CO Observations of Early-mid Stage Major Mergers in the MaNGA Survey

CO Observations of Early-mid Stage Major Mergers in the MaNGA Survey Qingzheng Yu (余清正) 1 , Taotao Fang (方陶陶) 1 , Cong Kevin Xu (徐聪) 2,3 , Shuai Feng (冯帅) 4,5 , Siyi Feng (冯思轶) 1 , Yu Gao (高煜) 1 , Xue-Jian Jiang (蒋雪健) 6 , and Ute Lisenfeld 7,8 1 Department of Astronomy, Xiamen University, Xiamen 361005, People’s Republic of China; [email protected],[email protected] 2 Chinese Academy of Sciences South America Center for Astronomy, National Astronomical Observatories, CAS, Beijing 100101, People’s Republic of China 3 National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100101, People’s Republic of China 4 College of Physics, Hebei Normal University, 20 South Erhuan Road, Shijiazhuang, 050024, People’s Republic of China 5 Hebei Key Laboratory of Photophysics Research and Application, Shijiazhuang 050024, People’s Republic of China 6 Research Center for Astronomical Computing, Zhejiang Laboratory, Hangzhou 311100, People’s Republic of China 7 Dept. Física Teórica y del Cosmos, Campus de Fuentenueva, Edificio Mecenas, Universidad de Granada, E-18071 Granada, Spain 8 Instituto Carlos I de Fśica Tórica y Computacional, Facultad de Ciencias, Granada E-18071, Spain Received 2024 March 5; revised 2024 April 19; accepted 2024 April 28; published 2024 June 18 Abstract We present a study of the molecular gas in early-mid stage major mergers, with a sample of 43 major-merger galaxy pairs selected from the Mapping Nearby Galaxies at Apache Point Observatory survey and a control sample of 195 isolated galaxies selected from the xCOLD GASS survey. Adopting kinematic asymmetry as a new effective indicator to describe the merger stage, we aim to study the role of molecular gas in the merger-induced star formation enhancement along the merger sequence of galaxy pairs. We obtain the molecular gas properties from CO observations with the James Clerk Maxwell Telescope, Institut de Radioastronomie Milimetrique 30 m telescope, and the MaNGA-ARO Survey of CO Targets survey. Using these data, we investigate the differences in molecular gas fraction (fH 2 ), star formation rate (SFR), star formation efficiency (SFE), molecular-to-atomic gas ratio (MH 2 /M H I ), total gas fraction (f gas ), and the SFE of total gas (SFE gas )between the pair and control samples. In the full pair sample, our results suggest the fH 2 of paired galaxies is significantly enhanced, while the SFE is comparable to that of isolated galaxies. We detect significantly increased fH 2 and MH 2 /M H I in paired galaxies at the pericenter stage, indicating an accelerated transition from atomic gas to molecular gas due to interactions. Our results indicate that the elevation of fH 2 plays a major role in the enhancement of global SFR in paired galaxies at the pericenter stage, while the contribution of enhanced SFE in specific regions requires further explorations through spatially resolved observations of a larger sample spanning a wide range of merger stages. Unified Astronomy Thesaurus concepts: Galaxy pairs (610);Galaxy mergers (608);Molecular gas (1073);Star formation (1569) 1. Introduction Merging galaxies are believed to play a fundamental role in regulating hierarchical galaxy formation and evolution (e.g., Toomre & Toomre 1972; Toomre 1977; Barnes & Hernquist 1992). Numerous observations and numerical simulations have revealed the drastic influences of galaxy interactions and mergers, such as the enhancement of star formation (e.g., Xu & Sulentic 1991; Mihos & Hernquist 1996; Ellison et al. 2008;Li et al. 2008; Xu et al. 2010), regulation of gas (e.g., Hibbard & van Gorkom 1996; Ellison et al. 2018; Hani et al. 2018; Lisenfeld et al. 2019; Moreno et al. 2019), triggering of active galactic nuclei (e.g., Kennicutt & Keel 1984; Ellison et al. 2011; Satyapal et al. 2014; Goulding et al. 2018), and redistribution of metallicities (e.g., Kewley et al. 2006; Rupke et al. 2010; Scudder et al. 2012; Torrey et al. 2012).Asa crucial and evident effect, the enhancement of star formation rate (SFR)depends on multiple factors, such as the properties of the progenitor galaxies (e.g., Mihos & Hernquist 1996; Cox et al. 2008; Xu et al. 2010), orbital parameters of the interacting galaxies (e.g., Kennicutt et al. 1987; Keel 1993; Sparre & Springel 2016; Xu et al. 2021), and the interacting phase of galaxies (Di Matteo et al. 2007; Scudder et al. 2012; Patton et al. 2013). The strongest SFR enhancement or starbursts are believed to occur after first pericenter and during coalescence, supported by studies of major-merger galaxy pairs (Nikolic et al. 2004; Scudder et al. 2012; Moreno et al. 2015; Pan et al. 2019)and ultraluminous infrared galaxies (ULIRGs)in interacting systems (e.g., Sanders & Mirabel 1996; Veilleux et al. 2002; Haan et al. 2011; Ellison et al. 2013; Thorp et al. 2019). Theoretical models and numerical simulations have predicted that the gravitational tidal torques induced by galaxy interactions can trigger strong gas inflows in the interstellar medium (ISM), resulting in the enhancement of SFR and nuclear starbursts (Barnes & Hernquist 1991,1996; Mihos & Hernquist 1996; Iono et al. 2004; Hopkins et al. 2009,2013). Hence, studies of the cold gas in the ISM provide a crucial approach for investigating how star formation is enhanced during galaxy interactions, and two major mechanisms have been commonly proposed by observational studies. The first scenario suggests that the merger-induced external pressure can accelerate the transition from atomic (HI)to molecular (H 2 ) gas (e.g., Braine & Combes 1993; Elmegreen 1993; Kaneko et al. 2017), leading to the observed enrichment of the molecular gas reservoir (traced by CO)and enhancement of SFR (Braine & Combes 1993; Combes et al. 1994; Casasola et al. 2004; Wilson et al. 2008; Lisenfeld et al. 2019; Shangguan et al. 2019). The second perspective attributes enhanced star formation to the increased density of molecular The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July https://doi.org/10.3847/1538-4365/ad4547 © 2024. