The abundance of dwarf galaxies around low-mass giants in the Local Volume
AAstronomy & Astrophysics manuscript no. aanda c (cid:13)
ESO 2020August 21, 2020
The abundance of dwarf galaxies around low-mass giants in theLocal Volume
Oliver Müller and Helmut Jerjen Observatoire Astronomique de Strasbourg (ObAS), Universite de Strasbourg - CNRS, UMR 7550 Strasbourg, Francee-mail: [email protected] Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, AustraliaReceived tba; accepted tba
ABSTRACT
The abundance of satellite dwarf galaxies has long been considered a crucial test for the current model of cosmology leading to thewell-known missing satellite problem. Recent advances in both simulations and observations have allowed to study dwarf galaxiesaround host galaxies in more detail. We have surveyed a 72 deg area of the nearby Sculptor group using the Dark Energy Camera –also encompassing the two low-mass Local Volume galaxies NGC 24 and NGC 45 residing behind the group – to search for hithertoundetected dwarf galaxies. Apart from the previously known dwarf galaxies we have found only two new candidates down to a 3 σ surface brightness detection limit of 27.4 r mag arcsec − . Both systems are in projection close to NGC 24. However, one of thesecandidates could be an ultra-di ff use galaxy associated to a background galaxy. We compared the number of known dwarf galaxycandidates around NGC 24, NGC 45, and five other well-studied low-mass giant galaxies (NGC 1156, NGC 2403, NGC 5023, M 33,and the LMC) with predictions from cosmological simulations and found that for the stellar-to-halo mass models considered, theobserved satellite numbers tend to be on the lower end of the expected range. This could either mean that there is an over-predictionof luminous subhalos in Λ CDM or – and more likely – that we are missing some of the satellite members due to observational biases.
Key words.
Galaxies: dwarf – Galaxies: abundance – Galaxies: groups: individual: Sculptor group – Galaxies: groups: general
1. Introduction
In the standard cosmological framework dwarf galaxies arethought to be the building blocks of the visible Universe. Largergalaxies form through a cascade of minor mergers of these dwarfgalaxies (Frenk & White 2012) leading to a strong correlationbetween the number of dwarf galaxy satellites and the mass ofthe host galaxy (e.g., Javanmardi et al. 2019), as the more mas-sive halos are able to accrete more matter. The left-overs of theseaccretion processes are still detectable today as satellite galaxiesswarming the central galaxies. The specific frequency of satel-lites and their luminosities can be described by the galaxy lu-minosity function (LF, Binggeli et al. 1988) and be comparedto cosmological predictions. This led to the well-known miss-ing satellite (Moore et al. 1999) and the too-big-to-fail (Boylan-Kolchin et al. 2011) problems. These challenges for the Λ CDMmodel of cosmology, however, have mainly been studied in theLocal Group of galaxies. Only recently new technology allowedto survey for dwarf galaxies in other nearby groups to a su ffi -cient surface brightness depth that such cosmological tests canbe conducted more systematically.The Local Volume ( D <
11 Mpc, Kraan-Korteweg & Tam-mann 1979; Karachentsev et al. 2004, 2013) hosts over 30 largegalaxies with total luminosities in excess of M tot ≈ − K mag.Several surveys have targeted the more prominent of these giantgalaxies like M 83 (Müller et al. 2015), Centaurus A (Crnojevi´cet al. 2014, 2016; Müller et al. 2017; Taylor et al. 2018), andothers (Merritt et al. 2014; Karachentsev et al. 2015; Javanmardiet al. 2016; Park et al. 2017; Smercina et al. 2018; Bennet et al.2019; Carlsten et al. 2020a; Davis et al. 2020). Furthermore,dwarf galaxy surveys reach to even more distant galaxy clusters (Venhola et al. 2017; Wittmann et al. 2019), groups (Geha et al.2017; Cohen et al. 2018; Habas et al. 2020) and the field (Grecoet al. 2018; Prole et al. 2019).These surveys have revealed first interesting results. For in-stance, the recent deep search for dwarf galaxies around the giantspiral galaxy M 94 (NGC 4736; M ∗ ≈ × M (cid:12) , Karachentsevet al. 2013; D = . ff erent view). On the otherhand, there seems to emerge a correlation between the number ofsatellites and the bulge-to-disk ratio of the host galaxies, whichis again unexpected in Λ CDM (Javanmardi et al. 2019; Javan-mardi & Kroupa 2020). All these findings ask for more obser-vations of di ff erent environments. While there appears to be aconsensus that the missing-satellite problem for the Milky Wayand the Andromeda galaxy are resolved today (Simon & Geha2007; Sawala et al. 2016; Simpson et al. 2018), there are still dis-crepancies between observations and the Λ CDM model when itcomes to the abundance of dwarf galaxies around the giants inthe Local Volume.One of the closest galaxy aggregates from our point of viewis the Sculptor group in the southern hemisphere. It is longknown to be a loose association of galaxies (Jerjen et al. 1998,2000), stretching approximately from NGC 55 (D = Article number, page 1 of 7 a r X i v : . [ a s t r o - ph . GA ] A ug & A proofs: manuscript no. aanda with the starburst spiral galaxy NGC 253 at a distance of 3.7 Mpc(Karachentsev et al. 2013; Lucero et al. 2015) being the dom-inant member. An imaging survey of its immediate surround-ings has revealed only two faint companions (Sand et al. 2014;Toloba et al. 2016), which already suggests that indeed theSculptor group is a low-density environment. This is surpris-ing because NGC 253 is as massive (Lucero et al. 2015) asthe Milky Way or the Andromeda galaxy, which both host aplethora of dwarf galaxies (e.g., Belokurov et al. 2010; Richard-son et al. 2011; Kim et al. 2015a). Due to its proximity to us,the Sculptor group covers several hundred square degrees in thesky, making a full coverage of the group observationally highlydemanding. Here we present the results from a first 72 deg sur-vey based on dedicated CCD observations of the eastern partof the Sculptor group, which encompasses two additional giantgalaxies, NGC 24 (D = =
2. Observation and data reduction
The gr CCD images for our search of Sculptor group dwarf can-didates were obtained as part of the Stromlo Milky Way Satel-lite Survey (e.g. Kim et al. 2015b, 2016). Imaging data werecollected for a total of ∼
500 deg with the DECam at the 4 mBlanco telescope at CTIO over three photometric nights from17th to 19th July 2014. DECam is an array of sixty-two 2k × field of view and a pixel scaleof 0 (cid:48)(cid:48) . ×
60 s ditheredexposures in the g and r band for each pointing under pho-tometric conditions. To cover the 72 deg of the Sculptor re-gion we acquired a total of 24 pointings (see Fig. 1 for the sur-vey footprint). The seeing in those Sculptor fields ranged from0 (cid:48)(cid:48) . ≤ σ g ≤ (cid:48)(cid:48) .
