Properties of giant molecular clouds in the strongly barred galaxy NGC1300
MMNRAS , 1–17 (2019) Preprint 24 February 2020 Compiled using MNRAS L A TEX style file v3.0
Properties of giant molecular clouds in the strongly barredgalaxy NGC 1300
Fumiya Maeda, (cid:63) Kouji Ohta, Yusuke Fujimoto, , and Asao Habe Department of Astronomy, Kyoto University, Kitashirakawa-Oiwake-Cho, Sakyo-ku, Kyoto, Kyoto 606-8502, Japan Research School of Astronomy & Astrophysics, Australian National University, Canberra, Australian Capital Territory 2611, Australia Department of Terrestrial Magnetism, Carnegie Institution for Science, 5241 Broad Branch Road, NW, Washington, DC 20015, USA Graduate School of Science, Hokkaido University, Kita 10 Nishi 8, Kita-ku, Sapporo, Hokkaido 060-0810, Japan
Accepted XXX. Received YYY; in original form ZZZ
ABSTRACT
Star formation activity depends on galactic-scale environments. To understand thevariations in star formation activity, comparing the properties of giant molecularclouds (GMCs) among environments with different star formation efficiency (SFE)is necessary. We thus focus on a strongly barred galaxy to investigate the impact ofthe galactic environment on the GMCs properties, because the SFE is clearly lowerin bar regions than in arm regions. In this paper, we present the CO( − ) observa-tions toward the western bar, arm and bar-end regions of the strongly barred galaxyNGC 1300 with ALMA 12-m array at a high angular resolution of ∼
40 pc. We detectedGMCs associated with the dark lanes not only in the arm and bar-end regions butalso in the bar region, where massive star formation is not seen. Using the CPROPSalgorithm, we identified and characterized 233 GMCs across the observed regions.Based on the Kolmogorov-Smirnov test, we find that there is virtually no significantvariations in GMC properties (e.g., radius, velocity dispersion, molecular gas mass,and virial parameter) among the bar, arm and bar-end region. These results suggestthat systematic differences in the physical properties of the GMCs are not the causefor SFE differences with environments, and that there should be other mechanismswhich control the SFE of the GMCs such as fast cloud-cloud collisions in NGC 1300.
Key words:
ISM: clouds – ISM: structure – galaxies: star formation – galaxies:structure
It is important to investigate the relation between star for-mation rate (SFR) and gas density in the context of galaxyevolution. This relation describes how efficiently galaxiesconvert their gases into stars. Previous studies on the MilkyWay and nearby disc galaxies show that there is a tight cor-relation between the SFR and the surface density of molec-ular gas; Σ SFR ∝ Σ N H , where the index N is between 1 and2 (e.g., Kennicutt 1998; Bigiel et al. 2008; Schruba et al.2011). However, variations in the relation have been found;star formation activity changes among galactic-scale envi-ronments, and the gas surface density is not the only factorcontrolling the star formation. Momose et al. (2010) mea-sured the star formation efficiency (SFE = Σ SFR / Σ H ) in abarred galaxy of NGC 4303 at a spatial resolution of 500 pcand reported that the SFEs in the arm regions are about twotimes higher than those in the bar regions (see also Yajima (cid:63) E-mail: [email protected] et al. 2019). Such variations of the SFE with environmentsare reported for other nearby galaxies and the Milky Way(e.g., Watanabe et al. 2011; Leroy et al. 2013; Longmoreet al. 2013; Hirota et al. 2014; Usero et al. 2015; Gallagheret al. 2018), but physical mechanism which controls the SFEwithin galaxies is still unclear.To understand the variation of the SFE, it is importantto unveil the properties of giant molecular clouds (GMCs)where star formation occurs. In particular, comparing theGMC properties among environments with different SFEs isnecessary. In the Milky Way, GMCs’ mass, size, and veloc-ity dispersion are typically ∼ − M (cid:12) , ∼ − pc, and −
10 km s − , respectively (e.g., Solomon et al. 1987; Heyeret al. 2009). In recent years, thanks to high sensitive inter-ferometers, extragalactic GMCs can be observed at a highangular resolution of 20 ∼
50 pc; e.g., M51 (Colombo et al.2014), M83 (Hirota et al. 2018), PHANGS survey (A. K.Leroy et al. 2019, in preparation). For example, Hirota et al.(2018) investigated GMC properties in an intermediate-typebarred galaxy of M83 where the SFE in the bar regions is © a r X i v : . [ a s t r o - ph . GA ] F e b F. Maeda et al. about two times smaller than that in the arm regions. Theyfound the virial parameter, which is a measure for gravi-tational binding of GMCs, in the bar ( ∼ ∼ ii regions, while inthe arm regions H ii regions are associated with dust lanes.In this study, therefore, we focus on a nearby prototypestrongly barred galaxy of NGC 1300 (Fig. 1). Maeda et al.(2018) carried out CO( − ) observations toward the barand arm region of NGC 1300 with a single dish telescopeof Nobeyama 45-m telescope. They find that the Σ H inthe bar region is comparable to that in the arm region( Σ H ∼ M (cid:12) pc − ), indicating the star formation activ-ity in the bar region is clearly suppressed.In this paper, we report CO( − ) observations towardthe western bar, arm, and bar-end regions in NGC 1300 at ahigh angular resolution of ∼
40 pc with Atacama Large Mil-limeter/submillimeter Array (ALMA). Our main goals areto measure the properties of GMCs and investigate whetherthere are differences in the properties with environments. Inaddition, we compare the properties of GMCs in NGC 1300with those in a normal spiral galaxy. As pointed out byHughes et al. (2013), for comparison with different datacubes, it is essential to match the spatial and spectral res-olution and line sensitivity to minimize observational bias.In this study, we compare the properties of GMCs in spiralarms of proto-type spiral galaxy of M51 by Colombo et al.(2014, C14) because the spatial resolution and line sensitiv-ity are mostly comparable to those of our observations.This paper is structured as follows: In Section 2, we de-scribe the CO( − ) observations and data reduction. Theresultant CO( − ) distribution is presented in Section 3.In Section 4, we summarize the method used to identifyGMCs. The basic properties of the GMCs and examinationof the variations of GMC physical properties with environ-ments are described in Section 5. In Sections 6 and 7, weexamine scaling relations and mass spectra of the GMCs.In Section 8, we discuss what physical mechanism controlsthe SFE of the GMC. Our conclusions are presented in Sec-tion 9. We discuss the reliability of the measurements of theGMC properties in Appendix A. The catalog of GMCs weidentified is presented in Appendix B. Table 1 summarizesparameters of NGC 1300 adopted throughout this paper. We carried out CO ( − ) line observations of NGC 1300on 2017 December 30 and 2018 January 6, 7, 13, and16 with ALMA (program ID: 2017.1.00248.S, PI = F.Maeda). To cover the regions observed with CO( − ) by Maeda et al. (2018), two pointings were cen-tered at ( RA , Dec ) = ( h m s . , − ◦ (cid:48) (cid:48)(cid:48) . ) and D e c ( J ) Figure 1.
V-band image of NGC 1300 taken with F555W fil-ter on Advanced Camera for Surveys (ACS) of the Hubble SpaceTelescope (HST). We obtained this image from the Hubble LegacyArchive ( https://hla.stsci.edu/ ). Green circles represent fieldof views (FoVs; HPBW = (cid:48)(cid:48) φ ) observed with ALMA (see Sec-tion 2). Table 1.
Adopted parameters of NGC 1300Parameter ValueMorphology ∗ SB(s)bcCenter position (J2000.0) † h m s . − ◦ (cid:48) (cid:48)(cid:48) . Inclination § ◦ . Distance ‡ pc arcsec − ∗ Sandage & Tammann (1981) † The peak of Fig. 1. § England (1989) ‡ We adopted the systemic velocity with corrections forthe Virgo cluster, the Great Attractor, and the Shapleyconcentration of − (Mould et al. 2000) andthe Hubble constant of
73 km s − Mpc − . ( h m s . , − ◦ (cid:48) (cid:48)(cid:48) . ) in J2000 as shown with thegreen circles in Fig. 1. The ALMA primary beam for the12-m array is 54 (cid:48)(cid:48) at HPBW.The ALMA observations were taken during five sepa-rated periods with seven execution blocks in total. Table 2summarizes the details of the ALMA observations. The totalon-source time was 5.31 hours (2.65 hours for each position).For all observations, we used about 44 antennas with C43-5 configuration. The projected baseline length ranged from15.1 m to 2.5 km, which corresponds to a maximum recover-able scale (MRS) of ∼ . (cid:48)(cid:48) at 115 GHz. We used the Band 3receiver with the central frequency of 114.664 GHz, channelwidth of 244.1 kHz ( ∼ .
64 km s − ), and bandwidth of 468.8MHz ( ∼ − ). Bandpass and phase were calibratedwith J0423-0120 and J0340-2119, respectively. J0423-0120was also used as a flux calibrator. The T sys and PWV weretypically 100 ∼
150 K and 1 ∼ MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 Table 2.
Observation settingsExecution Block Start time (UTC) On source Number of Baselinetime (min) antennas rangeuid A002 Xc889b6 X21a3.ms 2017/12/30 02:27:10 45.55 46 15.1m − − − − − − − we combined the calibrated visibility data of the 2 point-ing positions using concat task. Then, we imaged the con-catenated visibility using the multiscale CLEAN algorithm(Cornwell 2008), which models an image by a collection ofmultiple Gaussians with different FWHM values. As shownby Rich et al. (2008), this method works well in reducingthe depth of negative emission features (so-called ‘negativebowl’) and recovering extended emission in comparison tothe standard CLEAN algorithm, which models an image bya collection of point sources. We used the task tclean forimaging by adopting the factors of 1, 2, and 5 times the syn-thesized beam as multiscale parameter and Briggs weightingwith robust = 0.5. To ensure consistency with C14 and toachieve a reasonable S/N, we choose a velocity resolution of − and a pixel size of . (cid:48)(cid:48) . The resultant rms noiseis 0.51 mJy beam − , corresponding to 0.36 K. Finally, we ap-plied the primary beam correction on the output restoredimage. In this study, we used the region within the primarybeam correction factor smaller than 2.0. The final data cubehas an angular resolution of . (cid:48)(cid:48) × . (cid:48)(cid:48) . Fig. 2(a) shows a map of the velocity-integrated inten-sity ( I CO ). This map is created from channel maps withinthe LSR velocity range − − clipped at 3 σ ( = .
