ALMA Observations of Massive Clouds in the Central Molecular Zone: Ubiquitous Protostellar Outflows
Xing Lu, Shanghuo Li, Adam Ginsburg, Steven N. Longmore, J. M. Diederik Kruijssen, Daniel L. Walker, Siyi Feng, Qizhou Zhang, Cara Battersby, Thushara Pillai, Elisabeth A. C. Mills, Jens Kauffmann, Yu Cheng, Shu-ichiro Inutsuka
DD RAFT VERSION J ANUARY
21, 2021Typeset using L A TEX twocolumn style in AASTeX63
ALMA Observations of Massive Clouds in the Central Molecular Zone: Ubiquitous Protostellar Outflows X ING L U ( 吕 行 ), S HANGHUO L I ,
2, 3, 4 A DAM G INSBURG , S TEVEN
N. L
ONGMORE , J. M. D
IEDERIK K RUIJSSEN , D ANIEL
L. W
ALKER , S IYI F ENG ,
9, 10, 11 Q IZHOU Z HANG , C ARA B ATTERSBY , T HUSHARA P ILLAI , E LISABETH
A. C. M
ILLS , J ENS K AUFFMANN , Y U C HENG , AND S HU - ICHIRO I NUTSUKA
National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan Korea Astronomy and Space Science Institute, 776 Daedeokdae-ro, Yuseong-gu, Daejeon 34055, Republic of Korea Shanghai Astronomical Observatory, Chinese Academy of Sciences, 80 Nandan Road, Shanghai 200030, P. R. China University of Chinese Academy of Sciences, 19A Yuquanlu, Beijing 100049, P. R. China Department of Astronomy, University of Florida, P.O. Box 112055, Gainesville, FL 32611, USA Astrophysics Research Institute, Liverpool John Moores University, IC2, 146 Brownlow Hill, Liverpool, L3 5RF, United Kingdom Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstraße 12-14, D-69120 Heidelberg, Germany Department of Physics, University of Connecticut, 196A Auditorium Road, Storrs, CT 06269, USA National Astronomical Observatories, Chinese Academy of Science, Beijing 100101, P. R. China Academia Sinica Institute of Astronomy and Astrophysics, No. 1, Section 4, Roosevelt Road, Taipei 10617, Taiwan National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo, 181-8588, Japan Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA Institute for Astrophysical Research, 725 Commonwealth Ave, Boston University Boston, MA 02215, USA Department of Physics and Astronomy, University of Kansas, 1251 Wescoe Hall Dr., Lawrence, KS 66045, USA Massachusetts Institute of Technology, 99 Millstone Road, Haystack Observatory, Westford, MA 01886, USA Department of Astronomy, University of Virginia, Charlottesville, VA 22904, USA Department of Physics, Graduate School of Science, Nagoya University, Nagoya 464-8602 , Japan (Received - -, –; Revised - -, –; Accepted - -, –)
Submitted to ApJABSTRACTWe observe 1.3 mm spectral lines at 2000 AU resolution toward four massive molecular clouds in the Cen-tral Molecular Zone of the Galaxy to investigate their star formation activities. We focus on several potentialshock tracers that are usually abundant in protostellar outflows, including SiO, SO, CH OH, H CO, HC N, andHNCO. We identify 43 protostellar outflows, including 37 highly likely ones and 6 candidates. The outflowsare found toward both known high-mass star forming cores and less massive, seemingly quiescent cores, while791 out of the 834 cores identified based on the continuum do not have detected outflows. The outflow massesrange from less than 1 M (cid:12) to a few tens of M (cid:12) , with typical uncertainties of a factor of 70. We do not findevidence of disagreement between relative molecular abundances in these outflows and in nearby analogs suchas the well-studied L1157 and NGC7538S outflows. The results suggest that i) protostellar accretion disksdriving outflows ubiquitously exist in the CMZ environment, ii) the large fraction of candidate starless coresis expected if these clouds are at very early evolutionary phases, with a caveat on the potential incompletenessof the outflows, iii) high-mass and low-mass star formation is ongoing simultaneously in these clouds, and iv)current data do not show evidence of difference between the shock chemistry in the outflows that determinesthe molecular abundances in the CMZ environment and in nearby clouds. Keywords:
Galatic: center — stars: formation — ISM: clouds
Corresponding author: Xing [email protected], [email protected] INTRODUCTIONStar formation in the Central Molecular Zone (CMZ; theinner 500 pc of our Galaxy) has been a controversial topic.With more than M (cid:12) gas of mean density at cm − (Morris & Serabyn 1996; Ferrière et al. 2007; Longmore a r X i v : . [ a s t r o - ph . GA ] J a n L U ET AL .et al. 2013a), the CMZ exhibits about 10 times less efficientstar formation than expected by dense gas-star formation re-lations that have been tested toward nearby molecular cloudsand external galaxies (Longmore et al. 2013a; Kruijssen et al.2014; Barnes et al. 2017). Massive clouds in the CMZ havebeen suggested to be progenitors of young massive star clus-ters (Longmore et al. 2013b; Rathborne et al. 2015; Walkeret al. 2016), but observations reveal inefficient star formationin these clouds (Kauffmann et al. 2017; Walker et al. 2018;Lu et al. 2019a,b), with an overall dearth of compact densecores across much of the CMZ (Battersby et al. 2020; Hatch-field et al. 2020).In Lu et al. (2020, hereafter Paper I), we reported ALMABand 6 continuum observations toward four clouds, includ-ing the 20 km s − cloud, the 50 km s − cloud, Sgr B1-off,and Sgr C, which are some of the most massive clouds in theCMZ and show signs of embedded star formation (Kauff-mann et al. 2017). We identified hundreds of 2000 AU-scale cores in three of the clouds (the exception being the50 km s − cloud), and suggested that the three clouds willlikely form OB associations that contain less than 20 high-mass stars and have a spatial extent of ∼ − cloud, no cores above the 5 σ level and larger thanthe synthesized beam were found, likely because this cloudhas evolved to a much later phase when cold cores vanishand H II regions dominate (Mills et al. 2011). At sub-0.1 pcscales, we found evidence of thermal Jeans fragmentationand a similar core mass function as in Galactic disk clouds,which may hint at similar star formation processes at smallspatial scales taking place in the CMZ and elsewhere in theGalaxy.However, it is unclear whether these cores are prestellaror protostellar (i.e., whether there are already embedded pro-tostars). In Lu et al. (2019a,b), we used H O masers, classII CH OH masers, and ultra-compact H II regions to tracehigh-mass star formation and identified a few high-mass starforming regions in these clouds. Yet, the relatively poor res-olution of those observations, ∼ (cid:48)(cid:48) ( ∼ II regions trace a later evolutionaryphase of high-mass star formation, such that we may misslow to intermediate-mass star formation or early evolution-ary phases of high-mass star formation. The masers are ableto reveal low to intermediate-mass star formation, but sufferfrom potentially low detection rates and contamination frommasing sources other than star forming regions.To this end, molecular outflows associated with the 2000AU-scale cores are a promising tracer of star formation. Out-flows are ubiquitously found in star forming regions, andare detected around both low-mass and high-mass protostarsacross a wide range of evolutionary phases as long as gas ac- cretion is underway (e.g., Zhang et al. 2005; Arce et al. 2010;Li et al. 2019, 2020). Several molecular lines that are poten-tial outflow tracers were observed along with the continuumdata in Paper I. Therefore, in this paper we use the lines tosearch for direct evidence of star formation in the form ofprotostellar outflows.In addition, the shock chemistry in protostellar outflows inthe CMZ is poorly constrained. For one thing, only a hand-ful of protostellar outflows have been detected in the CMZ,which are mostly in the most actively star forming region,Sgr B2 (Qin et al. 2008; Higuchi et al. 2015). More re-cently, with the advent of high resolution ALMA observa-tions, more outflows are being detected outside of Sgr B2(e.g., D. Walker et al. submitted, 2020). On the other hand,the chemistry of the molecular gas at pc scales in the CMZseems to be distinct from that in the solar neighborhood,with noticeable enhancement of complex organic moleculesand shock tracers throughout the CMZ (Martín-Pintado et al.1997; Requena-Torres et al. 2006, 2008; Menten et al. 2009),likely caused by the extreme conditions such as widespreadshocks, high gas temperatures, high cosmic ray fluxes, andhigh X-ray fluxes (Mills & Morris 2013; Ginsburg et al.2016; Henshaw et al. 2016; Padovani et al. 2020; Bykov et al.2020). Once we obtain a large sample of outflows, we willbe able to systematically compare the relative abundances ofthe molecules in these outflows to those in nearby clouds, toinvestigate whether the shock chemistry differs between theCMZ and elsewhere in the Galaxy at sub-0.1 pc scales.In the following, we first introduce our ALMA observa-tion and data reduction strategies, as well as an assessmentof the missing flux issue in Section 2. Then in Section 3 wesummarize our observational results, including an overviewof the line emission and a visual identification of outflows.In Section 4, we estimate column densities, molecular abun-dances, and masses of the outflows, and discuss the implica-tions to chemistry and star formation. We conclude our paperin Section 5. In Appendix A, we introduce the procedures toestimate column densities using the molecular line data. InAppendix B, we list properties of the identified outflows in adetailed table. Throughout the paper we adopt a distance of8.178 kpc to the CMZ (Gravity Collaboration et al. 2018). OBSERVATIONS AND DATA REDUCTION2.1.
ALMA Observations
The ALMA observations were carried out in the C40-3 andC40-5 configurations in April and July of 2017 (project code:2016.1.00243.S). Details of the sample selection, observationsetup, and data calibration can be found in Paper I. The fourclouds in the sample are listed in Table 1. The covered fieldsare chosen based on Submillimeter Array (SMA) and VLAobservations that revealed potential sites of high-mass starformation including H O masers and massive dense cores
ROTOSTELLAR O UTFLOWS IN
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LOUDS
20 km s − Hot Core ( V lsr =26.6 km s − ) S i O - c - C H ( , )- ( , ) H C O - HC N - CH O H - H C O - C O - HNC O , - , H C O -
11 13 C O - S O - CH CN -
217 218 219 220020406080100
20 km s − Filament ( V lsr =12.0 km s − )
232 233 234 235 − − − −
20 0 20 40 60 V lsr (km/s) − I ν ( m Jy bea m − ) CO spectrumC O spectrum × I ν ( m Jy bea m − ) Sky Frequency (GHz)
Figure 1.