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s)and the title of the work, journal citation and DOI. 1 gas in the galactic center, thereby boosting the efficiency of star formation (Solomon & Sage 1988; Sofue et al. 1993; Gao & Solomon 1999; Michiyama et al. 2016; Yamashita et al. 2017). Recent observations of galaxy pairs have found enhancement of both H 2 gas fraction (fH 2 )and star formation efficiency (SFE; Pan et al. 2018; Violino et al. 2018). Thus, it remains unclear whether the enhancement of SFR is driven by the total amount of molecular gas, SFE, or both. To test the theoretical predictions and investigate the mutual impact of molecular gas and SFR along the evolutionary merger sequence, several factors that may affect the results should be addressed for observational studies. First, the selection and comparison of galaxy pairs and control galaxies could introduce biased results if the global properties are not carefully controlled between samples (Braine & Combes 1993; Michiyama et al. 2016). Furthermore, single-dish CO observations provide a crucial and efficient approach to the evaluation and analysis of global galactic quantities. However, results from single-dish observations should be taken with caution, considering the limitation of spatial resolution. Previous CO observations performed with interferometers have found consistent results relative to the single-dish observations but often suffered from limited numbers and types of targets (e.g., Iono et al. 2009; Ueda et al. 2014; Xu et al. 2021; Hou et al. 2023). A recent study used the Atacama Large Millimeter Array to observe 31 mergers selected from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, and they have found that merger-induced star formation can be driven by a variety of mechanisms, with comparable contributions from both fH 2 and SFE (Thorp et al. 2022). Another less explored but crucial factor pertains to the lack of rigorously defined merger stages, particularly in studies involving galaxy pairs (Pan et al. 2019). The commonly adopted definition of the merger stage in galaxy pairs highly relies on the projected separation (d p )and the difference between line-of-sight velocities (Δv)(Ellison et al. 2008; Zuo et al. 2018; Feng et al. 2019; Zhang et al. 2020), which has been hampered by several shortcomings. Considering the projection effect, relying solely on the projected separation (d P )may introduce large uncertainty in deriving the physical separation of member galaxies (Soares 2007). Furthermore, galaxy pairs with the same separation can be in different merger stages. Although the degree of interactions has been commonly characterized by galaxy morphology (e.g., Toomre 1977; Barrera-Ballesteros et al. 2015; Smith et al. 2018; Pan et al. 2019), a more sensitive and quantitative indicator is required to study the early-stage galaxy pairs (Feng et al. 2020). With the emergence of integral field unit (IFU)surveys on nearby galaxies, such as the Calar Alto Legacy Integral Field Area survey (Sánchez et al. 2012)and the Sydney-AAO Multi-object Integral field spectrograph galaxy survey (Croom et al. 2012), recent studies have exploited unique data of gas kinematics and revealed connections between the asymmetry of gas kinematics and galaxy interactions (Barrera-Ballesteros et al. 2015; Bloom et al. 2018). Using the IFU data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA)survey (Bundy et al. 2015), Feng et al. (2020)investigated the kinematic asymmetry of the ionized gas in a large sample of paired galaxies. By fitting the velocity maps of Hαgas, Feng et al. (2020)quantified the degree of kinematic asymmetry (vasym), which depicts the asymmetry of the velocity field contributed by the interaction-induced nonrotating motion. The value of vasym serves as an indicator of galaxy interaction strength in statistical analyses (see the details in Feng et al. 2020). They find a significant enhancement in the SFR of paired galaxies with high kinematic asymmetries, while those with low kinematic asymmetries show no enhancement of SFR, whether at small or large projected separations. For paired galaxies with high kinematic asymmetries, the enhancement of SFR presents a tight anticorrelation with projected separation. These findings suggest that the combination of kinematic asymmetry and projected separation is effective in quantifying the stage of galaxy pairs, consistent with previous findings that used projected separation and morphology to determine merger stages (e.g., Pan et al. 2019). By employing 24 high-resolution idealized hydrodynamical galaxy merger simulations based on the Feedback In Realistic Environment (FIRE-2)model, this new method has been confirmed to be highly effective in distinguishing mergers in different stages, e.g., mergers during pericentric passages and in/after the final coalescence (McElroy et al. 2022). Given that the enhancement of star formation during galaxygalaxy interactions requires sustaining gas supply, we conduct studies on the cold gas properties of galaxy pairs at different merger stages. Yu et al. (2022)compiled a major-merger galaxy pair sample selected from the MaNGA survey to study the H Icontent of merging galaxies (Yu et al. 2022), adopting the kinematic asymmetry and projected separation as indicators of the merging stage (Feng et al. 2020). Their results suggest that the H Igas fraction of major-merger galaxy pairs, on average, is marginally decreased by ∼15% relative to isolated galaxies, implying mild H Idepletion during galaxy interactions (Yu et al. 2022). In particular, galaxy pairs during the pericenter passage present the largest H Ideficiency (∼26%, Yu et al. 2022). Based on these previous findings, it is necessary to observe the molecular gas to test whether the detection of H Ideficiency is attributed to the accelerated conversion from atomic gas to molecular gas in galaxy pairs. To study the interplay between galaxy–galaxy interactions and the molecular gas properties along the merger sequence, we conducted CO observations for a sample of 43 majormerger paired galaxies selected from the MaNGA survey (Bundy et al. 2015), with ancillary H Idata from the HIMaNGA survey (Stark et al. 2021)and Yu et al. (2022). This paper is organized as follows. In Section 2, we introduce the sample selection of galaxy pairs, observation setup, and data reduction in this work. We then present the main results of the molecular gas properties and star formation in Section 3, with a further discussion presented in Section 4. Finally, we summarize the main results in Section 5. Throughout the whole paper, we adopt the standard ΛCDM cosmology with H 0 =70 km s −1 Mpc −1 ,Ω M =0.3, and Ω Λ =0.7. 2. Samples and Data 2.1. Pair Sample In our parent sample (Feng et al. 2019,2020), we selected the isolated galaxy pairs based on the following criteria: (1) the projected separation for member galaxies: 5 h −1 kpc d p 200 h −1 kpc, (2)the line-of-sight velocity difference: |Δv|500 km s −1 ,(3)each member of the pair has only one neighbor satisfying the above criteria, (4)at least one member galaxy of each pair has been observed in the MaNGA survey 2 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Table 1 Identifiers and Properties of the Major-merger Galaxies in Pairs MaNGA ID R.A. Decl. zlog(M å )log(SFR)vasym d p log(M H1 )r 25 if aper log( M H2)Stage Type Blending (deg)(deg)(M e )(M e yr −1 )(h −1 kpc)(M e )(arcsec)(deg)(M ☉ ) (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16) 8078-6104 42.73943 0.36941 0.04421 10.03 0.66 0.179 18.35 9.88 2.9 58 1.52 9.39 2 S+SY 8078-6104B 42.73145 0.36689 0.04391 10.21 0.49 0.179 18.35 9.88 2.8 34 1.67 9.59 2 S+SY 8082-12703 49.51165 −0.53896 0.02104 10.33 −0.11 0.0295 63.14 9.50 5.3 69 1.73 9.65 3 S+SY 8085-12704 52.61990 0.81150 0.03080 10.55 −0.15 0.0221 98.10 10.07 4.6 65 1.69 <9.20 1 S+SY 