}^{-1}$. In Figure
10, the optical RGB image shows an obvious morphology with two nuclei
connected by arcs and a single kinked tidal tail, clearly indicating an
advanced merger (see also Darling & Giovanelli, 2001).

####  3.2.7 IRAS 08328+5148

The OHM IRAS 08328+5148 was first found and identified by the FASHI survey
(see Figures 11). At the eastern position (named OC-1 with RA, DEC =
129.1717∘, 51.6246∘) of the currently identified OC, there is an optical
spectroscopic object with a redshift of 0.237 from the SDSS catalog. However,
the OC coordinates are 48′′ away from the OH emission center measured by
FASHI. Fortunately, we find another optical object (named OC-2 with RA, DEC =
129.1505∘, 51.6267∘) at the center of the OH emission distribution. Although
this object has no spectroscopic redshift, its SDSS photometric redshift is
$0.234\pm 0.070$, which agrees well with the OH redshift of 0.23749. In
addition, OC-1 and OC-2 have a similar optical color feature. Furthermore, the
coordinates of IRAS 08328+5148 are in good agreement with the observed OH line
coordinates. Therefore, it is likely that the OC-2 is the optical counterpart
of this OHM, but its spectroscopic redshift is needed for further
confirmation. The FIR luminosity is $L_{\rm FIR}=10^{12.05\pm 0.05}L_{\odot}$,
which belongs to a ULIRG. The OH and infrared parameters are listed in Tables
1 and 3. The optical RGB image shows a possible merging system with a visible
tidal tail. The OH spectrum shows multiple velocity components, indicating an
active merging process.

####  3.2.8 IRAS 08566-0252

The OHM IRAS 08566-0252 was first found and identified by the FASHI survey
(see Figures 12). Its measured OH redshift is 0.20262, while the optically
observed redshift is 0.20201 (Saunders et al., 2000) (see Tables 1 and 3).
Their velocity difference is $\sim$400 ${\rm km~{}s}^{-1}$, but spatially the
two are in good agreement. A careful search for other optical objects shows
that there is no possible match to the radio observation. There is a weak
emission line ($<3\sigma$) at the position of the corresponding 1665 MHz line.
More integration time is needed to verify its authenticity. The optical RGB
image shows a possible merging system with two close nuclei. The OH spectrum
shows multiple velocity components, indicating an active merging process.

####  3.2.9 IRAS 10106+4708

The OHM IRAS 10106+4708 was first discovered by the FASHI survey (see Figures
13). The optical coordinates and the spectroscopic redshift
($z_{\odot}=0.20481$; Saunders et al., 2000) are in good agreement with the
observed OH line coordinates and redshift ($z_{\odot}=0.20529$) for this
object. The strong sharp peak of the OH line is $24.73\pm 1.32$ mJy. The OH
luminosity is $L_{\rm OH}=10^{3.67\pm 0.01}L_{\odot}$ (see Table 1). IRAS
10106+4708 has a FIR luminosity of $L_{\rm FIR}=10^{12.04\pm 0.05}L_{\odot}$
(see Table 3), which belongs to a ULIRG. In Figure 13, the optical RGB image
shows a compact nucleus with extended tidal tails. The object is bright in all
four WISE bands, and the optical data display an evident tidal tail. Despite
that, the optical extinction is significant, leading to the absence of the
H$\beta$ and [OIII] lines. The WISE color at ([4.6]-[12], [3.4]-[4.6]) is
approximately estimated to be (4.18, 0.86) based on the WISE flux. As a
result, this object is speculated to be a dusty quasar (Nikutta et al., 2014).
The measured OH and infrared parameters are listed in Tables 1 and 3.

####  3.2.10 IRAS 10558+3845

The OHM IRAS 10558+3845 was first found and identified by the FASHI survey
(see Figures 14). Its measured OH redshift is 0.20788, while the optically
observed redshift is 0.20660 (Saunders et al., 2000) (see Tables 1 and 3). The
velocity difference is $\sim$400 ${\rm km~{}s}^{-1}$, but spatially the two
are in good agreement. A careful search for other optical objects shows that
there is no possible match to the radio observation. The optical RGB image
shows an apparent spiral tidal tails surrounding the nucleus. The OH spectrum
shows multiple velocity components, indicating an active merging process. The
velocity position of the 1665 MHz line shows a weak emission profile. The
measured line ratio is $R_{1667:1665}=1.62\pm 0.52$.

####  3.2.11 IRAS 10597+5926

This OHM is first found and reported by (Willett, 2012), where the detected
peak flux density is 17.56 mJy, while it is $32.27\pm 2.23$ mJy measured by
FAST. The both flux densities have large difference. However, the line
profiles are consistent between the two. We also detected the 1665 MHz
emission. The measured line ratio is $R_{1667:1665}=15.22\pm 1.46$ between the
1667 and 1665 MHz lines. The optical RGB image shows a possible merging system
with interacting activity. The OH spectrum shows strong and multiple velocity
components, indicating an active merging process.

####  3.2.12 IRAS 11029+3130

This OHM was first found and reported by the Arecibo OHM surveys (Darling &
Giovanelli, 2001). The line profile and flux density observed by FAST are in
good agreement with that of (Darling & Giovanelli, 2001). The only difference
is that Darling & Giovanelli (2001) identified it as the name of IRAS
11028+3130, which is not listed in the PSCz catalog compiled by Saunders et
al. (2000). The central core is a LINER-type active galaxy nucleus (Alatalo et
al., 2016). The optical RGB image is unresolved (see Figure 16), but there is
an extended structure to the west of the main nucleus. This may be probably
indicative of an active merging system.

####  3.2.13 IRAS 11087+5351

The OHM IRAS 11087+5351 was first discovered by the FASHI survey (see Figures
17). The optical coordinates and the spectroscopic redshift
($z_{\odot}=0.14270$; Saunders et al., 2000) are in good agreement with the
observed OH line velocities ($z_{\odot}=0.14314$) and spatial coordinates. The
1665 MHz emission line is clearly visible. The measured line ratio is
$R_{1667:1665}=1.32\pm 0.21$, which is the measured lowest ratio among all
sources in this work. In Figure 17, the optical RGB image shows an extended
morphology with a bright nucleus in the center that may be indicative of
interaction. The central nucleus is identified as a LINER-type active galaxy
nucleus by (Toba et al., 2014). The OH and infrared parameters are listed in
Tables 1 and 3.

####  3.2.14 IRAS 11161+6020

The OHM IRAS 11161+6020 was first discovered by the FASHI survey (see Figures
18). The optical coordinates and spectroscopic redshift ($z_{\odot}=0.26428$;
Abazajian et al., 2009) are in good agreement with the observed OH line
coordinates and redshift ($z_{\odot}=0.26434$). The OH luminosity is $L_{\rm
OH}=10^{3.68\pm 0.02}L_{\odot}$ (see Table 1). It has a FIR luminosity of
$L_{\rm FIR}=10^{12.21\pm 0.04}L_{\odot}$ (see Table 3), which belongs to a
ULIRG. Toba et al. (2014) classified it spectroscopically as a Seyfert 2
galaxy. In Figure 18 the optical RGB image shows a compact nucleus with
complex tidal tails. The OH spectrum has multiple velocity components,
probably due to the interaction in the merger process.

####  3.2.15 IRAS 11301-0523

The OHM IRAS 11301-0523 was first discovered by the FASHI survey (see Figures
19). The optical spectroscopic redshift ($z_{\odot}=0.23019$; Saunders et al.,
2000) is in good agreement with the observed OH redshift
($z_{\odot}=0.22984$). The spatial coordinate offset between them is $\sim$1′.
In Figure 18 the optical RGB image shows an arc-like structure with several
close and connected nuclei, which may be an interacting merging system. The OH
spectrum has multiple velocity components, and the 1665 MHz line is not
visible.

####  3.2.16 IRAS 12018+1941

This OHM was first found and reported by the Arecibo OHM surveys (Darling &
Giovanelli, 2002). The line profile and flux density observed by FAST are in
good agreement with those of (Darling & Giovanelli, 2002). The 1665 MHz line
is clearly visible in the FAST observations, but not in (Darling & Giovanelli,
2002). The measured line ratio is $R_{1667:1665}=4.59\pm 1.25$ (see Table 2).
In Figure 20 the optical RGB image shows an apparent merging system with two
extended tidal tails.

####  3.2.17 IRAS 12232+5532

The OHM IRAS 12232+5532 was first found and identified by the FASHI survey
(see Figures 21). Its measured OH redshift is 0.23250, while the optically
observed redshift is 0.23143 (Saunders et al., 2000) (see Tables 1 and 3). The
velocity difference is only $\sim$150 ${\rm km~{}s}^{-1}$, and spatially the
two are in good agreement. A careful search for other optical objects shows
that there is no possible match to the radio observation. The optical RGB
image shows an apparent merging system with tidal tails to the west and east
of the nucleus. The OH spectrum shows several velocity components, probably
indicating an active merging process. The velocity position of the 1665 MHz
line shows a bright emission profile. The measured line ratio is
$R_{1667:1665}=1.54\pm 0.18$.

####  3.2.18 IRAS 12447+3721

The OHM IRAS 12447+3721 was first found and identified by the FASHI survey
(see Figures 22). Its measured OH redshift is 0.15847, which is in good
agreement with the optically observed redshift of 0.15870 (Saunders et al.,
2000) (see Tables 1 and 3). Moreover, the two are in good spatial agreement. A
careful search for other optical objects shows that there is no possible match
to the radio observation. The optical RGB image shows an apparent merging
system with tidal tails to the west and east of the nucleus, or a spiral
structure surrounding the nucleus. Duarte Puertas et al. (2017) classified it
as a H II galaxy with a high star formation rate.

####  3.2.19 IRAS 13070+6412

The OHM IRAS 13070+6412 was first found and identified by the FASHI survey
(see Figures 23). Its measured OH redshift is 0.20523, which is in good
agreement with the optically observed redshift of 0.20492 (Saunders et al.,
2000) (see Tables 1 and 3). Moreover, the two are in good spatial agreement. A
careful search for other optical objects shows that there is no possible match
to the radio observation. The optical RGB image shows a possible merging
system with tidal tails to north and south of the nucleus. The OH spectrum is
strong and has multiple velocity components, probably due to the merging
interaction. There is a weak emission at 1665 MHz position, but it does not
have enough SNR to be identified as a real signal.