Typical 1.3 mm spectra captured by ALMA, toward a star forming hot core and a chemically quiescent region spatially offset fromstar forming regions in the 20 km s − cloud, respectively. The corresponding positions where the spectra are extracted are denoted by bluearrows and labeled in Figure 2. The lines plotted in Figure 2 are highlighted by vertical dashed lines. Most of the other lines detected towardthe hot core are from rotational transitions of complex organic molecules. The inset shows the CO and C O spectra toward the hot corealong the V lsr axis. Absorption at − −
30, and − − owing to foreground gas is seen. of 0.2 pc scale (Lu et al. 2019a). We imaged the Band 6(1.3 mm) spectral lines using CASA 5.4.0. The covered fre-quencies range from 217–221 GHz to 231–235 GHz with auniform channel width of 0.977 MHz (1.3 km s − ). The ef-fective spectral resolution is 1.129 MHz (1.5 km s − ) after aHanning smoothing done by the observatory.We first manually identified line-free channels in the vis-ibility data, and fed them to the uvcontsub task to subtractthe continuum baseline. Then we used the tclean task to im-age the spectral lines, with Briggs weighting and a robustparameter of 0.5, and multi-scale algorithm with scales of [0,5, 15, 50, 150] pixels and a pixel size of 0 . (cid:48)(cid:48)
04. The imagereconstruction was carried out in a two-step manner: first,the auto-masking algorithm with the recommended parame-ters was employed in tclean to automatically identify andclean signals; then the tclean task was restarted using cleanmodels and residuals from the previous step as input, andall pixels within 20% primary beam response included inthe clean mask, to a threshold of ∼ σ (8 mJy beam − perchannel), in order to clean any residual significant signals.In a few cases where strong spatially diffuse emission is de-tected (e.g., H CO in the 20 km s − cloud), a threshold of8 mJy beam − may be too low and causes the clean algorithmto diverge. We elevated the threshold to 10 mJy beam − for https://casaguides.nrao.edu/index.php/Automasking_Guide these lines. We have compared images produced by our auto-matic approach with those produced by a fine-tuned manual tclean of several lines, and found that the images are almostidentical.The resulting synthesized beam is on average 0 . (cid:48)(cid:48) × . (cid:48)(cid:48) × (cid:48)(cid:48) ( ∼ − (0.8–1.0 K in brightness temperatures) per 1.3 km s − chan-nel depending on frequencies and regions.2.2. Assessing the Missing Flux
By their nature, interferometric observations do not re-cover structures on size scales larger than their largest recov-erable angular scale (10 (cid:48)(cid:48) or 0.4 pc for these observations).If structures larger than this exist in the field, the flux cap-tured by interferometers will be smaller than the true flux,which is referred to as the missing flux problem. Spatially ex-tended ( (cid:38)
U ET AL . Table 1.
Properties of the clouds.
Cloud V lsr No. of cores No. of outflows Fraction with outflows ¯ X (SiO) ¯ X (SO) ¯ X (CH OH) ¯ X (H CO) ¯ X (HC N) ¯ X (HNCO)(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)The 20 km s − cloud 12.5 471 20 0.042 1.69 × − × − × − × − × − × − Sgr B1-off 31.1 89 5 0.056 1.39 × − × − × − × − × − × − Sgr C − × − × − × − × − × − × − All three clouds · · ·
834 43 0.052 2.05 × − × − × − × − × − × − The 50 km s − cloud 48.6 0 0 · · · · · · · · · · · · · · · · · · · · · N OTE —Column (1): cloud name. Column (2): V lsr of the cloud (Kauffmann et al. 2017). Column (3): number of the identified cores (Paper I). Column (4): number of the identified outflows inthis work. Column (5): fraction of the cores that have identified outflows. Columns (6–11): mean molecular abundances of all the outflows in the cloud. Only the abundances with independentmeasurements are considered (entries without notes in the last column in Table 3; see Section 4.1.2). However, we note several issues that prevent us from ef-ficiently combining the data: i) The sensitivity of the SMAdata is not optimal for the combination. For several regions,e.g., Sgr C, the SMA observation recovers an even smallerflux than the ALMA data, suggesting that some weaker emis-sion is missed by the SMA data due to its lower sensitivity. ii)Several regions of particular interest (e.g., the western part ofSgr C) are not well sampled by existing SMA observations.We attempted to combine the ALMA and SMA data, byconcatenating the visibility data and imaging them together.The resulting image is not improved compared to the ALMAimage, e.g., the rms becomes higher, and the integrated fluxesof several spatially extended structures do not increase sig-nificantly (in the extreme case of Sgr C, the fluxes even de-crease).Therefore, we conclude that the imaging of diffuse struc-tures does not benefit from the addition of the SMA data.This does not rule out the possibility that better shorter base-line data may help. A longer SMA observation, or an ACAobservation that provides better sensitivity than the SMA,would be necessary to be combined with the ALMA data torecover spatially extended emission.Meanwhile, we compared the integrated fluxes recoveredby the CSO and ALMA, focusing on the SiO emission inSgr C which is the most spatially extended in our data andthus the most affected by the missing flux. In a circle of50 (cid:48)(cid:48) diameter centered in between the two clusters in Sgr C,the ALMA/CSO SiO integrated fluxes are measured to be120/200 Jy km s − . The ALMA data recover 60% of the fluxobserved by the CSO. We thus estimate an upper limit of 40%for the missed flux in our ALMA data. In Section 4.1.4, wewill see that this does not affect our estimate of outflow prop-erties, as the dominant uncertainty is the molecular abun-dance that is unconstrained by several orders of magnitude. RESULTS3.1.
Overview of the Line Emission
Typical spectra toward a chemically active core and a rel-atively quiescent region spatially offset from any cores but with line emission are shown in Figure 1. The former showscharacteristic hot molecular core chemistry, while the lat-ter represents regions that are likely influenced by pc scaleshocks prevailing in the CMZ. Note that there exist evenmore chemically active cores (e.g., the two UC H II regionsin Sgr C), with many more spectral lines detected, mostlyfrom complex organic molecules. Here, we focus on the spa-tially extended spectral line emission detected outside of thehot cores or UC H II regions, and leave the discussion of theline-rich chemically active cores to a future paper.We identified spatially extended line species, and plottedtheir integrated intensities in Figures 2–5. The line speciesinclude the CO isotopologue C O, a group of potentialshock tracers (SiO, SO, HNCO, CH OH), and several densegas tracers that are sometimes found in outflows (H CO,H
CO, CH CN, c-C H , HC N). CO emission is morespatially extended than C O and is not plotted. Three fea-tures are clearly seen: i) Linear structures spatially associ-ated with dust emission are prominent, which may be out-flow lobes (black boxes in the figures). ii) Multiple lines aretracing similar filamentary structures that are spatially offsetfrom any dust emission, including some that are more typ-ically confined to hot cores in environments outside of theCMZ (e.g., CH CN), whose nature is unclear. An exam-ple is marked by the blue arrow in Figure 2. iii) Point-likeSiO emission with large linewidths ( >
20 km s − ) is foundtoward two H O masers that have known AGB star counter-parts (magenta crosses in Figures 2 & 4; see Lu et al. 2019a),with no associated dust emission within a radius of 0.1 pc,which is probably originated from the atmosphere of AGBstars (González Delgado et al. 2003). Here we focus on thefirst feature, potential outflows, while leaving the discussionof the other features to future papers.The two CO isotopologue lines, CO and C O, presentstrong absorption at velocities of − −
30, and − − against strong continuum emission (see the inset in Fig-ure 1). These are consistent with the absorption features seenin other line observations toward the Galactic Center (e.g.,Jones et al. 2012), and are attributed to foreground gas in spi- ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ Spitzer µ m& 1.3 mm continuum 0.3 pcHot CoreFilament ABC DE FG SiO 5-4 h m s s s s − ◦ RA (J2000) D e c ( J ) CO 3(0,3)-2(0,2) h m s s s s CO 3(2,1)-2(2,0) h m s s s s CO 3(1,2)-2(1,1)
Figure 2.
Molecular line emission in the 20 km s − cloud. The inner and outer dashed loops in all panels demonstrate the 50% and 30%primary beam responses of the ALMA mosaics. The first panel shows a three-color image made from Spitzer
IRAC 3.6, 4.5, and 5.8 µ m bands,with yellow contours overlaid illustrating the ALMA 1.3 mm continuum emission at levels of [5,25,45] × µ Jy beam − . Positions of H Omasers are marked by crosses, among which those with AGB star counterparts (Lu et al. 2019a) are colored in magenta. The other panels showintegrated intensities of molecular lines in a logarithmic scale, which are integrated in a velocity range of [ − , ] km s − , except for CH OHand CH CN where this range is adjusted to avoid confusion with adjacent lines. The colorbars are in unit of Jy beam − km s − . In selectedpanels, black boxes show regions where outflows are identified, with zoomed-in views presented in Figures 6–22. L U ET AL . − ◦ O 2-1 H h m s s s s − ◦ RA (J2000) D e c ( J ) N 24-23 h m s s s s OH 4(2,2)-3(1,2) h m s s s s CN 12(0/1)-11(0/1)
Figure 2.
Continued.
ROTOSTELLAR O UTFLOWS IN
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LOUDS − ◦ Spitzer µ m& 1.3 mm continuum 0.3 pcSiO 5-4 − ◦ CO 3(0,3)-2(0,2) CO 3(2,1)-2(2,0)
CO 3(1,2)-2(1,1) − ◦ O 2-1 H h m s s s − ◦ RA (J2000) D e c ( J ) N 24-23 h m s s s OH 4(2,2)-3(1,2) h m s s s CN 12(0/1)-11(0/1)
Figure 3.