53 mJy beam − ). The clipping is only for visualizationpurpose. We detected CO( − ) emission from the westernarm to the bar region. Thanks to the high angular resolu-tion of ∼
40 pc , the CO emission is resolved into GMC scale.Fig. 2(b) compares the CO distribution with the map of H ii regions and dust lanes. The gray scale image is the V-bandimage (same as Fig. 1). The magenta contours in Fig. 2(b)show the CO emission with 8.0 K km s − . These contours arecreated from the significant emission identified by CPROPS(so-called ‘island’ regions; see section 4.1).In this study, to compare physical properties of GMCsamong galactic environments, we separated NGC 1300 into Bar , Arm and
Bar-end regions, according to Fig. 2. Bluerectangle is defined as the
Bar region, which covers the darklane and associated spurs that are connected almost perpen-dicularly to the dark lane. The
Arm region is defined as ared polygon. Green polygon that covers the intersection re-gion of the bar and the arm is defined as the
Bar-end region.These color codes will be kept throughout this paper. Thedeprojected area is 5.1, 9.9, and 3.6 kpc in Bar , Arm and
Bar-end , respectively. Here we see the feature of the CO emissions in each re-gion. In
Arm and
Bar-end , the mean I CO within the regionwe detected significant emission is 20 and 32 K km s − in Arm and
Bar-end , respectively. These values correspond to55 and 90 M (cid:12) pc − assuming the standard CO-to-H con-version factor ( α CO ) of . M (cid:12) ( K km s − pc ) − . In theseregions, most of CO emissions are associated with H α emis-sions and coexist with dust lanes. This good correspondenceof the CO emissions to the dust lanes and displacement ofthe H α and CO emissions are often seen in spiral galaxies ata high angular resolution of ∼ pc (e.g., M51; Schinnereret al. 2013). This is naturally interpreted with respect tothe spiral density wave; the gases go into the spiral densitywave, then dense shocked gas regions form in the spiral armswhich result in the formation of GMCs. In the GMCs, starsform, and massive stars born produce H ii regions. The stel-lar feedback (e.g., stellar wind, supernova) would dispersethe molecular gas, thus contributing to the observed offset.In Bar , we detected GMC-like CO emissions on the dustlanes. The mean I CO is 22 K km s − , corresponding to 60 M (cid:12) pc − . Unlike Arm , however, no prominent H ii regionis associated with the CO emissions. This result indicatesthat massive star formation in the bar region of the stronglybarred galaxy is suppressed despite the presence of GMC-like molecular gases. Note that we did not detect significantCO emission above 4 σ of T peak = .
44 K , corresponding to anaverage surface density of 20 M (cid:12) pc − for a single pixel andspectral channel, in part of the dust lane in the bar region. The choice of an algorithm for identifying GMCs can be thelargest source of uncertainty in measuring and comparingGMC properties. In this study, we used 3-D clumps findingalgorithm CPROPS (Rosolowsky & Leroy 2006) which is de-signed to identify GMCs well even at low sensitivities. Thespatial resolution and line sensitivity of our data cube arecomparable to those of the data cube of M51 by Schinnereret al. (2013) which was observed with the Plateau de BureInterferometer and IRAM 30-m telescope at a spatial reso-lution of ∼ pc and a line sensitivity of . K at 5 km s − bin. Using CPROPS, C14 identified GMCs in M51 from thedata cube. Therefore, we adopt almost the same CPROPSparameters adopted in C14 to make a proper comparisonand minimize systematics. MNRAS000
44 K , corresponding to anaverage surface density of 20 M (cid:12) pc − for a single pixel andspectral channel, in part of the dust lane in the bar region. The choice of an algorithm for identifying GMCs can be thelargest source of uncertainty in measuring and comparingGMC properties. In this study, we used 3-D clumps findingalgorithm CPROPS (Rosolowsky & Leroy 2006) which is de-signed to identify GMCs well even at low sensitivities. Thespatial resolution and line sensitivity of our data cube arecomparable to those of the data cube of M51 by Schinnereret al. (2013) which was observed with the Plateau de BureInterferometer and IRAM 30-m telescope at a spatial reso-lution of ∼ pc and a line sensitivity of . K at 5 km s − bin. Using CPROPS, C14 identified GMCs in M51 from thedata cube. Therefore, we adopt almost the same CPROPSparameters adopted in C14 to make a proper comparisonand minimize systematics. MNRAS000 , 1–17 (2019)
F. Maeda et al. D e c ( J ) Bar Arm Bar-end(a) 1 kpc0 20 40 60 80 100K km/s 3h19m36s39s RA (J2000)45.0"-19°24'00.0" D e c ( J ) (b) 1 kpc Figure 2. (a) Velocity integrated intensity CO( − ) image of NGC 1300 generated from the ALMA data cube. We used channelmaps within the velocity range − − clipped at 3 σ (1.53 mJy beam − ). Black dotted circles ( (cid:48)(cid:48) φ ) represent FoV observedwith ALMA. Color solid lines indicate the definition of the environmental mask. Bar , Arm , and
Bar-end are indicated with blue, red,and green lines, respectively. (b) CO contours in magenta are superimposed on the F555W image obtained from HST archive data. COcontours are created from the significant emission identified by CPROPS. The contour level of the CO map is 8.0
K km s − . Here, we provide a brief summary of CPROPS.CPROPS has been fully described by Rosolowsky & Leroy(2006). This algorithm begins with the identification of re-gions with significant emissions within the data cube (calledthe ‘islands’ in CPROPS). CPROPS identifies pixels inwhich the signal is above t σ rms in at least two adjacentvelocity channels, where σ rms is the rms noise of the datacube. Since the data cube is corrected for the primary beampattern, the noise in the map is non-uniform. Thus, we cal-culated a spatially varying of the rms noise in the map bycalling NONUNIFORM flag in CPROPS. CPROPS then growsthese regions to include adjacent pixels in which the signalis above e σ rms . The t and e are the THRESHOLD and
EDGE parameters in CPROPS, respectively. We chose t = . and e = . to ensure consistency with C14.After the identification of the islands, the islands aredivided into individual GMCs using a modified watershedalgorithm. CPROPS searches for local maxima within a boxof three times the beam and channel width, correspondingto ∼
120 pc ×
120 pc ×
15 km s − . All local maxima are re-quired to lie at least 2 σ rms above the merge level with an-other maximum. Only emission that is uniquely associatedwith each local maximum is given an assignment (i.e., onlythat emission which is above all merge levels with other localmaxima).For every pair of local maxima in an island, CPROPScompares the values of the moments at contour levels justabove and just below the merge level. If the moments jump by more than a user-defined fraction, called SIGDISCONT parameter, the two local maxima are categorized as dis-tinct, otherwise they are merged into a single cloud. Thedefault parameter of
SIGDISCONT = . requires 100% ormore fractional change. As described in C14, however, set-ting of SIGDISCONT > . does not work well for the CObright regions where a lot of local maxima are connected ata very low contour level; CPROPS misses objects that vi-sual inspection suggests are GMCs (see Appendix B in C14).In our data cube, some GMCs are missed with SIGDISCONT > . in Bar-End where CO emission is the brightest. Toavoid this failure, we set SIGDISCONT to 0.0 which makes noattempt to merge the two local maxima into a single cloud.In other words, each local maximum is assigned to an indi-vidual independent cloud. The remainder of the emission isconsidered to be in the watershed, and CPROPS does notassign it to any cloud.A large number of objects were found whose peak tem-perature is above 4 σ rms but temperature of the adjacentpixels in the velocity axis is lower than 4 σ rms . These ob-jects seem to be GMCs because their size, velocity disper-sion, and luminosity are similar to those in M51 spiral arms.However, they are missed by CPROPS because CPROPSdoes not identify objects which do not contain two consec-utive pixels above 4 σ rms in the velocity axis. Therefore, toidentify such GMCs for which signal above 4 σ rms is detectedin only a single channel, we allowed CPROPS to identify anisland which has pixels above σ rms in only one channel. As MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 we will discuss in Section 5, the possibility that these GMCsare spurious is very low. CPROPS determines the size, velocity width and flux ofGMCs using moment methods. CPROPS corrects for thesensitivity by extrapolating GMC properties to those wewould expect to measure with perfect sensitivity (i.e., 0 K)and the resolution by deconvolution for the beam and chan-nel width. Details of the measurement method of CPROPSare described in Rosolowsky & Leroy (2006).The effective radius of the GMC is defined as R = ( . /√ π ) σ r , where σ r is geometric mean of the secondintensity-weighted moments along the major and minor axis(i.e., rms size) and . /√ π is an empirical factor defined bySolomon et al. (1987). If the extrapolated rms size is smallerthan the beam size of . pc, we set this value as an upperlimit of the rms size. The velocity width, σ v , is computed asthe intensity-weighted second moment of the velocity afterthe deconvolution to correct the velocity resolution ( ∆ V chan ).CPROPS approximates the shape of the channel as a Gaus-sian with an integral area equal to that of the channel width(i.e., ∆ V chan /√ π ). The CO luminosity, L CO , is derived from (cid:18) L CO K km s − pc (cid:19) = (cid:18) F CO K km s − arcsec (cid:19) (cid:18) D pc (cid:19) (cid:16) π × (cid:17) , (1)where F CO is the zeroth moment of the intensity and the D is the distance to NGC 1300 of 20.7 Mpc.The median ratio of the extrapolated (i.e., without de-convolution) radius and velocity dispersion to the directlymeasured (i.e., without deconvolution and extrapolation)are 1.5 and 1.4, respectively. For the CO luminosity, themedian ratio of the extrapolated value to the directly mea-sured value is 2.1. These correction factors are comparableto those of the GMCs in M51 (C14). The molecular gas mass of a GMC, M mol , is converted fromthe CO luminosity by adapting an α CO : (cid:18) M mol M (cid:12) (cid:19) = α CO (cid:18) L CO K km s − pc (cid:19) . (2)We adopt the standard α CO of . M (cid:12) ( K km s − pc ) − toensure consistency with C14. Note that this α CO includes afactor of 1.36 to account for the presence of helium.Assuming a spherical GMC with the power-law densityprofile of ρ ∝ r − n , we calculate the virial mass of a GMC, M vir , from the size and velocity dispersion as M vir = ( − n ) − n R σ v G = (cid:18) R pc (cid:19) (cid:18) σ v km s − (cid:19) [ M (cid:12) ] . (3)We adopt the profile of n = to ensure consistency with pre-vious studies. We assume that magnetic fields and externalpressure are negligible. The average molecular gas surface density, Σ mol , is de-fined as Σ mol = M mol π R . (4)The virial parameter, α vir , is a useful measure of thegravitational binding and is defined as α vir = σ v RGM mol (5)by Bertoldi & McKee (1992). This definition assumes n = ,but the impact of the difference between n = and is onlyabout 10%. GMCs with α vir (cid:46) are typically considered tobe bound. A value of α vir > indicates that the GMC isgravitationally unbound.The scaling coefficient, c , characterizes the scaling be-tween the size and the velocity dispersion of a GMC as c ≡ σ v R . . (6)For a GMC with a vir = , c can be related to the moleculargas surface density as c = ( π G Σ mol / ) . .CPROPS estimates the uncertainty of these GMC prop-erties using a bootstrapping method, and the final uncer-tainty is the standard deviation of the bootstrapped valuesscaled up by the square root of the oversampling rate. Theoversampling rate is equal to the number of pixels per beam,which accounts for the nonindependence of the pixels. C14found that 50 bootstrapping measurements provided a re-liable estimation of the uncertainty, thus we adopted thisnumber. CPROPS identified 233 GMCs in the data cube. 166 of theGMCs have at least two consecutive pixels above 4 σ rms inthe velocity axis direction. The remaining 67 GMCs havepixels above 4 σ rms in only one channel. Fig. 3 shows GMCdistribution in NGC 1300. We detected 34, 119, and 49GMCs in Bar , Arm , and
Bar-end , respectively. 31 GMCsare outside the three regions (i.e., in interarm regions). TheGMC catalog in NGC 1300 is presented in Appendix B.We inspected the CO line profiles from each GMCCPROPS identified visually, and an obvious spurious signalwas not found. To check contamination by spurious sources,we counted the number of local maxima in the data cubescaled by − with the same settings described in Section 4.1.We found no false positives which have two consecutive pix-els above 4 σ rms in the velocity axis direction. For the 166GMCs, therefore, we believe there is no contamination byspurious sources. On the other hand, CPROPS identifiedthree false positives which have pixels above σ rms in onlyone channel. Thus, ∼ ∼ ) GMCs for whichsignal above 4 σ rms is detected in only a single channel areexpected to be spurious.With the adopted parameters for CPROPS, GMCs with T peak > σ rms , which corresponds to ∼ .