22 and 0 (cid:48)(cid:48) . ≤ σ r ≤ (cid:48)(cid:48) .
16, with median values µ / ( σ g ) = (cid:48)(cid:48) .
94 and µ / ( σ r ) = (cid:48)(cid:48) .
94, respectively.The images were reduced via the DECam communitypipeline (Valdes et al. 2014), which included overscan subtrac-tion, bias calibration, flat field gain calibration, single exposurecosmic ray masking, illumination correction, astrometric cali-bration to refine the world coordinate system of each frame, andphotometric calibration. For the sky subtraction we employed
SEP – the python version (Barbary 2016) of Source Extractor(Bertin & Arnouts 1996). A 400 ×
400 px box was used as ref-erence for the local background measurement. This size is largeenough ( ≈ × SWarp program (Bertin et al. 2002) tomake a final, deep image.The photometric zero points of the g and r images were de-rived using the PanSTARRS DR2 catalog (Magnier et al. 2016).We performed aperture photometry with the python package photutils (Bradley et al. 2019) and compared them to standardstars in the magnitude range 15.0 - 19.5 mag. A linear regressionwith a 0.3 mag clipping was applied to derive the slope and in- ! " $ % &’’’ ( ) * + , - ./0/ !" Fig. 1.
The field of the Sculptor group. The small black dots correspondto dwarf galaxies in the Sculptor group with its main galaxy NGC 253(large black dot). The small gray dots are background dwarf galaxies,which are still within the Local Volume ( D <
11 Mpc. The two largegray dots are the two LSB giants NGC 24 and NGC 45. The red dots areour dwarf galaxy candidates dw0009-25 and dw0010-25. The grey areacorresponds to our survey footprint. tercept in each band and for each field. The slope was consistentwith 1.0 so that the intercept corresponds to the zero point. Theerrors are 0.04 mag in the g -band and 0.08 mag in the r -band.
3. Search for new dwarf galaxies in the Scl Groupregion
In our survey area only four Local Volume dwarf galaxies wereknown to date: ESO 409-15 ( D = . D = .
9; Tully et al. 2013), Sculptor-dE1 (Jerjen et al.2000, D = . D = . D = . D = . . × M (cid:12) and 3 . × M (cid:12) , respectively (Chemin et al. 2006).To find new dwarf galaxies we rely on both visual inspectionof the images and on an automatic detection pipeline. The searchis done on the stacked gr images. The classical approach to search for faint low-surface bright-ness galaxies is via careful visual inspection of the digital im-ages. This approach has been proven successful to detect dozensof new dwarf galaxies in surveys around other nearby galaxies(e.g., Jerjen et al. 2000; Karachentsev et al. 2000; Trentham &Tully 2002; Chiboucas et al. 2009; Merritt et al. 2014; Park et al.2017; Müller et al. 2018; Habas et al. 2020; Byun et al. 2020). Toenhance any low-surface brightness features, a standard imageprocessing algorithm is applied to the images, i.e. the convolu-tion with a Gaussian kernel (with σ of 1.5 px). Afterwards all im- Article number, page 2 of 7liver Müller and Helmut Jerjen: The abundance of dwarf galaxies around low-mass giants in the Local Volume ages are scanned by eye for di ff use and extended patches whichresemble the morphology of dwarf galaxies. This approach leadsto a good understanding of the quality and limitations of the dataat hand, which will also benefit the more automated detectiontechniques. Assuming that a faint dwarf galaxy detectable in ourimages has a typical e ff ective radius of r e ff =
140 pc (Mülleret al. 2019b) this would give an angular size of 30 px at the meandistance of the Sculptor Group (3.45 Mpc) and 14 px at the dis-tance of NGC 24. Such an object is well distinguishable fromlarger background dwarf galaxies, the latter being more compactcompared to their surface brightness. Our visual search revealedone good dwarf galaxy candidate which we dubbed dw0010-25,and another potential candidate named dw009-25 (see Fig. 2).