Molecular line emission in the 50 km s − cloud. The layout of panels and symbols is the same as in Figure 2. L U ET AL .ral arms along the line of sight. In particular, the absorptionat −
55 km s − is close to the cloud velocity of Sgr C, whichcomplicates the interpretation of the two lines in Sgr C. Manyof the lines, including H CO, CH OH, SiO, and the two COisotopologues themselves, also present absorption features ata few km s − blue-shifted with respect to the cloud veloc-ity toward continuum emission peaks (e.g., the absorption at ∼
12 km s − in the inset of Figure 1). These features arelikely owing to a combination of missing flux as a result of in-terferometer observations and self absorption when the linesbecome optically thick.3.2. Identification of Outflows
Signatures of protostellar outflows have been detected to-ward Sgr B2(M) and (N), the two high-mass protoclusters inthe Sgr B2 complex (Qin et al. 2008; Higuchi et al. 2015;Bonfand et al. 2017). Outside of Sgr B2, detecting proto-stellar outflows has been challenging in the CMZ, becauseof the lack of resolution to spatially resolve outflows andthe prevalence of broad linewidth gas produced by phenom-ena other than outflows (Henshaw et al. 2019; Sormani et al.2019). Previous Submillimeter Array (SMA) observationshave detected widespread emission of potential shock trac-ers (e.g., SiO, SO, CH OH) at 0.2 pc scales in CMZ clouds(Kauffmann et al. 2013; Lu et al. 2017; Battersby et al. 2020).However, limited by the angular resolution and the imagingsensitivity, it was unclear whether the emission seen by theSMA is owing to protostellar outflows or pc-scale shocks pre-vailing in the CMZ. Only recently, ALMA observations withhigh resolution and high sensitivity start to detect outflows inthe CMZ, e.g., in the G0.253 + CO, HNCO, HC N, andCH OH. All these tracers have been previously found to beenhanced by at least one order of magnitude in shocked re-gions in protostellar outflows (e.g., Bachiller & Pérez Gutiér-rez 1997). We applied the following criteria to identify out-flows:i) We used the H O masers from Lu et al. (2019a) asa guidance to search for associated shock tracer emission.First, we made integrated intensity maps of SiO across thefull velocity range, and searched for linear structures spa-tially associated with the masers. If linear emission isfound, then, we made integrated intensity maps of blue andred shifted components based on the V lsr of the cloud (see Table 1), and checked whether the linear structures showsymmetric blue and red shifted emission with respective tothe masers. Finally, we determined the systematic velocityof each individual outflow driving source, by using densegas tracers in the ALMA data toward the maser position(CH CN, HC N, CH OH, or C O, in a decreasing order ofpreference; C O was used only once, towards the 20 km s − cloud-F V lsr . Ifthe shock tracer emission exhibits blue and red shifted com-ponents with respect to the systematic velocity at oppositepositions to the maser position, it is considered as an outflow.ii) In cases where H O masers are not present, we checkedthe emission of the six tracers around the 2000-AU scalecores from Paper I following the same procedures, to searchfor blue and/or red shifted line emission spatially offset fromthe cores. We require the blue and/or red shifted features tobe seen in at least two shock tracers, including the canonicalshock tracer SiO, plus any of the five supplemental tracers.We identified 43 outflows, and marked regions where theyare detected with boxes in Figures 2–5. The zoomed-in viewsare in Figures 6–22, in which we plot the red/blue shiftedshock tracer emission with respect to the systematic velocityand highlight individual outflows with arrows. The position-velocity diagrams of the 43 outflows made from the SiO lineare displayed in Figure 23. The numbers of outflows identi-fied in the individual clouds are listed in Table 1.In several cases, lobes from different outflows spatiallyoverlap with each other (e.g., outflows − cloud; see Figure 8), but we were able to sepa-rate them apart unambiguously based on velocities (see Fig-ure 23). Most of the other outflows are easily distinguishedspatially from nearby outflows and the diffuse emission. Allthese outflows are considered as ‘highly likely’. However,there exist cases where the outflows cannot be robustly sepa-rated from other outflows or the diffuse emission, either spa-tially or kinematically. One example is the two blue-shiftedlobes in region B of the 20 km s − cloud, where the lobesoverlap in both projected locations and velocities (see Fig-ures 7 & 23). Following the definitions in Li et al. (2020),we classified these ambiguous identifications as ‘candidates’.The classifications are noted with asterisks in Table 3, Fig-ures 6–22, and Figure 23. Among the 43 outflows, 37 arehighly likely, and 6 are candidates.We stress that this visual identification is likely to be in-complete. Potential outflows could have been missed if theycannot be distinguished from the background emission orother outflows, or if their emission is too weak. The ac-tual (in)completeness, however, is difficult to quantify, as theidentification is based on visual inspection and is subjectivein nature. Recent ALMA surveys toward infrared dark cloudsin the Galactic disk using CO lines as the primary outflow ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ Spitzer µ m& 1.3 mm continuum 0.3 pcAB CSiO 5-4 h m s s s s − ◦ RA (J2000) D e c ( J ) CO 3(0,3)-2(0,2) h m s s s s RA (J2000) CO 3(2,1)-2(2,0) h m s s s s RA (J2000)
CO 3(1,2)-2(1,1)
Figure 4.
Molecular line emission in Sgr B1-off. The layout of panels and symbols is the same as in Figure 2.
U ET AL .tracer yield detection rates of 14%–22% (e.g., 62 out of 280cores in Kong et al. 2019 and 41 out of 301 cores in Li et al.2020 are identified with outflows). The detection rate usingSiO as the primary tracer in this paper is 4–7% (Table 1),which is much lower. It is infeasible to directly compare,e.g., the outflow mass sensitivities of previous surveys andours, considering that the observations use different lines asoutflow tracers and assume different abundances. Assumingthat the observations are sufficiently sensitive to detect allexiting outflows, the lower detection rate in our sample maysuggest that we have missed a substantial number of outflowsthat are not traced by SiO, or may reflect the variation of out-flow occurrence rates along the evolutionary stages.Meanwhile, we also note that due to the complicated en-vironment in the CMZ (e.g., the wide-spread shock traceremission; Martín-Pintado et al. 1997) and possible contam-ination from the foreground, it is likely that false positiveidentifications exist in our sample if such large scale shocktracer emission accidentally lies upon cores. But such acci-dental spatial coincidence should be rare, as the velocities ofthe identified outflows and cores have a continuous overlap(Figure 23). Note that the cores associated with the outflowsare all likely in the CMZ, given that the velocities of theirline emission (e.g., C O; see Figure 1 inset) are consistentwith the overall velocity field in the CMZ (e.g., Henshawet al. 2016), while spiral arm clouds along the line of sightare mostly seen as absorption in CO and C O (Figure 1inset), indicating that the overlapping spiral arm clouds con-sist of low-density gas and hence are unlikely to have densecores.SiO and SO seem to be the best outflow tracers amongthe six molecules. Their emission is usually well separatedfrom the background, and is usually collimated as expectedfor outflows. CH OH, H CO, and HNCO often suffer fromcontamination from the background or foreground emission,and thus are not tracing the outflows as well as SiO and SO.HC N traces both cores and outflows. Its emission is weakerthan the other molecules, therefore is not an optimized out-flow tracer either. As pointed out by several previous studies,CH OH, H CO, HC N, and HNCO may be released intothe gas phase by slow ( (cid:46)
20 km s − ) shocks that evaporateice mantles of dust or be produced by gas phase reactionsin post-shock regions, therefore probe the widespread low-velocity shocks in the CMZ (Lu et al. 2017; Tanaka et al.2018; Taniguchi et al. 2018). SiO and SO, on the other hand,may be released from the dust by sputtering of the grain core,thus better probe fast ( (cid:38)
20 km s − ) shocks induced by theoutflows. ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ O 2-1 H h m s s s s − ◦ RA (J2000) D e c ( J ) N 24-23 h m s s s s RA (J2000) OH 4(2,2)-3(1,2) h m s s s s RA (J2000) CN 12(0/1)-11(0/1)
Figure 4.
Continued.
U ET AL . − ◦ Spitzer µ m& 1.3 mm continuum 0.3 pcA B CDE FGSiO 5-4 − ◦ CO 3(0,3)-2(0,2) h m s s s s − ◦ RA (J2000) D e c ( J ) CO 3(2,1)-2(2,0) h m s s s s CO 3(1,2)-2(1,1)
Figure 5.
Molecular line emission in Sgr C. The layout of panels and symbols is the same as in Figure 2.
ROTOSTELLAR O UTFLOWS IN
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LOUDS − ◦ O 2-1 − ◦ H N 24-23 h m s s s s − ◦ RA (J2000) D e c ( J ) OH 4(2,2)-3(1,2) h m s s s s CN 12(0/1)-11(0/1)
Figure 5.
Continued.
U ET AL . − ◦ D e c ( J )
20 km s − -A SiO[27, 45] km s − [0, 24] km s − − [2, 24] km s − OH[27, 38.3] km s − [-5, 24] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[27, 39.5] km s − [2.8, 24] km s − h m s s RA (J2000) N[27, 40] km s − [5.7, 24] km s − h m s s RA (J2000) − [11, 24] km s − Figure 6.
Outflows in region A in the 20 km s − cloud. The gray scale image in all panels shows the ALMA 1.3 mm continuum emission, withthe scale bar at the top in unit of mJy beam − in a logarithmic scale. The green crosses mark positions of the H O masers in Lu et al. (2019a).In each panel, the blue and red contours illustrate the blue and red shifted line emission integrated within the specified velocity ranges, at levelsof [3,6,12] σ , where σ = √ Nσ c v c , N being the number of channel, σ c the rms of individual channels, and v c the channel width in km s − .When there are multiple outflows in the panel, the velocity ranges are chosen to highlight the bipolar morphologies of all the outflows, but forindividual outflows, the blue and red shifted lobes may extend beyond these velocity ranges or be contaminated by diffuse gas, which can bebetter visualized in Figure 23. Identified outflows are highlighted by blue and red arrows, but note that some outflows are not seen in all thelines (in the case shown here, outflow ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ D e c ( J ) − -B SiO ] ] [17, 38] km s − [-10, 14] km s − − [-10, 14] km s − OH[17, 25] km s − [-10, 14] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[17, 30] km s − [-15, 14] km s − h m s s RA (J2000) N[17, 26.1] km s − [0, 14] km s − h m s s RA (J2000) − [2, 14] km s − Figure 7.
Outflows in region B in the 20 km s − cloud. − ◦ D e c ( J ) − -C SiO ] ] [16, 40] km s − [-10, 14] km s − − [-10, 14] km s − OH[16, 35] km s − [-5, 14] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[16, 35] km s − [-5, 14] km s − h m s s RA (J2000) N[16, 30] km s − [0, 14] km s − h m s s RA (J2000) − [5, 14] km s − Figure 8.
Outflows in region C in the 20 km s − cloud. U ET AL . − ◦ D e c ( J )
20 km s − -D SiO[12, 35] km s − [-20, 10] km s − − [-20, 10] km s − OH[12, 18] km s − [-10, 10] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[12, 20] km s − [-10, 10] km s − h m s s RA (J2000) N[12, 17.9] km s − [-1.1, 10] km s − h m s s RA (J2000) − [-6, 10] km s − Figure 9.