44 K , were detected.The mass completeness limit is estimated to be . × M (cid:12) by assuming that a minimum detectable GMC has a size anda velocity width comparable to the beam size and the chan-nel width, respectively, and α CO is . M (cid:12) ( K km s − pc ) − .We find that 154 of these 233 GMCs are resolved by the MNRAS000
44 K , were detected.The mass completeness limit is estimated to be . × M (cid:12) by assuming that a minimum detectable GMC has a size anda velocity width comparable to the beam size and the chan-nel width, respectively, and α CO is . M (cid:12) ( K km s − pc ) − .We find that 154 of these 233 GMCs are resolved by the MNRAS000 , 1–17 (2019)
F. Maeda et al. D e c ( J ) Figure 3.
GMC distribution in NGC 1300 superimposed on thevelocity integrated CO map (gray scale). The GMCs are repre-sented as ellipses with the extrapolated and deconvolved majorand minor axes, oriented according to the measured position an-gle. Colors indicate the environment defined in Fig. 2. R (corrected)[pc])1234 R ( m e a s u r e d ) / R ( c o rr e c t e d ) Figure 4.
Ratio of measured radius to corrected (i.e., with decon-volution and extrapolation) radius for all resolved GMCs againstcorrected radius. Vertical orange line indicates 15 pc. synthesized beam. When the observed size is similar to thebeam size, uncertainties of R are greatly magnified by thedeconvolution process (e.g., Faesi et al. 2018). Fig. 4 showsthe ratio of directly measured radius to the corrected radius(i.e., with extrapolation and deconvolution) as a function ofthe corrected radius. Below 15 pc ( log R = . ), the ratio isoften larger than a factor of 2, or even higher. Further, wefind only 47 % of the GMCs with M mol < . × M (cid:12) areresolved, while 95 % of the GMCs with M mol ≥ . × M (cid:12) are resolved. Therefore, we defined the GMCs with M mol ≥ . × M (cid:12) and R > pc as a resolved sample for the inves-tigation of R , M vir , Σ mol , α vir , and c , and defined the GMCswith M mol > . × M (cid:12) as a mass completed sample forthe investigation of T peak , σ v , and M mol . Fig. 5 shows the distribution of GMC properties. We use abox and whiskers plot as C14 used for M51. In this plot, theends of the box represent the upper and lower quartiles ( Q and Q , respectively). The median value or Q is marked bya vertical line in the box. The upper whisker expands to thelargest data point below Q + . ∆ Q and the lower whiskerexpands to the smallest data point above Q − . ∆ Q , where ∆ Q is the box length or Q − Q . For a Gaussian distribution,the region within the whiskers contains . ( ± . σ ) ofthe population. The data points outside the whiskers areconsidered to be outliers. Except for T peak , σ v , and M mol , weshow a box and whiskers plot for the resolved sample. Theorange lines and bands in Fig. 5 show the median value andthe range from Q to Q of those in M51 spiral arms fromthe catalog of C14. The median value and the range from Q to Q of each physical property are listed in Table 3.We investigated the environmental variation of GMCproperties in NGC 1300 and compared to the GMC proper-ties in M51 spiral arms. We used the two-sided Kolmogorov-Smirnov (K-S) test to statistically evaluate differences inGMC property distributions for different environments inNGC 1300. We used stats.ks_2samp function of python’sScipy package, which calculates p -value based on the ap-proximately formula given by Stephens (1970). To estimatethe uncertainties of the p -values, we made resampling with100 realizations. In one realization, random values of a givenproperty were generated within the bootstrap uncertaintiesCPROPS calculated. The most likely p -value and its uncer-tainty are the median and the median absolute deviation(MAD) of 100 realizations, respectively. Table 4 shows theresults for each GMC physical parameter. Since CPROPSdoes not provide uncertainties of the T peak , we applied rmsnoise of the data cube, 0.36 K as the uncertainty. We alsoshow the p -value for the observed value in parentheses. Fol-lowing the conventional criteria, the two cumulative distri-bution functions are considered to be significantly differentif the p -value is less than 0.01. A p -value within 0.01 to0.05 indicates that the difference is marginally significant.Note that the approximation of p -value is quite good for N N /( N + N ) ≥ , where N and N are the number ofdata points in the first and second distribution, respectively(Stephens 1970). Our sample sufficiently meets this crite-rion, N N /( N + N ) ≥ . Peak temperature (Fig. 5 (a)): The T peak in Bar-end is MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 All Bar Arm Bar-end0510 T p e a k [ K ] (a) Peak temperature All Bar Arm Bar-end051015 v [ k m s ] (b) Velocity dispersion All Bar Arm Bar-end050100 R [ p c ] (c) Radius All Bar Arm Bar-end567 l o g ( M m o l [ M ]) (d) Molecular gas mass All Bar Arm Bar-end567 l o g ( M v i r [ M ]) (e) Virial mass All Bar Arm Bar-end123 l o g ( m o l [ M p c ]) (f) Molecular gas surface density All Bar Arm Bar-end0246 v i r (g) Virial parameter All Bar Arm Bar-end012 c [ k m s p c / ] (h) Scaling coefficient Figure 5.
Box-and-whisker plots for GMC’s (a) peak temperature ( T peak ), (b) velocity dispersion ( σ v ), (c) radius ( R ), (d) moleculargas mass ( M mol ), (e) virial mass ( M vir ), (f) molecular gas surface density ( Σ mol ), (g) virial parameter ( α vir ), and (h) scaling coefficient( c ) in the whole region (gray) and each environment ( Bar : blue,
Arm : red, and
Bar-end : green) of NGC 1300. We used the GMCs with M mol ≥ . × M (cid:12) for T peak , σ v , and M mol and the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc for other properties. The medianvalue is represented as a white horizontal line within each box. Upper and lower edges of each box indicate the upper and lower quartile,respectively ( Q and Q , respectively). The upper whisker expands to the largest data point below Q + . ∆ Q and the lower whiskerexpands to the smallest data point above Q − . ∆ Q . The data points outside the whiskers are considered outliers and shown as opencircles. The orange solid line and bands show the median value and the range from Q to Q of each property of GMCs in M51 spiralarms (C14). Horizontal red dash-dotted lines indicate 1.44 K (= 4 σ ), 2.0 km s − ( = ∆ V chan /√ π ), 15 pc, and . × M (cid:12) . Horizontalblue dash-dotted lines in panel (g) indicate α vir = . and . .MNRAS000
Bar-end : green) of NGC 1300. We used the GMCs with M mol ≥ . × M (cid:12) for T peak , σ v , and M mol and the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc for other properties. The medianvalue is represented as a white horizontal line within each box. Upper and lower edges of each box indicate the upper and lower quartile,respectively ( Q and Q , respectively). The upper whisker expands to the largest data point below Q + . ∆ Q and the lower whiskerexpands to the smallest data point above Q − . ∆ Q . The data points outside the whiskers are considered outliers and shown as opencircles. The orange solid line and bands show the median value and the range from Q to Q of each property of GMCs in M51 spiralarms (C14). Horizontal red dash-dotted lines indicate 1.44 K (= 4 σ ), 2.0 km s − ( = ∆ V chan /√ π ), 15 pc, and . × M (cid:12) . Horizontalblue dash-dotted lines in panel (g) indicate α vir = . and . .MNRAS000 , 1–17 (2019) F. Maeda et al.
Table 3.
GMC properties in the different environments of NGC 1300Envir. Area ∗ T peak † σ v † R ‡ M mol † M vir ‡ Σ mol ‡ α vir ‡ c ‡ ( kpc ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) ) ( M (cid:12) pc − ) ( km s − pc − . )All 37.9 203(104) . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Bar 5.1 28(12) . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Arm 9.9 108(55) . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Bar-end 3.6 43(31) . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . M51 SA (cid:63) . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . ∗ The number of the GMCs with M mol ≥ . × M (cid:12) . In parentheses, we show the number of the GMCswith M mol ≥ . × M (cid:12) and R ≥ pc. † For the GMCs with M mol ≥ . × M (cid:12) . ‡ For the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc. (cid:63) For M51 spiral arms (SA) (C14). We extract GMCs with the same selection criteria as described in Section 5.