####  3.2.20 IRAS 13469+5833

The OHM IRAS 13469+5833 was first found and identified by the FASHI survey
(see Figures 24). Its measured OH redshift is 0.15716, while the optically
observed redshift is 0.15778 (Saunders et al., 2000) (see Tables 1 and 3). The
difference between the two is $\sim$350 ${\rm km~{}s}^{-1}$, but the two are
in good spatial agreement. A careful search for other optical objects shows
that there is no possible match to the radio observation. The optical RGB
image shows a possible merging system with several tidal tails surrounding the
nuclei (see also the HST F814W-band images in Murata et al., 2017). The OH
spectrum has double velocity components, probably indicating merging activity.
The IRAS 13469+5833 is identified as an H II galaxy (Lin et al., 2018).

####  3.2.21 IRAS 14170+4545

The OHM IRAS 14170+4545 was first found and identified by the FASHI survey
(see Figures 25). Its measured OH redshift is 0.15009, which is in good
agreement with the optically observed redshift of 0.15026 (Saunders et al.,
2000) (see Tables 1 and 3). Moreover, the two are in good spatial agreement. A
careful search for other optical objects shows that there is no possible match
to the radio observation. The optical RGB image could not resolve the dense
nucleus, but the extended materials show a possible tidal tail surrounding the
nucleus. The OH spectrum has a very weak peak below $\sim$3.0 mJy, but the
integrated flux shows a compact structure at the position of the OC.

####  3.2.22 IRAS 14202+2615

This source has been observed by the Arecibo OHM surveys (Darling &
Giovanelli, 2000, 2006), but they do not have sufficient sensitivity to see
the OH emission line. In the FASHI survey we detected the OHM emission line
with a peak flux density of $4.38\pm 1.15$ mJy, and the SNR is only about 3.
The optical redshift from Saunders et al. (2000) is in good agreement with the
OH line measured by FAST, while the spatially projected coordinate offset is
$\sim$2.0′. The optical RGB image shows two close nuclei, one of which has a
visible tidal tail. This probably indicates a merging system.

####  3.2.23 IRAS 15043+5754

The OHM IRAS 15043+5754 was first found and identified by the FASHI survey
(see Figures 27). Its measured OH redshift is 0.15029, which is in good
agreement with the optically observed redshift of 0.15059 (Saunders et al.,
2000) (see Tables 1 and 3). Moreover, the two are in good spatial agreement. A
careful search for other optical objects shows that there is no possible match
to the radio observation. The optical RGB image show a possible merging system
with two nuclei interacting. The OH spectrum has a very weak peak below
$\sim$4.0 mJy, but the integrated flux shows a compact structure at the
position of the optical object.

####  3.2.24 IRAS 15160+5307

The OHM IRAS 15160+5307 was first found and identified by the FASHI survey
(see Figures 28). Its measured OH redshift is 0.15227, which is in good
agreement with the optically observed redshift of 0.15199 (Saunders et al.,
2000) (see Tables 1 and 3). Moreover, the two are in good spatial agreement. A
careful search for other optical objects shows that there is no possible match
to the radio observation. The optical RGB image shows a possible merging
system with two interacting nuclei and at least two tidal tails. The OH
spectrum has a weak peak of $\sim$2.5 mJy, but the blue wing is broad and the
red wing has an absorption feature.

####  3.2.25 IRAS 15261+5502

The new OHM IRAS 15261+5502 was first discovered by the FASHI survey (see
Figures 29). The optical coordinates and spectroscopic redshift
($z_{\odot}=0.22921$; Abazajian et al., 2009) are in good agreement with the
observed OH line coordinates and redshift ($z_{\odot}=0.22902$) for this
object. The OH luminosity is $L_{\rm OH}=10^{3.43\pm 0.01}L_{\odot}$ (see
Table 1). It has a FIR luminosity of $L_{\rm FIR}=10^{11.99\pm 0.03}L_{\odot}$
(see Table 3), which belongs to a LIRG. Hou et al. (2009) classified it as a
starburst galaxy. In Figure 29 the optical RGB image shows two interacting
nuclei with a visible tidal tail. The OH spectrum has a broad linewidth and
multiple velocity components, probably resulting from a merger process.

####  3.2.26 IRAS 16468+5200

The new OHM IRAS 16468+5200 was first discovered by the FASHI survey (see
Figures 30). The OH and the corresponding infrared parameters are listed in
Tables 1 and 3. The optical coordinates and the spectroscopic redshift
($z_{\odot}=0.15054$; Saunders et al., 2000) are in good agreement with the
observed OH line coordinates and redshift ($z_{\odot}=0.15032$) for this
object. The OH luminosity is $L_{\rm OH}=10^{2.60\pm 0.04}L_{\odot}$ (see
Table 1). It has a FIR luminosity of $L_{\rm FIR}=10^{11.84\pm 0.02}L_{\odot}$
(see Table 3), which belongs to a LIRG. Weedman & Houck (2008) classified it
as a LINER-type active galaxy nucleus. In Figure 29 the optical RGB image
shows a typical merging system with two interacting nuclei, one of which has
an elongated tidal tail. The OH spectrum has multiple velocity components.

####  3.2.27 IRAS 23129+2548

This source has been confirmed as an OHM by the Arecibo OHM surveys (Darling &
Giovanelli, 2001). In the FAST observation the 1665 MHz line is not blind to
the 1667 MHz line, but the 1665 MHz line shows no emission feature. The
optical RGB image shows an interacting merging system with visible tidal
tails. The nucleus of this OHM host is classified as a LINER by Veilleux et
al. (1999). The OH spectrum has a broad linewidth and multiple velocity
components, probably due to a merging process.

###  3.3 OHM catalog

Table 1: FASHI detected OHMs including coordinate, redshift, line width, peak
flux.

[1] | [2] | [3] | [4] | [5] | [6] | [7] | [8] | [9] | [10] | [11]
---|---|---|---|---|---|---|---|---|---|---
FASHI ID | FASHI name | IRAS name | RAoh | DECoh | $z_{\odot}$ | $V_{\rm heli}$ | $V_{\rm CMB}$ | $W_{50}$ | $F_{\rm peak}$ | rms
| J2000 | B1950 | deg | deg |  | ${\rm km~{}s}^{-1}$ | ${\rm km~{}s}^{-1}$ | ${\rm km~{}s}^{-1}$ | mJy | mJy
20240066172 | J002814.52-015310.0 | 00256-0208 | 7.061 | -1.886 | 0.27656 | 82912.1 | 82873.3 | 279.6 | 3.05 | 0.88
20240066090 | J015902.56+254224.7 | 01562+2527 | 29.761 | 25.707 | 0.16600 | 49766.2 | 49727.5 | 272.8 | 6.72 | 1.43
20240066093 | J025515.32+205835.5 | 02524+2046 | 43.814 | 20.977 | 0.18067 | 54164.0 | 54124.2 | 86.4 | 21.78 | 1.83
20240066181 | J031336.48-023255.8 | 03111-0244 | 48.402 | -2.549 | 0.18956 | 56827.9 | 56784.9 | 77.1 | 15.27 | 1.67
20240066097 | J065143.27+220518.1 | 06487+2208 | 102.930 | 22.088 | 0.14347 | 43012.5 | 42973.8 | 130.4 | 5.82 | 1.37
20240066055 | J082310.95+275137.6 | 08201+2801 | 125.796 | 27.860 | 0.16793 | 50343.5 | 50306.4 | 242.3 | 11.45 | 1.50
20240099047 | J083634.98+513745.8 | 08328+5148 | 129.146 | 51.629 | 0.23749 | 71196.3 | 71161.8 | 105.9 | 10.63 | 1.10
20240066185 | J085909.64-030430.6 | 08566-0252 | 134.790 | -3.075 | 0.20262 | 60743.1 | 60702.9 | 190.2 | 7.73 | 1.27
20240066025 | J101347.44+465356.6 | 10106+4708 | 153.448 | 46.899 | 0.20529 | 61543.0 | 61509.7 | 159.4 | 24.73 | 1.32
20240066062 | J105837.38+382836.6 | 10558+3845 | 164.656 | 38.477 | 0.20788 | 62319.4 | 62286.1 | 26.3 | 4.35 | 1.04
20240066027 | J110245.08+591005.0 | 10597+5926 | 165.688 | 59.168 | 0.19607 | 58780.0 | 58748.4 | 236.2 | 32.27 | 2.23
20240066060 | J110537.56+311427.4 | 11029+3130 | 166.407 | 31.241 | 0.19885 | 59613.8 | 59579.5 | 130.2 | 3.36 | 0.97
20240066028 | J111136.57+533514.0 | 11087+5351 | 167.902 | 53.587 | 0.14314 | 42913.0 | 42881.3 | 101.9 | 3.65 | 0.87
20240129741 | J111908.12+600432.5 | 11161+6020 | 169.784 | 60.076 | 0.26434 | 79246.5 | 79215.1 | 288.2 | 9.07 | 2.05
20240066187 | J113239.21-053833.9 | 11301-0523 | 173.163 | -5.643 | 0.22984 | 68903.1 | 68862.2 | 168.0 | 6.98 | 1.46
20240066105 | J120420.53+192456.7 | 12018+1941 | 181.086 | 19.416 | 0.16783 | 50315.5 | 50278.4 | 254.6 | 1.90 | 0.83
20240066030 | J122539.49+551528.9 | 12232+5532 | 186.415 | 55.258 | 0.23250 | 69702.5 | 69672.8 | 166.1 | 2.40 | 0.66
20240066069 | J124709.66+370508.6 | 12447+3721 | 191.790 | 37.086 | 0.15847 | 47506.6 | 47478.6 | 198.0 | 1.40 | 0.68
20240066013 | J130854.87+635636.6 | 13070+6412 | 197.229 | 63.944 | 0.20523 | 61525.8 | 61496.1 | 154.6 | 12.48 | 1.97
20240066035 | J134841.23+581817.8 | 13469+5833 | 207.172 | 58.305 | 0.15716 | 47114.4 | 47085.9 | 20.6 | 9.43 | 1.26
20240066034 | J141859.45+453206.3 | 14170+4545 | 214.748 | 45.535 | 0.15009 | 44997.1 | 44970.9 | 68.7 | 2.43 | 0.85
20240066110 | J142227.98+260225.7 | 14202+2615 | 215.617 | 26.040 | 0.15925 | 47740.6 | 47718.6 | 16.0 | 4.38 | 1.15
20240066037 | J150535.42+574248.3 | 15043+5754 | 226.398 | 57.713 | 0.15029 | 45054.5 | 45026.5 | 115.9 | 2.17 | 1.16
20240066039 | J151732.61+525616.8 | 15160+5307 | 229.386 | 52.938 | 0.15227 | 45648.2 | 45620.9 | 195.3 | 1.34 | 0.51
20240102609 | J152725.70+545139.2 | 15261+5502 | 231.857 | 54.861 | 0.22902 | 68657.8 | 68630.3 | 218.0 | 8.42 | 1.04
20240066042 | J164800.26+515535.2 | 16468+5200 | 252.001 | 51.926 | 0.15032 | 45065.1 | 45037.3 | 151.3 | 3.98 | 1.28
20240066122 | J231519.36+260419.1 | 23129+2548 | 348.831 | 26.072 | 0.17881 | 53605.7 | 53570.5 | 278.4 | 3.42 | 0.96

Notes. The IRAS names in bold are previously known OHMs, while the others are
first discovered by FAST.