Outflows in region D in the 20 km s − cloud. − ◦ D e c ( J )
20 km s − -E SiO[12.3, 24.5] km s − [-34.9, 9.9] km s − − [-10, 10.1] km s − OH[12.5, 18] km s − [5.8, 9.9] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[12.3, 20.5] km s − [-0.1, 9.9] km s − h m s s RA (J2000) N[12.4, 22.4] km s − [-0.1, 9.9] km s − h m s s RA (J2000) − [0.1, 10.1] km s − Figure 10.
Outflows in region E in the 20 km s − cloud. ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ D e c ( J )
20 km s − -F SiO[7.4, 29.9] km s − [-21.4, 4.8] km s − − [-2, 4.8] km s − OH[7.1, 17.1] km s − [-1, 4.8] km s − h m s s s − ◦ RA (J2000) D e c ( J ) CO[7.4, 16.5] km s − [-3.9, 4.8] km s − h m s s s RA (J2000) N[7.4, 17.4] km s − [-5.2, 4.8] km s − h m s s s RA (J2000) − [-2, 4.8] km s − Figure 11.
Outflows in region F in the 20 km s − cloud. − ◦ D e c ( J ) ]
20 km s − -G SiO[9.6, 29.9] km s − [-12, 7.2] km s − − [-0.6, 7.5] km s − OH[9.8, 16.7] km s − [0.4, 7.2] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[9.6, 17.8] km s − [-2.8, 7.2] km s − h m s s RA (J2000) N[9.7, 16.6] km s − [4.3, 7.2] km s − h m s s RA (J2000) − [-0.6, 7.5] km s − Figure 12.
Outflows in region G in the 20 km s − cloud. U ET AL . − ◦ D e c ( J ) Sgr B1-off-A SiO[29.7, 51.5] km s − [3.2, 27.2] km s − − [4.7, 27.1] km s − OH[29.7, 49.1] km s − [-2.3, 27.1] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[29.7, 51.6] km s − [4.2, 27.3] km s − h m s s RA (J2000) N[29.7, 39.6] km s − [9.7, 27.4] km s − h m s s RA (J2000) − [22.1, 27.1] km s − Figure 13.
Outflows in region A in Sgr B1-off. − ◦ D e c ( J ) Sgr B1-off-B SiO[29.9, 39.4] km s − [17.7, 27.5] km s − − [18.3, 27.5] km s − OH[30.1, 35.6] km s − [22.0, 27.5] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[29.9, 40.8] km s − [18.3, 27.5] km s − h m s s RA (J2000) N[30.0, 39.3] km s − [18.3, 27.5] km s − h m s s RA (J2000) − [18.3, 27.5] km s − Figure 14.
Outflows in region B in Sgr B1-off.
ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ D e c ( J ) Sgr B1-off-C SiO[31, 50] km s − [8.3, 29] km s − − [20, 29] km s − OH[31, 40] km s − [20, 29] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[31, 40] km s − [20, 29] km s − h m s s RA (J2000) N[31, 39.6] km s − [21.9, 29] km s − h m s s RA (J2000) − [20.7, 29] km s − Figure 15.
Outflows in region C in Sgr B1-off. − ◦ D e c ( J ) Sgr C-A SiO[-50.3, -15] km s − [-80, -52.8] km s − − [-70, -52.9] km s − OH[-50.3, -45] km s − [-60, -52.9] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[-50.3, -35] km s − [-65, -52.9] km s − h m s s RA (J2000) N[-50.3, -40] km s − [-60, -52.9] km s − h m s s RA (J2000) − [-63.3, -52.9] km s − Figure 16.
Outflows in region A in Sgr C.
U ET AL . − ◦ D e c ( J ) ] Sgr C-B SiO[-50, -35] km s − [-80, -54] km s − − [-70, -54] km s − OH[-50, -40] km s − [-60, -54] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[-50, -40] km s − [-70, -54] km s − h m s s RA (J2000) N[-50, -40] km s − [-60, -54] km s − h m s s RA (J2000) − [-60, -54] km s − Figure 17.
Outflows in region B in Sgr C. − ◦ D e c ( J ) Sgr C-C SiO[-50, -42] km s − [-80, -52] km s − − [-65, -52] km s − OH[-50, -40] km s − [-65, -52] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[-50, -25] km s − [-70, -52] km s − h m s s RA (J2000) N[-50, -45] km s − [-70, -52] km s − h m s s RA (J2000) − [-60, -52] km s − Figure 18.
Outflows in region C in Sgr C.
ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS − ◦ D e c ( J ) Sgr C-D SiO[-50, -20] km s − [-80, -52] km s − − [-80, -52] km s − OH[-50, -45] km s − [-65, -52] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[-50, -32] km s − [-70, -52] km s − h m s s RA (J2000) N[-50, -40] km s − [-60, -52] km s − h m s s RA (J2000) − [-56, -52] km s − Figure 19.
Outflows in region D in Sgr C. − ◦ D e c ( J ) Sgr C-E SiO[-60, -45] km s − [-75, -63] km s − − [-67.3, -63] km s − OH[-60, -43] km s − [-67, -63] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[-60, -40] km s − [-70, -63] km s − h m s s RA (J2000) N[-60, -55] km s − [-68, -63] km s − h m s s RA (J2000) − [-67.3, -64.9] km s − Figure 20.
Outflows in region E in Sgr C.
U ET AL . − ◦ D e c ( J ) Sgr C-F SiO [-48, -25] km s − [-80, -51] km s − − [-80, -51] km s − − ◦ D e c ( J ) OH [-48, -39.8] km s − [-60, -51] km s − CO [-48, -33] km s − [-70, -51] km s − h m s s s s − ◦ RA (J2000) D e c ( J ) N [-48, -31.9] km s − [-63.1, -51] km s − h m s s s s RA (J2000) − [-69.9, -51] km s − Figure 21.
Outflows in region F in Sgr C.
ROTOSTELLAR O UTFLOWS IN
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LOUDS − ◦ D e c ( J ) Sgr C-G SiO[-58.3, -40.6] km s − [-73.1, -60.9] km s − − [-74, -60.9] km s − OH[-58.3, -45.3] km s − [-67, -60.9] km s − h m s s − ◦ RA (J2000) D e c ( J ) CO[-58.3, -42.8] km s − [-82.2, -60.9] km s − h m s s RA (J2000) N[-58.3, -50.8] km s − [-68.5, -60.9] km s − h m s s RA (J2000) − [-64.6, -60.9] km s − Figure 22.
Outflows in region G in Sgr C.
U ET AL .
20 km s − -A
20 km s − -A
20 km s − -B ]
20 km s − -B ]
20 km s − -C
20 km s − -C ]
20 km s − -C
20 km s − -C ]
20 km s − -C
20 km s − -C
20 km s − -C
20 km s − -C
20 km s − -C
20 km s − -D
20 km s − -D
20 km s − -D
20 km s − -D
20 km s − -E
20 km s − -F
20 km s − -G ] Sgr B1-off-A
Sgr B1-off-B
Sgr B1-off-C
Sgr B1-off-C
Sgr B1-off-C
Sgr C-A
Sgr C-A
Sgr C-B ] Sgr C-B
Sgr C-B
Sgr C-B
Sgr C-B
Sgr C-C
Sgr C-C
Sgr C-C
Sgr C-D
Sgr C-D
Sgr C-D
Sgr C-D
Sgr C-E
Offset (AU) V l s r ( k m s − ) Sgr C-F
Sgr C-F
Sgr C-G
Figure 23.
Position-velocity diagrams of the 43 outflows using the SiO line. The slices are taken along the arrows shown in Figures 6–22, fromthe blue-shifted to red-shifted side, averaged within a width of 5000 AU. The background image and the cyan contours show the SiO emission,with contour levels starting at 2 σ in step of 2 σ where σ ≈ − . The x axis is the spatial offset along the slices, and the y axis is V lsr .The vertical and horizontal dashed lines mark the position and V lsr of the cores, respectively. ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS DISCUSSION4.1.
Estimate of Physical Properties of the Outflows
In this section, we calculate the column densities of thesix molecules detected toward the identified outflows (Sec-tion 4.1.1), introduce the method to estimate the molecularabundances in the outflows (Section 4.1.2), and estimate theoutflow masses, and where possible, the outflow energetics(Section 4.1.3). The uncertainties involved in the estimate ofcolumn densities, abundances, and masses are discussed inSection 4.1.4. We need an order-of-magnitude estimate onthese parameters to discuss implications for astrochemistryand star formation in following sections, so the unavoidablesignificant uncertainties in these results (one to two orders ofmagnitude, as detailed in Section 4.1.4) are acceptable.4.1.1.