8153-12701 39.63722 −0.86747 0.03923 9.72 −0.35 0.0422 158.83 10.00 3.2 48 1.65 <8.79 3 S+SY 8250-6101 138.75315 42.02439 0.02790 10.28 0.89 0.0396 44.97 9.88 4.1 53 1.79 9.75 2 S+SY 8260-6101 182.40876 42.00967 0.02288 9.89 0.15 0.0293 28.93 9.50 3.7 57 1.69 8.86 2 S+SY 8338-6102 172.68267 22.36354 0.02236 9.45 −0.09 0.0360 76.13 9.29 3.0 41 1.68 8.34 3 S+SN 8450-6102 171.74883 21.14168 0.04177 10.17 0.67 0.0516 57.37 9.72 3.1 34 1.77 9.37 3 S+EN 8456-12702 149.96826 45.28310 0.02349 9.39 −0.04 0.0813 13.35 9.98 6.5 76 1.76 8.55 2 S+SY 8547-12702 217.91070 52.74946 0.04566 10.62 0.02 0.0187 137.28 10.40 5.8 81 1.64 9.31 1 S+EN 8552-12702 227.92840 43.97044 0.02758 9.25 0.05 0.0558 90.60 9.73 4.0 73 1.55 8.92 3 S+SY 8588-12702 250.31305 39.29009 0.03054 9.71 −0.08 0.0648 88.57 9.95 5.2 54 1.91 8.93 3 S+SN 8656-1901 7.71740 0.52876 0.01914 9.08 −0.31 0.0293 101.03 9.22 3.1 44 1.67 8.55 3 S+SN 8656-3703 7.75250 0.43575 0.01917 9.36 −0.55 0.0232 101.21 9.22 3.3 54 1.63 8.11 1 S+SN 8657-12704 10.40833 0.25764 0.01807 9.08 −0.50 0.0998 47.61 9.41 3.1 35 1.74 8.10 2 S+SN 8728-12701 57.72958 −7.06065 0.02841 10.50 −0.03 0.0716 66.78 9.78 4.8 20 2.19 9.36 3 S+EN 8981-6101 185.94406 36.15281 0.03332 10.82 0.09 0.0320 81.77 9.89 5.0 49 1.94 9.68 3 S+SY 8981-6101B 186.00444 36.15589 0.03336 10.82 −0.22 0.0320 81.77 9.59 2.9 24 1.75 9.10 3 S+SY 9027-12702 243.98368 31.40677 0.02256 10.00 0.06 0.0210 129.06 9.80 5.7 65 1.83 9.02 1 S+SN 9027-9101 243.90740 31.32130 0.02220 10.15 −0.11 0.0352 126.97 9.59 3.8 66 1.59 8.76 3 S+SY 9030-3702 241.23416 30.52573 0.05540 10.67 0.86 0.0219 48.27 10.49 2.5 30 1.66 9.79 1 S+SY 9032-3704 241.21561 30.52601 0.05537 10.49 0.73 0.0152 48.27 10.49 2.3 34 1.56 9.99 1 S+SY 9050-9101 245.99844 21.79503 0.03209 10.24 0.52 0.0310 41.92 9.20 3.9 43 1.82 9.71 2 S+SY 9050-9101B 245.99284 21.82049 0.03209 10.24 0.28 0.0310 41.92 9.20 2.8 35 1.67 9.45 2 S+SY 9093-12701 239.75272 27.98539 0.05140 10.61 0.30 0.1533 24.43 L4.0 68 1.58 9.90 2 S+SY 9094-12703 239.74204 27.98753 0.05210 10.63 0.78 0.0411 24.43 L4.6 73 1.60 10.00 2 S+SY 9094-12705 240.46430 26.31944 0.04393 9.85 −0.11 0.0445 176.34 10.05 4.1 74 1.54 9.24 3 S+EN 9185-9101 256.21228 34.81733 0.05683 10.81 1.39 0.193 7.25 10.09 2.3 21 1.62 10.49 2 S+SY 9488-9102 126.70413 20.36485 0.02510 9.75 0.27 0.0804 190.82 10.31 4.4 23 2.14 8.48 3 S+SN 9499-12703 118.42323 26.49270 0.03742 10.82 0.07 0.0281 78.04 10.17 4.4 40 1.98 9.60 1 S+EN 9507-12701 128.25074 26.01405 0.01763 9.87 −0.47 0.0668 21.83 9.62 12.8 82 2.14 9.09 2 S+EN 9509-6103 123.06447 26.20257 0.02508 10.04 −0.06 0.0147 87.35 9.71 3.1 33 1.75 9.30 1 S+SN 9881-6102 205.21316 24.47331 0.02705 10.77 −0.05 0.0195 152.23 9.99 5.4 19 2.32 9.81 1 S+EN 9889-1902 234.85860 24.94357 0.02286 9.98 0.63 0.0240 7.92 9.13 3.0 53 1.58 8.91 1 S+SY 9889-1902B 234.86460 24.94762 0.02291 10.41 0.99 0.0240 7.92 9.13 4.7 46 1.93 9.65 1 S+SY 8252-9101 144.69238 48.56287 0.02478 9.45 0.13 0.0383 82.20 9.27 0.7 25 1.09 9.04 3 S+SY 8624-12703 264.23954 59.20029 0.03070 10.46 0.62 0.0501 143.76 9.51 5.0 66 1.34 9.54 3 S+SY 8945-12701 171.89808 47.37939 0.03273 9.94 0.45 0.0578 100.36 10.32 3.9 29 1.43 8.89 3 S+SY 8979-3704 244.42297 40.93382 0.06209 10.80 0.96 0.0376 188.99 L4.3 51 1.37 9.57 3 S+SN 8987-3701 136.24989 28.34772 0.04864 10.04 0.85 0.0157 44.75 10.08 2.2 38 1.24 9.12 1 S+SY 9034-3702 226.28033 46.96366 0.03771 9.83 0.39 0.0174 63.88 L3.2 51 1.29 9.10 1 S+SY 9508-6104 127.55302 26.62732 0.05299 10.82 1.12 0.0294 105.66 10.03 3.7 66 1.26 9.77 3 S+SY Note. A detailed description of this table’s contents is given in Section 2.1. 3 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. (Bundy et al. 2015), and the member galaxy has more than 70% spaxels with Hαemission at a signal-to-noise ratio (S/N)>5 within a 1.5 effective radius (R e ), and (5)we only study star-forming galaxies (log (sSFR yr −1 )>−11)in this work. To study major-merger pairs, we constrain the mass ratio as M 1 /M 2 <3, where M 1 and M 2 represent the stellar masses of primary galaxies and companions, respectively. Among the selected major-merger galaxy pairs, we adopt a mass cut of ()MMlog 9  to match the stellar mass range of the control sample (Saintonge et al. 2017)used in this work (see Section 2.2). The final pair sample consists of 43 major-merger galaxies in pairs, of which 36 paired galaxies are observed through our PI programs, and seven sources are adopted from MASCOT (Wylezalek et al. 2022). Based on the previous morphological classification (Yu et al. 2022), this sample comprises 36 spiral +spiral (S+S)and seven spiral+elliptical (S+E)pairs, and all the observed sources in the sample are spiral galaxies. The redshift range of this sample spans from 0.017–0.062. We adopt the SFR and stellar mass (M å )for each pair from the public catalog of MPA-JHU DR7. 9 For all the galaxies in the pair sample, the following key parameters are presented in Table 1: 1. MaNGA ID: source name presented by MaNGA plateifu, with B representing the companion galaxy of the primary MaNGA galaxy. 2. R.A.: R.A. in degrees. 3. Decl.: decl. in degrees. 4. z: Sloan Digital Sky Survey (SDSS)spectroscopic redshift. 5. log(M å ): stellar mass from the MPA-JHU Catalog. 6. log(SFR): SFR from the MPA-JHU Catalog. 7. vasym: kinematic asymmetry measured from Hαvelocity maps. The velocity map is divided into a sequence of concentric elliptical rings and fitted with the Fourier series, and the kinematic asymmetry is defined as the ratio between high-order (sum from 2–5 orders)and first-order coefficients: ()=+++vkkkkk4 asym 2 3 4 5 1, where k n is the coefficient of the nth-order Fourier component (Feng et al. 2020). 8. d p : projected separation. 9. log(M H I ):HIgas mass from HI-MaNGA (Stark et al. 2021)and Yu et al. (2022). 10. r 25 : isophotal optical major radius at the isophotal level 25 mag arcsec −1 in the rband from the NASA/IPAC Extragalactic Database (NED). 10 11. i: inclination from NED. 12. f aper : aperture correction calculated with Equation (3). 13. log(MH 2 ): molecular gas mass calculated from the total CO line luminosity after aperture correction, details in Section 2.4. 14. Stage: merging stage based on vasym and d p , see Section 2.2 for the definition; 1, 2, and 3 represent prepassage, pericenter, and apocenter, respectively. 15. Type: type of galaxy pair, with S+S and S+E representing spiral+spiral and spiral+elliptical pairs, respectively. 16. Blending: source blending in H Iobservations, with Y and N representing yes and no for source blending problems, respectively. 