Table 1 presents the main results of 27 OHMs detected by FASHI, including
coordinate, redshift, line width, and flux. Each column in Table 1 is
introduced as follows:

  * •

Column 1: Index number for each FASHI extragalactic source. This index number
is unique to each FASHI source.

  * •

Column 2: Centroid coordinate (J2000) for the OH source in the format of
Jhhmmss.ss$\pm$ddmmss.s.

  * •

Column 3: IRAS source name (Helou & Walker, 1988).

  * •

Column 4-5: Right ascension (RA) and declination (DEC) in units of deg from
the FASHI source centroid (J2000).

  * •

Column 6: Redshift, $z_{\odot}$ of the 1667 MHz OH line, corresponding to the
heliocentric velocity in Column 6.

  * •

Column 7: Heliocentric velocity of the H I source, c$z_{\odot}$ in units of
${\rm km~{}s}^{-1}$. Values have been converted from the “radio” definition
($\delta\nu/\nu$) to the optical definition $\delta\lambda/\lambda$. All
results are presented in this work using the optical helio-centric definition
of velocity.

  * •

Column 8: Cosmic microwave background (CMB) rest-frame velocity. This is
calculated from the heliocentric velocity using the solar motion with respect
to the CMB as measured by Fixsen et al. (1996) with $v_{\sun}=371\pm 1\,{\rm
km~{}s}^{-1}$ to $(l,b)=(264\hbox to0.0pt{.\hss}{{}^{\circ}}14\pm 0\hbox
to0.0pt{.\hss}{{}^{\circ}}15,48\hbox to0.0pt{.\hss}{{}^{\circ}}26\pm 0\hbox
to0.0pt{.\hss}{{}^{\circ}}15)$.

  * •

Column 9: Velocity width of the OH line profile, $W_{50}$ in ${\rm
km~{}s}^{-1}$, measured at the 50% level of each peak.

  * •

Column 10: OH line peak intensity, $F_{\rm peak}$ in mJy.

  * •

Column 11: OH line noise level for the spatially integrated spectral profile,
$\sigma_{\rm{rms}}$ in mJy. It was obtained by measuring over the signal and
RFI free portions of the integrated H I spectrum at a spectral resolution of
6.4 ${\rm km~{}s}^{-1}$.

###  3.4 Hyperfine ratio catalog

Table 2: Hyperfine ratio between the 1667 and 1665 MHz lines.

[1] | [2] | [3] | [4] | [5] | [6] | [7] | [8] | [9]
---|---|---|---|---|---|---|---|---
FASHI ID | IRAS name | $S_{\rm int}^{1667}$ | $V_{\rm min}^{1667}$ | $V_{\rm max}^{1667}$ | $S_{\rm int}^{1665}$ | $V_{\rm min}^{1665}$ | $V_{\rm max}^{1665}$ | $R_{1667:1665}$
|  | mJy$\cdot$${\rm km~{}s}^{-1}$ | ${\rm km~{}s}^{-1}$ | ${\rm km~{}s}^{-1}$ | mJy$\cdot$${\rm km~{}s}^{-1}$ | ${\rm km~{}s}^{-1}$ | ${\rm km~{}s}^{-1}$ | ratio
20240066172 | 00256-0208 | 1089.2 $\pm$ 65.1 | 82246.2 | 83457.0 |  |  |  |
20240066090 | 01562+2527 | 2026.8 $\pm$ 93.5 | 49363.3 | 50148.7 |  |  |  |
20240066093 | 02524+2046 | 1781.4 $\pm$ 59.1 | 54028.3 | 54243.2 | 607.3 $\pm$ 42.6 | 54481.4 | 54812.4 | 2.93 $\pm$ 0.23
20240066181 | 03111-0244 | 1167.6 $\pm$ 54.0 | 56703.8 | 56921.8 | 424.2 $\pm$ 57.8 | 57147.9 | 57600.9 | 2.75 $\pm$ 0.40
20240066097 | 06487+2208 | 848.0 $\pm$ 58.9 | 42839.9 | 43178.3 | 259.7 $\pm$ 46.8 | 43272.0 | 43524.6 | 3.27 $\pm$ 0.63
20240066055 | 08201+2801 | 2110.0 $\pm$ 77.8 | 50065.3 | 50568.3 |  |  |  |
20240099047 | 08328+5148 | 1325.4 $\pm$ 50.6 | 70921.6 | 71376.2 | 140.4 $\pm$ 27.1 | 71578.6 | 71755.9 | 9.44 $\pm$ 1.85
20240066185 | 08566-0252 | 1427.1 $\pm$ 51.1 | 60584.7 | 60919.2 |  |  |  |
20240066025 | 10106+4708 | 4011.7 $\pm$ 68.5 | 61332.6 | 61876.2 |  |  |  |
20240066062 | 10558+3845 | 212.3 $\pm$ 46.7 | 62083.1 | 62492.4 | 130.7 $\pm$ 30.6 | 62604.4 | 62845.9 | 1.62 $\pm$ 0.52
20240066027 | 10597+5926 | 7259.4 $\pm$ 112.5 | 58535.6 | 59039.4 | 477.0 $\pm$ 45.2 | 59110.0 | 59489.0 | 15.22 $\pm$ 1.46
20240066060 | 11029+3130 | 424.8 $\pm$ 40.6 | 59463.6 | 59819.7 |  |  |  |
20240066028 | 11087+5351 | 289.4 $\pm$ 27.2 | 42818.6 | 43005.8 | 219.1 $\pm$ 28.2 | 43200.4 | 43438.6 | 1.32 $\pm$ 0.21
20240129741 | 11161+6020 | 2468.3 $\pm$ 114.1 | 78901.6 | 79578.7 |  |  |  |
20240066187 | 11301-0523 | 1014.8 $\pm$ 66.7 | 68669.5 | 69110.5 |  |  |  |
20240066105 | 12018+1941 | 370.6 $\pm$ 37.4 | 50139.7 | 50530.3 | 80.8 $\pm$ 20.5 | 50688.3 | 50823.8 | 4.59 $\pm$ 1.25
20240066030 | 12232+5532 | 399.8 $\pm$ 26.0 | 69534.9 | 69869.2 | 259.2 $\pm$ 25.2 | 69969.6 | 70287.9 | 1.54 $\pm$ 0.18
20240066069 | 12447+3721 | 287.8 $\pm$ 33.0 | 47306.6 | 47749.7 |  |  |  |
20240066013 | 13070+6412 | 2016.0 $\pm$ 91.6 | 61324.5 | 61764.1 |  |  |  |
20240066035 | 13469+5833 | 556.0 $\pm$ 51.5 | 46975.8 | 47292.6 |  |  |  |
20240066034 | 14170+4545 | 197.8 $\pm$ 36.1 | 44860.1 | 45194.9 |  |  |  |
20240066110 | 14202+2615 | 319.4 $\pm$ 49.4 | 47601.5 | 47949.1 |  |  |  |
20240066037 | 15043+5754 | 211.0 $\pm$ 44.5 | 44925.3 | 45202.0 |  |  |  |
20240066039 | 15160+5307 | 305.5 $\pm$ 28.4 | 45368.5 | 45923.7 |  |  |  |
20240102609 | 15261+5502 | 1857.3 $\pm$ 57.5 | 68312.8 | 68944.2 |  |  |  |
20240066042 | 16468+5200 | 640.3 $\pm$ 57.8 | 44889.0 | 45267.6 |  |  |  |
20240066122 | 23129+2548 | 845.4 $\pm$ 57.8 | 53272.0 | 53960.7 |  |  |  |

Notes. The IRAS names in bold are previously known OHMs, while the others are
first discovered by FAST.

Table 2 presents the integrated flux and the hyperfine ratio between the 1667
and 1665 MHz lines. Each column in Table 2 is introduced as follows:

  * •

Column 1: Index number for each FASHI extragalactic source. This index number
is unique to each FASHI source.

  * •

Column 2: IRAS source name (Helou & Walker, 1988).

  * •

Column 3: Integrated flux of the 1667 MHz line, $S_{\rm int}$, in ${\rm
mJy~{}beam}^{-1}{\rm km~{}s}^{-1}$, by summing all velocity channels
containing signal within an appropriate velocity range from each integrated
spectrum. The velocity range is listed in Columns 3 and 4.

  * •

Columns 4-5: The minimum ($V_{\rm min}^{1667}$) and maximum ($V_{\rm
max}^{1667}$) of the integrated flux range for the 1667 MHz line.

  * •

Column 6: Integrated flux of the 1665 MHz line, $S_{\rm int}$, in ${\rm
mJy~{}beam}^{-1}{\rm km~{}s}^{-1}$, by summing all velocity channels
containing signal within an appropriate velocity range from each integrated
spectrum. The velocity range is listed in Columns 6 and 7.

  * •

Columns 7-8: The minimum ($V_{\rm min}^{1665}$) and maximum ($V_{\rm
max}^{1665}$) of the integrated flux range for the 1665 MHz line.

  * •

Column 9: Hyperfine line ratio between the 1667 and 1665 MHz lines.

###  3.5 OHM optical counterpart catalog

Table 3: OHM optical counterparts including IRAS flux and FIR properties.