Column Densities of the Shock Tracers
We measure the molecular line integrated fluxes of the out-flows in the primary beam corrected maps within a contourlevel of 3 σ for each line, and list the results in Table 3. Thevelocity range of the integration is chosen to start from onechannel ( ∼ − ) away from V lsr of the core to avoiddiffuse emission around the system velocity, and end at thechannel where the emission drops below 2 σ . The separationof 1.3 km s − should be able to role out most of the diffusecomponent as the FWHM linewidth at 0.1 pc scale in theseclouds drops to this value and the linewidth at even smallerscales should be narrower (Kauffmann et al. 2017). The in-tegrated fluxes should be lower limits given limited sensitiv-ities and potential missed flux by the interferometer.We then derive column densities with the measured fluxes,using the calcu toolkit (Li et al. 2020). Local thermody-namic equilibrium (LTE) conditions and optically thin lineemission has been assumed. A constant excitation tempera-ture of 70 K, which is the characteristic gas kinetic tempera-ture in the CMZ (Ao et al. 2013; Ginsburg et al. 2016; Kriegeret al. 2017), is assumed for all the lines. Note that the adoptedtemperature is different from that assumed for the dust in thecores in Paper I, 20 K. Observations show that the gas tem-perature at ∼ N emission, which we choose as the an-chor molecule in the next section. The positions are adjusted https://github.com/ShanghuoLi/calcu to include emission of as many shock tracers as possible.A circle of 0 . (cid:48)(cid:48) Molecular Abundances
In order to obtain the masses of the outflows, we mustadopt an abundance for each shock tracer. However, theabundances of these molecules are known to be highly vari-able, especially toward the environment of our outflow sam-ple with both strong shocks and complicated factors in theCMZ. One example is SiO, whose abundance has been foundto vary by a factor of > across different regions (e.g.,Martín-Pintado et al. 1997; Sanhueza et al. 2012; Csengeriet al. 2016; Li et al. 2019).The dust emission is not always detected toward the out-flows, so anchor molecules with relatively well-constrainedabundances are often used to determine abundances of othermolecules. One commonly used anchor molecule is CO andits isotopologues (e.g., Feng et al. 2016). By assuming acanonical CO abundance of 10 − with respect to H (Blakeet al. 1987), one might in principle use CO emission to de-rive the H column density at a reference position in the out-flow, and then determine the abundances of other moleculesby dividing their column densities by the H column density.However, in our data, the CO lines suffer from strong absorp-tion and missing flux, and more importantly, morphologi-cally they are not tracing the outflows seen in other molecules(Figures 2–5), probably because they are optically thick thustracing the surface of the clouds instead of the outflows in theinterior.Therefore, we choose to anchor our estimate of molecularabundances on HC N, which is detected toward both coresand outflows and has shown a relatively stable abundance be-tween the core/outflow environments in other observations(e.g., a factor of ∼
30 enhancement from cores to outflowlobes around low-mass and high-mass protostars; Bachiller& Pérez Gutiérrez 1997; Feng et al. 2016; Mendoza et al.2018). The other molecules either show up only toward theoutflows (e.g., SiO, SO) or suffer from contamination by pc-scale diffuse emission or strong absorption toward the cores(e.g., CH OH, H CO, and HNCO), and thus are not appro-priate as the anchor tracer.First, we compare the column densities of HC N and of H toward the cores, and estimate abundances of HC N in thecores. The column densities of HC N is derived followingthe procedures in Section 4.1.1. The H column densities arederived using the dust continuum from Paper I. Then we as-6 L U ET AL .sume an enhancement of factor 30 (Bachiller & Pérez Gutiér-rez 1997; Feng et al. 2016), and obtain the abundances ofHC N in the outflows. Finally we derive the H column den-sity in the outflows and use it to calibrate the abundances ofthe other shock tracers. The adopted molecular abundanceswith respect to molecular hydrogen are listed in Table 3, andthe mean values of individual clouds are given in Table 1.The estimated HC N abundances in the outflows are con-sistent in terms of the order of magnitude with previous resulttoward the 20 km s − cloud using multiple HC N transitions( − – − depending on the assumptions; Walmsley et al.1986).We note that the estimated abundances of the moleculesspan a large range. For example, the SiO abundance with re-spect to H in our outflow sample ranges from 10 − to 10 − ,with a mean value of 2.05 × − . This justifies our choice ofestimating molecular abundances case by case, rather thanassuming a constant abundance, for the latter case will biasthe mass estimates significantly.There are several cases where we cannot directly determinethe abundance of a molecule in an outflow, and then we haveto circumvent them by making reasonable assumptions: i)One lobe of an outflow has a well-defined reference positionand the abundance can be determined from a scaling of theHC N emission, while the other lobe does not. In this case,we assume that the abundances of the blue/red-shifted lobesof the same outflow are identical and adopt the abundance ofthe other lobe. ii) An outflow has well-defined reference po-sitions in multiple molecular line emission including HC N,but the core associated with it does not have detectable HC Nemission, and therefore the abundance of HC N in the out-flow cannot be determined. In this case, we adopt a meanHC N abundance of all the other outflows in the region, andthen use it to determine abundances of other molecules inthis outflow. iii) An outflow has well-defined reference posi-tions in multiple molecular line emission, but not in HC N.We have to adopt mean molecular abundances of all the otheroutflows in the region for each of the detected molecules inthe outflow. All these cases are explicitly noted in Table 3.4.1.3.
Masses and Energetics of the Outflows
After the molecular column densities and abundances arederived, the outflow masses are estimated by assuming uni-form abundances within each outflow, using the calcu toolkit.The results are listed in Table 3, and plotted in Figure 24.For the same outflow lobe, multiple shock tracers could bedetected, in which case we derive more than one outflowmasses. All of these masses are deemed to be worth report-ing, as the different molecules may trace different compo-nents of the same outflow with different chemical environ-ments or excitation conditions. Nevertheless, the masses of Core mass ( M (cid:12) )10 − O u t fl o w m a ss ( M (cid:12) ) M (SiO) M (SO) M (CH OH) M (H CO) M (HC N) M (HNCO) Figure 24.
Outflow masses derived from different molecules, plot-ted against masses of the cores where the outflows originate. Theoutflow masses are the sum of those of the blue and red lobes,color-coded by molecular tracers based on which the masses areestimated. The systematic uncertainty of factor 70 in the outflowmasses is not plotted here. The black crosses denote the mean out-flow masses of the different molecules. the same outflow are consistent within an order of magnitudeas demonstrated in Figure 24.In a few cases where the outflow emission can be unam-biguously separated from contaminations and the lobes arewell collimated, we are able to measure the projected lengthand estimate a dynamical time-scale. Then the energeticsof the outflows, e.g., the outflow rate and the outflow me-chanical force, can be estimated following procedures in Liet al. (2020). One example of such well-defined outflowsis the blue-shifted lobe of the Sgr C region F (cid:48)(cid:48) ( ∼ − , the dynamical time-scaleis . × / cos ( θ ) yr where θ is the inclination angle of theoutflow lobe with respect to the plane of the sky. The out-flow mass rate is then ∼ × − cos ( θ ) M (cid:12) yr − . If the in-clination angle is not too large ( θ< ◦ ), the outflow massrate is (cid:38) − M (cid:12) yr − , which is usually found toward out-flows around high-mass young stellar objects (Maud et al.2015). It is also possible to estimate the accretion rate, withthe same assumptions in Li et al. (2020), e.g., a wind speed of500 km s − from the disk and a ratio between the accretionrate and the mass ejection rate of 3, which leads to a valueof . × − cos ( θ ) M (cid:12) yr − . However, there are significantuncertainties in the outflow masses (see next section) and thetrue physical scale of the outflow lobes (contamination, po-tentially missed weak emission, inclination angle), on top ofthe unconstrained assumptions made in the calculation of theaccretion rate (Li et al. 2020). We expect the uncertainty inthe estimated outflow mass rate and accretion rate to be po-tentially three orders of magnitude or even greater, which iscomparable to the dynamical range of our data (Figure 24).Therefore, we will not discuss these results further. ROTOSTELLAR O UTFLOWS IN
CMZ C
LOUDS
Uncertainties in the Estimated Parameters
There are several significant uncertainties in the estimateof column densities and outflow masses. First, we have as-sumed LTE conditions and a constant excitation temperatureof 70 K when calculating the column densities. If we con-sider subthermal excitation, then the excitation temperaturewould be substantially lower than the kinetic temperature. Ifthe temperature is varied between 20 and 100 K, a range thathas been observed toward the CMZ (Ao et al. 2013; Ginsburget al. 2016; Lu et al. 2017) and toward outflows in nearbyclouds (Lefloch et al. 2012), then the resulting mass willvary by 60%, or 0.2 dex. Considering that the temperaturecould be even higher in post-shock regions ( ∼ K; Tafallaet al. 2013), this uncertainty will only be larger. Second, wehave assumed optically thin emission for all the molecularlines, while this may be invalid especially for CH OH andH CO, whose optical depths are higher than the other molec-ular lines as evidenced by the strong self absorption towardthe cores. As shown in Figure 24, the masses of the sameoutflow estimated from different molecules are usually con-sistent within an order of magnitude. Therefore, the uncer-tainty in the outflow masses stemming from different opticaldepths of the molecular lines is estimated to be half of thisrange at most, or 0.5 dex. Third, as discussed in Section 2.2,the missing flux issue of the ALMA data may lead to an un-derestimate of 40% for the measured flux, or 0.15 dex. Thethree uncertainties above go into the calculation of columndensities.For outflow masses, the molecular abundances must betaken into account additionally. The abundances of theseshock tracers hinge on that of HC N, which is again basedon: i) the total molecular column densities in the cores thatare derived from the dust continuum, with dependences onthe assumed dust temperature, the dust opacity, and the gas-to-dust mass ratio (for detailed discussion, see Paper I), ii) theLTE condition assumed for the calculation of HC N columndensities in the cores, which may not hold given the non-LTEexcitation found in several CMZ clouds (Mills et al. 2018),and iii) the assumed enhancement of factor 30 of HC N fromthe core to the outflows. The estimated molecular abun-dances in the outflows usually span two orders of magnitude(Table 3). Therefore, we assign an uncertainty of one orderof magnitude to the abundances, and note that the uncertaintyis likely even greater.Taken together, we estimate an uncertainty of 0.85 dex(a factor of 7) in the column densities, and an uncertaintyof 1.85 dex (a factor of 70) in the outflow masses. Theseestimates are typical uncertainties for the individual out-flows, though for particular outflows the uncertainties may besmaller or larger (e.g., for outflows where molecular abun-dances cannot be determined so mean abundances of theregion are adopted, the uncertainties in the abundance and
SiO SO CH OH H CO HC N HNCOMolecules10 − − − − − − A bundan c e s (a) L1157 B1L1157 B2NGC7538S JetSSiO SO CH OH H CO HC N HNCOMolecules10 A bundan c e s no r m a li z edb y X ( HC N ) (b) L1157 B1L1157 B2NGC7538S JetS
Figure 25.
Absolute abundances of molecules with respect to H in the outflows are plotted in (a), and those normalized with respectto the abundance of HC N are plotted in (b). Here we only con-sider the abundances with independent measurements but excludethose guessed from other outflows (i.e., entries with notes in the lastcolumn in Table 3). The boxes denote the first to third quartileswhile the caps mark the full range of abundances in our outflowsample. The median of abundances of each molecule is marked bya horizontal orange line. The abundances of the low-mass outflowin L1157 and the high-mass outflow in NGC7538S are also plotted.The systematic uncertainties in the abundances are not plotted here. therefore the masses would be larger; for spatially compactoutflows, the underestimate of the fluxes because of the miss-ing flux issue would be less significant; for outflows withtemperatures higher than 100 K, the uncertainties in the col-umn densities and masses would be larger).4.2.