Fig. 2.
The stacked gr -band images of the newly discovered dwarfgalaxy candidates dw0009-25 (left) and dw0010-25 (right). North is tothe top, east to the left, the vertical length of the images correspondsto one arcmin. We note that dw0009-25 was detected close to the CCDedge. Novel development of automated detection algorithms showpromising results. One of the best software available today isMTObjects (Teeninga et al. 2013, 2015), a max-tree based al-gorithm, which was developed for medical image analysis andre-written for astronomical purposes (see e.g. Prole et al. 2019).It is non-parametric, this is, it automatically searches for thebest parameters for a given image, making MTObjects straight-forward to use. MTObjects provides a segmentation map and acatalog of basic photometric parameters for each detection. Onthese preliminary catalogs we apply further quality cuts for size,total magnitude and surface brightness. The limits for the ef-fective radius r e f f was set to be 0.1-3.0 kpc at the adopted dis-tance of the Sculptor group (3.7 Mpc), This reduced the numberof objects to a total of 3372 for the whole survey area. We in-spected each of the detections by eye and only kept the gooddwarf galaxy candidates leaving us with only one object, the al-ready known Sculptor-dE1 dwarf. This means the visually de-tected dwarf galaxy candidate dw0010-25 was not picked up byMTObjects. We attribute this to the presence of a backgroundspiral galaxy close in its proximity (see Fig. 2). The other dwarfgalaxy candidate dw0009-25 was too faint to get detected byMTObjects (see next paragraph). The large number of false posi-tives were mainly from artefacts at the edges of the CCD images.To assess the completeness of the dwarf galaxy detection,we have injected artificial dwarf galaxies into the images andre-run MTObjects with the same quality cuts. The dwarfs weremodelled with a Sérsic profile (Sersic 1968), employing di ff erentapparent magnitudes (i.e. between 14 mag and 19 mag) and ef-fective radii (i.e. between 5 arcsec and 160 arcsec). Sérsic indices between n = . n = . e = . e = . ff ective radius in ourquality cuts. This makes sure that there is no issue of overcrowd-ing the field. By design, some of the artificial dwarf galaxieswill be at the edge of the image, such that we also probe anybias coming from dwarf galaxies being at the edge of the cam-era. Ultimately, the detection rate was derived from a comparisonbetween the input and detection list, with an error tolerance ofone e ff ective radius for the position of the dwarf. This processwas repeated across di ff erent fields with a total of 8000 artifi-cial dwarf galaxies per field, where the position of the grid wasrandomized during each iteration. From the detection rate, wederived the mean surface brightness limit by binning the magni-tudes and e ff ective radii like in Figure 3 with bin sizes of 0.2 magand 10 arcsec, respectively. Then we extracted the bins as datapoints where we achieved a detection rate between 80 to 70 per-cent for the 75% completeness limit, data points between 45 to55 percent for the 50% completeness limit, and data points be-tween 20 to 30 percent for the 25% completeness limit. Throughthese data points we fitted the formula r ff = . µ lim − m r − . /π, (1)where µ lim is the quantity we are solving for. We have performedthis limit estimation on six di ff erent fields and find 50% com-pleteness limits of: 27 . ± .
10 mag arcsec − , 27 . ± .
09 magarcsec − , 27 . ± .
09 mag arcsec − , 27 . ± .
12 mag arcsec − ,27 . ± .
12 mag arcsec − , and 27 . ± .
09 mag arcsec − . To esti-mate the overall completeness limit of the survey, we have com-bined these individual runs to one final diagram with bin sizesof 0.1 mag and 5 arcsec, respectively. A mean surface brightnesslimit µ lim of 27 . ± .
08 mag arcsec − in the r -band best de-scribes our 50% detection rate limit (26 . ± .
10 mag arcsec − at 75% and 27 . ± .
08 mag arcsec − at 25%). The results areillustrated in Figure 3. This is consistent with the numbers esti-mated in Müller et al. (2015), which was part of the same imag-ing campaign with the same observation strategy. For the appar-ent magnitude m r (x-axis in Figure 3), the recovery rate dropsbellow 50% at 18.2 mag in the r -band, which translates into acompleteness limit for the automated detection of dwarf galax-ies of M r = − . − . − . r magnitude of ∼ .
5. This limit is brighter than oneof the dwarf candidate we detected by eye ( m r = . / saturated stars which could po-tentially hide dwarf galaxies. To estimate a number we have usedthe parameters given by MTObjects. Namely we integrated thearea of all objects with e ff ective radii larger than 7.5 px. To dothis, we have approximated the area of each object fulfilling thecriteria with a circle with two times the e ff ective radius. Thisgives a coverage of 0.2% which can potentially obfuscate thedwarf galaxies. This is indeed negligible and will not signifi-cantly alter the abundance of dwarf galaxies. Article number, page 3 of 7 & A proofs: manuscript no. aanda
14 15 16 17 18m r (mag)20406080100120140160 r _ e ff ( a r c s e c ) p e r c e n t o f d e t e c t i o n s Fig. 3.