[1] | [2] | [3] | [4] | [5] | [6] | [7] | [8] | [9] | [10]
---|---|---|---|---|---|---|---|---|---
FASHI ID | IRAS name | RAoc | DECoc | $z_{\odot}$ | $f_{60}$ | $f_{100}$ | $D_{\rm L}$ | log$L_{\rm FIR}$ | log$L_{\rm OH}$
| B1950 | deg | deg | PSCz | Jy | Jy |  $h_{75}^{-1}$Gpc | $h_{75}^{-2}L_{\odot}$ | $h_{75}^{-2}L_{\odot}$
20240066172 | 00256-0208 | 7.059 | -1.863 | 0.27630 | 0.65 $\pm$ 0.07 | 1.00 $\pm$ 0.00 | 1.258 | 12.22 $\pm$ 0.03 | 3.36 $\pm$ 0.03
20240066090 | 01562+2527 | 29.761 | 25.710 | 0.16580 | 0.80 $\pm$ 0.06 | 1.85 $\pm$ 0.15 | 0.718 | 11.90 $\pm$ 0.02 | 3.18 $\pm$ 0.02
20240066093 | 02524+2046 | 43.821 | 20.983 | 0.18153 | 0.94 $\pm$ 0.08 | 8.48 $\pm$ 0.00 | 0.787 | 12.43 $\pm$ 0.01 | 3.20 $\pm$ 0.01
20240066181 | 03111-0244 | 48.422 | -2.560 | 0.18833 | 0.69 $\pm$ 0.06 | 1.03 $\pm$ 0.00 | 0.829 | 11.88 $\pm$ 0.02 | 3.06 $\pm$ 0.02
20240066097 | 06487+2208 | 102.941 | 22.074 | 0.14370 | 2.07 $\pm$ 0.17 | 2.36 $\pm$ 0.26 | 0.614 | 12.06 $\pm$ 0.03 | 2.68 $\pm$ 0.03
20240066055 | 08201+2801 | 125.803 | 27.861 | 0.16750 | 1.13 $\pm$ 0.09 | 1.60 $\pm$ 0.18 | 0.727 | 11.98 $\pm$ 0.03 | 3.21 $\pm$ 0.02
20240099047 | 08328+5148 | 129.150 | 51.627 | 0.23700 | 0.37 $\pm$ 0.11 | 1.58 $\pm$ 0.00 | 1.061 | 12.05 $\pm$ 0.05 | 3.31 $\pm$ 0.02
20240066185 | 08566-0252 | 134.789 | -3.070 | 0.20201 | 0.79 $\pm$ 0.07 | 1.10 $\pm$ 0.00 | 0.891 | 11.99 $\pm$ 0.03 | 3.21 $\pm$ 0.02
20240066025 | 10106+4708 | 153.450 | 46.900 | 0.20481 | 0.77 $\pm$ 0.08 | 1.37 $\pm$ 0.30 | 0.904 | 12.04 $\pm$ 0.05 | 3.67 $\pm$ 0.01
20240066062 | 10558+3845 | 164.664 | 38.485 | 0.20660 | 0.70 $\pm$ 0.06 | 1.00 $\pm$ 0.00 | 0.917 | 11.97 $\pm$ 0.02 | 2.40 $\pm$ 0.10
20240066027 | 10597+5926 | 165.696 | 59.177 | 0.19583 | 1.02 $\pm$ 0.08 | 1.33 $\pm$ 0.17 | 0.860 | 12.06 $\pm$ 0.03 | 3.88 $\pm$ 0.01
20240066060 | 11029+3130 | 166.406 | 31.242 | 0.19890 | 1.04 $\pm$ 0.09 | 1.38 $\pm$ 0.11 | 0.873 | 12.09 $\pm$ 0.03 | 2.66 $\pm$ 0.04
20240066028 | 11087+5351 | 167.902 | 53.583 | 0.14270 | 1.00 $\pm$ 0.11 | 1.00 $\pm$ 0.13 | 0.613 | 11.73 $\pm$ 0.04 | 2.21 $\pm$ 0.04
20240129741 | 11161+6020 | 169.779 | 60.075 | 0.26428 | 0.61 $\pm$ 0.05 | 1.28 $\pm$ 0.19 | 1.196 | 12.21 $\pm$ 0.04 | 3.68 $\pm$ 0.02
20240066187 | 11301-0523 | 173.175 | -5.663 | 0.23019 | 0.70 $\pm$ 0.07 | 1.42 $\pm$ 0.16 | 1.024 | 12.13 $\pm$ 0.03 | 3.17 $\pm$ 0.03
20240066105 | 12018+1941 | 181.102 | 19.419 | 0.16865 | 1.64 $\pm$ 0.18 | 1.86 $\pm$ 0.22 | 0.727 | 12.10 $\pm$ 0.04 | 2.46 $\pm$ 0.04
20240066030 | 12232+5532 | 186.410 | 55.264 | 0.23143 | 0.62 $\pm$ 0.06 | 1.63 $\pm$ 0.00 | 1.037 | 12.14 $\pm$ 0.02 | 2.77 $\pm$ 0.03
20240066069 | 12447+3721 | 191.782 | 37.094 | 0.15870 | 1.11 $\pm$ 0.12 | 1.00 $\pm$ 0.00 | 0.683 | 11.85 $\pm$ 0.04 | 2.30 $\pm$ 0.05
20240066013 | 13070+6412 | 197.231 | 63.941 | 0.20492 | 0.74 $\pm$ 0.05 | 0.71 $\pm$ 0.11 | 0.904 | 11.93 $\pm$ 0.03 | 3.37 $\pm$ 0.02
20240066035 | 13469+5833 | 207.167 | 58.315 | 0.15778 | 1.34 $\pm$ 0.11 | 1.99 $\pm$ 0.14 | 0.677 | 12.00 $\pm$ 0.02 | 2.58 $\pm$ 0.04
20240066034 | 14170+4545 | 214.745 | 45.537 | 0.15026 | 0.73 $\pm$ 0.06 | 1.19 $\pm$ 0.12 | 0.645 | 11.70 $\pm$ 0.03 | 2.09 $\pm$ 0.08
20240066110 | 14202+2615 | 215.631 | 26.035 | 0.15915 | 1.45 $\pm$ 0.16 | 1.95 $\pm$ 0.23 | 0.687 | 12.03 $\pm$ 0.04 | 2.35 $\pm$ 0.07
20240066037 | 15043+5754 | 226.415 | 57.719 | 0.15059 | 0.99 $\pm$ 0.07 | 1.42 $\pm$ 0.10 | 0.645 | 11.82 $\pm$ 0.02 | 2.12 $\pm$ 0.09
20240066039 | 15160+5307 | 229.374 | 52.947 | 0.15199 | 0.64 $\pm$ 0.03 | 1.38 $\pm$ 0.08 | 0.655 | 11.71 $\pm$ 0.02 | 2.29 $\pm$ 0.04
20240102609 | 15261+5502 | 231.861 | 54.864 | 0.22921 | 0.53 $\pm$ 0.05 | 1.00 $\pm$ 0.00 | 1.020 | 11.99 $\pm$ 0.03 | 3.43 $\pm$ 0.01
20240066042 | 16468+5200 | 252.006 | 51.929 | 0.15054 | 1.01 $\pm$ 0.07 | 1.61 $\pm$ 0.00 | 0.646 | 11.84 $\pm$ 0.02 | 2.60 $\pm$ 0.04
20240066122 | 23129+2548 | 348.839 | 26.076 | 0.17810 | 1.80 $\pm$ 0.20 | 1.70 $\pm$ 0.17 | 0.778 | 12.18 $\pm$ 0.04 | 2.87 $\pm$ 0.03

Notes. The IRAS names in bold are previously known OHMs, while the others are
first discovered by FAST.

Table 3 presents the main results of the OCs corresponding to the OHMs,
including WISE magnitude, IRAS flux, and FIR properties. Each column in Table
3 is introduced as follows:

  * •

Column 1: Index number for each FASHI extragalactic source. This index number
is unique to each FASHI source.

  * •

Column 2: IRAS source catalog name.

  * •

Column 3-4: RA and DEC with centroid coordinate (J2000) in units deg for OHM
OCs extracted from the SDSS catalog.

  * •

Column 5: Heliocentric optical redshift, $z_{\odot}$, extracted from the SDSS
catalog.

  * •

Column 6-9: WISE 3.4, 4.6, 12, and 22 $\mu$m Vega magnitudes extracted from
the unwise catalog.

  * •

column 10-11: IRAS 60 and 100 $\mu$m flux densities $f_{60}$ and $f_{100}$ in
units of Jy (Helou & Walker, 1988).

  * •

Column 12: Luminosity distance $D_{\rm L}$ in $h_{75}^{-1}{\rm Gpc}$,
estimated using the following equation from Darling & Giovanelli (2000) with

$D_{L}=(V_{\rm CMB}/H_{0})(1+0.5z_{\rm CMB}),$ (1)

where $V_{\rm CMB}$, listed in Table 1, is the radial velocity of the source
in the cosmic microwave background (CMB) rest frame.

  * •

Column 12: Logarithm of the FIR luminosity $L_{\rm FIR}$ in units of
$h_{75}^{-2}L_{\sun}$, estimated using the following equation from Sanders &
Mirabel (1996) with

$L_{\rm FIR}=3.96\times 10^{5}D_{\rm L}^{2}(2.58f_{60}+f_{100}),$ (2)

where $f_{60}$ and $f_{100}$ are listed in Columns 9-10.

  * •

Column 13: OH line luminosity $L_{\rm OH}$ in units of $h_{75}^{-2}L_{\sun}$.
From the integrated line flux $S_{\rm int}$ we use the general relation for
the spectral line luminosity (e.g., Briggs, 1998) with

${\frac{L_{\rm OH}}{L_{\odot}}}=\Big{(}{\frac{1.7064}{1+z_{\rm
OH}}}\Big{)}\,\Big{(}{\frac{S_{\rm int}}{\rm
mJy\,km\,s^{-1}}}\Big{)}\,\Big{(}{\frac{D_{L}}{\rm Gpc}}\Big{)}^{2},$ (3)

where we take the stronger of the two main OH lines with a rest frequency of
1667.35903 MHz to define $z_{\rm OH}$.

###  3.6 OHM catalog corss-matching with GSWLC

Table 4: Cross-matched sources between all the known 154 OMHs and GSWLC.