Table 4. p -values of the Kolmogorov-Smirnov Test for GMC propertiesProp. Bar vs. Arm Bar vs. Bar-end Arm vs. Bar-end T peak ∗ . ± . ( . ) (cid:28) . ((cid:28) . ) (cid:28) . ((cid:28) . ) σ v ∗ . ± . ( . ) . ± . ( . ) . ± . ( . ) R † . ± . ( . ) . ± . ( . ) . ± . ( . ) M mol ∗ . ± . ( . ) . ± . ( . ) . ± . ( . ) M vir † . ± . ( . ) . ± . ( . ) . ± . ( . ) Σ mol † . ± . ( . ) . ± . ( . ) . ± . ( . ) α vir † . ± . ( . ) . ± . ( . ) . ± . ( . ) c † . ± . ( . ) . ± . ( . ) . ± . ( . ) In parentheses, we show the p -value for observed values. ∗ For the GMCs with M mol ≥ . × M (cid:12) . † For the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc. the highest ( . − . K), followed by
Arm ( . − . K) and
Bar ( . − . K). The K-S test indicates that the differencesbetween
Bar-end and
Arm or Bar are significant, and thatbetween
Bar and
Arm is marginally significant. Thus weconclude that the T peak in Bar-end is significantly higherthan those in
Arm and
Bar . This result does not change forthe resolved sample. The ∆ Q of T peak distribution in Arm and
Bar-end is within that in M51 spiral arm, but that in
Bar is lower.
Velocity dispersion (Fig. 5 (b)): We find no environ-mental variations based on the K-S test: . − . − in Bar , . − . − in Arm , and . − . − in Bar-end .In
Bar-end , some GMCs have a σ v larger than
10 km s − .The ∆ Q of σ v distribution in each region is roughly withinthose in M51 spiral arm. One caveat of measurement of σ v is that we may overestimate σ v of GMCs. We discuss thisbias in section 5.2 and appendix A. Radius (Fig. 5 (c)): There are no environmental vari-ations of R ( . − . in Bar , . − . in Arm ,and . − . in Bar-end ) and, the ∆ Q of R distributionin each region is roughly within those in M51 spiral arms.Note that we evaluate differences in radius without decon-volution for all sample using the K-S test, and we find noenvironmental variations. Molecular gas mass (Fig. 5 (d)): Molecular gas massis proportional to a combination of brightness temperature,velocity dispersion, and size: M mol ∝ L CO ∝ (cid:104) T (cid:105) R σ v , where (cid:104) T (cid:105) is an average brightness temperature. Since the R and σ v are roughly equal in each region, M mol is mainly proportionalto (cid:104) T (cid:105) in NGC 1300. Therefore, M mol in Bar-end is expectedto be larger than those in
Arm and
Bar like the T peak . Infact, the M mol in Bar-end is higher ( ( . − . ) × M (cid:12) )than those in Bar ( ( . − . )× M (cid:12) ) and Arm ( ( . − . )× M (cid:12) ). The median value in Bar-end is by a factor of 1.6larger than those in
Bar and
Arm . The K-S test indicatesthat the difference between
Bar-end and
Arm ( Bar ) is sig-nificant (marginally significant), and there is no significantdifference between
Bar and
Arm . The median M mol in Bar-end is comparable to that in M51 spiral arms, but those in
Arm and
Bar are about 2 times lower.
Virial mass (Fig. 5 (e)): Since the R and σ v are roughlyequal in each region, M vir ∝ R σ v is expected to be equal. Infact, we find no significant environmental variation: ( . ×− . ) × M (cid:12) in Bar , ( . × − . ) × M (cid:12) in Arm , and ( . × − . ) × M (cid:12) in Bar-end . Molecular gas surface density (Fig. 5 (f)): Because S mol is proportional to (cid:104) T (cid:105) σ v , S mol is expected to showthe same tendency as T peak . In fact, S mol in Bar-end is thehighest ( . − . M (cid:12) pc − ), followed by Arm ( . − . M (cid:12) pc − ) and Bar ( . − . M (cid:12) pc − ). Based onK-S test, however, we do not find the significant difference. Virial parameter (Fig. 5 (g)): Because α vir is propor-tional to σ v /((cid:104) T (cid:105) R ) , α vir is expected to show a reverse ten-dency of T peak . In fact, α vir in Bar is the highest ( . − . ),followed by Arm ( . − . ) and Bar-end ( . − . ). Based onthe resampling method, ± % of the GMCs in Bar is gravi-
MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 tationally unbound ( α vir > ). This percentage is larger thanthat in Arm and
Bar-end ( ± % and ± %), and in M51spiral arm (35 %). However, the K-S test gives high p -valuewhich indicates there is no significant environmental varia-tion in α vir . Note that the K-S test for the observed valueshows the marginally significant difference between Arm and
Bar . But based on the resampling method, it is rare thatK-S test gives a p -value less than or equal to 0.05. In con-clusion, there is no significant environmental variations in α vir in NGC 1300. Scaling coefficient (Fig. 5 (h)): As expected from thefact that c = σ v / R . is a combination of σ v and R , wefind no environmental variation in c . The c in NGC 1300 iscomparable to that in M51 spiral arms.In summary, there is a significant environmental varia-tion in the T peak ; the highest value in Bar-end followed by
Arm and
Bar . Since σ v and R do not exhibit environmentalvariation, the variation of T peak is mainly responsible for thevariation of median value of M mol , Σ mol , and α vir . But basedon the two-sided K-S tests, the (marginally) significant dif-ferences are only seen in the distribution of M mol between Bar and
Bar-end , and
Arm and
Bar-end ; there is virtuallyno significant difference in GMC physical properties amongthe
Bar , Arm and
Bar-end . In addition, we find the proper-ties of GMCs in NGC 1300 are roughly comparable to thosein M51 spiral arms. In particular, the properties in
Bar-end are very similar.
As described in section 4.2.1, the extrapolated (but non-deconvolved) R , σ v and L CO is typically . ∼ . timeshigher than the directly measured values. The accuracy ofthe CPROPS correction (i.e., extrapolation and deconvolu-tion) depends on the sensitivity, spatial resolution and ve-locity resolution (Rosolowsky & Leroy 2006). In order toassess the reliability of the measurements of GMC proper-ties, we simulated ALMA observation of mock GMCs, whichare three-dimensional Gaussian clouds in position-position-velocity space with a given masses, sizes, and velocity disper-sions, in CASA under the same condition of our observations(Section 2). After reconstructing the image from the simu-lated visibility, we identify the GMCs using CPROPS withthe same parameters described in Section 4 and comparethe input and output values. The details of the simulationmethod and results are described in Appendix A, and webriefly describe the results and discussion here.We find that the corrected σ v is overestimated by ∼
50 % if the directly measured velocity width, . σ v , is lessthan half the channel width of . − . Such GMC ac-counts for 56 %, 64 %, and 64 % in Bar , Arm , and
Bar-end ,respectively. Therefore, a large number of cataloged GMCsmay be overestimated in the σ v by a factor of ∼ M mol and R in comparison to σ v . We find thatthe corrected M mol is mostly equal to the input M mol for theGMC with higher S/N ( ≤ S / N ≤ ), but the corrected M mol is typically underestimated by ∼
10 % for the GMCwith lower S/N ( ≤ S / N < ). The corrected R is typicallyunderestimated by ∼
20 % and ∼
10 % for the GMC with lower S/N and higher S/N, respectively. We retested theenvironmental variation of the GMC properties using thecatalog corrected for the over/underestimation factor. As aresult of the K-S test, p -values do not change much (see Ta-ble A2). Thus we concluded that the over/underestimationof the measurements does not influence on the discussionabout the environmental variations described in Section 5.1. Measurements of GMC properties may be affected by themissing flux (e.g., Rosolowsky & Leroy 2006; Pan & Kuno2017). Our ALMA observations did not recover the totalCO( − ) flux due to the lack of Atacama Compact Ar-ray (ACA) measurements. To estimate the recovery frac-tion of the total CO( − ) flux, we compared the CO( − )flux obtained from ALMA with those from Nobeyama 45-msingle-dish telescope by Maeda et al. (2018), which presentedsingle-pointing observations of several regions in NGC 1300.First, we convolved the CO( − ) data cube to (cid:48)(cid:48) . , thebeam size of the Nobeyama 45-m telescope at 115 GHz. Wethen obtained spectra at the pointing positions of the 45-mtelescope and measured the recovery fraction (i.e., the ratioof the two flux). We find that the average recovery fractionis 54 % with typical uncertainty of 5 %; about half of thetotal flux was missed, which could affect the measurementsof GMC properties.To investigate the relationship between the spatial scaleof the gas distribution and missing flux, we simulated ALMAobservation of a mock Gaussian component. We created afits image of a circular Gaussian component with total fluxof 1.0 Jy and given FWHM. The FWHM was set from 100pc to 1500 pc every 100 pc. In order to extract the effectoriginated from the uv-distribution, we simulated the obser-vation under the same configuration and noise-free conditionby using the task of simobserve in CASA. After reconstruct-ing the image with tclean task, we measured the flux of thecomponent and recovery fraction. Fig. 6 shows the recov-ery fraction of the Gaussian component as a function of theFWHM. We find that the recovery fraction of the Gaussiancomponent with FWHM ≤ pc is ∼ . and that withFWHM > pc is under 1.0. For the large Gaussian com-ponent with the FWHM ≥ pc, more than half of the fluxis missed.According to the simulation results, total flux of aGMC smaller than ∼ pc can be recovered in our ob-servations. Since the radius of the GMCs we identified issmaller than pc (the maximum is ∼ pc), their prop-erties would not be affected by the missing flux and theover/underestimates described in 5.2.1 would be mainly dueto the sensitivity. In our observations, a molecular gas struc-ture larger than ∼ pc is mostly resolved out. This resultwould mainly be responsible for the missing flux in our dataand imply the presence of the large scale gas structures suchas diffuse molecular gas components, as have been seen inother galaxies (e.g., M51; Pety et al. 2013). Note that themissing flux would also depend on shape of the GMCs anddistribution of them. Thus it is difficult to figure out the realimpact of the missing flux on the GMC properties by sim-ulations. This issue will be expected to be clear by the newACA observations of NGC 1300 in Cycle 7 (PI: F. Maeda). MNRAS000
10 % for the GMC with lower S/N and higher S/N, respectively. We retested theenvironmental variation of the GMC properties using thecatalog corrected for the over/underestimation factor. As aresult of the K-S test, p -values do not change much (see Ta-ble A2). Thus we concluded that the over/underestimationof the measurements does not influence on the discussionabout the environmental variations described in Section 5.1. Measurements of GMC properties may be affected by themissing flux (e.g., Rosolowsky & Leroy 2006; Pan & Kuno2017). Our ALMA observations did not recover the totalCO( − ) flux due to the lack of Atacama Compact Ar-ray (ACA) measurements. To estimate the recovery frac-tion of the total CO( − ) flux, we compared the CO( − )flux obtained from ALMA with those from Nobeyama 45-msingle-dish telescope by Maeda et al. (2018), which presentedsingle-pointing observations of several regions in NGC 1300.First, we convolved the CO( − ) data cube to (cid:48)(cid:48) . , thebeam size of the Nobeyama 45-m telescope at 115 GHz. Wethen obtained spectra at the pointing positions of the 45-mtelescope and measured the recovery fraction (i.e., the ratioof the two flux). We find that the average recovery fractionis 54 % with typical uncertainty of 5 %; about half of thetotal flux was missed, which could affect the measurementsof GMC properties.To investigate the relationship between the spatial scaleof the gas distribution and missing flux, we simulated ALMAobservation of a mock Gaussian component. We created afits image of a circular Gaussian component with total fluxof 1.0 Jy and given FWHM. The FWHM was set from 100pc to 1500 pc every 100 pc. In order to extract the effectoriginated from the uv-distribution, we simulated the obser-vation under the same configuration and noise-free conditionby using the task of simobserve in CASA. After reconstruct-ing the image with tclean task, we measured the flux of thecomponent and recovery fraction. Fig. 6 shows the recov-ery fraction of the Gaussian component as a function of theFWHM. We find that the recovery fraction of the Gaussiancomponent with FWHM ≤ pc is ∼ . and that withFWHM > pc is under 1.0. For the large Gaussian com-ponent with the FWHM ≥ pc, more than half of the fluxis missed.According to the simulation results, total flux of aGMC smaller than ∼ pc can be recovered in our ob-servations. Since the radius of the GMCs we identified issmaller than pc (the maximum is ∼ pc), their prop-erties would not be affected by the missing flux and theover/underestimates described in 5.2.1 would be mainly dueto the sensitivity. In our observations, a molecular gas struc-ture larger than ∼ pc is mostly resolved out. This resultwould mainly be responsible for the missing flux in our dataand imply the presence of the large scale gas structures suchas diffuse molecular gas components, as have been seen inother galaxies (e.g., M51; Pety et al. 2013). Note that themissing flux would also depend on shape of the GMCs anddistribution of them. Thus it is difficult to figure out the realimpact of the missing flux on the GMC properties by sim-ulations. This issue will be expected to be clear by the newACA observations of NGC 1300 in Cycle 7 (PI: F. Maeda). MNRAS000 , 1–17 (2019) F. Maeda et al.