2.2. Subsamples and Control Sample The definition of the merger stage follows previous H I observations (Yu et al. 2022)and the statistical studies of SFR enhancement in MaNGA galaxy pairs (Feng et al. 2020), which relies on the combination of kinematic asymmetry (vasym)and projected separation (d p ). Adopting the statistical results of Feng et al. (2020),wedividethepair sample into two subsamples based on their vasym values: low asymmetry (<<v 0 .007 0.029 asym )andhighasymmetry (<<v 0 .029 0.316 asym ). We adopt the boundary of =v0.029 asym basedonpreviousHIobservations (Yu et al. 2022), which has also been confirmed to be effective in determining merger stages by simulations of 24 galaxy mergers using the FIRE-2 model (McElroy et al. 2022).In particular, paired galaxies after the pericentric passage exhibit a more disturbed velocity fieldcomparedtopairs before the passage (Hung et al. 2016; McElroy et al. 2022). Hence, we consider the galaxy pairs with low vasym values as pairs to be in the pre-passage stage, indicating no significant interactions between member galaxies. During the sequence of galaxy interactions in pair-phase, simulations suggest a constant decrease in the physical separation before the pericentric passage, and then the separation will increase until the paired galaxies are approaching apocenter (Torrey et al. 2012;Morenoetal.2015,2019). In this work, we use the projected separation (d p )as a reference to distinguish the pericenter and apocenter stages of galaxy pairs. Galaxy pairs with a high vasym value and d p <50 kpc are defined to be at the stage of pericenter passage, and those with a high vasym value and d p >50 kpc are regarded as being in the apocenter stage. The number of pairs in each stage is as follows: (1) pre-passage: 13, (2)pericenter passage: 12, and (3) apocenter passage: 18. To systematically investigate the impacts of galaxy interactions on star formation and molecular gas properties, we compiled a control sample of isolated galaxies. The isolated galaxies are selected from the Extended CO Legacy Database for GASS (xCOLD GASS; Saintonge et al. 2017), with the requirement of having no bright neighbors (r<17.77)within d p 200 h −1 kpc and |Δv|500 km s −1 (Feng et al. 2020). To match with the starforming galaxies in our pair sample, we require that the isolated galaxies have log (sSFR yr −1 )>−11. In total, we selected 195 isolated galaxies with both H Iand CO data from xCOLD GASS as our control sample pool. To fairly compare with the paired galaxies, we also adopt the SFR and stellar mass (M å )from the public catalog of MPA-JHU DR7 for the isolated galaxies. As shown in Figure 1, we compared the distributions of redshift and stellar mass between the galaxy pair sample and the control sample. The control sample tends to include more nearby galaxies at lower redshift (z<0.015)and more massive galaxies (()>MMlog 11 )at the high-mass end. To compare the galaxy properties in pairs and controls fairly, we conducted a galaxy-by-galaxy matching between the paired galaxies and isolated galaxies from the control sample pool for further analysis (see details in Section 3.3). Regarding kinematic asymmetry in isolated galaxies, a systematic study suggests that vasym shows a significant anticorrelation with stellar mass only in low-mass 9 https://wwwmpa.mpa-garching.mpg.de/SDSS/DR7/#derived 10 https://ned.ipac.caltech.edu/ 4 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. galaxies at ()<MMlog 9.7 , and it is independent of H Igas content (Feng et al. 2022). Thus, after matching for stellar mass, we minimized potential bias due to the dependence of kinematic asymmetry on stellar mass at the low-mass end. In Figure 2,we present the distributions of paired galaxies and isolated galaxies in the SFR–M å plane. Galaxies in our galaxy pair sample are marked by blue circles. For the control sample, isolated galaxies selected from the xCOLD GASS survey are represented by gray squares. At a given stellar mass, the mean SFR of paired galaxies is higher than that of the isolated galaxies in the control sample. 2.3. Observations and Data 2.3.1. James Clerk Maxwell Telescope Observations For part of the sources in our galaxy pair sample, we performed CO(2−1)observations through our PI program (M21BP051, PI: Q. Yu)with the James Clerk Maxwell Telescope (JCMT). 12 CO(2−1)observations for 23 paired galaxies were carried out between 2021 September and 2021 December, using the Nāmakanui receiver at 230 GHz on JCMT. The beam size is ∼21″at the observed frequency. The observed sample consists of nine major-merger galaxy pairs and 14 minor-merger pairs. The observations were conducted in beam-switching mode with a throw of 180″in the azimuthal direction. The integration time for each source ranged between 10 and 60 minutes. The data were reduced using the Starlink software (Currie et al. 2014). We followed the standard procedure to calibrate individual exposures of each galaxy, and subsequently, we co-added the spectra for each source. After calibration, we rebinned the spectra to a velocity resolution of 10 km s −1 . In some cases, the spectra were rebinned to a velocity of ∼20 km s −1 to achieve tentative detections. By utilizing line-free channels as the fitting region, we subtracted a linear or second-order polynomial baseline from the spectrum. We converted the spectra from antenna temperature in kelvin to jansky, adopting a conversion factor of 15.6/η a , where the aperture efficiency η a is 0.57. In total, we detected 17 CO(2−1) lines out of 23 sources, including nine major-merger galaxies and eight minor-merger galaxies. For each detected spectrum, we visually determined the line widths at zero level (ΔV)and derived the velocity-integrated flux. For nondetections, we calculated the upper limits of velocity-integrated flux as () () d=´ ´ D - IVV3rms , 1 CO 2 1 where δVis the channel width in kilometers per second, ΔVis the zero-level line width in kilometers per second, and rms is the rms noise in kelvin. The nondetections are all minor mergers and are not included in the final pair sample. All the observing results are presented in Section 3.1 and Table 2. 2.3.2. Institut de Radioastronomie Milimetrique 30 m Observations Through our PI programs (E01-21, 029-22, PI: Q. Yu)with the Institut de Radioastronomie Milimetrique (IRAM)30 m telescope on Pico Veleta, we performed CO observations for 29 galaxies in the galaxy pair sample between 2022 March and 2022 July. For each target, the 12 CO(1−0)and 12 CO(2−1) lines were observed simultaneously, using the dual polarization receiver EMIR in combination with the autocorrelator fast Fourier transform spectrometers at a frequency resolution of Figure 1. The left panel shows the distributions of redshift for the galaxy pair and the control sample. The right panel shows the distributions of stellar mass for the galaxy pair and the control sample. Figure 2. Global SFR as a function of stellar mass. The blue circles represent galaxy pairs selected from the MaNGA survey, while the gray squares are isolated galaxies from the control sample. From top to bottom, the three dashed lines correspond to log(sSFR yr −1 )=−9.5, −10.5, and −11.5. 5 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. 