[1] | [2] | [3] | [4] | [5] | [6] | [7] | [8]
---|---|---|---|---|---|---|---
IRAS name | OBJID | RA | DEC | $z_{\odot}$ | log($M_{\star})$ | log($\rm SFR_{SED})$ | $A_{\rm V}$
B1950 |  | deg | deg |  | $\rm M_{\odot}$ | $\rm M_{\odot}\,yr^{-1}$ | mag
0758+2851 | 1237657629506142647 | 119.727 | 28.886 | 0.1262 | 10.70 $\pm$ 0.03 | -0.54 $\pm$0.71 | 0.24 $\pm$ 0.10
08122+0505 | 1237660668730408974 | 123.723 | 4.937 | 0.1033 | 11.04 $\pm$ 0.04 | 0.57 $\pm$0.24 | 0.43 $\pm$ 0.16
08449+2332 | 1237664834854518934 | 131.959 | 23.353 | 0.1517 | 10.71 $\pm$ 0.06 | 1.47 $\pm$0.05 | 0.47 $\pm$ 0.06
09039+0503 | 1237658423543595297 | 136.642 | 4.858 | 0.1250 | 10.81 $\pm$ 0.03 | 1.56 $\pm$0.06 | 0.86 $\pm$ 0.06
09116+0334 | 1237654605316358298 | 138.574 | 3.365 | 0.1460 | 10.91 $\pm$ 0.03 | 0.43 $\pm$0.16 | 0.23 $\pm$ 0.10
09320+6134 | 1237651272966275163 | 143.965 | 61.353 | 0.0394 | 11.25 $\pm$ 0.03 | 1.16 $\pm$0.01 | 0.75 $\pm$ 0.00
09531+1430 | 1237671261205495893 | 148.958 | 14.269 | 0.2152 | 11.34 $\pm$ 0.04 | 1.00 $\pm$0.18 | 0.62 $\pm$ 0.12
09540+3521 | 1237664669506863314 | 149.246 | 35.119 | 0.1006 | 10.72 $\pm$ 0.03 | 0.36 $\pm$0.23 | 0.59 $\pm$ 0.11
10378+1108 | 1237661949170155593 | 160.122 | 10.888 | 0.1363 | 11.03 $\pm$ 0.03 | 1.57 $\pm$0.02 | 0.82 $\pm$ 0.03
10558+3845 | 1237664668975562850 | 164.664 | 38.485 | 0.2081 | 11.01 $\pm$ 0.09 | 1.56 $\pm$0.14 | 0.69 $\pm$ 0.14
11011+4107 | 1237662194520293391 | 165.976 | 40.850 | 0.0348 | 9.97 $\pm$ 0.14 | 0.58 $\pm$0.18 | 0.49 $\pm$ 0.11
11087+5351 | 1237657590319022140 | 167.902 | 53.583 | 0.1429 | 10.91 $\pm$ 0.07 | 1.44 $\pm$0.20 | 0.73 $\pm$ 0.18
11257+5850 | 1237655107301277787 | 172.140 | 58.563 | 0.0105 | 10.40 $\pm$ 0.04 | 0.85 $\pm$0.08 | 0.86 $\pm$ 0.09
12018+1941 | 1237667914881892435 | 181.102 | 19.419 | 0.1679 | 10.89 $\pm$ 0.09 | 1.44 $\pm$0.12 | 0.60 $\pm$ 0.15
12447+3721 | 1237664672714653739 | 191.782 | 37.094 | 0.1582 | 10.39 $\pm$ 0.09 | 0.96 $\pm$0.18 | 0.24 $\pm$ 0.15
13254+4754 | 1237661149769760972 | 201.900 | 47.647 | 0.0607 | 9.77 $\pm$ 0.07 | 0.33 $\pm$0.08 | 0.17 $\pm$ 0.08
13428+5608 | 1237661387602853939 | 206.176 | 55.887 | 0.0373 | 10.77 $\pm$ 0.05 | 0.35 $\pm$0.33 | 0.39 $\pm$ 0.14
13469+5833 | 1237659326015537309 | 207.167 | 58.314 | 0.1575 | 11.00 $\pm$ 0.05 | 0.90 $\pm$0.14 | 0.40 $\pm$ 0.14
14202+2615 | 1237665441523957822 | 215.631 | 26.035 | 0.1587 | 11.05 $\pm$ 0.05 | 1.38 $\pm$0.02 | 0.20 $\pm$ 0.02
14312+2825 | 1237665351854784676 | 218.365 | 28.200 | 0.1748 | 11.30 $\pm$ 0.09 | 1.59 $\pm$0.05 | 0.73 $\pm$ 0.08
14488+3521 | 1237662305655717891 | 222.726 | 35.144 | 0.2057 | 11.41 $\pm$ 0.04 | 2.23 $\pm$0.02 | 0.73 $\pm$ 0.01
15043+5754 | 1237671769072206053 | 226.415 | 57.719 | 0.1506 | 10.67 $\pm$ 0.06 | 1.29 $\pm$0.10 | 0.44 $\pm$ 0.14
15160+5307 | 1237655463779631232 | 229.374 | 52.946 | 0.1522 | 11.21 $\pm$ 0.06 | 1.47 $\pm$0.08 | 0.37 $\pm$ 0.11
15224+1033 | 1237662636908478686 | 231.213 | 10.380 | 0.1346 | 10.78 $\pm$ 0.05 | 1.13 $\pm$0.05 | 0.34 $\pm$ 0.03
15250+3608 | 1237662335714852881 | 231.748 | 35.977 | 0.0552 | 10.63 $\pm$ 0.04 | 0.97 $\pm$0.06 | 0.38 $\pm$ 0.06
15327+2340 | 1237665537075511390 | 233.738 | 23.504 | 0.0184 | 10.87 $\pm$ 0.02 | 0.37 $\pm$0.08 | 0.69 $\pm$ 0.07
16145+4231 | 1237665356696846411 | 244.050 | 42.400 | 0.0232 | 9.76 $\pm$ 0.04 | -0.33 $\pm$0.10 | 0.19 $\pm$ 0.09
16300+1558 | 1237665536008520057 | 248.089 | 15.863 | 0.2418 | 11.20 $\pm$ 0.09 | 1.71 $\pm$0.13 | 0.49 $\pm$ 0.15

Notes. The listed Columns [2]-[8] in this catalog are extracted from GSWLC
(Salim et al., 2007).

Table 4 shows the cross-matched 28 sources between all known 154 OMHs and the
entire GSWLC catalog (Salim et al., 2007) under the condition
$\rm\delta_{RA}\leq 3^{\prime}$, $\rm\delta_{DEC}\leq 3^{\prime}$ and
$\rm\delta_{HI\,velocity}\leq 300\,{\rm km~{}s}^{-1}$. Nine OHMs are detected
by FAST. Each column in Table 3 is introduced as follows:

  * •

Column 1: IRAS source catalog name.

  * •

Column 2: OBJID, SDSS photometric identification number, from GSWLC.

  * •

Column 3-4: RA and DEC with centroid coordinate (J2000) in units deg, from
GSWLC.

  * •

Column 5: Redshift, $z_{\odot}$, from GSWLC.

  * •

Column 6: Stellar mass, log($M_{\star})$ with its error, from GSWLC.

  * •

Column 7: UV/optical (SED) star formation rate, log($\rm SFR_{SED})$ with its
error, from GSWLC.

  * •

Column 8: Dust attenuation, $A_{\rm V}$, in rest-frame $V$, from GSWLC.

##  4 Discussion

###  4.1 Hyperfine ratio

The 1667 and 1665 MHz lines refer to the main lines of OH at the radio rest
frequencies of 1667.359 and 1665.402 MHz, while two satellite lines are
located at 1720.530 and 1612.231 MHz (Radford, 1964). In local thermodynamic
equilibrium (LTE), the OH line ratios are approximately 1:5:9:1 for 1612,
1665, 1667, and 1720 MHz lines (Henkel et al., 1991; Hess et al., 2021). The
1667 MHz line is relatively common in extragalactic observations, but the 1665
MHz line is very rare because of its weakness. McBride et al. (2013) reported
that the hyperfine line ratio is $1<R_{1667:1665}<10$ with an average of
$R_{1667:1665}\approx 5$. In previous observations (e.g., Darling &
Giovanelli, 2000, 2001, 2002), the 1667 and 1665 MHz lines often blend into
each other, resulting in a barely measurable line ratio. The main reason for
this is the inherently large line width ($>500\,{\rm km~{}s}^{-1}$) of the
1667 MHz line. In Table 2 we present the hyperfine line ratio between the
integrated fluxes of 1667 and 1665 MHz. Totally we have detected 27 OHMs, 9 of
which show a visible 1665 MHz line. The detection rate is 33.3% for the 1665
MHz line. The line ratio $R_{1667:1665}$ ranges from 1.32 to 15.22, with an
average of $R_{1667:1665}=4.74$, in agreement with the results reported by
McBride et al. (2013). Although the hyperfine ratio is often consistent with
the thermal emission condition (Baan et al., 1982), e.g. for IRAS 10558+3845
with $R_{1667:1665}=1.62\pm 0.52$, 11087+5351 with $R_{1667:1665}=1.32\pm
0.21$, and 12232+5532 with $R_{1667:1665}=1.54\pm 0.18$, which have relatively
low hyperfine ratios with $R_{1667:1665}<2$, McBride et al. (2013) suggested
that the OH emission probably includes a significant non-thermal contribution.
Furthermore, the variable ratios with a wide range from 1.32 to 15.22 are
indicative of complex maser pumping mechanisms.

###  4.2 Host galaxy properties

Figure 3: The distributions between log($M_{\star})$, log($\rm SFR_{SED})$,
and $A_{\rm V}$. The background shows all the data in the GSWLC catalog. The
red dots indicate the cross-matched 28 sources between all known 154 OMHs and
the entire GSWLC catalog. The blue triangles indicate the cross-matched OHMs
detected by FAST.

OHMs are predominantly found in the core of a class of galaxies called
Luminous Infrared Galaxies (LIRGs) with $L_{\rm FIR}>10^{11}L_{\odot}$, and
ultra-luminous infrared galaxies (ULIRGs) with FIR luminosities $L_{\rm
FIR}>10^{12}L_{\odot}$ (e.g., Darling & Giovanelli, 2002). In this work, 13
OHMs are ULIRGs and 14 OHMs are LIRGs based on the measured $L_{\rm FIR}$,
which ranges from $10^{11.70\pm 0.03}$ to $10^{12.43\pm 0.01}L_{\odot}$ with a
median of $10^{12.00\pm 0.02}L_{\odot}$. This means that all 27 OHMs have
relatively high FIR luminosities. The strong FIR emission suggest that the
host system has undergone a very recent and strong starburst (e.g., Sanders &
Mirabel, 1996).