100 500 1000 1500FWHM[pc]0.00.51.0 r e c o v e r y f r a c t i o n Figure 6.
Recovery fraction of the Gaussian component as afunction of the FWHM. We simulated ALMA observation ofthe mock Gaussian component with a given FWHM under thesame configuration and noise-free condition. Horizontal dashedlines indicate the recovery fraction of 1.0 and 0.5. Vertical dash-dotted line indicates 1350 pc, corresponding to the beam size ofNobeyama 45-m telescope.
In this section, we present the analysis of the scaling re-lations for the GMCs, which are commonly referred to asLarson’s laws (Larson 1981). Here, we investigate the size-velocity dispersion relation, the virial-luminous mass rela-tion, the size-mass relation, and the relationship between σ v / R and Σ mol for the resolved GMCs ( M mol ≥ . × M (cid:12) and R > pc) in NGC 1300. In each analysis, we calculatethe Spearman’s rank correlation coefficient ( r s ) to evaluatethe strength of a link between two sets of data. Consider-ing the number of GMCs, we regard r s ≥ . as a sign ofstrong correlation and . < r s < . as that of moderatecorrelation. Fig. 7 shows the size-velocity dispersion relation inNGC 1300. The relation in M51 spiral arms from C14 isshown as gray squares. In panel (a), although the majorityof the data points lies around the Galactic fit (Solomon et al.1987), the correlation is not seen ( r s = − . ) which is alsoobserved in M51 spiral arms ( r s = . ). Even with divisioninto subregions, the correlations are not seen ( | r s | < . ).The existence of the size-velocity dispersion relation hasbeen discussed. In M51, there was no correlation in not onlyspiral arms but also center and inter-arm regions (C14). Hi-rota et al. (2018) reported the apparent lack of correlation inthe various environments including arm and bar regions ofM83. On the contrary, Bolatto et al. (2008) found a correla-tion of σ v ∝ R . ± . for the multigalaxy GMC populationincluding spiral galaxies and dwarf galaxy. Faesi et al. (2018) found also a correlation of σ v ∝ R . ± . in NGC 300. Insection 6.4, we will discuss the cause for the weak correlationin NGC 1300. Upper panels in Fig. 8 show the relation between virialmass and the molecular gas mass derived from CO lumi-nosity in NGC 1300. We find moderate correlations for allGMCs ( r s = . ) in Arm ( . ) and in Bar-end ( . ), whilethere is no apparent correlation in Bar ( . ). In the pan-els with r s ≥ . , a magenta solid line represents the best-fitted line determined by the ordinary least-squares method: M vir ∝ M . ± . in the whole region, M vir ∝ M . ± . in Arm , and M vir ∝ M . ± . in Bar-end . These relation-ships agree with that in M51 spiral arms shown as orangesolid line ( M vir ∝ M . ). In lower panels of Fig. 8, weplot the virial parameter ( α vir ) as a function of M mol . Asinferred from the slope lower than 1.0 in upper panels inFig. 8, α vir (cid:27) M vir / M mol decreases with increasing M mol .This suggests that the high mass GMCs tend to be morestrongly bound than low mass GMCs in arm and Bar-end of NGC 1300 as seen in M51.
Fig. 9 shows the size-mass relation in NGC 1300. Thereis a moderate correlation in each panel ( . < r s < . ).Magenta solid line represents the best fit line determinedby the ordinary least-squares method. The slope of the rela-tion in Bar (0.57) is the shallowest, followed by
Arm (1.00)and
Bar-end (1.36). The fact that the index is smaller than2.0, the molecular gas surface density ( Σ mol ) of GMCs is notroughly constant but decreases with increasing GMC size inNGC 1300. The difference in the index shows that the molec-ular gas surface density ( Σ mol ) in Bar is lower than GMCswith similar size in
Arm and
Bar-end , which is consistentwith the tendency of Σ mol (Fig. 5 (g)). Orange solid line rep-resents the best fit line for the GMCs ( M mol ≥ . × M (cid:12) and R ≥ pc) in M51 spiral arms and slope is 1.23. The Σ mol in Bar and
Arm is lower than GMCs with similar sizein M51 spiral arms. σ v / R and Σ mol Recent studies on molecular gas at GMC scale argued thatthe relationship between σ v / R = c and Σ mol is useful to in-vestigate the physical state of the GMCs (e.g., Heyer et al.2009; Leroy et al. 2015; Sun et al. 2018). This is becausethe position of the GMC in σ v / R - Σ mol space gives informa-tion about not only virial parameter, α vir , but also internalturbulent pressure, P int of the GMC. Here, the P int can beexpressed as P int k = ρσ v k = (cid:18) Σ mol M (cid:12) pc − (cid:19) (cid:18) c km s − pc − . (cid:19) [ cm − K ] , (7)where ρ is the molecular gas volume density of the GMC.Fig. 10 plots the σ v / R - Σ mol relation of NGC 1300. The α vir = and 2 are represented by a black solid and dotted MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 log( R [pc]) l o g ( v [ k m / s ]) r s = -0.04 (a)All log( R [pc]) r s = -0.17 (b)Bar log( R [pc]) r s = -0.22 (c)Arm log( R [pc]) r s = 0.29 (d)Bar-end l o g ( v [ k m / s ]) Figure 7. (a) Size-velocity dispersion relation for the GMCs in the whole region in NGC 1300. (b) - (d) Same as panel (a) but for thedifferent environments in NGC 1300. We show the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc in filled circles and the rest in opencircles. The average error bars are indicated as a cross in the bottom right corner of each panel. The range below the spatial (15 pc) andspectral (2.0 km s − ) sensitivity limit is indicated as shaded regions. The Spearman’s correlation rank, r s , for the filled circle is given inthe top right corner of each panel. Gray squared show the relationship for GMCs in M51 spiral arms (C14). Black dotted line indicatesthe Galactic fit, σ v = . R . (Solomon et al. 1987). log( M mol [ M ]) l o g ( M v i r [ M ]) r s = 0.52 M vir M (a)All log( M mol [ M ]) r s = 0.25 (b)Bar log( M mol [ M ]) r s = 0.53 M vir M (c)Arm log( M mol [ M ]) r s = 0.70 M vir M (d)Bar-end l o g ( M v i r [ M ]) log( M mol [ M ]) -1.00.01.0 l o g ( v i r ) log( M mol [ M ]) log( M mol [ M ]) log( M mol [ M ]) -1.00.01.0 l o g ( v i r ) Figure 8. (a) Virial mass-luminosity based mass relation (upper) and virial parameter-luminosity based mass relation (lower) for theGMCs in the whole region of NGC 1300. (b) - (d) Same as panel (a) but for the different environments in NGC 1300. We show theGMCs with M mol ≥ . × M (cid:12) and R ≥ pc in filled circles and the rest in open circles. The average error bars are indicated as across in each panel. The range below M mol = . × M (cid:12) is indicated as a shaded region. Black solid and dotted line indicate the linefor α vir = . and α vir = . , respectively. For upper panels, the Spearman’s correlation rank, r s , for the filled circle is given in the bottomright corner (BRC) of each panel. If r s is larger than 0.5, we show the best fitted line as a magenta solid line and its slope is given in theBRC. Gray squares and orange solid line show the relationship and the best fitted line for GMCs in M51 spiral arms (C14), respectively. line, respectively, and magenta dotted lines indicate con-stant P int . Note that the σ v / R - Σ mol relation is mathemati-cally equivalent to the M vir - M mol relation (Fig. 8). We cansee a moderate correlation in the whole region ( r s = . ) , Bar (0.66),
Arm (0.60), and
Bar-end (0.72) in NGC 1300,which shows the scaling coefficient, c , increases with increas-ing Σ mol . The same tendency is seen in Milky Way; Heyeret al. (2009) pointed out that c is proportional to Σ / .As shown in panel (a), P int of the GMCs in NGC 1300 is spread about 3 dex ( ≤ P int / k /[ cm − K ] ≤ ).The median values and the ∆ Q of P int / k are roughly con-stant across the different environments: . + . − . , . + . − . , and . + . − . × cm − K in Bar , Arm , and
Bar-end , respec-tively. The K-S tests give high p -values of > . . Thesevalues are slightly lower than that in M51 spiral arms of . + . − . × cm − K .Fig. 10 can be interpreted to explain the cause for weakcorrelation between size and velocity dispersion (Fig. 7). MNRAS000