Shock Chemistry in the Outflows
We compare the relative abundances of the six shock trac-ers and investigate the shock chemistry in the outflows. Thisis the first spatially resolved astrochemical study toward out-flows in the CMZ, and one of the very few such studies evenincluding works toward Galactic disk targets.The abundances of the six shock tracers are presented inFigure 25. For each molecule, we plot the median of its abun-dances in all the outflows as a horizontal orange line.To understand the relative abundances of the six molecules,we compare our result with similar studies toward nearby8 L
U ET AL .star forming clouds. However, we note that spatially re-solved observations toward outflows that include all the sixmolecules, even for popular targets such as the Orion molec-ular cloud, are rare. For example, we are not able to finda paper that reports SiO, H CO, or HC N column densi-ties or abundances in the explosive outflow around OrionKL, even though results of SO, CH OH, and HNCO areavailable (Feng et al. 2015). In the end, we are ableto find only two representative outflows in nearby clouds:L1157, a well-studied, prototypical low-mass outflow arounda low-mass protostar (e.g., Bachiller & Pérez Gutiérrez 1997;Rodríguez-Fernández et al. 2010; Podio et al. 2017; Holdshipet al. 2019), and NGC7538S, a prototypical massive outflowaround a high-mass protostar (e.g., Naranjo-Romero et al.2012; Feng et al. 2016).We take the abundances of the six molecules towardL1157-B1 and B2 (two reference positions in the blue-shifted lobe) from Bachiller & Pérez Gutiérrez (1997) andRodríguez-Fernández et al. (2010). For NGC7538S, we takethe results from JetS, a reference position on the red-shiftedside of the protostar, from Feng et al. (2016), except for SiOthat is not observed by the authors. We instead obtain the SiOabundance at the reference position using data from Naranjo-Romero et al. (2012) (L. Zapata, private communications).The JetN position in Feng et al. (2016) does not show HC Nemission, and therefore only an upper limit of its abundancecan be detected, which prevents an appropriate comparisonto our results as we use HC N to infer the abundances of theother molecules. All the results from the above publicationshave assumed LTE conditions and optically thin line emis-sion. The abundances are plotted in Figure 25(a).In addition, we note that the abundances toward L1157-B1/B2 are estimated based on CO lines, which may be-come optically thick and therefore result in overestimatedabundances for other molecules (Bachiller & Pérez Gutiér-rez 1997). This may explain the systematically higher abun-dances for all the six molecules in L1157-B1/B2 than theother targets in Figure 25(a). To eliminate such biases, wenormalize the abundances with respect to that of HC N inthe outflows, and plot the relative abundances of the sixmolecules in Figure 25(b).By comparing the two samples in Figure 25(b), the CMZclouds vs. the two nearby clouds, we do not find clear evi-dence of difference between the relative abundances of thesix shock tracers in the outflows. The relative abundances ofthe two nearby clouds usually fall within an order of mag-nitude apart from the medians of our CMZ outflow sample.However, given the significant uncertainty of the abundancesand a limited sample from nearby clouds, it is premature toconclude any consistency between the two samples.4.3.
Implications for Star Formation and Chemistry
Protostellar outflows are ubiquitously detected in starforming regions, suggesting active gas accretion around pro-tostars (e.g., Shang et al. 2007; Bally 2016). Here we investi-gate star formation and chemistry in the four massive cloudsin the CMZ based on our observations of the outflows.The first implication, obviously, is that protostellar accre-tion disks ubiquituously exist in these clouds, as protostellaroutflows are supposedly driven by disks (Shang et al. 2007).Direct observational evidence of protostellar accretion disksin the CMZ has been limited to the hot cores in the Sgr B2cloud (e.g., Hollis et al. 2003; Higuchi et al. 2015), and evenfor these cases the evidence is ambiguous given the compli-cated kinematic environments in Sgr B2. More recently, D.Walker et al. (submitted, 2020) reported detection of pro-tostellar outflows in G0.253 + − cloud, which is likely in amore evolved phase of star formation; Mills et al. 2011; Luet al. 2019a), suggests that active accretion is ongoing aroundprotostars in these CMZ clouds.The second implication concerns the evolutionary phasesof star formation in these clouds based on the statistics ofthe cores with or without star formation signatures. In Pa-per I, we identify 834 cores at 2000 AU scales in the threeCMZ clouds. Among them, only 43 are found to be associ-ated with outflows. The remaining 791 cores are not asso-ciated with other signatures of star formation (masers, H II regions) either, and therefore are candidates of starless cores(gravitationally bound and prestellar, or simply unbound).However, as mentioned in Section 3.2, the outflow sample isvery likely to be incomplete because of the subjectivity of theidentification, thus potential outflows, even those with suffi-ciently strong emission, may have been missed. In addition,deeper observations may reveal more signatures of star for-mation such as weaker outflows or new masers. Therefore,the fraction of protostellar and starless cores is highly uncer-tain. For individual clouds, the fractions of cores associatedwith outflows range from 0.04 to 0.07 (Table 1), although thisis unlikely to suggest any evolutionary trend among the threeclouds given the small numbers of the outflow detections andthe potential incompleteness of the outflow sample.If we base our analysis on the current observations, i.e.,4–7% of the cores identified in Paper I are protostellar (Ta-ble 1), then we may put a constraint on the evolutionary phaseof the clouds. The time scale needed to enter the protostellarphase is of the order 1–2 Myr for both low-mass and high-mass star forming cores (Enoch et al. 2008; Könyves et al.2015; Battersby et al. 2017). This time scale is similar to theproposed lifetime of molecular clouds in the CMZ (Jeffresonet al. 2018; Barnes et al. 2020). Assuming that all the coreswe detected will eventually evolve into the protostellar phasein a time scale of 1–2 Myr, the small fraction of the currently ROTOSTELLAR O UTFLOWS IN
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LOUDS ∼ II regions (Kendrew et al. 2013; Barneset al. 2020). Again, we stress that this estimate depends onthe (in)completeness of the outflow sample, and the age ofstar formation in these clouds is likely longer as the fractionof protostellar cores is potentially higher.The third implication is related to the result presented inFigure 24, where we find outflows from both high-mass( > M (cid:12) ) and low-mass ( < M (cid:12) ) cores. Here the coremasses have a strong dependence on the unconstrained dusttemperature and may be overestimated by a factor of 3, asdemonstrated in Paper I. Several of the high-mass cores areknown to be forming high-mass protostars, with UC H II re-gions and class II CH OH masers (Lu et al. 2019a,b). Thelow-mass cores, on the other hand, are only capable of form-ing low-mass stars with the current mass even assuming ahigh star formation efficiency of 50%. Meanwhile, the ma-jority of the outflow masses lie in the range of 1–10 M (cid:12) , al-beit with a large uncertainty of factor 70. This mass range ischaracteristically found around high-mass protostars (Zhanget al. 2005; Lu et al. 2018). Some of the outflows have lowermasses of < M (cid:12) , which are typical for low-mass star form-ing regions (Arce et al. 2010). Therefore, considering themass ranges of the cores and the outflows, the detected out-flows likely trace a mix of high-mass and low-mass star for-mation. Simultaneous low-mass and high-mass star forma-tion has been observed ubiquitously in massive clouds in theGalactic disk (e.g., Cyganowski et al. 2017; Pillai et al. 2019;Sanhueza et al. 2019), which we now confirm to take placein the CMZ as well.The last implication, as discussed in Section 4.2, is aboutthe shock chemistry in the outflows. Given the large uncer-tainties involved in the abundances (at least one order of mag-nitude), we are not able to conclude consistency between theshock chemistry in the CMZ clouds and in nearby analogs,but we do not find evidence of difference either. This is incontrast to the situation on the cloud scale of a few pc, wherethe chemistry in the CMZ is distinctly different from that innearby clouds, e.g., an anomalous enhancement of complexorganic molecules and shock tracers as compared to those innearby clouds, suggesting the presence of wide-spread low-velocity shocks (Martín-Pintado et al. 1997; Requena-Torreset al. 2006; Menten et al. 2009). Several previous studieshave pointed out that at the sub-0.1 pc scale, physical pro-cesses such as gas fragmentation and turbulent linewidths inthe CMZ and in nearby regions may start to converge (e.g., Kauffmann et al. 2017; Lu et al. 2019a; Paper I; D. Walkeret al. submitted, 2020) despite distinct properties on largerscales. Our results set the first step toward a similar compar-ison of the shock chemistry in protostellar outflows in theCMZ and in nearby clouds. Multi-transition spectral lineobservations toward the CMZ outflows that enable a morerobust estimate of column densities and abundances, and alarger sample of resolved astrochemical studies toward out-flows in nearby clouds, will help clarify whether the shockchemistry in the two environments are consistent or not. CONCLUSIONSAs a follow-up of our Paper I, in which we used ALMA1.3 mm continuum emission to study cores of 2000 AU scalein four massive clouds in the CMZ, we further use 1.3 mmmolecular lines to identify protostellar outflows and investi-gate star formation activities associated with the cores. Wechoose six commonly used shock tracer molecules, includ-ing SiO, SO, CH OH, H CO, HC N, and HNCO. In threeclouds (the 20 km s − cloud, Sgr B1-off, and Sgr C), weidentify 43 outflows traced by the six molecules, including 37highly likely ones and 6 less likely ones that are consideredas candidates. This is by far the largest sample of protostellaroutflows identified in the CMZ. Then we estimate molecularabundances and masses of the outflows. Based on these find-ings and our previous studies (Lu et al. 2019a; Paper I), weconclude that:• We find no evidence of differences between the physics(existence of accretion disks, Jeans fragmentation) andshock chemistry (relative abundances of the six shocktracer molecules in the outflows) in the sub-0.1 pc scalein the CMZ and in nearby clouds. Although on thecloud scale of a few pc, gas in the CMZ exhibits ex-traordinary physical and chemical properties as com-pared to gas in the Galactic disk or in nearby clouds,such as large turbulence linewidth, strong magneticfields, and enhancements of particular molecules, inthe smaller scale of < ∼ (cid:28) (cid:46) M (cid:12) and are associated with low-mass coresof (cid:46) M (cid:12) , and therefore likely trace low-mass star0 L U ET AL .formation. Several high-mass outflows are associatedwith high-mass cores with known evidence of high-mass star formation. Therefore, low-mass and high-mass star formation are ongoing simultaneously inthese clouds.ACKNOWLEDGMENTSWe thank the anonymous referee for helpful comments.X.L. thanks Yuxin Lin, Luis Zapata, Luca Matrà, and HauyuBaobab Liu for helpful discussions. X.L. thanks his fam-ily, Qinyu E and Xiaoe Lyu, for their support during theCOVID-19 outbreak during which this manuscript was pre-pared. X.L. was supported by JSPS KAKENHI grants No.18K13589 & 20K14528. J.M.D.K. gratefully acknowledgesfunding from the Deutsche Forschungsgemeinschaft (DFG,German Research Foundation) through an Emmy NoetherResearch Group (grant number KR4801/1-1), the DFG Sach-beihilfe (grant number KR4801/2-1), and the SFB 881 “TheMilky Way System” (subproject B2), as well as from the Eu-ropean Research Council (ERC) under the European Union’sHorizon 2020 research and innovation programme via theERC Starting Grant MUSTANG (grant agreement num-ber 714907). C.B. and D.W. gratefully acknowledge sup-port from the National Science Foundation under AwardNo. 1816715. This paper makes use of the following ALMAdata: ADS/JAO.ALMA
Software:
CASA (McMullin et al. 2007), APLpy (Ro-bitaille & Bressert 2012), Astropy (Astropy Collaborationet al. 2013) , pvextractor (http://pvextractor.readthedocs.io),calcu (Li et al. 2020)
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LOUDS Table 2.