The majority of [U]LIRGs or OHMs show evidence of interaction with other
galaxies or have recently undergone a galaxy merger (Andreasian & Alloin,
1994; Darling & Giovanelli, 2002). Moreover, the hosts of [U]LIRGs are rich in
molecular gas compared to spiral galaxies (Burdiuzha & Vikulov, 1990). Mergers
could be a way to funnel molecular gas into the core of the [U]LIRG, producing
high molecular densities and stimulating the high star formation rates that
are characteristic of [U]LIRGs. Pihlström (2007) suggested that the maser
emission may originate in thick, circumnuclear structures, based on a general
consensus with high-resolution imaging.

OHMs are likely a disturbed system in a galaxy merger, as evidenced by tidal
tails (Clements et al., 1996). We found that almost all of the 27 OHMs have
recently merged or interacted with another galaxy (see Figure 2 and the other
figures in Appendix) and may be undergoing a burst of star formation. The
detected OHMs have almost multiple velocity features, suggesting a velocity
substructure throughout the detected regions. This could be an indication that
this galaxy is in the process of merging as seen in the optical morphology
(see Figure 2 and the other figures in Appendix). In general, OHM line
emission is always detected in [U]LIRGs. It is likely that OHMs occur during a
particular state or stage of the merger, which are consequences of tidal
density enhancements that accompany galaxy interactions (Darling, 2007;
Pihlström, 2007). In fact, very-long-baseline interferometry (VLBI) radio
images of Arp220 show that the OHM emission arises in regions only a few
parsecs in size in its core, and have been used to support active galactic
nucleus (AGN) models for this galaxy (Skinner et al., 1997).

The multi-wavelength SED fitting results in Figure 3 also show that the OH
host galaxies are massive ($M_{*}\simeq 10^{11}M_{\odot}$) galaxies with the
SFR above the star-forming main sequence. The higher $A_{V}$ value of the OH
galaxies from the SED fit is also consistent with the high IR luminosities. On
the other hand, not all ULIRGs have detectable OH emission, suggesting that
the OH emission may be triggered within a specific stage of the merger. High-
resolution OH mapping observations, e.g. with the Very Large Array (VLA), are
still needed to better constrain the physical origin of the OH emission.

###  4.3 $L_{\rm OH}$ and $L_{\rm FIR}$ Relationship

Figure 4: $L_{\rm OH}$ vs. $L_{\rm FIR}$ distribution including 154 sources.
The blue triangles indicate five OHMs discovered by FASHI. The grey dots
indicate the detection results of previously known OHMs (Darling & Giovanelli,
2002, 2006; Willett, 2012; Suess et al., 2016; Hess et al., 2021; Glowacki et
al., 2022; Jarvis et al., 2023), where the sources with $L_{\rm OH}$ having
only an upper limit are excluded from the current fitting statistics. The red
dashed line shows the fitting result of the $L_{\rm OH}$-$L_{\rm FIR}$
relation.

An OHM is proposed as radiatively pumped by the FIR radiation ﬁeld at 35 and
53 $\mu$m, and then masing could be stimulated by 18 cm continuum emission
from the surrounding condition (Henkel et al., 1987). In a simple scenario of
low-gain unsaturated masing, the maser power is proportional to the pumping
rate and the stimulated emission rate (Baan, 1989). If the observed OHM
represents an ensemble of many individual masing regions with different
saturation states, then the relationship between OH and FIR luminosity is
$L_{\rm OH}\propto L_{\rm FIR}^{1<\gamma<2}$ (Baan, 1989; Darling &
Giovanelli, 2002; Yun et al., 2001). The measurement of $\gamma$ has always
been frustrated by small samples, survey bias, and theoretical bias. Darling &
Giovanelli (2002) derived the relationship between OH and far IR luminosity
with 95 data points as ${\rm log}L_{\rm OH}=(1.57\pm 0.11){\rm log}L_{\rm
FIR}-(15.76\pm 1.22)$. In this work we detect 27 OHMs and 18 new OHMs, plus
127 other previously known OHMs with OH and FIR luminosities from the
literature (Darling & Giovanelli, 2002, 2006; Willett, 2012; Suess et al.,
2016; Hess et al., 2021; Glowacki et al., 2022), where 31 sources with $L_{\rm
OH}$ having only an upper limit are excluded from the current fitting
statistics. Using the least-squares fitting method, the samples produce a
fitting result with ${\rm log}L_{\rm OH}=(1.58\pm 0.10){\rm log}L_{\rm
FIR}-(15.93\pm 1.20)$ in Figure 4. The $\gamma=1.58\pm 0.10$ agrees well with
the result of Darling & Giovanelli (2002) with $\gamma=1.57\pm 0.11$.
Therefore, $\gamma$ remains almost the same when the OHM samples reach up to
154, which is $\sim$1.6 times the previously known OHMs.

###  4.4 FAST OHM detectability

Figure 5: $L_{\rm OH}$ vs. $z_{\odot}$ distribution including 154 sources. The
blue triangles indicate 18 new found OHMs by FASHI and . The grey dots
indicate the detection results of previously known OHMs (Darling & Giovanelli,
2002, 2006; Willett, 2012; Suess et al., 2016; Hess et al., 2021; Glowacki et
al., 2022; Jarvis et al., 2023). Each grey dot with a down arrow indicates the
source with $L_{\rm OH}$ having only an upper limit.

Currently, the highest redshift detection of such an OHM in the main 1667 MHz
OH emission line is J095903.22+025356.1 with a redshift of $z_{\rm
OH}=0.7092$, recently found by Jarvis et al. (2023). The second highest is
LADUMA J033046.20-275518.1 with a redshift of $z_{\rm OH}=0.5225$, found by
Glowacki et al. (2022). However, the third highest redshift of OHMs is IRAS
00256-0208 with $z_{\rm OH}=0.27656$, found in this paper. The large gap (see
Figure 5) between the three highest redshifts of OHMs requires more new
observatories to complete the OHM picture. The 19-beam receiver with FAST is
capable of simultaneously covering a frequency range of 1000-1500 MHz, and the
Ultra-Wide Bandwidth (UWB) receiver with FAST could simultaneously cover
500-3300 MHz. FAST will be a powerful instrument for observing highly
redshifted OH emission in extragalactic objects (Zhang et al., 2023).

Furthermore, radio frequency interference (RFI) always affects the search
results of astronomical observations for all radio telescopes on Earth. At
present, the redshifts of all known OHMs are mainly below $z\approx 0.27$ or
$f\approx 1310$ MHz (Darling & Giovanelli, 2002; Willett, 2012; Haynes et al.,
2018; Suess et al., 2016; Hess et al., 2021; Roberts et al., 2021), which is
mainly due to the existence of strong RFI above $z\approx 0.27$. From the
statistics of RFI in the FAST 19-beam array (Zhang et al., 2023), we can see
that there is a lot of seriously strong RFI from communication and navigation
satellites, over two broad frequency bands in 1150-1310 and 1465-1500 MHz,
corresponding to a redshift of $0.27\lesssim z\lesssim 0.45$ and $0.11\lesssim
z\lesssim 0.14$, respectively. It is because the frequency band in 1310-1465
MHz is very clear that the FAST has already detected 27 OHMs in this band. In
addition, the RFI is bearable in the frequency band of 1050-1150 MHz or
$0.45\lesssim z\lesssim 0.55$. Therefore, it is feasible to search for the
potential OHMs within $0.45\lesssim z\lesssim 0.55$ using the FASHI data in
the future.

Moreover, the FASHI data have detected 27 OHMs in the frequency range
1310-1465 MHz with a typical spectral detection sensitivity of $\sim$1.50 mJy
at a spectral resolution of $\sim$6.4 ${\rm km~{}s}^{-1}$ at 1.4 GHz (Zhang et
al., 2024). The coverage of the current FASHI data is $\sim$10000 deg2. If the
FASHI observation could cover $\sim$20000 deg2 in the future, FASHI is
expected to obtain a total of 54 OHMs at the current detection sensitivity. If
a longer integrated time than the current FASHI drift survey is applied to
each PSCz source, more OHMs would be extracted. Please note that the method of
source identification in this work is to directly compare the PSCz catalog
with the corresponding FASHI data cube to see if there are any emission lines
(see Section 2.2). A blind and complete OHM identification throughout the
FASHI data cube would expand the sample again. Thus, FASHI or FAST could
provide great opportunities to detect more samples.

##  5 Summary

The FAST All Sky H I survey (FASHI) aims to cover the entire sky observable by
the Five-hundred-meter Aperture Spherical radio Telescope (FAST), covering
$\sim$22000 square degrees of declination between $-14^{\circ}$ and
$+66^{\circ}$, and in the frequency range of 1000-1500 MHz, with an
expectation of detecting more than 100000 H I sources finally. At present,
FASHI had observed more than 7600 square degrees. It has a typical spectral
detection sensitivity of $\sim$1.50 mJy and a spectral line velocity
resolution of $\sim$6.4 ${\rm km~{}s}^{-1}$ at a frequency of $\sim$1.4 GHz.
As of now, a total of 41741 extragalactic H I sources have been detected and
released by FASHI.

To efficiently expand the OHM sample, we have directly cross-checked the PSCz
catalog with the corresponding FASHI data cube. We finally detected 27 OHMs
including 9 previously known and 18 new ones within a redshift range of
$0.14314\lesssim z_{\rm OH}\lesssim 0.27656$. For 9 of the detected 27 OHMs,
we also measured the hyperfine line ratio between the integrated fluxes of
1667 and 1665 MHz. The detection rate is 33.3% for the 1665 MHz line. The line
ratio $R_{1667:1665}$ ranges from 1.32 to 15.22, with an average of
$R_{1667:1665}=4.74$, in agreement with the results reported by McBride et al.
(2013).