Bar-end , respec-tively. The K-S tests give high p -values of > . . Thesevalues are slightly lower than that in M51 spiral arms of . + . − . × cm − K .Fig. 10 can be interpreted to explain the cause for weakcorrelation between size and velocity dispersion (Fig. 7). MNRAS000 , 1–17 (2019) F. Maeda et al. R [pc])5.06.07.0 l o g ( M m o l [ M ]) r s = 0.63 M mol R (a)All R [pc]) r s = 0.66 M mol R (b)Bar R [pc]) r s = 0.60 M mol R (c)Arm R [pc]) r s = 0.72 M mol R (d)Bar-end l o g ( M m o l [ M ]) Figure 9. (a) Size-molecular gas mass relation for the GMCs in the whole region of NGC 1300. (b) - (d) Same as panel (a) but for thedifferent environments in NGC 1300. We show the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc in filled circles and the rest in opencircles. The average error bars are indicated as a cross in each panel. The range below M mol = . × M (cid:12) and R = pc is indicatedas shaded regions. The Spearman’s correlation rank, r s , for the filled circle is given in the top left corner (TLC) of each panel. We showthe best fitted line as a magenta solid line and its slope is given in the TLC. Gray squares and orange solid line show the relationshipand the best fitted line for GMCs in M51 spiral arms (C14), respectively. log( mol [ M /pc ]) -1.0-0.50.00.5 l o g ( c = v / R [ k m s p c ]) r s = 0.56 (a)All log( mol [ M /pc ]) [cm K] r s = 0.52 (b)Bar log( mol [ M /pc ]) r s = 0.63 (c)Arm log( mol [ M /pc ]) r s = 0.52 (d)Bar-end l o g ( c = v / R [ k m s p c ]) Figure 10. (a) Scale coefficient as a function of molecular gas surface density in the whole region of NGC 1300. (b) - (d) Same as panel(a) but for the different environments in NGC 1300. We show the GMCs with M mol ≥ . × M (cid:12) and R ≥ pc in filled circles and therest in open circles. The average error bars are indicated as a cross in each panel. The Spearman’s correlation rank, r s , for the filled circleis given in the BRC of each panel. Gray squares show the relationship for the GMCs in M51 spiral arms (C14). Black solid and dottedline indicate the line for α vir = . and . , respectively. Magenta dotted lines indicate the line for P int / k = , , , and [ cm − K ] . The GMCs in NGC 1300 cover a wider range of Σ mol ( ∼ ∼ c in NGC 1300 becomes widerthan that in Milky Way, leading to a decorrelation between σ v and R . The dependence of the c on the Σ mol also maybe the part of the cause of weak correlation seen in M51and M83 (see Hirota et al. 2018). Note that the limited dy-namic range of the size parameter and the errors in the mea-surements with CPROPS could be responsible for the weakcorrelation. In this section, we investigate the mass spectra of GMCs inNGC 1300. The mass spectrum provides information aboutGMCs formation and destruction processes (e.g., Kobayashiet al. 2017), and is usually expressed in differential formknown to follow a power law relation as dNdM ∝ M γ , (8) where M is the molecular gas mass, N is the number ofmolecular clouds and γ is an index of the power law relation.Integration of this expression gives a cumulative massdistribution. Several studies reported the GMC mass spec-tra are underpopulated at higher masses, i.e., it is thoughtthat there is an upper limit to the GMC mass (e.g., Williams& McKee 1997; Fukui et al. 2001, 2008; Rosolowsky 2007;Gratier et al. 2012). Considering the existence of the uppercutoff mass, a truncated power-law is suitable as a cumula-tive mass spectrum (Williams & McKee 1997): N ( > M ) = − N u γ + (cid:34)(cid:18) MM u (cid:19) γ + − (cid:35) , (9)where M u is an upper cutoff mass of GMCs and N u is ameasure of the number of GMCs at the upper cutoff mass.The index γ shows how the GMC mass is distributed. If γ is larger than − , massive GMCs dominate the total cloudmass.The parameters of the mass spectrum ( γ and M u ) isconsidered to be determined in the balance between the for-mation and destructive processes of GMCs. Enhance of the MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 l o g ( N ( M > M )[ k p c ]) (a)All log( M mol [ M ]) l o g ( N ( M > M )[ k p c ]) (b)Bar l o g ( N ( M > M )[ k p c ]) (c)Arm l o g ( N ( M > M )[ k p c ]) (d)Bar-end log( M mol [ M ]) l o g ( N ( M > M )[ k p c ]) (e)M51 SA Figure 11. (a) Cumulative mass spectrum for GMCs in the wholeregion of NGC 1300. (b)-(d) Same as panel (a), but for the dif-ferent environments in NGC 1300. (e) Same as panel (a), but forGMCs in M51 spiral arms (C14). In each plot, filled and opencircles indicate the GMCs that are and are not used for fittingthe spectrum with equation (9), respectively. The orange solidline indicates the best-fitted function. The dash-dotted verticalline indicates the lower mass limit, × M (cid:12) , for the fitting ofmass spectra. formation process of massive GMCs (e.g., agglomeration ofsmall clouds and self gravity; Dobbs 2008) leads to a steepermass spectrum and a higher M u . On the contrary, the de-struction process (e.g., stellar feedback, cloud-cloud colli-sion, and large-scale shear motion) plays a role to make massspectrum shallow and decrease the M u .Fig. 11 shows the cumulative GMC mass spectrum indifferent environments in NGC 1300 (panel (a) - (d)) and inM51 spiral arms (panel (e); C14). The y-axis shows the GMCnumber density. The number density of high mass GMC( M mol ≥ . × M (cid:12) ) in Bar-end is the highest (5.2 kpc − ),followed by in Bar (1.2 kpc − ) and Arm (2.6 kpc − ). Althoughthese values depend on the definition of the environmentalmask, there is no doubt that the number densities of highmass GMC with ≥ . × M (cid:12) in Bar (5.1 kpc ) and Arm (9.9 kpc ) are lower than that in Bar-end (3.6 kpc ). Inparticular, GMCs more than . × M (cid:12) are only observedin Bar-end . Note that the number density in M51 spiral armsis 18.2 kpc − , and is the factor of ∼ larger than that inany environments of NGC 1300.We fitted the cumulative GMC mass spectrum withequation (9). Although the mass completeness limit is ex-pected to be . × M (cid:12) in uncrowded regions (see sec-tion 5), the completeness limit might be effectively raisingin a crowded region like Bar-end (e.g., Colombo et al. 2014;Hirota et al. 2018). Thus, we fitted the mass spectrum usingthe GMCs with M (cid:12) ≥ . × M (cid:12) indicated as a verticalblack dash-dotted line in Fig. 11. To estimate the fittinguncertainties, we made resampling with 100 realizations. Inone realization, random values of a molecular gas mass weregenerated within the uncertainties CPROPS calculated. Themedian and the MAD of 100 realizations for each parameterwere adopted as the best-fitted value and the confidence in-terval (Table 5). The orange solid line in Fig. 11 shows thebest-fitted cumulative mass function. We list the p -values ofthe K-S tests as an indication of the goodness-of-fit in thelast column of Table 5. Here we fitted the mass spectrum ofGMCs in M51 spiral arms in the same way.No clear difference was found in the shape of mass spec-tra between in Bar and
Arm : the slope and upper mass limitis γ ∼ − . and M u ∼ . × M (cid:12) , respectively. However,the mass spectrum in Bar-end is obviously different fromthose in
Bar and
Arm . The slope in
Bar-end is flatter than − , which indicates that massive GMCs account for a largepopulation of total cloud mass in Bar-end . The upper masslimit in
Bar-end of M u = ( . ± . ) × M (cid:12) is twice as largeas that in Bar and Arm regions. The presence or absenceof differences in the mass spectrum between environments isconsistent with that in the box plot of M mol (see Section 5.1).The γ and M u in Bar-end are similar to those in M51 spiralarms.Since the γ in Bar-end is larger than those in
Bar and
Arm , Bar-end would be an environment where the massiveGMCs forms more than in
Bar and
Arm . The similarity ofthe feature betwen
Bar-end and M51 spiral arms suggeststhe mechanism which regulate the formation and destructionof GMCs is similar to that in M51 spiral arms. Although themass spectra in
Bar and
Arm is similar, the GMC destruc-tion mechanism would be different because the star forma-tion activity is apparently different (Section 1). The stel-lar feedback process may be predominant in
Arm , but the
MNRAS000
MNRAS000 , 1–17 (2019) F. Maeda et al.
Table 5.
Truncated Power-law Fits to the GMC Mass Spectra inDifferent Environments in NGC 1300Envir. γ M u N u p -value( M (cid:12) )All − . ± .
04 13 . ± .
67 2 . ± . − . ± .
20 6 . ± .
04 1 . ± . − . ± .
10 5 . ± .
36 5 . ± . − . ± .
07 14 . ± .
93 2 . ± . − . ± .
03 13 . ± .
34 35 . ± .