Transition spectral parameters of the outflow tracers.
Molecule Transition Frequency (GHz) E u /k B (K) A ul (s − ) g J / g K / g I Q rot Rotation Constants (MHz)SiO 5–4 217.104919 31.3 5.197 × − k B T ex hB + B = 21711 . HC N 24–23 218.324723 131.0 0.826 × − " B = 4549 . SO 6(5)–5(4) 219.949442 35.0 1.335 × − " B = 21523 . H CO 3(0,3)–2(0,2) 218.222192 21.0 2.818 × − (cid:18) πk B T ex h A B C (cid:19) . A = 281970 . B = 38833 . C = 34004 . CH OH 4(2) –3(1)E1 218.440063 45.5 4.686 × − (cid:18) πk B T ex h A B C (cid:19) . A = 127523 . B = 24690 . C = 23759 . HNCO 10(0,10)–9(0,9) 219.798274 58.0 1.510 × − (cid:18) πk B T ex h A B C (cid:19) . A = 912711 . B = 11071 . C = 10910 . APPENDIX A. CALCULATION OF MOLECULAR COLUMN DENSITIESAssuming optically thin emission, negligible background, Rayleigh-Jeans approximation, and local thermodynamic equilib-rium (LTE) conditions, the beam-averaged column density of a molecule can be derived following Mangum & Shirley (2015): N tot = 8 πk B ν hc A ul Q rot g J g K g I exp (cid:18) E u k B T ex (cid:19) (cid:90) T B d v, (A1)where k B is the Boltzmann constant, ν is the rest frequency of the transition, h is the Planck constant, c is the speed of light, A ul is the spontaneous emission coefficient from the upper state u to the lower state l , Q rot is the partition function of the molecule, g i ( i = J , K , or I ) are the degeneracies, E u is the energy of the upper state above the ground level, T ex is the excitationtemperature, and (cid:82) T B d v is the integrated brightness temperature of the transition along the velocity axis. The spontaneousemission coefficient of the transition is A ul = 64 π ν hc Sµ , (A2)where S is the line strength and µ is the permanent dipole moment of the molecule. Here we directly take the values of A ul fromthe LAMDA database (Schöier et al. 2005).The partition functions Q rot are approximated using the equations in Mangum & Shirley (2015), as listed in Table 2. Therotation constants that are used in the calculation of Q rot are also listed in Table 2.Then the column densities of the molecules are derived using Equation A1. The calculations are implemented in the calcutoolkit (Li et al. 2020). B. OBSERVATIONAL AND PHYSICAL PROPERTIES OF THE OUTFLOWSThe observational and physical properties of the identified outflows are listed in Table 3.2 L
U ET AL . Table 3 . Properties of the outflows. ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)20 km s − -A × × − CN] SO-blue [3.4, 23.5] 1.31 3.54 × × − OH-blue [1.7, 23.4] 2.30 7.68 × × − CO-blue [2.8, 23.4] 1.89 6.32 × × − N-blue [5.7, 23.4] 0.97 9.19 × × − X (HC N) of · · · · · · · · · · · · · · ·
SiO-red [25.8, 42.1] 0.79 5.14 × × − × × − OH-red [26.0, 35.6] 0.73 2.92 × × − CO-red [25.9, 36.8] 0.61 2.76 × × − N-red [26.0, 36.9] 0.22 4.65 × × − X (HC N) of · · · · · · · · · · · · · · ·
20 km s − -A − × × − CN] SO-blue [2.0, 25.8] 2.03 1.20 × × − OH-blue [ − × × − CO-blue [4.2, 26.0] 0.36 7.23 × × − N-blue [5.7, 26.1] 1.69 1.95 × × − × × − × × − × × − OH-red [28.4, 38.3] 1.19 5.30 × × − CO-red [28.4, 39.5] 1.13 7.49 × × − N-red [28.4, 43.6] 1.21 9.21 × × − × × − − -B − × × − OH] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [ − × × − × × − × × − × × − OH-red [17.9, 24.8] 0.68 2.55 × × − CO-red [17.7, 26.0] 1.58 3.18 × × − N-red [17.8, 26.1] 0.33 7.20 × × − · · · · · · · · · · · · · · ·
20 km s − -B − · · · × − X (SiO) of the red lobe[CH CN] SO-blue [8.7, 13.8] 0.04 · · · × − X (SO) of the red lobeCH OH-blue [ − · · · × − X (CH OH) of the red lobeH CO-blue [ − · · · × − X (H CO) of the red lobeHC N-blue · · · · · · · · · · · · · · ·
HNCO-blue · · · · · · · · · · · · · · ·
SiO-red [16.4, 35.3] 1.73 1.39 × × − × × − OH-red [16.4, 27.5] 0.65 6.60 × × − CO-red [16.4, 31.4] 1.06 9.99 × × − N-red [16.4, 26.1] 0.18 9.11 × × − · · · · · · · · · · · · · · ·
20 km s − -C − · · · × − X (SiO) of region C[CH OH] SO-blue · · · · · · · · · · · · · · ·
Table 3 continued
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LOUDS Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)CH OH-blue [7.1, 12.6] 0.26 · · · × − X (CH OH) of region CH CO-blue [1.5, 12.6] 0.26 · · · × − X (H CO) of region CHC N-blue · · · · · · · · · · · · · · ·
HNCO-blue · · · · · · · · · · · · · · ·
SiO-red [15.0, 31.3] 0.67 · · · × − X (SiO) of region CSO-red · · · · · · · · · · · · · · · CH OH-red [15.2, 20.7] 0.67 · · · × − X (CH OH) of region CH CO-red [15.0, 23.2] 0.35 · · · × − X (H CO) of region CHC N-red · · · · · · · · · · · · · · ·
HNCO-red [15.2, 18.2] 0.03 · · · × − X (HNCO) of region C20 km s − -C − × × − OH] SO-blue [6.0, 15.5] 0.29 2.00 × × − OH-blue [ − × × − CO-blue [0.1, 15.3] 1.03 4.02 × × − N-blue [4.3, 15.3] 0.22 4.19 × × − − × × − · · · · · · · · · · · · · · · SO-red · · · · · · · · · · · · · · · CH OH-red · · · · · · · · · · · · · · · H CO-red · · · · · · · · · · · · · · · HC N-red · · · · · · · · · · · · · · ·
HNCO-red · · · · · · · · · · · · · · ·
20 km s − -C − · · · × − X (SiO) of the red lobe[CH OH] SO-blue · · · · · · · · · · · · · · · CH OH-blue [8.5, 12.6] 0.02 · · · × − X (CH OH) of the red lobeH CO-blue · · · · · · · · · · · · · · · HC N-blue · · · · · · · · · · · · · · ·
HNCO-blue · · · · · · · · · · · · · · ·
SiO-red [15.0, 74.5] 2.14 1.17 × × − × × − OH-red [15.2, 24.8] 0.25 3.38 × × − CO-red [15.0, 25.9] 0.30 4.20 × × − N-red [15.1, 34.2] 0.18 4.15 × × − X (HC N) of region CHNCO-red · · · · · · · · · · · · · · ·
20 km s − -C − × × − OH] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [ − × × − X (HC N) of region CHNCO-blue [ − × × − × × − · · · · · · · · · · · · · · · CH OH-red · · · · · · · · · · · · · · · H CO-red [12.3, 25.9] 0.36 2.46 × × − N-red [12.4, 15.2] 0.02 3.39 × × − X (HC N) of region CHNCO-red · · · · · · · · · · · · · · ·
20 km s − -C − × × − CN] SO-blue [3.4, 11.5] 0.33 2.16 × × − OH-blue [3.1, 11.3] 1.01 7.29 × × − CO-blue [1.5, 11.2] 0.13 2.91 × × − N-blue [1.6, 11.2] 0.20 8.65 × × − × × − Table 3 continued
U ET AL . Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)SiO-red [13.7, 42.1] 2.12 1.43 × × − × × − OH-red [13.8, 22.1] 1.07 8.52 × × − CO-red [13.7, 25.9] 1.55 7.95 × × − N-red [13.8, 32.8] 0.73 6.37 × × − × × − − -C − × × − CN] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [ − × × − − × × − × × − × × − OH-red [13.8, 35.6] 0.71 9.70 × × − CO-red [13.7, 34.1] 1.09 1.10 × × − N-red [13.8, 30.1] 0.24 1.03 × × − × × − − -C − × × − CN] SO-blue [0.7, 13.8] 0.94 4.48 × × − OH-blue [4.4, 14.0] 2.05 1.23 × × − CO-blue [2.8, 13.8] 0.24 3.21 × × − N-blue [5.7, 13.9] 0.32 8.40 × × − × × − × × − × × − OH-red [16.4, 27.5] 1.68 3.64 × × − CO-red [16.4, 30.0] 3.65 8.18 × × − N-red [16.4, 22.0] 0.13 7.06 × × − × × − − -C − × × − CN] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [9.7, 13.9] 0.07 7.45 × × − · · · · · · · · · · · · · · · SiO-red [16.4, 47.5] 3.54 1.33 × × − × × − OH-red [16.4, 27.5] 0.50 3.22 × × − CO-red [16.4, 38.1] 1.41 7.75 × × − N-red [16.4, 22.0] 0.12 1.85 × × − × × − − -C − × × − N] SO-blue [2.0, 10.1] 0.08 2.18 × × − OH-blue [3.1, 9.9] 0.23 5.77 × × − CO-blue [1.5, 9.8] 0.30 5.64 × × − N-blue [7.0, 9.8] 0.03 4.51 × × − · · · · · · · · · · · · · · · SiO-red [12.3, 44.8] 0.75 1.45 × × − × × − OH-red [12.4, 20.7] 0.21 4.93 × × − CO-red [12.3, 27.3] 0.16 4.28 × × − Table 3 continued
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LOUDS Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)HC N-red [12.4, 16.6] 0.03 1.87 × × − × × − − -D · · · · · · · · · · · · · · · [CH CN] SO-blue · · · · · · · · · · · · · · · CH OH-blue · · · · · · · · · · · · · · · H CO-blue · · · · · · · · · · · · · · · HC N-blue · · · · · · · · · · · · · · ·
HNCO-blue · · · · · · · · · · · · · · ·
SiO-red [12.3, 35.3] 1.35 · · · × − X (SiO) of region DSO-red [12.4, 16.8] 0.25 · · · × − X (SO) of region DCH OH-red [12.4, 18.0] 0.40 · · · × − X (CH OH) of region DH CO-red [12.3, 19.2] 0.63 · · · × − X (H CO) of region DHC N-red · · · · · · · · · · · · · · ·