Now we have a total of 154 OHMs, including the 18 OHMs first detected by
FASHI. All samples produce a new fitting $L_{\rm OH}$ and $L_{\rm FIR}$
relationship with ${\rm log}L_{\rm OH}=(1.58\pm 0.10){\rm log}L_{\rm
FIR}-(15.93\pm 1.20)$, which agrees well with the result of Darling &
Giovanelli (2002) with $\gamma=1.57\pm 0.11$ with 95 data points. This
indicates that $\gamma$ remains almost the same when the OHM samples reach up
to $\sim$1.6 times the previously known OHMs.

In the detected 27 OHMs of this work, 13 OHMs are ULIRGs and 14 OHMs are
LIRGs, ranging from $10^{11.70\pm 0.03}$ to $10^{12.43\pm 0.01}L_{\odot}$ with
a median of $10^{12.00\pm 0.02}L_{\odot}$. This means that all 27 OHMs have
relatively high FIR luminosities. The strong FIR emission suggest that the
host system has undergone a very recent and strong starburst. The multi-
wavelength SED fitting results also show that the OH host galaxies are massive
($M_{*}\simeq 10^{11}M_{\odot}$) galaxies with the SFR above the star-forming
main sequence. The higher $A_{V}$ value of the OH galaxies from the SED fit is
also consistent with the high IR luminosities. On the other hand, not all
ULIRGs have detectable OH emission, suggesting that the OH emission may be
triggered within a specific stage of the merger.

FAST, with its 19-beam array and UWB receiver, will be a powerful tool for
observing more OHMs and unraveling their mystery in the future.

## Acknowledgements

This work is supported by the National Key R&D Program of China
(2022YFA1602901). CPZ acknowledges support by the West Light Foundation of the
Chinese Academy of Sciences (CAS). CC is supported by the National Natural
Science Foundation of China, Nos. 11803044, 11933003, and 12173045. This work
is sponsored (in part) by the Chinese Academy of Sciences (CAS), through a
grant to the CAS South America Center for Astronomy (CASSACA). We acknowledge
the science research grants from the China Manned Space Project with No. CMS-
CSST-2021-A05. We also wish to thank the anonymous referee for comments that
improved the clarity of the paper.

FAST is a Chinese national mega-science facility, operated by the National
Astronomical Observatories of Chinese Academy of Sciences (NAOC). SDSS
acknowledges support and resources from the Center for High-Performance
Computing at the University of Utah. The SDSS web site is www.sdss4.org. SDSS
is managed by the Astrophysical Research Consortium for the Participating
Institutions of the SDSS Collaboration including the Brazilian Participation
Group, the Carnegie Institution for Science, Carnegie Mellon University,
Center for Astrophysics — Harvard & Smithsonian (CfA), the Chilean
Participation Group, the French Participation Group, Instituto de Astrofísica
de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and
Mathematics of the Universe (IPMU) / University of Tokyo, the Korean
Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut
für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA
Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-
Institut für Extraterrestrische Physik (MPE), National Astronomical
Observatories of China, New Mexico State University, New York University,
University of Notre Dame, Observatório Nacional / MCTI, The Ohio State
University, Pennsylvania State University, Shanghai Astronomical Observatory,
United Kingdom Participation Group, Universidad Nacional Autónoma de México,
University of Arizona, University of Colorado Boulder, University of Oxford,
University of Portsmouth, University of Utah, University of Virginia,
University of Washington, University of Wisconsin, Vanderbilt University, and
Yale University.

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Figure 6: OHM IRAS 01562+2527. Refer to caption in Figure 2

Figure 7: OHM IRAS 02524+2046. Refer to caption in Figure 2

Figure 8: OHM IRAS 03111-0244. Refer to caption in Figure 2

Figure 9: OHM IRAS 06487+2208. Refer to caption in Figure 2

Figure 10: OHM IRAS 08201+2801. Refer to caption in Figure 2

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Figure 12: OHM IRAS 08566-0252. Refer to caption in Figure 2

Figure 13: OHM IRAS 10106+4708. Refer to caption in Figure 2

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Figure 19: OHM IRAS 11301-0523. Refer to caption in Figure 2

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Figure 30: OHM IRAS 16468+5200. Refer to caption in Figure 2

Figure 31: OHM IRAS 23129+2548. Refer to caption in Figure 2


# Conversations as a Source for Teaching Scientific Concepts at Different
Education Levels

###### Abstract

Open conversations are one of the most engaging forms of teaching. However,
creating those conversations in educational software is a complex endeavor,
especially if we want to address the needs of different audiences. While
language models hold great promise for educational applications, there are
substantial challenges in training them to engage in meaningful and effective
conversational teaching, especially when considering the diverse needs of
various audiences. No official data sets exist for this task to facilitate the
training of language models for conversational teaching, considering the
diverse needs of various audiences. This paper presents a novel source for
facilitating conversational teaching of scientific concepts at various
difficulty levels (from preschooler to expert), namely dialogues taken from
video transcripts. We analyse this data source in various ways to show that it
offers a diverse array of examples that can be used to generate contextually
appropriate and natural responses to scientific topics for specific target
audiences. It is a freely available valuable resource for training and
evaluating conversation models, encompassing organically occurring dialogues.
While the raw data is available online, we provide additional metadata for
conversational analysis of dialogues at each level in all available videos.

Keywords: Natural Language Conversations, Education

Conversations as a Source for Teaching Scientific Concepts at Different
Education Levels

Donya Rooein, Dirk Hovy
---
Bocconi University
Milan, Italy
donya.rooein<EMAIL_ADDRESS>

Abstract content

## 1\. Introduction

Language adaptation in teaching is essential for optimal learning outcomes,
especially when addressing learners of varying educational levels. As learners
grow and progress from one educational level to another, their cognitive
abilities, comprehension levels, and subject familiarity evolve Council et al.
(2015). Tailoring teachers’ language to suit the learner’s educational level
ensures that the content is neither too simplistic nor overwhelmingly complex.
By adapting language to a student’s academic maturity, educators can create a
more inclusive, effective, and engaging learning environment that acknowledges
and addresses the unique needs of every learner Islam and Mares (2003).

The majority of NLP research studies have concentrated on text simplification
to enhance comprehension by addressing the syntactic and lexical complexities
of a sentence Siddharthan (2002); Zhu et al. (2010); Alva-Manchego et al.
(2020). Limited research has been conducted on sentence complexification,
which augments the syntactic and lexical intricacy of a provided sentence
Berov and Standvoss (2018). Complexification in learning refers to the
situation when a learner might want to see more advanced or idiomatic ways of
learning content Chi et al. (2023). The task of paraphrasing a sentence to a
specific level of complexity within NLP has been relatively overlooked Bhagat
and Hovy (2013); Chi et al. (2023).

Figure 1: Examples of conversations of an instructor with a child and expert
learners.

As Large Language Models (LLMs) continue to gain prominence and exhibit
remarkable linguistic powers, the educational landscape stands to benefit
significantly. The advent of these advanced language models opens the door to
developing teaching materials and educational chatbots that are powerful and
exceptionally flexible. However, to address this challenge, we need to collect
and analyse datasets to adapt language models to serve diverse audience
levels. We present a comprehensive study on available sources to facilitate
the construction of adaptable educational resources with different complexity
levels. We consider this conversational dataset a valuable testing ground to
evaluate the adaptability of LLMs to a wide range of audience levels.
Ultimately, our research endeavors to bridge the gap between LLMs’ immense
promise and their (still limited) real-world applicability in education, thus
charting a path toward a more accessible and personalized learning experience
for all. In this paper, we collect and analyse the 5-Levels conversation
dataset, an annotated resource to facilitate the advancement of educational
dialogue systems capable of adapting to various levels of complexity. It
builds on publicly available raw data of educational conversations and adds an
analysis and meta-data to make it actionable for LLM research. Specifically,
the dataset addresses simplifying and complexifying the same learning topic
within conversational data to teach scientific concepts across various
difficulty levels. It can offer valuable insights into how to address the
challenge of developing a language-teaching chatbot capable of customizing the
learning experience to suit its audience.

Our contributions are:

  * •

We collect and analyse the 5-Levels dataset, a high-quality conversational
dataset sourced from the WIRED website, featuring interactions between
instructors and learners of varying backgrounds in general scientific topics.

  * •

We publish the script for collecting video transcriptions to facilitate future
research.

  * •

We quantitatively and qualitatively analyse the interactions between
instructors and learners for different levels, providing relevant insights
with various statistical metrics.

## 2\. 5-Levels Videos

“5-Levels” is a video series by WIRED 1115-Levels videos from Wired, Condé
Nast to answer the question, “Can everything be explained to everyone in terms
they can understand?”. In each video, an expert scientist explains a high-
level scientific subject in five different levels of complexity: first to a
child, then a teenager, then an undergrad majoring in the same subject, a
graduate student, and finally, an expert colleague. Each video segment
features an engaging and interactive dialogue among participants. Like
personalized one-on-one instruction, the teacher initiates conversations and
queries learners on various concepts.

The pairs of dialogue transcription and education level in the 5-level videos
offer single-round dialogues between instructors and learners with varying
subject knowledge levels. The publicly available transcriptions of these
dialogues serve as a rich source for text simplification and language
adaptation when conveying scientific concepts to diverse audiences. These
transcriptions are self-contained among each complexity level, implying that
no prior background or contextual information is required to grasp the core of
the conversation. All videos are multi-modal conversations, but the
transcription alone suffices to comprehend the dialogue, even without its
visual contents. These videos were published from 2017 to 2023 as 25
episodes222Twenty-three videos were recorded as in-person teaching
discussions, two as remote video discussions. covering various general science
topics spanning physics, mathematics, astronomy, machine learning, and
cryptography. The list of participants’ gender is available in Table 1. The
instructors in these videos are between 38 and 67 years old, with a minimum
qualification of a Master of Science degree, and the specific ages of the
participants are not explicitly provided. Based on the transcriptions, the age
of child participants ranged from 5 to 10 years old, teens were within the 11
to 18 age bracket, college students were 19 to 22 years, and graduate students
were typically 21 years or older.

|  Ins. |  child |  teen |  coll. |  grad. |  exp.
---|---|---|---|---|---|---
female |  10 |  17 |  18 |  13 |  12 |  7
male |  15 |  8 |  7 |  12 |  13 |  18
Table 1: Gender distribution of participants in the videos.