Result from the artificial dwarf galaxy test with MTObjectsshowing the recovery rate (color scheme) as a function of total appar-ent magnitude m r and half-light radius r ef f . The red line indicates thelower surface brightness cut (22 mag arcesc − ), the white line the esti-mated completeness at 50% (27.5 mag arcesc − ), and the dashed whitelines the 75% (26 . − ) and 25% (27 . − ) limit,respectively. The black dot indicates the known dwarf galaxy Sculptor-dE1. The photometry for the two dwarf galaxy candidates was doneusing GALFIT (Peng et al. 2002). To achieve the best Sérsic fitwe provided GALFIT with a mask created from the segmenta-tion map of MTObjects, which we further adjusted by hand. Dueto their low surface brightness levels we had to impose tighterconstraints on the center of the object (i.e. ± g and r bands.The errors for the magnitudes are a combination of the uncer-tainty from the photometric zero point and the error from GAL-FIT, the rest is taken from the uncertainties provided by GAL-FIT. The measured photometric parameters are given in Table 1.We have measured the surface brightness limit around our dwarfgalaxy candidates in randomly distributed 10 ×
10 arcsec boxes(Müller et al. 2019c) and derived a 3 σ limit of 27.4 mag arcsec − in the r -band. This limit is well consistent with the 50% detec-tion limit we derived from our artificial galaxy tests. Table 1.
Photometric properties of the dwarf galaxy candidates. dw0009-25 dw0010-25R.A. (J2000) 00:09:37.8 00:10:38.2DEC (J2000) − − m g (mag) 21.50 ± ± m r (mag) 20.62 ± . ± . A g , A r (mag) 0.06, 0.04 0.06, 0.04( g − r ) (mag) 0.87 ± ± r e f f , r (arcsec) 8.0 ± ± µ e f f , r (mag arcsec − ) 26.9 ± ± PA (north to east) 1 ±
19 168 ± e = − b / a ± ± n ± ±
4. Membership of the dwarf galaxy candidate
Both dwarf galaxy candidates dw0009-25 and dw0010-25 arein projection close to the edge-on spiral galaxy NGC 24 andalso close to each other (see Fig. 1). Their on-sky separation isonly 0.11 deg and 0.40 deg from NGC 24, which at its distance( D = . ff ective radius and absolute magnitude would be r e f f =
283 pcand M r = − . r e f f = M r = − . D = . D = . M r = − . r e f f =
144 pc for dw0009-25 and M r = − . r e f f =
542 pc for dw0010-25.How do these quantities compare to the structural parame-ters of other known dwarf galaxies? Habas et al. (2020) stud-ied a population of over 2000 dwarf galaxies in the nearbyuniverse and presented the structural parameters in their Fig-ure 11. Our dwarf galaxy candidates are compatible with thesedwarf galaxies at either distance, so no potential membershipcan be confirmed or excluded. Also the integrated ( g − r ) colorof 0.87 mag and 0.55 mag are consistent with the mean colorof 0.46 ± z = .
065 (Loveday et al. 1996), i.e., ≈
290 Mpcaway from us. At that distance dw0010-25 would have an ab-solute magnitude of M r = − . ff ective radius of r e f f =
42 kpc, which seems highly unrealistic. The same is truefor dw0009-25. It has the background galaxy LEDA 783199 inits vicinity, but no distance information is available in that case.Assuming a conservative distance of 100 Mpc this would trans-late into M r = − . ff ective radius of r e f f = ff use galaxy in thebackground (e.g. Barbosa et al. 2020).
5. The luminosity function of low-mass giantgalaxies
All dwarf galaxy satellites of the two host galaxies NGC 24 andNGC 45 should have been identified within the M V < −
10 magluminosity range by now. For NGC 24, we find two possiblesatellites while there are none for NGC 45. Is this expected?Indeed, with total masses of 2 . × M (cid:12) and 3 . × M (cid:12) (Chemin et al. 2006), respectively, the two host galaxies are atthe low-mass end of the giant galaxy population. Let us com-pare these results to other such galaxies. The LMC is proba-bly the most iconic low-mass giant with an enclosed mass of1 . × M (cid:12) (van der Marel & Kallivayalil 2014). It has onesatellite – the SMC – more massive than 10 M (cid:12) , but has alsomany light-weight satellites (Erkal & Belokurov 2020) whichwould be impossible to detect outside of the Local Group. Carl-sten et al. (2020b) conducted a deep survey for dwarf galaxies Article number, page 4 of 7liver Müller and Helmut Jerjen: The abundance of dwarf galaxies around low-mass giants in the Local Volume
70 80 90 100 110 120 130 v rot (km/s)024681012 n r . o f s a t e lli t e s N G C N G C N G C N G C N G C M L M C observedBrook14GK17 Fig. 4.