0.195 MHz (∼0.5 km s −1 at CO(1−0)) and with the autocorrelator WILMA with a frequency resolution of 2 MHz (∼5kms −1 at CO(1−0)). The beam sizes are ∼22″and ∼11″ for the CO(1−0)and CO(2−1)observations, respectively. We used the wobbler-switching mode to observe each source with a wobbler throw ranging between 90″and 110″in the azimuthal direction. The wobbler throw was individually chosen to mitigate potential contamination from the companion galaxy. We divided the observations of paired galaxies into different groups based on their redshifts, ensuring that both the CO(1−0)and CO(2−1)lines can be covered within the bandwidth of the receiver for each source. In our observing strategy, we continued observing each source until it achieved a detection with S/N5 or until an rms of <2mK(* TA)was achieved for a velocity resolution of ∼20 km s −1 . The data were reduced using the CLASS software in the GILDAS package 11 (Gildas 2013). We initially inspected the spectra in individual scans and discarded low-quality scans with severe baseline issues before standard calibration. The baseline was subtracted with a constant or a linear function for each scan. Subsequently, we averaged and rebinned the spectra to achieve a velocity resolution of ∼20 km s −1 . The final spectra were converted to the main beam temperature scale using the equation () * =´TFBT mb eff eff A, where F eff and B eff represent the IRAM forward efficiency and the beam efficiency, respectively. For 115 GHz (230 GHz), the IRAM 30 m telescope has the F eff of 0.95 (0.91)and the B eff of 0.77 (0.58). In the subsequent analysis, we obtained the flux of the spectra by applying the T mb -to-flux conversion factor of the IRAM 30 m telescope (5JyK −1 ). We visually determined the line widths at zero level (ΔV)and derived the velocityintegrated flux (S CO )for each spectrum. Given that the CO(1−0)and CO(2−1)lines were observed simultaneously, we constrained the line widths between the two transitions based on detected lines with higher S/N. 2.3.3. MaNGA-ARO Survey of Targets Data The MaNGA-ARO Survey of Targets (MASCOT; Wylezalek et al. 2022)is a CO(1−0)follow-up survey of MaNGA galaxies using the 12 m millimeter single-dish telescope at the Arizona Radio Observatory (ARO). Aiming to measure the molecular gas content in MaNGA star-forming galaxies with ()>MMlog 9.5 , the MASCOT survey presents CO(1−0)observations for 187 MaNGA galaxies in its first data release (Wylezalek et al. 2022), with a beam size of ∼55″. After crossmatching with the parent sample described in Section 2.1, we included seven major-merger paired galaxies in our final galaxy pair sample, with CO data from the MASCOT survey. 2.4. Aperture Correction and Molecular Gas Mass Considering the optical sizes of some galaxies are more extended than the telescope beams, single-pointing observations at the center of a galaxy need an aperture correction to derive the CO flux for the entire galaxy. Thus, we applied an aperture correction to all of the measured CO line fluxes following the method of Lisenfeld et al. (2011,2019).We assume an exponential molecular gas disk with a scale length Table 2 CO(2−1)Emission Line Results from JCMT Observations Source Name R.A. Decl. rms S/NI CO(2−1) ΔV CO(2−1) f aper (deg)(deg)(mK)(Kkms −1 )(km s −1 ) (1)(2)(3)(4)(5)(6)(7)(8) 8078-6103 42.41654 −0.06985 2.10 26.4 3.47 ±0.37 415 ±10 1.93 8250-6101 138.75315 42.02439 2.11 39.7 4.94 ±0.51 368 ±10 1.79 8260-6101 182.40876 42.00967 2.35 6.1 1.02 ±0.19 320 ±10 1.69 8450-6102 171.74883 21.14168 2.02 11.2 0.93 ±0.12 174 ±10 1.77 8456-12702 149.96826 45.28310 1.78 5.4 0.43 ±0.09 215 ±10 1.76 8567-6102 119.31545 47.80304 0.75 L<0.28 LL 8606-9102 255.70905 36.70675 1.84 10.4 1.07 ±0.15 324 ±10 1.69 8715-12704 121.17245 50.71853 0.98 L<0.37 LL 8952-6103 204.67418 27.74241 1.95 19.9 2.5 ±0.28 431 ±10 1.85 8982-9102 202.68920 26.52161 1.02 L<0.39 LL 9025-3701 246.41772 29.14761 1.18 L<0.46 LL 9030-3702 241.23417 30.52578 3.08 9.3 1.51 ±0.22 278 ±10 1.66 9093-12703 239.75272 27.98539 1.94 10.2 1.24 ±0.17 395 ±10 1.60 9185-9101 256.21228 34.81733 2.41 27.3 4.96 ±0.53 569 ±10 1.65 9488-9102 126.70413 20.36485 1.52 6.3 0.28 ±0.05 94 ±10 2.14 9498-12704 118.18742 24.29509 0.81 L<0.32 LL 9499-12703 118.42323 26.49270 1.33 21.0 1.80 ±0.20 432 ±10 1.98 9501-12704 129.37073 26.01438 1.62 7.1 0.68 ±0.12 350 ±10 1.56 9503-6104 120.40348 24.43890 1.07 4.6 0.34 ±0.08 229 ±20 1.46 9510-6101 127.85323 27.58001 0.82 L<0.31 LL 9866-12702 243.20452 31.99319 4.02 10.1 2.43 ±0.34 380 ±10 1.99 9882-12705 207.78113 24.01823 1.47 25.7 2.42 ±0.26 434 ±10 1.88 10218-3704 119.16881 16.92011 2.26 34.9 3.94 ±0.41 264 ±10 1.86 Note. The columns are described as follows: (1)The name of our targets. (2)R.A. in degrees. (3)decl. in degrees. (4)rms noise of the spectra at ∼10–40 km s −1 , only nondetected spectra were rebinned to a velocity resolution of ∼40 km s −1 .(5)S/N. (6)Integrated flux in K km s −1 .(7)The CO line width in km s −1 measured at zero level. (8)Aperture correction. 11 http://www.iram.fr/IRAMFR/GILDAS 6 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. of r e , the CO flux can be described as () ( ) ()=-Sr S rrexp , 2 eCO CO,center where S CO,center represents the CO flux in the central position and derived from the measured I CO ,r e is the CO scale length. Lisenfeld et al. (2011)have found the CO scale length well correlated to the optical radius at the 25 mag isophote, r 25 , and it can be derived as r e =0.2 ×r 25 based on different CO observations of local spiral galaxies (Nishiyama et al. 2001; Regan et al. 2001; Leroy et al. 2008). Therefore, we collected the r 25 (see Table 1)measured in the rband from the NASA/ IPAC Extragalactic Database (NED)and calculated the r e for each source in the pair sample. Adopting the derived r e and inclination angle (i)from NED, we performed a 2D integration of the exponential disk following Equation (2)to compute the total CO flux from the entire disk (for details, see Lisenfeld et al. 2011). After deriving the central CO flux (S CO,center )and the total CO flux (S CO,tot ), the aperture correction factor (f aper ) is defined as () = = fSS MM ,3 aper CO,tot CO,center H H ,center 22 where MH 2 and MH ,center 2are the molecular masses of the entire galaxy and the central pointing, respectively. The molecular gas mass is derived from the CO(1−0)luminosity as [] ()a=¢ MM L,4 HCO CO 2 where α CO is the CO-to-H 2 conversion factor. Considering the paired galaxies in our sample are mostly massive (()>MMlog 9.7 )and do not exhibit extreme starbursts, we adopt the Galactic value with α CO =3.2 M ☉ /(Kkms −1 pc −2 ) (Bolatto et al. 2013). For the CO flux from the MASCOT survey, we performed the same aperture correction and adopted the Galactic value of α CO . For isolated galaxies from xCOLD GASS, we adopted the same α CO and recalculated the estimated H 2 mass. The ¢ L CO is calculated following Solomon et al. (1997) as [] ()()n ¢=´ + --- LSDzK km s pc 3.25 10 1 , 5 LCO 12 7 CO,tot rest 22 1 where S CO,tot is the total flux of CO(1−0)line in Jy km s −1 , ν rest represents the rest frequency of the spectral line in GHz, D L is the luminosity distance in megaparsecs, and zis the redshift of the galaxy. 