46 10 − Slopes γ , upper cutoff mass M u , and a measure of the numberof GMCs at the upper cutoff mass N u of the truncated power-law fits to the GMC mass spectra of the different environmentsin NGC 1300 The error are obtained through 100 resamplinginteraction. In the last column, we list the p -values of the K-Stests as an indication of the goodness-of-fit. dynamical effect (e.g., cloud-cloud collision and large-scaleshear motion) may be important process in Bar . As described in Sections 1 and 3, SFE differences with envi-ronments are clearly seen in typical strongly barred galaxies.In the arms, H ii regions are associated with dust lanes, andGMCs coexist with the dust lanes. However, in bar regions,prominent H ii regions are often not seen while the GMCsdo exist. What physical mechanism controls the SFE of theGMC? Based on the K-S tests, there is no significant varia-tion in the physical properties ( σ v , R , M mol , M vir , Σ mol , α vir ,and c ) of the GMCs between Bar and
Arm (Table 4). Com-paring to the GMCs between
Bar and
Bar-end , and
Arm and
Bar-end , (marginally) significant difference is only seenin the distribution of M mol . Therefore, it appears that sys-tematic differences in the GMC properties are not the causefor the SFE differences with environments.Many previous studies investigated the cause for thelow SFE in the bar regions. Some previous studies proposedthat GMCs can not form due to a strong shock and/or shearalong the bar (e.g., Tubbs 1982; Athanassoula 1992; Rey-naud & Downes 1998). Recent studies suggest molecularclouds in bar regions may be gravitationally unbound dueto the strong internal turbulence of the clouds. Sorai et al.(2012) made CO( − ) map of Maffei 2 at an angular res-olution of 200 pc, and pointed out a possibility that cloudsin the bar regions are gravitationally unbound, which causesthe low SF activity. Nimori et al. (2013) performed a two-dimensional hydrodynamical simulation and also found theunbound clouds in bars. In NGC 1300, the number fractionof GMC with α vir > in Bar (60 %) is larger than that in
Arm and
Bar-end (30 %), which may partly contribute todecreasing the SFE in the bar region. However, there is nosignificant difference in α vir based on the K-S test (Table 4).This result suggests that the lack of massive star formationin the strong bar of NGC 1300 can not be explained by asystematic difference of α vir only.Hirota et al. (2018) found the α vir of the GMCs in thebar of M83 (median is ∼ . ) is larger than that in the arm( ∼ . ). This result seems to be inconsistent with our re- sults. However, a direct comparison with our results is notstraightforward because the algorithm for identifying GMCsthey used was different from ours. It is necessary to comparethe GMC properties between M83 and NGC 1300 under thesame data quality and methodology. This comparison is im-portant but beyond our scope in this paper, which remainsas a future subject.Although the galactic environments seem not to af-fect the physical properties of GMCs in NGC 1300, thereis a possibility that the interaction of GMCs is affected.Cloud-cloud collisions (CCCs), which induces clump for-mation by shock compressions, has been suggested as themechanism of massive star formation (e.g., Habe & Ohta1992; Fukui et al. 2014). Recent studies suggest that the ef-ficiency of massive star formation strongly depends on thecollision speed. Takahira et al. (2014, 2018) performed hy-drodynamical simulations of CCCs. They found that massiveclumps ( ∼ M (cid:12) ) finally form in the case of slower CCCs( ∼ − ). However, in faster CCCs ( >
10 km s − ), cloudsare highly compressed, but the duration of the collision is notlong enough for the clump mass to grow via gas accretionand no massive clump is formed. Based on a high resolu-tion ( ∼ a few pc) 3D hydrodynamical simulations aiming atmodeling a barred galaxy M83, Fujimoto et al. (2014) foundthat collision speed among clouds in bar regions is fasterthat in arm regions and proposed this difference makes SFEvariations.CO observations towards NGC 1300 with a single-dishtelescope of Nobeyama 45-m show the higher velocity dis-persion in bar regions than in arm regions at a kpc-scale res-olution (Maeda et al. 2018). This result suggests the relativevelocity among the clouds in the bar regions is larger thanthat in the arm regions and is qualitatively consistent withthe fast CCC scenario in the bar region. Other CO obser-vations towards barred galaxies with a single-dish telescopeshow the same tendency (e.g., Regan et al. 1999; Morokuma-Matsui et al. 2015; Muraoka et al. 2016; Yajima et al. 2019).Egusa et al. (2018) finds that a probability distribution func-tion of velocity dispersion in the bar of M83 is systematicallylarger than in the arm (see also Sun et al. 2018). Querejetaet al. (2019) found a significant anti-correlation between theSFE and velocity dispersion of the dense gas at a 100 pcscale in M51. The velocity dispersion of the dense gas isthought to be largely reflecting velocity dispersion amongdifferent clumps. According to these results, the differencein SFE between the arm and bar regions would be due tothe difference in CCC speed rather than the difference inthe physical properties of the GMCs.Fujimoto et al. (2019, submitted) present a hydrody-namical simulation of a strongly barred galaxy, using a stel-lar potential model of NGC 1300. They found that there isno significant environmental dependence of cloud propertiesincluding the virial parameter, which is consistent with ourresult presented in this paper. Further, they show that thecollision speed in the bar is significantly faster than the otherregion due to the elongated global gas motion by the stel-lar bar. The fraction of colliding clouds with collision speedmore than
20 km s − in bar regions ( ∼ < MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 The CCC occurs only a few times within 1 Myr in thebar and arm region and the effects of collision do not lastfor long time; the excited internal gas motion induced by thecollision decays quickly within at most a few Myr, which isthought to be shorter than cloud lifetimes (10-40 Myr; e.g.,Kawamura et al. 2009; Meidt et al. 2015; Chevance et al.2019; Fujimoto et al. 2019). Therefore, in a snapshot of thegalaxy, there are a few or less GMCs affected by the colli-sion in the bar and arm regions. Thus the GMC propertiesobserved would not be affected by this effect.As a next step of this study, we should directly comparethe simulation of Fujimoto et al. (2019, submitted) and ourobservational data to investigate the relative velocity amongGMCs we detected. Although direct measurement of colli-sion speed from observation data is difficult, the velocity de-viation between the GMCs and their surrounding GMCs canbe an observable indicator of the collision speed of clouds.Fujimoto et al. (2019, submitted) found that the velocitydeviation in the bar region is larger than that in the arm re-gion, which reflects the fast CCCs in the bar. Whether thesame tendency is seen in NGC 1300 or not will be clarifiedby further investigations using our GMC catalog (Maeda etal. 2020, in preparation).
We made CO( − ) observations towards the stronglybarred galaxy NGC 1300 at a high angular resolution about40 pc with ALMA. We detected CO emissions from the west-ern arm to the bar region. Using the CPROPS algorithm, weidentified 233 GMCs (34, 119, and 49 in Bar , Arm , and
Bar-end , respectively) with S/N > . We measured R , σ v , and L CO of these GMCs and then derived M mol , M vir , Σ mol , α vir ,and c of them. We focus on a mass completed sample with M mol > . × M (cid:12) for the investigation of T peak , σ v , and M mol and a resolved sample with M mol > . × M (cid:12) and R > pc for the investigation of R , M vir , Σ mol , α vir , and c .We compare the GMCs properties among the environments.The main results are as follows:(i) Based on the two-sided K-S tests, there is a significantenvironmental variation in the T peak ; the highest value in Bar-end followed by
Arm and
Bar . However, there is hardlyany significant variations in GMC physical properties ( σ v , R , M mol , M vir , Σ mol , α vir , and c ; Fig. 5); (marginally) sig-nificant difference is only seen in the distribution of M mol between Bar and
Bar-end , and
Arm and
Bar-end (Table 4).The properties of GMCs in NGC 1300 are roughly compara-ble to those in M51 spiral arms. In particular, the propertiesin
Bar-end are very similar.(ii) We find no obvious R − σ v relation although the ma-jority of the data points lies around the Galactic fit (Fig. 7).For the relation between M vir and M mol , there is a moderatecorrelation in Arm and
Bar-end , while there is no apparentcorrelation in
Bar (Fig. 8). We find the α vir decreases withincreasing M mol , which suggests the high mass GMCs tendto be strongly bound as seen in M51. There is a moderatecorrelation between R and M mol in each environment (Fig.9). Further, we find the P int / k is roughly constant across thedifferent environments in NGC 1300 (Fig. 10).(iii) No clear difference is found in the shape of GMC mass spectra between in Bar and
Arm . The slope of thespectrum in the
Bar-end is slightly flatter than those in
Arm and
Bar , and massive GMCs are seen only in the
Bar-end (Fig. 11). The similarity of the feature between
Bar-end and M51 spiral arms suggests the mechanism regulating for-mation and destruction of GMCs is similar to that in M51spiral arms.(iv) It appears that systematic differences in the physicalproperties of the GMCs are not the cause for the low SFEin the bar region. Other mechanisms such as fast CCCs maycontrol the SFE of GMCs in NGC 1300 (Section 8).