The predicted (gray boxes) and observed (red lines) number ofsatellites as a function of the rotation curve of the host galaxy. For thepredictions, the assumed stellar-to-halo mass model by Brook et al.(2014) and Garrison-Kimmel et al. (2017) in Dooley et al. (2017) areemployed. around 10 giants within the Local Volume and studied their lu-minosity functions. Two of those, NGC 1156 and NGC 5023 areof similar low mass than the two giants studied here. NGC 1156has two possible dwarf galaxy satellites and one is known forNGC 5023. Another well studied low-mass giant galaxy is M 33with an observed dark matter mass of 5 × M (cid:12) (Corbelli2003). Only one possible satellite has been reported for M 33 todate (Martin et al. 2009). The MADCASH survey (Carlin et al.2016) aimed at finding satellite companions of LMC analogs. Ina first search around NGC 2403 one dwarf galaxy was discov-ered, increasing the number of known NGC 2403 satellites totwo. The flat part of the rotation curves of all these low-mass gi-ant galaxies reaches between v rot , f lat =
75 and 131 km s − , whichsets them apart from galaxies like the Milky Way (Fich et al.1989) or NGC 253 (Lucero et al. 2015), with significantly higherrotation velocities in the range between 200 < v rot , f lat < − . We have compiled the values for these low-mass giantgalaxies in Table 2.How do the observed number of possible dwarf satellitescompare with predictions from the current Λ CDM model of cos-mology? Dooley et al. (2017) has calculated the expected num-ber of satellites with masses larger than 10 M (cid:12) . This mass limitcoincides with the depths reached in the various surveys allow-ing for a more or less direct comparison. More or less, becausethe completeness to this limit is still not fully reached, under-estimating the total abundance of observed satellite galaxies. InTable 2 and Fig. 4 we present the number of expected and ob-served satellites for the stellar-to-halo mass models by Brooket al. (2014) and Garrison-Kimmel et al. (2017). They corre-spond to the low and high end of the estimates. For the Brookmodel, the number of possible dwarf galaxies coincide for allof the seven here studied systems with the 80% confidence in-terval of Dooley et al. (2017). However, there is a systematictrend. The observed satellite number for most of the low-masshost galaxies is at the lower end of the Λ CDM predictions. Thedi ff erence is even more evident when comparing to the predic-tions from the GK17 model. Half of the systems seems o ff fromthe observations. This can be interpreted that either Λ CDM isover-producing massive subhalos, or – more likely – that somedwarf satellites have been overlooked in all these surveys. The former is a known problem in simulations (Garrison-Kimmelet al. 2014), while the latter is observationally unavoidable, withsome dwarf galaxy satellites potentially being obscured by thehost galaxy or other sources (i.e. cirrus, bright stars, large back-ground galaxies, or noise), or simply too faint to be detectable.This incompleteness becomes an even larger problem towardsthe faint end of the luminosity function where larger numbers ofsmaller dwarf galaxies are expected. For NGC 24, the automateddetection limit is at − . × L (cid:12) (with an absolute r -band luminosity ofthe sun of 4.61, Willmer 2018). This is still a factor ten higherthan what was used in the predictions by Dooley et al. (2017)– note though that the dwarf galaxy candidate dw0009-25 has aluminosity of − . × L (cid:12) , so being right in the ballpark of the luminositylimit. For a statistically robust comparison the luminosity func-tion should be complete down to ≈ − ffi -cient depth was reached, but the field of view was too small tocover its virial radius and thus the survey lacks the full cover-age of the satellite system. There could be a handful of dwarfgalaxies still residing outside the survey footprint (Carlin et al.2016).
6. Summary and conclusion
The Sculptor group is the closest galaxy aggregate to the MilkyWay and thus extends over a large area of the sky. With the DarkEnergy Camera and in the g and r bands, we have observed a72 deg area in the Eastern part of the Sculptor group. Thisregion also encloses the two low-mass spiral galaxies NGC 24and NGC 45 of the Local Volume, which are further in the back-ground and therefore unrelated to the Sculptor group. We havesearched for low-surface brightness dwarf galaxies employingtwo di ff erent strategies. We have visually inspected all CCD im-ages by eye and we have applied automatic detection methodsto find the dwarf galaxies. To test the level of completeness forthe search we have injected artificial dwarf galaxies and foundto be 50% complete down to 18.2 mag or M r ≈ −
11 to −
10 mag.In our visual search we have found only two dwarf galaxy can-didate, which are in projection closest to NGC 24. These candi-date were not picked up by the automated detection algorithmdue to the proximity to a background galaxy in one case, andits faint luminosity in the other. The latter case is noteworthy, asit shows that a visual search for dwarf galaxies can reach somedeeper limit than the automated one. The physical properties ofthe candidates are compatible with the scaling relations definedby known dwarf galaxies (Habas et al. 2020), independent of theassociation to the two background Local Volume galaxies or theSculptor group. Follow-up observations are needed to pin downtheir true host galaxy memberships via distance measurements(Carlsten et al. 2019; Müller et al. 2019a; Monelli & Trujillo2019).We have compared the observed number of dwarf galaxycandidates around NGC 24 and NGC 45, as well as for five otherwell-studied low-mass giant galaxies (NGC 1156, NGC 2403,NGC 5023, M 33, and the LMC), to predictions from high-resolution dark matter simulation employing di ff erent stellar-to-halo mass models. We find that for the mass model by Brooket al. (2014) the observed abundance of dwarf galaxies gen- Article number, page 5 of 7 & A proofs: manuscript no. aanda
Table 2.
Low-mass giant galaxies and their number of satellite galaxies within the virial radius. M K M ∗ , host v rot , f lat observed predicted (Brook14) predicted (GK17)Name (mag) (10 M (cid:12) ) (km s − ) ( M tot > M (cid:12) ) ( M tot > M (cid:12) ) ( M tot > M (cid:12) )NGC 24 − . . ± − . . ± ∗ − . . ± − . . ± − . . ± + − . . ± − . . ± Notes.