2.5. Atomic Gas We use the H Idata for 39 galaxy pairs from the pair sample taken from Yu et al. (2022). For the H Idata used in this work, six sources were observed by our PI programs with the Fivehundred-meter Aperture Spherical radio Telescope (FAST). The remaining data are extracted from the HI-MaNGA survey. The HI-MaNGA survey is designed as an H Ifollow-up project for the SDSS-VI MaNGA survey, which mainly uses the Robert C. Byrd Green Bank Telescope to perform H I observations in combination with data crossmatched from the Arecibo Legacy Fast ALFA survey (Haynes et al. 2018). The HI-MaNGA survey focuses on galaxies with a stellar mass in the range of ()<<MM8.5 log 11.2 and a redshift of z<0.05 (Masters et al. 2019; Stark et al. 2021). Due to the relatively large beam sizes, the H Iobservations of paired galaxies often suffered from the source blending problem (Zuo et al. 2018; Yu et al. 2022). Therefore, we adopt the same method of Yu et al. (2022)and consider a galaxy pair as a single system when calculating H I-related properties. For the S+S pairs, the M å and SFR are sums of two subcomponents, and then we divide these values and the H Imass by two to obtain the typical value for one of the member galaxies. For the S+E pairs, we follow the approach of previous studies (Zuo et al. 2018; Lisenfeld et al. 2019; Yu et al. 2022)and assume the H Icontent is mostly contributed by the spiral component, so only the spiral component is considered for M å and SFR. 3. Results 3.1. Molecular Gas Properties and SFR We detected 17 CO(2−1)emission lines out of 23 paired galaxies from JCMT observations. The detailed results of JCMT observations are listed in Table 2, and the profiles of the emission line are shown in Figure A1 in the appendix. In our IRAM 30 m observations, we observed 29 paired galaxies and all sources have detections of CO(1−0)and CO(2−1)lines, including a couple of tentative detections (S/N<5). The results of IRAM observations are listed in Table 3, and the CO spectra are presented in appendix (Figures A2 and A3). The molecular gas mass is estimated from the CO luminosity using Equations (4)and (5). Given that JCMT observations only cover the CO(2−1)line, we adopt a CO(2−1)-to-CO(1−0) ratio of 0.8 when calculating the CO luminosity (Leroy et al. 2009). Considering JCMT observations contain minor-merger galaxy pairs that are beyond the scope of this paper, we performed the following analysis using major-merger galaxy pairs as described in Section 2.1. Therefore, we only consider 43 major-merger paired galaxies that have CO data from JCMT observations, IRAM 30 m observations, and the MASCOT survey. For the tentative detections with S/N<5, we treat these measurements as upper limits in the statistical analysis, adopting the Kaplan–Meier estimator (Kaplan & Meier 1958; Feigelson & Nelson 1985)to calculate the mean values and errors for the corresponding physical properties. After deriving the molecular mass, we compared the molecular gas fraction (fH 2 )and star formation efficiency (SFE)between paired galaxies and isolated galaxies. The molecular gas fraction fH 2 is defined as ()=fM M.6 H H 2 2  Despite the definition of ( ) =+fMMM HHH 222 used in some studies, here we adopt the definition frequently adopted by previous observational studies (Violino et al. 2018; Lisenfeld et al. 2019)for comparison. In Figure 3, we compare the distributions of galaxy properties in paired galaxies and control galaxies. The blue histogram represents the distribution of the pair sample, while the open histogram represents the control sample. As shown in Figure 3(a), we compare the distributions of fH 2 for galaxies in pairs and controls. The mean molecular gas fraction of the pair sample in logarithm is log fH 2 =−0.89 ±0.05. In contrast, the mean molecular gas fraction of the control sample (log fH 2 =−1.22 ±0.02)is lower by a factor of ∼2 compared to the pair sample. We conduct the Anderson–Darling (AD)twosample test to check any discrepancy between distributions. The AD test is more sensitive than the classic Kolmogorov– 7 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Smirnov (K-S)test to test whether the two distributions are drawn from the same parent distribution (Anderson & Darling 1952; Feigelson & Babu 2012). We use the scipy. stats.anderson_ksamp to perform the AD two-sample test, which calculates the truncated p-value in the range between 0.001 and 0.25. In the following analysis, we adopt pvalues of <0.001 (significant)and <0.01 (moderate)as significance levels to reject the null hypothesis that the two samples are drawn from the same parent population. Therefore, the AD test suggests the distributions of fH 2 for galaxies in pairs and controls are different (p-value <0.001). However, multiple factors may contribute to the difference in molecular gas fraction. For example, more galaxies with lower stellar mass in the sample can bias the average fH 2 toward a higher value, since fH 2 is tightly anticorrelated with M å for star-forming galaxies (Boselli et al. 2014; Cicone et al. 2017; Saintonge et al. 2017). Therefore, in Section 3.3, we conduct a galaxy-by-galaxy matching between the galaxy pair sample and the control sample to minimize bias. As shown in Figure 3(b),thespecific star formation rate (sSFR) of the pair sample is distributed at the higher region relative to the control sample. The average sSFR of the pair sample (log (sSFR yr −1 )=−9.88 ±0.08)is significantly higher than that of the control sample (log (sSFR yr −1 )=−10.11 ±0.03).TheAD test suggests the distributions of sSFR in the pair sample and the control sample are distinct at the significance level of p-value <0.001. The SFE is defined as [] ()= - M SFE yr SFR .7 1 H2 In Figure 3(c), we present the distributions of SFE in the pair sample and the control sample. The SFE of paired galaxies distributes from −9.86 to −8.21 yr −1 , with the mean ()=-  - log SFEyr 8.99 0.06 1. In contrast, the SFE of isolated galaxies distributes from −9.90 to −7.90 yr −1 , with the mean ()=-  - log SFEyr 8.90 0.0 3 1. An AD test returns ap-value =0.24, suggesting the distributions of SFE in paired galaxies and isolated galaxies are likely drawn from the same distribution. 