ACKNOWLEDGEMENTS
We would like to thank the referee for useful commentsand suggestions. We are grateful to K. Nakanishi, F. Egusa,Y. Miyamoto, K. Saigo, R. Kawabe and the staff at theALMA Regional Center for their help in data reduction.F.M. is supported by Research Fellowship for Young Sci-entists from the Japan Society of the Promotion of Sci-ence (JSPS). K.O. is supported by Grants-in-Aids for Scien-tific Research (C) (16K05294 and 19K03928) from JSPS.A.H. is funded by the JSPS KAKENHI Grant NumberJP19K03923. This paper makes use of the following ALMAdata: ADS/JAO.ALMA
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APPENDIX A: CPROPS BIAS
CPROPS corrects for the sensitivity by extrapolating GMCproperties to those we would expect to measure with perfectsensitivity (i.e., 0 K). As described in section 4.2.1, the ex-trapolated R , σ v and L CO is typically . ∼ . times higherthan the directly measured values. CPROPS also corrects forthe resolution by deconvolution for beam and channel width.The corrected R , σ v is typically by a factor of . ∼ . lower than the extrapolated values. Since the accuracy ofthese corrections (extrapolation and deconvolution) dependson the sensitivity, spatial resolution and velocity resolution(Rosolowsky & Leroy 2006), it is necessary to assess the re-liability of the measurements of GMC properties.Using CASA, we simulated ALMA observation of mockGMCs, which are three-dimensional Gaussian clouds witha given M mol , R , and σ v in a position-position-velocity space. We create a fits image with 100 mock GMCs cen-tered in fixed positions. The M mol , R , and σ v are randomlydetermined in the range of . ≤ log ( M mol /[ M (cid:12) ]) ≤ . , . ≤ log ( R /[ pc ]) ≤ . , and . ≤ log ( σ v /[ km s − ]) ≤ . ,respectively. The GMCs are round clouds (i.e., axis ratio= 1.0). Here, we assume the CO-to-H conversion factor of . M (cid:12) ( K km s − pc ) − . Then, using the task of simobserve in CASA, we simulate observation under the same configu-ration, pointings, and noise condition of our ALMA obser-vations (see Section 2). After reconstructing the image withthe same tclean parameters (see Section 2), we identify theGMCs using CPROPS with the same settings described insection 4. We repeated this procedure 12 times, and then weextracted the GMCs with ≤ S / N ≤ , corresponding tothe observed value.Fig. A1 shows the results of this simulation. The super-script in denotes the input value of the mock GMC and out denotes the output value CPROPS measured and corrected.We plot the ratio of output value to input value as a func-tion of input value for σ v , R , and M mol , dividing GMCs intolower S/N ( ≤ S / N < ) and higher S/N ( ≤ S / N ≤ ). Inpanel (a), we find CPROPS measurements work well for theGMCs whose σ in v is larger than . − . However, for theGMCs with σ in v ≤ . − , CPROPS overestimates σ v bya factor of ∼ . regardless of S/N.According to Rosolowsky & Leroy (2006), the extrap-olation works well regardless of the S/N, if the line widthof the identified GMC is at least twice the channel width.In Fig. A2, we plot the σ out v / σ in v as a function of the ra-tio of the velocity dispersion without CPROPS correction( σ obs v ) to channel width ( σ ch = (cid:113) ∆ V / π = . − ).We find that the σ out v is overestimated by a factor of ∼ . if the σ obs v is less than half the channel width. Such GMCaccounts for 56 %, 64 %, and 64 % in Bar , Arm , and
Bar-end , respectively. Therefore, a large number of the catalogedGMCs may be overestimated in the σ v by a factor of ∼ M mol and R in comparison to σ v . Inpanel (b), we find CPROPS slightly underestimate radius:the R out is typically underestimated by a factor of ∼ . and ∼ . for the GMC with lower S/N and higher S/N,respectively. In panel (c), the corrected M mol is mostly equalto the input M mol for the GMC with higher S/N, but thecorrected M mol is typically underestimated by a factor of ∼ . for the GMC with lower S/N. Because about 70 % ofthe cataloged GMCs were detected with ≤ S / N ≤ , R and M mol may be slightly underestimated by a factor of ∼ . and ∼ . . Note that the factors of over/underestimation donot change if the GMC’s minor-to-major axis ratio is set tobe 0.5.These over/underestimation can propagate to the mea-surements of M vir , Σ mol , α vir , and c , which are a combinationof σ v , R , and M mol . Thus, we recalculated the GMC prop-erties. We corrected the cataloged σ v by dividing by 1.5 if σ obs v ≥ σ ch . The cataloged R is corrected by dividing by 0.8and 0.9 for the GMCs with lower and higher S/N. For the M mol , we corrected by dividing by 0.9 for the GMCs withlower S/N. Then, we recalculated other properties based onthe corrected σ v , R , and M mol . Table A1 is the same asTabel 3 but corrected for the over/underestimation. We findthe recalculated median M vir , Σ mol , and c become by a fac- MNRAS , 1–17 (2019)
MC properties in the strongly barred galaxy NGC 1300 tor of . ∼ . smaller and the correction factor is roughlycomparable in the different environments. The α vir becomesby a factor of 0.8, 0.5, and 0.8 smaller in Bar , Arm , and
Bar-end , respectively. This suggests we overestimate the fractionof gravitationally unbound clouds. Based on the corrected(uncorrected) values, the number fraction is 50 % (58 %),29 % (33 %), and 23 % (29 %) in
Bar , Arm , and
Bar-end ,respectively.We retested the environmental variation of the GMCproperties using the corrected catalog. Table A2 showsthe result of the two-sided K-S test. Comparing theTable 4, p -values do not change much. Therefore, theover/underestimation of the measurements does not influ-ence on the discussion about the environmental variationdescribed in Section 5.1. It is notable that ∼ % and ∼ %of the GMCs in M51 measured by Colombo et al. (2014) maybe underestimated and overestimated by a factor of ∼ . .Thus, the over/underestimation seems not to influence onthe discussion about the comparison with the GMCs in M51. APPENDIX B: GMC CATALOG
Table B presents the GMC catalog in NGC 1300, whichcontains columns as follws:(i)
Column 1 : ID, GMC identification number(ii)
Column 2 : RA, GMC right ascension as measured bythe intensity-weighted 1st moment along this direction(iii)
Column 3 : Dec, GMC declination measured as above(iv)
Column 4 : v LSR , GMC central velocity as measuredby the intensity-weighted first moment along the velocityaxis(v)
Column 5 : T peak , GMC’s peak brightness temperaturein K(vi) Column 6 : S/N, GMC’s peak signal-to-noise ratio(vii)
Column 7 : σ v , GMC’s deconvolved, extrapolated ve-locity dispersion in km s − with uncertainty(viii) Column 8 : R , GMC’s deconvolved, extrapolated ef-fective radius in pc with uncertainty(ix) Column 9 : M mol , GMC’s mass in M (cid:12) calculatedfrom CO luminosity and α CO = . M (cid:12) ( K km s − pc ) − with uncertainty(x) Column 10 : M vir , GMC’s mass inferred from virial the-orem in M (cid:12) with uncertainty(xi) Column 11 : α vir , GMC’s virial parameter with uncer-tainty(xii) Column 12 : Region where a given GMC has beenidentified, i.e., Bar, Arm, Bar-end(BE), and ”other”, whichrepresents the GMC outside the three regions(xiii)
Column 13 : Flag for the measurement of radius: = actual measurement of radius, = upper limit This paper has been typeset from a TEX/L A TEX file prepared bythe author.MNRAS000
Column 13 : Flag for the measurement of radius: = actual measurement of radius, = upper limit This paper has been typeset from a TEX/L A TEX file prepared bythe author.MNRAS000 , 1–17 (2019) F. Maeda et al. in v [km/s])0.51.01.52.02.53.0 o u t v / i n v (a)Velocity dispersion R in [pc])0.51.01.5 R o u t / R i n (b)Radius M inmol [ M ])0.00.51.01.52.0 M o u t m o l / M i n m o l (c)Molecular gas mass in v [km/s])0.51.01.52.02.53.0 o u t v / i n v (a)Velocity dispersion R in [pc])0.51.01.5 R o u t / R i n (b)Radius M inmol [ M ])0.00.51.01.52.0 M o u t m o l / M i n m o l (c)Molecular gas mass Figure A1.
Results of the ALMA observation simulation of the mock GMCs. (a): Ratio of the output velocity dispersion by CPROPS( σ out v ) to the input (model) velocity dispersion ( σ in v ) as a function of the σ in v . We shows the GMCs with lower S/N ( ≤ S / N < ) andhigher S/N ( ≤ S / N ≤ ) in upper and lower panel, respectively. Red square shows the median value in a bin whose range is shown aserror bar in x-axis, and a error bar in y-axis shows the ∆ Q in the bin. Orange solid line shows the channel width of . − . Blackdash-dotted line shows σ out v / σ in v = . . (b),(c): Same as panel (a) but for radius and molecular gas mass. obs v / ch o u t v / i n v Figure A2.
Ratio of the output velocity dispersion by CPROPS ( σ out v ) to the input (model) velocity dispersion ( σ in v ) as a function ofthe ratio of the velocity dispersion without CPROPS correction ( σ obs v ) to channel width ( σ ch = (cid:113) ∆ V / π = . − ). Red squareshows the median value in a bin whose range is shown as error bar in x-axis, and a error bar in y-axis shows the ∆ Q in the bin. Blackdash-dotted line shows σ out v / σ in v = . . Blue dotted line shows σ obs v / σ ch = . . MNRAS , 1–17 (2019) MC properties in the strongly barred galaxy NGC 1300 Table A1.
GMC properties in the different environments of NGC 1300 corrected for the CPROPS biasEnvir. σ v R M mol M vir Σ mol α vir c ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) ) ( M (cid:12) pc − ) ( km s − pc − . )All . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Bar . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Arm . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Bar-end . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . . + . − . Table A2.
Kolmogorov-Smirnov Test for GMC properties corrected for the CPROPS biasProp. Bar vs. Arm Bar vs. Bar-end Arm vs. Bar-end σ v . ± . ( . ) . ± . ( . ) . ± . ( . ) R . ± . ( . ) . ± . ( . ) . ± . ( . ) M mol . ± . ( . ) . ± . ( . ) . ± . ( . ) M vir . ± . ( . ) . ± . ( . ) . ± . ( . ) Σ mol . ± . ( . ) . ± . ( . ) . ± . ( . ) α vir . ± . ( . ) . ± . ( . ) . ± . ( . ) c . ± . ( . ) . ± . ( . ) . ± . ( . ) MNRAS000
Kolmogorov-Smirnov Test for GMC properties corrected for the CPROPS biasProp. Bar vs. Arm Bar vs. Bar-end Arm vs. Bar-end σ v . ± . ( . ) . ± . ( . ) . ± . ( . ) R . ± . ( . ) . ± . ( . ) . ± . ( . ) M mol . ± . ( . ) . ± . ( . ) . ± . ( . ) M vir . ± . ( . ) . ± . ( . ) . ± . ( . ) Σ mol . ± . ( . ) . ± . ( . ) . ± . ( . ) α vir . ± . ( . ) . ± . ( . ) . ± . ( . ) c . ± . ( . ) . ± . ( . ) . ± . ( . ) MNRAS000 , 1–17 (2019) F. Maeda et al.
Table B1.
GMC catalogID RA Dec v LSR T peak S/N σ v R M mol M vir α vir Reg Flag(J2000) (J2000) ( km s − ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) )1 h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± , 1–17 (2019) MC properties in the strongly barred galaxy NGC 1300 Table B1 – continued GMC catalogID RA Dec v LSR T peak S/N σ v R M mol M vir α vir Reg Flag(J2000) (J2000) ( km s − ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) )63 h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ±000
GMC catalogID RA Dec v LSR T peak S/N σ v R M mol M vir α vir Reg Flag(J2000) (J2000) ( km s − ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) )1 h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± , 1–17 (2019) MC properties in the strongly barred galaxy NGC 1300 Table B1 – continued GMC catalogID RA Dec v LSR T peak S/N σ v R M mol M vir α vir Reg Flag(J2000) (J2000) ( km s − ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) )63 h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ±000 , 1–17 (2019) F. Maeda et al.
Table B1 – continued GMC catalogID RA Dec v LSR T peak S/N σ v R M mol M vir α vir Reg Flag(J2000) (J2000) ( km s − ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) )125 h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± , 1–17 (2019) MC properties in the strongly barred galaxy NGC 1300 Table B1 – continued GMC catalogID RA Dec v LSR T peak S/N σ v R M mol M vir α vir Reg Flag(J2000) (J2000) ( km s − ) (K) ( km s − ) (pc) ( M (cid:12) ) ( M (cid:12) )187 h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± ± ± ± ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ± h m . s − ◦ (cid:48) . (cid:48)(cid:48) ± < ±000