The M K magnitudes were taken from the Local Volume catalog (Karachentsev et al. 2013). The baryonic mass M ∗ , host of the galaxy isderived from M K and a mass-to-light ratio of 0.6 (Lelli et al. 2017) and a solar K band luminosity of K = .
28 mag (Binney & Merrifield 1998).The flat rotation velocity v rot , flat corresponds to the flat part of the host galaxy rotation curve. The references for v rot , flat are: (1) Dicaire et al.(2008); (2) Chemin et al. (2006); (3) Karachentsev & Petit (1990); (4) Daigle et al. (2006); (5) Kamphuis et al. (2013); (6) Corbelli et al. (2014);(7) van der Marel & Kallivayalil (2014). We have calculated the mean value of the flat part of the rotation curve ourselves when not explicitlygiven in these references. The observed number of satellites must be considered a lower limit. The predicted number of satellites comes from theassumed stellar-to-halo mass model relation by Brook14 (Brook et al. 2014) and GK17 (Garrison-Kimmel et al. 2017) in Dooley et al. (2017) fordwarf galaxies more massive than 10 M (cid:12) . (*) For NGC 1156 no Λ CDM prediction of the number of satellites is available. Here we have assumedthe same number as for NGC 5023 due to their similar v rot , flat . ( + ) For M 33 we use the prediction by Patel et al. (2018) who adapted the Dooleyet al. (2017) predictions for the LMC with a GK17 model. erally follows the predictions, but still being systematically onthe lower end. As we are dealing with very low number statis-tics the di ff erence could either arise from observational biasesor be first evidence for a true tension between the observedand predicted satellite population for low-mass galaxies. For theGarrison-Kimmel et al. (2017) model there seems to be an over-prediction of satellites and the tension becomes more evident.The strongest disagreement is found for the most luminous sam-ple galaxy NGC 2403. It will be interesting to see whether thistrend persists once the environments of more low-mass giantshave been carefully investigated, e.g. by the MADCASH survey(Carlin et al. 2016), or it is indeed rather an observational biasdue to the incompleteness kicking in at the low-end of the lu-minosity function. On this aspect it is interesting that a recentHubble Space Telescope study of low-mass galaxies at redshifts0.1 to 0.8 has found good agreement between the observed lu-minosity function down to M V = −
15 mag and the predictedabundance of satellites (Roberts et al. 2020). Furthermore, Carl-sten et al. (2020b) found that the abundance of satellites of moremassive Local Volume galaxies is in good agreement betweenthe observed and expected number of satellites. This is compat-ible with our earlier assessment of the Cen A group, where wefound that the luminosity function matches the prediction withinthe 90% confidence interval (Müller et al. 2019b). This indicatesthat in general, the luminosity function is well described by ourcurrent model of cosmology.
Acknowledgements.
We thank the referee for the constructive report, whichhelped to clarify and improve the manuscript. O.M. wants to thank the Swiss Na-tional Science Foundation for financial support. H.J. acknowledges support fromthe Australian Research Council through the Discovery Project DP150100862.
References
Barbary, K. 2016, The Journal of Open Source Software, 1, 58Barbosa, C. E., Zaritsky, D., Donnerstein, R., et al. 2020, ApJS, 247, 46Belokurov, V., Walker, M. G., Evans, N. W., et al. 2010, ApJ, 712, L103Bennet, P., Sand, D. J., Crnojevi´c, D., et al. 2019, ApJ, 885, 153Bertin, E. & Arnouts, S. 1996, A&AS, 117, 393Bertin, E., Mellier, Y., Radovich, M., et al. 2002, in Astronomical Society of thePacific Conference Series, Vol. 281, Astronomical Data Analysis Softwareand Systems XI, ed. D. A. Bohlender, D. Durand, & T. H. Handley, 228 Binggeli, B., Sandage, A., & Tammann, G. A. 1988, ARA&A, 26, 509Binney, J. & Merrifield, M. 1998, Galactic AstronomyBoylan-Kolchin, M., Bullock, J. S., & Kaplinghat, M. 2011, MNRAS, 415, L40Bradley, L., Sip˝ocz, B., Robitaille, T., et al. 2019, astropy / photutils: v0.6Brook, C. B., Di Cintio, A., Knebe, A., et al. 2014, ApJ, 784, L14Byun, W., Sheen, Y.