3.2. Molecular-to-atomic Gas Mass Ratio and Total Gas Mass Utilizing the combination of molecular gas properties and HI data from previous observations (Stark et al. 2021; Yu et al. 2022), we further derived and analyzed the molecular-toatomic gas mass ratio (MH 2 /M H I ), the total gas mass fraction (f gas ), and the SFE of the total gas (SFE gas ). The total gas mass Table 3 CO(1−0)and CO(2−1)Emission Line Results from IRAM 30 m Observations MaNGA ID rms 10 S/N 10 I CO(1−0) ΔV CO(1−0) f aper rms 21 S/N 21 I CO(2−1) ΔV CO(2−1) plate-ifu (mK)(mK)(Kkms −1 )(km s −1 )(mK)(mK)(Kkms −1 )(km s −1 ) (1)(2)(3)(4)(5)(6)(7)(8)(9)(10) 8078-6104 1.13 14.3 1.14 ±0.39 223 ±21 1.52 3.99 11.2 2.05 ±0.27 189 ±10 8078-6104B 2.01 9.6 1.67 ±0.24 335 ±21 1.67 4.29 21.7 5.68 ±0.62 334 ±10 8082-12703 3.76 21.4 8.07 ±0.89 471 ±21 1.73 9.98 27.0 16.73 ±1.78 363 ±10 8085-12704 1.83 4.8 1.43 ±0.34 611 ±42 1.69 3.43 8.1 2.40 ±0.38 347 ±21 8153-12701 0.72 4.2 0.33 ±0.08 265 ±42 1.65 1.74 6.2 0.91 ±0.17 330 ±21 8338-6102 1.10 5.8 0.36 ±0.07 149 ±21 1.68 2.11 8.2 1.29 ±0.20 257 ±21 8547-12702 1.54 5.5 0.80 ±0.17 403 ±21 1.64 3.43 9.2 3.72 ±0.55 626 ±21 8552-12702 1.23 5.1 0.97 ±0.21 561 ±42 1.55 2.63 7.0 1.43 ±0.25 280 ±21 8588-12702 1.26 8.5 0.65 ±0.10 174 ±21 1.91 6.06 4.1 1.69 ±0.45 217 ±21 8656-1901 0.80 5.1 0.81 ±0.18 937 ±42 1.67 2.18 7.7 1.68 ±0.27 467 ±21 8656-3703 0.61 5.1 0.30 ±0.07 212 ±42 1.63 2.27 8.4 1.52 ±0.24 298 ±21 8657-12704 0.65 5.6 0.31 ±0.06 169 ±42 1.74 3.02 3.3 1.02 ±0.33 254 ±42 8728-12701 3.92 11.6 1.77 ±0.23 141 ±10 2.19 7.03 6.7 3.24 ±0.58 216 ±21 8981-6101 1.75 12.7 3.02 ±0.38 836 ±21 1.94 3.93 9.9 4.66 ±0.66 656 ±21 8981-6101B 1.62 10.0 0.89 ±0.13 274 ±10 1.75 3.27 13.1 1.98 ±0.25 196 ±10 9027-12702 2.55 11.2 1.56 ±0.21 279 ±10 1.83 4.70 7.4 2.77 ±0.47 299 ±21 9027-9101 2.09 6.3 1.01 ±0.19 278 ±21 1.59 3.41 15.8 4.60 ±0.54 341 ±21 9032-3704 3.42 12.6 2.79 ±0.36 366 ±10 1.56 13.50 10.2 8.47 ±1.19 331 ±10 9050-9101 3.43 19.3 3.74 ±0.42 294 ±10 1.82 6.00 32.9 12.34 ±1.29 359 ±10 9050-9101B 2.95 16.1 2.26 ±0.27 207 ±10 1.67 5.86 22.5 6.57 ±0.72 228 ±10 9093-12701 2.63 13.9 2.58 ±0.32 442 ±10 1.58 5.39 5.4 2.99 ±0.63 476 ±21 9094-12703 2.33 13.1 3.16 ±0.40 475 ±21 1.60 8.85 10.5 10.07 ±1.39 522 ±21 9094-12705 1.01 6.1 0.79 ±0.15 359 ±42 1.54 2.62 6.5 1.37 ±0.25 289 ±21 9185-9101 6.00 16.5 8.00 ±0.94 572 ±10 1.62 10.80 34.3 26.7 ±2.78 456 ±10 9507-12701 2.48 12.2 2.57 ±0.33 341 ±21 2.14 5.19 8.3 3.40 ±0.53 297 ±21 9509-6103 2.35 19.6 2.49 ±0.28 270 ±10 1.75 5.13 19.5 4.56 ±0.51 193 ±10 9881-6102 4.27 23.5 5.21 ±0.57 249 ±10 2.32 11.75 16.5 10.02 ±1.17 248 ±10 9889-1902 1.69 8.1 1.34 ±0.21 452 ±21 1.58 2.91 17.8 5.30 ±0.61 492 ±21 9889-1902B 4.32 15.3 6.05 ±0.72 388 ±21 1.93 9.52 8.0 6.72 ±1.08 364 ±21 Note. The columns are described as follows: (1)Source name. (2)rms noise of CO(1−0)line at the velocity resolution of ∼10−42 km s −1 .(3)S/N achieved in the CO(1−0)line. (4)Integrated CO(1−0)line intensity measured after rebinning the spectra to velocity resolution of ∼10−42 km s −1 .(5)Zero-level line width of CO(1−0). (6)Aperture correction. (7)rms noise of CO(2−1)line at the velocity resolution of ∼10−42 km s −1 .(8)S/NachievedintheCO(2−1)line. (9)Integrated CO(2−1)line intensity measured after rebinning the spectra to a velocity resolution of ∼10−42 km s −1 .(10)Zero-level line width of CO(2−1). 8 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Figure 3. The upper panels show distributions of galaxy properties of the galaxy pair sample and the control sample, while the lower panels present the offset of these properties relative to the controls. The paired galaxies and control galaxies are plotted as filled and open histograms, respectively. The dashed lines represent the mean value of distributions for paired galaxies. (a)Distributions of fH 2 .(b)Distributions of sSFR. (c)distributions of SFE. (d)Distributions of DfH 2 .(e)Distributions of ΔSFR. (f)Distributions of ΔSFE. Figure 4. The upper panels show distributions of galaxy properties of the galaxy pair sample and the control sample, while the lower panels present the offset of these properties relative to the controls. The paired galaxies and control galaxies are plotted as filled and open histograms, respectively. The dashed lines represent the mean value of distributions for paired galaxies. (a)Distributions of the total gas fraction f gas .(b)Distributions of molecular-to-atomic gas mass ratio M H2/M H I .(c) Distributions of the SFE of the total gas SFE gas .(d)Distributions of Δf gas .(e)Distributions of DMH2/M H I .(f)Distributions of ΔSFE gas . 9 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. EAO. The Nāmakanui instrument is a backup receiver for the GLT. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. This work is based on observations carried out under project numbers E01-21 and 029-22 with the IRAM 30 m telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany), and IGN (Spain). We acknowledge the staff at IRAM for their help during the observations. SDSS-IV 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, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, 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, Observatário 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. Facilities: JCMT, IRAM:30m. Software: Starlink (Currie et al. 2014), GILDAS (Gildas 2013), Astropy (Astropy Collaboration et al. 2013), SciPy (Virtanen et al. 2020). Appendix CO Spectra We present the calibrated and rebinned CO spectra from JCMT observations (Figure A1)and IRAM 30 m observations (Figures A2 and A3)as follows. The data can be obtained from the corresponding author upon reasonable request. 16 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Figure A1. CO(2−1)spectra of the detected galaxies from JCMT observations. Most of the spectra were rebinned to a velocity resolution of ∼10 km s −1 , and some spectra were rebinned to a velocity resolution of ∼20 km s −1 to achieve detections. The velocity of each spectrum is Doppler corrected and converted to the barycentric frame, and the zero-point is set based on the optical spectroscopy redshift of the galaxy. 17 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Figure A2. CO(1−0)spectra of the detected galaxies from IRAM 30 m observations. Most of the spectra were rebinned to a velocity resolution of ∼20 km s −1 , and some spectra were rebinned to a velocity resolution of ∼40 km s −1 to achieve detections. The velocity of each spectrum is Doppler corrected and converted to the barycentric frame, and the zero-point is set based on the optical spectroscopy redshift of the galaxy. 18 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Figure A2. (Continued.) 19 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Figure A3. CO(2−1)spectra of the detected galaxies from IRAM 30 m observations. Most of the spectra were rebinned to a velocity resolution of ∼20 km s −1 , and some spectra were rebinned to a velocity resolution of ∼40 km s −1 to achieve detections. The velocity of each spectrum is Doppler corrected and converted to the barycentric frame, and the zero-point is set based on the optical spectroscopy redshift of the galaxy. 20 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. Figure A3. (Continued.) 