## 3\. Transcriptions

The transcriptions of the videos are available on the WIRED website. We obtain
these transcriptions through a semi-automated method.333We obtained permission
from WIRED to publish our findings on their data. First, we parse all the HTML
pages for the videos and extract the transcriptions from them. Then, we
manually segment and refine the transcriptions for learners at different
levels and separate the turns of instructors and learners. Each video consists
of seven segments. The initial and final segments are introductions and
conclusions, where the instructor addresses the topic. The remaining segments
feature discussions between professional instructors and five distinct learner
profiles (child, teenager, college student, graduate student, and expert). We
exclude these discussions’ introductory and concluding portions, retaining
only the dialogues between the instructor and the participants in each video.

The transcriptions contain around 570 minutes of 125 one-to-one conversations,
revealing the depth and range of engagement between the 150 involved
interlocutors. The transcriptions encompassed 102,656 words and consisted of
2,881 conversational turns, highlighting the dynamic back-and-forth of the
educational discourse. Additionally, the gender distribution of the
instructors in these videos was notably diverse, with 10 female instructors
and 15 male. Table 1 shows the gender distribution among all participants at
different levels. The average length of these videos is 23 minutes.

## 4\. Conversational Analysis

Conversation analysis (CA) explores how interactions are structurally
organized among interlocutors Okeke and van der Westhuizen (2020). For videos,
it uses text-level metrics like the number of turns, words, and sentences for
each utterance. We also calculate standard readability metrics like Flesch-
Kincaid Readability Ease (FKRE) and Flesch-Kincaid Grade Level (FKGL) to
explore the level of readability of transcription for each complexity level
across utterances. FKRE and FLGL calculate with a weighted scoring formula
that considers both sentence length and the number of syllables. The FKRE
range from 0 to 100, with lower scores suggesting that the text is more
challenging for readers to comprehend. Kincaid et al. (1975). For consistency
and clarity, we labeled each instructor in the videos as ’INS.‘ followed by
their respective sequence number of the episode. Our effort serves as the
groundwork for teaching science concepts adapted to different levels of
complexity, opening insights that can be used in how we impart knowledge and
facilitate the development and integration of state-of-the-art computational
solutions such as language models, and can be harnessed with precision and
effectiveness.

Table 2 presents the ratio of words spoken by the instructor to those spoken
by the learner for each video. Our analysis captures a notable trend:
instructors dominate conversations when interacting with younger audiences,
especially children and teenagers. In these interactions, 64% of the
instructors spoke at least three times more than their younger counterparts.
However, when conversing with more knowledgeable groups such as graduate
students, only 16% of instructors spoke more than 3 times the learners.
Intriguingly, at the expert level, the trend reversed, with 72% of experts
speaking more than the instructors. Furthermore, an observable trend in some
videos, highlighted in Table 2, is the decreasing ratio of words spoken by
instructors compared to learners as the audience’s proficiency level rises
from child to expert. This suggests that the instructors tend to speak less as
the learner’s expertise increases, allowing the more knowledgeable
participants to contribute more to the conversation. It highlights the dynamic
nature of instructor-learner interactions, adapting based on the audience’s
knowledge level.

Among all the videos, videos 8 and 25 tackle the topic of black holes. Some
noteworthy trends emerge when examining the word count ratio of instructors to
learners across different educational levels. For video 8, presumably a more
basic explanation, the word count ratio is the highest for children at 3.69,
indicating a more detailed or elaborative teaching approach. As the
educational level progresses to teens and college students, the ratio drops,
with the least for graduates at 1.05. In contrast, video 25 shows a different
word count distribution. Here, the ratio is highest for teens at 5.34 and
least for graduates at 0.95, suggesting that different instructors might have
different teaching styles, even over the same topic.

Video | child | teen | coll. | grad. | exp.
---|---|---|---|---|---
1 | 3.36 | 9.84 | 1.65 | 1.86 | 1.12
2 | 11.19 | 7.65 | 3.36 | 2.24 | 0.8
3 | 2.83 | 12.05 | 5.25 | 1.15 | 1.02
4 | 4.85 | 5.23 | 3.78 | 0.49 | 0.54
5 | 1.87 | 5.73 | 2.16 | 0.93 | 0.55
6 | 2.89 | 3.52 | 1.93 | 2.63 | 0.49
7 | 9.31 | 7.46 | 2.50 | 1.36 | 0.94
8 | 3.69 | 1.25 | 1.35 | 1.05 | 1.32
9 | 1.09 | 4.83 | 8.04 | 1.18 | 0.72
10 | 2.61 | 4.57 | 3.97 | 3.37 | 1.45
11 | 5.57 | 2.91 | 0.44 | 2.04 | 0.38
12 | 1.08 | 1.25 | 4.35 | 0.72 | 0.58
13 | 6.25 | 1.93 | 1.13 | 0.48 | 0.96
14 | 3.02 | 1.82 | 2.68 | 0.34 | 0.86
15 | 2.29 | 1.66 | 3.68 | 1.56 | 0.83
16 | 6.91 | 4.16 | 0.91 | 0.61 | 0.35
17 | 0.15 | 0.29 | 3.93 | 3.33 | 0.51
18 | 4.6 | 1.99 | 7.51 | 0.58 | 0.29
19 | 3.03 | 1.19 | 0.26 | 4.20 | 1.10
20 | 7.05 | 4.35 | 5.07 | 2.20 | 0.78
21 | 4.98 | 3.80 | 3.34 | 1.34 | 0.92
22 | 6.81 | 7.63 | 3.60 | 5.32 | 0.94
23 | 6.83 | 4.82 | 3.90 | 1.17 | 0.49
24 | 11.43 | 5.17 | 2.90 | 1.53 | 1.50
25 | 2.19 | 5.34 | 3.11 | 0.95 | 1.96
Table 2: Instructor to learner word count ratio: highlighted rows show decreasing ratio as audience proficiency increases. |  child |  teen |  coll. |  grad. |  exp.
---|---|---|---|---|---
INS.1 |  84.57 |  72.66 |  71.04 |  56.29 |  55.24
INS.3 |  85.59 |  74.79 |  63.90 |  62.27 |  61.16
INS.22 |  88.16 |  75.13 |  69.19 |  65.96 |  58.50
Table 3: Example FKRE metrics of instructor turns when teaching various
learners.

Our study measures different readability scores associated with instructors
and learners. The investigations show how instructors tailor their language
complexity to suit different audiences. Notably, the FKRE of instructors, such
as INS.1 and INS.3, demonstrated reduced value and increased complexity as the
conversational level progressed from a child to an expert, as shown in Table
3. For example, in Video 1, the FKRE scores revealed a pattern where the child
had a higher readability score of 84.57, gradually decreasing to 55.24 for the
expert.

### 4.1. Presentation styles

The presentation of scientific concepts across these videos varies in depth,
complexity, and technical jargon. For children, educators often start with
questions about whether they know the concept. For instance, INS.9 asked a
child, “Do you know what gravity is?”. Similarly, INS.10 initiated a
conversation with, “Have you heard the word ‘physics’ before? Do you know what
that means?”. Simple language, visual content, and real-world analogies are
commonly used. The emphasis is on making the concept engaging, relatable, and
easily digestible by using storytelling and a playful approach to explain it.
For example, INS.1 uses a conversation with her son to explain the concept of
Nuclear Fusion to the child learner. At the teen level, the depth of content
expands. Analogies are more sophisticated, and some basic technical terms have
been introduced. Instructors attempt to connect the new topic to the teens’
school knowledge with questions such as, “Have you played with magnets in
school?” posed by INS.6, or “So, have you had much exposure to lasers yet at
school?” asked by INS.20. The concept presentations to the college and
graduate schools are more specialized. Educators assume a foundational
understanding of the subject and thus delve into more detailed information.
Technical jargon is extensive, and the content might often be segmented into
various sub-topics on the topic. For expert-level explanations, educators
mostly ask them to explain highly specialized concepts and the cutting-edge
aspects of the subject. Discussions often involve current research and future
implications. Rather than basic explanations, the content is discussion-
driven, analysing the topic’s nuances and frontiers.

The use of analogies and metaphors varies across different audiences and
levels. For Example, INS.2 explains the concept of time to a child by
comparing the relation between aging and the number of Earth’s revolutions
around the sun, or INS.9 explains gravity as: “It’s something that, so, right
now, we would be floating if there was no gravity, but since there’s the
gravity we’re sitting right down on these chairs.”

College and graduate-level analogies aim to bridge the gap between fundamental
concepts and advanced theories. When INS.2 explains the time to the graduate
learner, it could be likened to a billiard ball metaphor, as “it goes into a
wormhole, comes out and hits the ball going into the hole. And in that way, if
it could knock it off course, we seem to be in some logical paradox”.

Instructors use various strategies to adapt their teaching to specific
audiences. While no single strategy fits all, we observe many common behaviors
across these conversations. They begin by assessing the prior knowledge of
their audience to determine the starting point. Instructors use simplified
content using basic vocabulary, some visuals, hands-on activities, and real-
world examples to teach scientific concepts to younger learners. College and
graduate students are assumed to have a foundation in the subject. They can
understand abstract notions and are ready for more in-depth discussions and
evaluations. Expert learners focus on the latest research, sharing ideas,
unresolved questions in the field, and collaborative projects. Discussions can
be highly technical and specialized. Instructors frequently tap into the
curiosity of less knowledgeable learners, such as children or teens, by
crafting examples and activities that enable them to explore scientific
concepts independently. After introducing a concept, they collect feedback
with questions from these learners to assess their understanding. For
instance, INS.7 might ask, “What have you learned about black holes?”.

## 5\. Conclusion

We present a 5-Levels dataset and its analysis containing transcriptions of
discussions featured on teaching scientific concepts with various difficulty
levels. It serves as a resource for researching educational interactions
within the context of adapting scientific topics to varying complexity levels,
a new domain that has been neglected in prior research. We use CA techniques
to analyse different turns of instructors and learners. Educators use various
strategies to tailor their teaching styles to these different complexity
levels. Analogies and metaphors are valuable tools for conveying complex
ideas, becoming more abstract and technical as the audience’s knowledge
deepens. This work addresses the absence of suitable datasets for more
computational approaches and training language models to aid adaptive teaching
practices.

## Ethical Considerations

Age is a protected category. However, it is inextricably linked to the study
of education in most cultures. In our study, we use data from the available
series of videos about teaching scientific concepts to different levels of
difficulty on the WIRED website, and evaluate the transcripts via automated
text analysis metrics. As the data is published presumably with the consent of
the subject, there is minimal risk of abuse and no concerns for the welfare of
human subjects in our analysis.

## 6\. References

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