-K., Park, H. S., et al. 2020, ApJ, 891, 18Carlin, J. L., Sand, D. J., Price, P., et al. 2016, ApJ, 828, L5Carlsten, S. G., Beaton, R. L., Greco, J. P., & Greene, J. E. 2019, ApJ, 879, 13Carlsten, S. G., Greco, J. P., Beaton, R. L., & Greene, J. E. 2020a, ApJ, 891, 144Carlsten, S. G., Greene, J. E., Peter, A. H. G., Beaton, R. L., & Greco, J. P. 2020b,arXiv e-prints, arXiv:2006.02443Chemin, L., Carignan, C., Drouin, N., & Freeman, K. C. 2006, AJ, 132, 2527Chiboucas, K., Karachentsev, I. D., & Tully, R. B. 2009, AJ, 137, 3009Cohen, Y., van Dokkum, P., Danieli, S., et al. 2018, ApJ, 868, 96Corbelli, E. 2003, MNRAS, 342, 199Corbelli, E., Thilker, D., Zibetti, S., Giovanardi, C., & Salucci, P. 2014, A&A,572, A23Crnojevi´c, D., Sand, D. J., Caldwell, N., et al. 2014, ApJ, 795, L35Crnojevi´c, D., Sand, D. J., Spekkens, K., et al. 2016, ApJ, 823, 19Daigle, O., Carignan, C., Amram, P., et al. 2006, MNRAS, 367, 469Davis, A. B., Nierenberg, A. M., Peter, A. H. G., et al. 2020, arXiv e-prints,arXiv:2003.08352Dicaire, I., Carignan, C., Amram, P., et al. 2008, MNRAS, 385, 553Dooley, G. A., Peter, A. H. G., Carlin, J. L., et al. 2017, MNRAS, 472, 1060Erkal, D. & Belokurov, V. A. 2020, MNRAS, 495, 2554Fich, M., Blitz, L., & Stark, A. A. 1989, ApJ, 342, 272Frenk, C. S. & White, S. D. M. 2012, Annalen der Physik, 524, 507Garrison-Kimmel, S., Boylan-Kolchin, M., Bullock, J. S., & Lee, K. 2014, MN-RAS, 438, 2578Garrison-Kimmel, S., Wetzel, A., Bullock, J. S., et al. 2017, MNRAS, 471, 1709Geha, M., Wechsler, R. H., Mao, Y.-Y., et al. 2017, ApJ, 847, 4Greco, J. P., Greene, J. E., Strauss, M. A., et al. 2018, ApJ, 857, 104Habas, R., Marleau, F. R., Duc, P.-A., et al. 2020, MNRAS, 491, 1901Javanmardi, B. & Kroupa, P. 2020, MNRAS, 493, L44Javanmardi, B., Martinez-Delgado, D., Kroupa, P., et al. 2016, A&A, 588, A89Javanmardi, B., Raouf, M., Khosroshahi, H. G., et al. 2019, ApJ, 870, 50Jerjen, H., Binggeli, B., & Freeman, K. C. 2000, AJ, 119, 593Jerjen, H., Freeman, K. C., & Binggeli, B. 1998, AJ, 116, 2873Kamphuis, P., Rand, R. J., Józsa, G. I. G., et al. 2013, MNRAS, 434, 2069Karachentsev, I. & Petit, M. 1990, A&AS, 86, 1Karachentsev, I. D., Grebel, E. K., Sharina, M. E., et al. 2003, A&A, 404, 93Karachentsev, I. D., Karachentseva, V. E., Huchtmeier, W. K., & Makarov, D. I.2004, AJ, 127, 2031Karachentsev, I. D., Karachentseva, V. E., Suchkov, A. A., & Grebel, E. K. 2000,A&AS, 145, 415Karachentsev, I. D., Makarov, D. I., & Kaisina, E. I. 2013, AJ, 145, 101Karachentsev, I. D., Riepe, P., Zilch, T., et al. 2015, Astrophysical Bulletin, 70,379Kim, D., Jerjen, H., Mackey, D., Da Costa, G. S., & Milone, A. P. 2015a, ApJ,804, L44 Article number, page 6 of 7liver Müller and Helmut Jerjen: The abundance of dwarf galaxies around low-mass giants in the Local Volume
Kim, D., Jerjen, H., Mackey, D., Da Costa, G. S., & Milone, A. P. 2016, ApJ,820, 119Kim, D., Jerjen, H., Milone, A. P., Mackey, D., & Da Costa, G. S. 2015b, ApJ,803, 63Kraan-Korteweg, R. C. & Tammann, G. A. 1979, Astronomische Nachrichten,300, 181Lelli, F., McGaugh, S. S., Schombert, J. M., & Pawlowski, M. S. 2017, ApJ, 836,152Loveday, J., Peterson, B. A., Maddox, S. J., & Efstathiou, G. 1996, ApJS, 107,201Lucero, D. M., Carignan, C., Elson, E. C., et al. 2015, MNRAS, 450, 3935Magnier, E. A., Schlafly, E. F., Finkbeiner, D. P., et al. 2016, arXiv e-prints[ arXiv:1612.05242 ]Martin, N. F., McConnachie, A. W., Irwin, M., et al. 2009, ApJ, 705, 758Merritt, A., van Dokkum, P., & Abraham, R. 2014, ApJ, 787, L37Monelli, M. & Trujillo, I. 2019, ApJ, 880, L11Moore, B., Ghigna, S., Governato, F., et al. 1999, ApJ, 524, L19Müller, O., Ibata, R., Rejkuba, M., & Posti, L. 2019a, A&A, 629, L2Müller, O., Jerjen, H., & Binggeli, B. 2015, A&A, 583, A79Müller, O., Jerjen, H., & Binggeli, B. 2017, A&A, 597, A7Müller, O., Jerjen, H., & Binggeli, B. 2018, A&A, 615, A105Müller, O., Rejkuba, M., Pawlowski, M. S., et al. 2019b, A&A, 629, A18Müller, O., Rich, R. M., Román, J., et al. 2019c, A&A, 624, L6Park, H. S., Moon, D.