21 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al. ORCID iDs Qingzheng Yu (余清正)https://orcid.org/0000-0003-32303981 Taotao Fang (方陶陶)https://orcid.org/0000-0002-28533808 Cong Kevin Xu (徐聪)https://orcid.org/0000-0002-15886700 Shuai Feng (冯帅)https://orcid.org/0000-0002-9767-9237 Siyi Feng (冯思轶)https://orcid.org/0000-0002-4707-8409 Yu Gao (高煜)https://orcid.org/0000-0003-0007-2197 Xue-Jian Jiang (蒋雪健)https://orcid.org/0000-0002-88994673 Ute Lisenfeld https://orcid.org/0000-0002-9471-5423 References Anderson, T. W., & Darling, D. A. 1952, Ann. Math. Stat., 23, 193 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33 Barnes, J. E., & Hernquist, L. 1992, ARA&A,30, 705 Barnes, J. E., & Hernquist, L. 1996, ApJ,471, 115 Barnes, J. E., & Hernquist, L. E. 1991, ApJL,370, L65 Barrera-Ballesteros, J. K., García-Lorenzo, B., Falcón-Barroso, J., et al. 2015, A&A,582, A21 Barton, E. J., Geller, M. J., & Kenyon, S. J. 2000, ApJ,530, 660 Bloom, J. V., Croom, S. M., Bryant, J. J., et al. 2018, MNRAS,476, 2339 Bolatto, A. D., Wolfire, M., & Leroy, A. K. 2013, ARA&A,51, 207 Boselli, A., Cortese, L., Boquien, M., et al. 2014, A&A,564, A66 Braine, J., & Combes, F. 1993, A&A, 269, 7 Bundy, K., Bershady, M. A., Law, D. R., et al. 2015, ApJ,798, 7 Casasola, V., Bettoni, D., & Galletta, G. 2004, A&A,422, 941 Cicone, C., Bothwell, M., Wagg, J., et al. 2017, A&A,604, A53 Combes, F., Prugniel, P., Rampazzo, R., & Sulentic, J. W. 1994, A&A, 281, 725 Cox, T. J., Jonsson, P., Somerville, R. S., et al. 2008, MNRAS,384, 386 Croom, S. M., Lawrence, J. S., Bland-Hawthorn, J., et al. 2012, MNRAS, 421, 872 Currie, M. J., Berry, D. S., Jenness, T., et al. 2014, in ASP Conf. Ser. 485, Astronomical Data Analysis Software and Systems XXIII, ed. N. Manset & P. Forshay (San Francisco, CA: ASP),391 Di Matteo, P., Combes, F., Melchior, A. L., & Semelin, B. 2007, A&A, 468, 61 Ellison, S. L., Catinella, B., & Cortese, L. 2018, MNRAS,478, 3447 Ellison, S. L., Mendel, J. T., Scudder, J. M., et al. 2013, MNRAS,430, 3128 Ellison, S. L., Patton, D. R., Mendel, J. T., & Scudder, J. M. 2011, MNRAS, 418, 2043 Ellison, S. L., Patton, D. R., Simard, L., & McConnachie, A. W. 2008, AJ, 135, 1877 Elmegreen, B. G. 1993, ApJ,411, 170 Feigelson, E. D., & Babu, G. J. 2012, Modern Statistical Methods for Astronomy (Cambridge: Cambridge Univ. Press) Feigelson, E. D., & Nelson, P. I. 1985, ApJ,293, 192 Feng, S., Shen, S.-Y., Yuan, F.-T., et al. 2019, ApJ,880, 114 Feng, S., Shen, S.-Y., Yuan, F.-T., et al. 2020, ApJL,892, L20 Feng, S., Shen, S.-Y., Yuan, F.-T., et al. 2022, ApJS,262, 6 Gao, Y., & Solomon, P. M. 1999, ApJL,512, L99 Gildas, T., 2013 GILDAS: Grenoble Image and Line Data Analysis Software, Astrophysics Source Code Library, ascl:1305.010 Goulding, A. D., Greene, J. E., Bezanson, R., et al. 2018, PASJ,70, S37 Haan, S., Surace, J. A., Armus, L., et al. 2011, AJ,141, 100 Hani, M. H., Sparre, M., Ellison, S. L., et al. 2018, MNRAS,475, 1160 Haynes, M. P., Giovanelli, R., Kent, B. R., et al. 2018, ApJ,861, 49 Hibbard, J. E., & van Gorkom, J. H. 1996, AJ,111, 655 Hopkins, P. F., Cox, T. J., Hernquist, L., et al. 2013, MNRAS,430, 1901 Hopkins, P. F., Cox, T. J., Younger, J. D., & Hernquist, L. 2009, ApJ, 691, 1168 Hou, M., Li, Z., Liu, X., et al. 2023, ApJ,943, 50 Hung, C.-L., Hayward, C. C., Smith, H. A., et al. 2016, ApJ,816, 99 Iono, D., Wilson, C. D., Yun, M. S., et al. 2009, ApJ,695, 1537 Iono, D., Yun, M. S., & Mihos, J. C. 2004, ApJ,616, 199 Kaneko, H., Kuno, N., Iono, D., et al. 2017, PASJ,69, 66 Kaplan, E. L., & Meier, P. 1958, JASA, 53, 457 Keel, W. C. 1993, AJ,106, 1771 Kennicutt, R. C. J., & Keel, W. C. 1984, ApJL,279, L5 Kennicutt, R. C. J., Keel, W. C., van der Hulst, J. M., et al. 1987, AJ,93, 1011 Kewley, L. J., Geller, M. J., & Barton, E. J. 2006, AJ,131, 2004 Leroy, A. K., Walter, F., Bigiel, F., et al. 2009, AJ,137, 4670 Leroy, A. K., Walter, F., Brinks, E., et al. 2008, AJ,136, 2782 Li, C., Kauffmann, G., Heckman, T. M., et al. 2008, MNRAS,385, 1903 Li, Y. A., Ho, L. C., & Shangguan, J. 2023, ApJ,953, 91 Lisenfeld, U., Espada, D., Verdes-Montenegro, L., et al. 2011, A&A, 534, A102 Lisenfeld, U., Xu, C. K., Gao, Y., et al. 2019, A&A,627, A107 Masters, K. L., Stark, D. V., Pace, Z. J., et al. 2019, MNRAS,488, 3396 McElroy, R., Bottrell, C., Hani, M. H., et al. 2022, MNRAS,515, 3406 Michiyama, T., Iono, D., Nakanishi, K., et al. 2016, PASJ,68, 96 Mihos, J. C., & Hernquist, L. 1996, ApJ,464, 641 Mirabel, I. F., & Sanders, D. B. 1989, ApJL,340, L53 Moreno, J., Torrey, P., Ellison, S. L., et al. 2015, MNRAS,448, 1107 Moreno, J., Torrey, P., Ellison, S. L., et al. 2019, MNRAS,485, 1320 Nikolic, B., Cullen, H., & Alexander, P. 2004, MNRAS,355, 874 Nishiyama, K., Nakai, N., & Kuno, N. 2001, PASJ,53, 757 Pan, H.-A., Lin, L., Hsieh, B.-C., et al. 2018, ApJ,868, 132 Pan, H.-A., Lin, L., Hsieh, B.-C., et al. 2019, ApJ,881, 119 Patton, D. R., Torrey, P., Ellison, S. L., et al. 2013, MNRAS,433, L59 Regan, M. W., Thornley, M. D., Helfer, T. T., et al. 2001, ApJ,561, 218 Renaud, F., Bournaud, F., Kraljic, K., & Duc, P. A. 2014, MNRAS,442, L33 Rupke, D. S. N., Kewley, L. J., & Chien, L. H. 2010, ApJ,723, 1255 Saintonge, A., Catinella, B., Tacconi, L. J., et al. 2017, ApJS,233, 22 Sánchez, S. F., Kennicutt, R. C., Gil de Paz, A., et al. 2012, A&A,538, A8 Sanders, D. B., & Mirabel, I. F. 1996, ARA&A,34, 749 Satyapal, S., Ellison, S. L., McAlpine, W., et al. 2014, MNRAS,441, 1297 Scoville, N., Murchikova, L., Walter, F., et al. 2017, ApJ,836, 66 Scoville, N. Z., Yun, M. S., & Bryant, P. M. 1997, ApJ,484, 702 Scudder, J. M., Ellison, S. L., Torrey, P., et al. 2012, MNRAS,426, 549 Shangguan, J., Ho, L. C., Li, R., et al. 2019, ApJ,870, 104 Smith, B. J., Campbell, K., Struck, C., et al. 2018, AJ,155, 81 Soares, D. S. L. 2007, AJ,134, 71 Sofue, Y., Wakamatsu, K.-I., Taniguchi, Y., & Nakai, N. 1993, PASJ, 45, 43 Solomon, P. M., Downes, D., Radford, S. J. E., & Barrett, J. W. 1997, ApJ, 478, 144 Solomon, P. M., & Sage, L. J. 1988, ApJ,334, 613 Sparre, M., & Springel, V. 2016, MNRAS,462, 2418 Stark, D. V., Masters, K. L., Avila-Reese, V., et al. 2021, MNRAS,503, 1345 Thorp, M. D., Ellison, S. L., Pan, H.-A., et al. 2022, MNRAS,516, 1462 Thorp, M. D., Ellison, S. L., Simard, L., et al. 2019, MNRAS,482, L55 Toomre, A. 1977, in Evolution of Galaxies and Stellar Populations, ed. B. M. Tinsley & R. B. Larson (New Haven, CT: Yale Univ. Observatory),401 Toomre, A., & Toomre, J. 1972, ApJ,178, 623 Torrey, P., Cox, T. J., Kewley, L., & Hernquist, L. 2012, ApJ,746, 108 Ueda, J., Iono, D., Yun, M. S., et al. 2014, ApJS,214, 1 Veilleux, S., Kim, D. C., & Sanders, D. B. 2002, ApJS,143, 315 Violino, G., Ellison, S. L., Sargent, M., et al. 2018, MNRAS,476, 2591 Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, NatMe,17, 261 Wilson, C. D., Petitpas, G. R., Iono, D., et al. 2008, ApJS,178, 189 Wylezalek, D., Cicone, C., Belfiore, F., et al. 2022, MNRAS,510, 3119 Xu, C., & Sulentic, J. W. 1991, ApJ,374, 407 Xu, C. K., Domingue, D., Cheng, Y.-W., et al. 2010, ApJ,713, 330 Xu, C. K., Lisenfeld, U., Gao, Y., & Renaud, F. 2021, ApJ,918, 55 Yamashita, T., Komugi, S., Matsuhara, H., et al. 2017, ApJ,844, 96 Yu, Q., Fang, T., Feng, S., et al. 2022, ApJ,934, 114 Zhang, H., Fang, T., Zaritsky, D., et al. 2020, ApJL,893, L3 Zuo, P., Xu, C. K., Yun, M. S., et al. 2018, ApJS,237, 2 22 The Astrophysical Journal Supplement Series, 273:2 (22pp), 2024 July Yu et al.