HNCO-red [12.4, 15.5] 0.17 · · · × − X (HNCO) of region D20 km s − -D − × × − CN] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [ − × × − − × × − × × − · · · · · · · · · · · · · · · CH OH-red [12.4, 18.0] 1.28 9.72 × × − CO-red [12.3, 16.5] 0.99 4.10 × × − N-red [12.4, 17.9] 0.16 8.66 × × − × × − − -D − × × − OH] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [ − × × − X (HC N) of region DHNCO-blue [ − × × − × × − × × − OH-red [11.2, 21.2] 0.14 1.24 × × − CO-red [11.0, 19.2] 0.11 2.10 × × − N-red [11.1, 21.1] 0.05 2.52 × × − X (HC N) of region DHNCO-red · · · · · · · · · · · · · · ·
20 km s − -D − × × − CN] SO-blue [ − × × − OH-blue [ − × × − CO-blue [ − × × − N-blue [3.0, 9.8] 0.08 3.17 × × − − × × − × × − × × − OH-red [12.4, 18.0] 0.52 2.86 × × − CO-red [12.3, 21.9] 0.77 4.33 × × − N-red [12.4, 13.9] 0.05 1.19 × × − × × − − -E − · · · × − X (SiO) of the cloud[CH OH] SO-blue [ − · · · × − X (SO) of the cloud Table 3 continued
U ET AL . Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)CH OH-blue [5.8, 9.9] 0.24 · · · × − X (CH OH) of the cloudH CO-blue [ − · · · × − X (H CO) of the cloudHC N-blue · · · · · · · · · · · · · · ·
HNCO-blue · · · · · · · · · · · · · · ·
SiO-red [12.3, 24.5] 0.88 · · · × − X (SiO) of the cloudSO-red [12.5, 20.8] 1.27 · · · × − X (SO) of the cloudCH OH-red [12.5, 18.0] 0.55 · · · × − X (CH OH) of the cloudH CO-red [12.3, 20.5] 1.11 · · · × − X (H CO) of the cloudHC N-red · · · · · · · · · · · · · · ·
HNCO-red [12.5, 22.5] 0.56 · · · × − X (HNCO) of the cloud20 km s − -F − · · · × − X (SiO) of the cloud[C O] SO-blue [ − · · · × − X (SO) of the cloudCH OH-blue [ − · · · × − X (CH OH) of the cloudH CO-blue [ − · · · × − X (H CO) of the cloudHC N-blue · · · · · · · · · · · · · · ·
HNCO-blue [ − · · · × − X (HNCO) of the cloudSiO-red [7.4, 29.9] 3.01 · · · × − X (SiO) of the cloudSO-red [7.4, 17.4] 0.82 · · · × − X (SO) of the cloudCH OH-red [7.4, 17.4] 0.22 · · · × − X (CH OH) of the cloudH CO-red [7.4, 16.5] 0.76 · · · × − X (H CO) of the cloudHC N-red · · · · · · · · · · · · · · ·
HNCO-red · · · · · · · · · · · · · · ·
20 km s − -G − × × − CN] SO-blue [ − × × − OH-blue [0.4, 7.2] 1.12 1.00 × × − CO-blue · · · · · · · · · · · · · · · HC N-blue [ − × × − · · · · · · · · · · · · · · · SiO-red [9.6, 29.9] 2.14 5.64 × × − × × − OH-red [9.8, 16.7] 0.60 6.68 × × − CO-red [9.6, 17.8] 0.74 3.58 × × − N-red [9.7, 16.6] 0.46 6.00 × × − · · · · · · · · · · · · · · · Sgr B1-off-A × × − CN] SO-blue [4.7, 27.1] 1.24 7.34 × × − OH-blue [ − × × − CO-blue [4.2, 27.3] 1.56 1.11 × × − N-blue [9.7, 27.4] 1.38 1.97 × × − × × − × × − × × − OH-red [29.7, 49.1] 1.31 6.57 × × − CO-red [29.7, 51.6] 1.02 6.77 × × − N-red [29.7, 39.6] 0.72 8.93 × × − × × − · · · × − X (SiO) of the cloud[CH OH] SO-blue · · · · · · · · · · · · · · · CH OH-blue [22.0, 27.5] 0.09 · · · × − X (CH OH) of the cloudH CO-blue · · · · · · · · · · · · · · · HC N-blue · · · · · · · · · · · · · · ·
HNCO-blue · · · · · · · · · · · · · · ·
Table 3 continued
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LOUDS Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)SiO-red [29.9, 39.4] 0.12 · · · × − X (SiO) of the cloudSO-red · · · · · · · · · · · · · · · CH OH-red [30.1, 35.6] 0.12 · · · × − X (CH OH) of the cloudH CO-red [29.9, 40.8] 0.11 · · · × − X (H CO) of the cloudHC N-red · · · · · · · · · · · · · · ·
HNCO-red · · · · · · · · · · · · · · ·
Sgr B1-off-C · · · × − X (SiO) of the red lobe[HC N] SO-blue · · · · · · · · · · · · · · · CH OH-blue [22.0, 28.9] 0.15 · · · × − X (CH OH) of the red lobeH CO-blue [11.0, 28.7] 0.52 · · · × − X (H CO) of the red lobeHC N-blue · · · · · · · · · · · · · · ·
HNCO-blue [24.7, 28.8] 0.09 · · · × − X (HNCO) of the red lobeSiO-red [31.2, 51.5] 0.55 8.64 × × − × × − OH-red [31.3, 39.7] 0.24 2.81 × × − CO-red [31.3, 47.5] 0.63 5.78 × × − N-red [31.3, 38.2] 0.17 3.40 × × − × × − × × − CN] SO-blue [20.7, 28.4] 0.77 4.52 × × − OH-blue [19.3, 28.4] 0.27 4.90 × × − CO-blue [11.0, 28.7] 0.44 4.61 × × − N-blue [24.6, 28.4] 0.20 5.34 × × − × × − · · · × − X (SiO) of the blue lobeSO-red [31.0, 36.8] 0.95 2.20 × × − OH-red [31.0, 35.6] 0.98 3.80 × × − CO-red [31.0, 40.8] 0.64 4.69 × × − N-red [31.0, 38.2] 0.27 8.47 × × − × × − × × − N] SO-blue [19.4, 28.8] 0.16 2.32 × × − OH-blue [17.9, 28.9] 0.32 4.16 × × − CO-blue [17.7, 28.7] 0.36 6.18 × × − N-blue [21.9, 28.8] 0.12 7.08 × × − × × − × × − × × − OH-red [31.3, 42.4] 0.92 5.52 × × − CO-red [31.3, 42.2] 1.81 8.52 × × − N-red [31.3, 39.6] 0.49 8.62 × × − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − Table 3 continued
U ET AL . Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)HC N-red [ − − × × − − − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − · · · × − X (SiO) of the red lobe[CH OH] SO-blue [ − − · · · × − X (SO) of the red lobeCH OH-blue [ − − · · · × − X (CH OH) of the red lobeH CO-blue [ − − · · · × − X (H CO) of the red lobeHC N-blue · · · · · · · · · · · · · · ·
HNCO-blue [ − − · · · × − X (HNCO) of the red lobeSiO-red [ − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − N] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red · · · · · · · · · · · · · · · H CO-red · · · · · · · · · · · · · · · HC N-red [ − − × × − · · · · · · · · · · · · · · · Sgr C-B − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − × × − − × × − OH-red [ − − × × − CO-red [ − × × − N-red [ − − × × − − − × × − − − − × × − N] SO-blue [ − − × × − Table 3 continued
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LOUDS Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)CH OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − · · · · · · · · · · · · · · · SiO-red [ − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − OH] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − · · · · · · · · · · · · · · · Sgr C-C − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − N] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − · · · · · · · · · · · · · · · CH OH-red · · · · · · · · · · · · · · · H CO-red [ − − × × − N-red [ − − × × − · · · · · · · · · · · · · · · Sgr C-C − − − × × − OH] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − Table 3 continued
U ET AL . Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)SiO-red [ − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − · · · · · · · · · · · · · · · Sgr C-D − − − × × − N] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − · · · · · · · · · · · · · · · CH OH-red · · · · · · · · · · · · · · · H CO-red [ − − × × − N-red [ − − × × − · · · · · · · · · · · · · · · Sgr C-D − − − × × − OH] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − · · · · · · · · · · · · · · · SiO-red [ − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − · · · · · · · · · · · · · · · Sgr C-D − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − Table 3 continued
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LOUDS Table 3 (continued) ID V lsr M core Lobes ∆ v F int N ref X M out
Notes(km s − ) ( M (cid:12) ) (km s − ) (Jy km s − ) (cm − ) ( M (cid:12) )(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)HC N-red [ − − × × − − − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − − − − × × − CN] SO-blue [ − − × × − OH-blue [ − − × × − CO-blue [ − − × × − N-blue [ − − × × − − − × × − − − × × − − − × × − OH-red [ − − × × − CO-red [ − − × × − N-red [ − − × × − − − × × − OTE —Column (1): outflow ID. Entries marked with asterisks are candidates, and those without asterisks are highly likely outflows. Column (2): V lsr of the core, and the lineused to determine the V lsr . Column (3): mass of the core (Paper I). Column (4): outflow lobe identifier. Column (5): velocity range of the outflow lobe. Column (6): integratedintensity of molecular emission. Column (7): column density at the reference positions, which are marked by black crosses in Figures 6–22. Column (8): adopted molecularabundance with respect to H . Column (9): outflow mass. Column (10): notes on the selection of molecular abundances. U ET AL .REFERENCES
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