-S., Zaritsky, D., et al. 2017, ApJ, 848, 19Patel, E., Carlin, J. L., Tollerud, E. J., Collins, M. L. M., & Dooley, G. A. 2018,MNRAS, 480, 1883Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2002, AJ, 124, 266Prole, D. J., van der Burg, R. F. J., Hilker, M., & Davies, J. I. 2019, MNRAS,488, 2143Radburn-Smith, D. J., de Jong, R. S., Seth, A. C., et al. 2011, ApJS, 195, 18Richardson, J. C., Irwin, M. J., McConnachie, A. W., et al. 2011, ApJ, 732, 76Roberts, D. M., Nierenberg, A. M., & Peter, A. H. G. 2020, arXiv e-prints,arXiv:2008.05479Sand, D. J., Crnojevi´c, D., Strader, J., et al. 2014, ApJ, 793, L7Sawala, T., Frenk, C. S., Fattahi, A., et al. 2016, MNRAS, 457, 1931Sersic, J. L. 1968, Atlas de galaxias australesSimon, J. D. & Geha, M. 2007, ApJ, 670, 313Simpson, C. M., Grand, R. J. J., Gómez, F. A., et al. 2018, MNRAS, 478, 548Smercina, A., Bell, E. F., Price, P. A., et al. 2018, ApJ, 863, 152Taylor, M. A., Eigenthaler, P., Puzia, T. H., et al. 2018, ApJ, 867, L15Teeninga, P., Moschini, U., Trager, S., & Wilkinson, M. 2013, power, 2, 1Teeninga, P., Moschini, U., Trager, S. C., & Wilkinson, M. H. 2015, in Inter-national Symposium on Mathematical Morphology and Its Applications toSignal and Image Processing, Springer, 157–168Tikhonov, N. A., Galazutdinova, O. A., & Drozdovsky, I. O. 2005, A&A, 431,127Toloba, E., Sand, D. J., Spekkens, K., et al. 2016, ApJ, 816, L5Trentham, N. & Tully, R. B. 2002, MNRAS, 335, 712Tully, R. B., Courtois, H. M., Dolphin, A. E., et al. 2013, AJ, 146, 86Valdes, F., Gruendl, R., & DES Project. 2014, in Astronomical Society of thePacific Conference Series, Vol. 485, Astronomical Data Analysis Softwareand Systems XXIII, ed. N. Manset & P. Forshay, 379van der Marel, R. P. & Kallivayalil, N. 2014, ApJ, 781, 121Venhola, A., Peletier, R., Laurikainen, E., et al. 2017, A&A, 608, A142Willmer, C. N. A. 2018, ApJS, 236, 47Wittmann, C., Kotulla, R., Lisker, T., et al. 2019, ApJS, 245, 10]Martin, N. F., McConnachie, A. W., Irwin, M., et al. 2009, ApJ, 705, 758Merritt, A., van Dokkum, P., & Abraham, R. 2014, ApJ, 787, L37Monelli, M. & Trujillo, I. 2019, ApJ, 880, L11Moore, B., Ghigna, S., Governato, F., et al. 1999, ApJ, 524, L19Müller, O., Ibata, R., Rejkuba, M., & Posti, L. 2019a, A&A, 629, L2Müller, O., Jerjen, H., & Binggeli, B. 2015, A&A, 583, A79Müller, O., Jerjen, H., & Binggeli, B. 2017, A&A, 597, A7Müller, O., Jerjen, H., & Binggeli, B. 2018, A&A, 615, A105Müller, O., Rejkuba, M., Pawlowski, M. S., et al. 2019b, A&A, 629, A18Müller, O., Rich, R. M., Román, J., et al. 2019c, A&A, 624, L6Park, H. S., Moon, D.-S., Zaritsky, D., et al. 2017, ApJ, 848, 19Patel, E., Carlin, J. L., Tollerud, E. J., Collins, M. L. M., & Dooley, G. A. 2018,MNRAS, 480, 1883Peng, C. Y., Ho, L. C., Impey, C. D., & Rix, H.-W. 2002, AJ, 124, 266Prole, D. J., van der Burg, R. F. J., Hilker, M., & Davies, J. I. 2019, MNRAS,488, 2143Radburn-Smith, D. J., de Jong, R. S., Seth, A. C., et al. 2011, ApJS, 195, 18Richardson, J. C., Irwin, M. J., McConnachie, A. W., et al. 2011, ApJ, 732, 76Roberts, D. M., Nierenberg, A. M., & Peter, A. H. G. 2020, arXiv e-prints,arXiv:2008.05479Sand, D. J., Crnojevi´c, D., Strader, J., et al. 2014, ApJ, 793, L7Sawala, T., Frenk, C. S., Fattahi, A., et al. 2016, MNRAS, 457, 1931Sersic, J. L. 1968, Atlas de galaxias australesSimon, J. D. & Geha, M. 2007, ApJ, 670, 313Simpson, C. M., Grand, R. J. J., Gómez, F. A., et al. 2018, MNRAS, 478, 548Smercina, A., Bell, E. F., Price, P. A., et al. 2018, ApJ, 863, 152Taylor, M. A., Eigenthaler, P., Puzia, T. H., et al. 2018, ApJ, 867, L15Teeninga, P., Moschini, U., Trager, S., & Wilkinson, M. 2013, power, 2, 1Teeninga, P., Moschini, U., Trager, S. C., & Wilkinson, M. H. 2015, in Inter-national Symposium on Mathematical Morphology and Its Applications toSignal and Image Processing, Springer, 157–168Tikhonov, N. A., Galazutdinova, O. A., & Drozdovsky, I. O. 2005, A&A, 431,127Toloba, E., Sand, D. J., Spekkens, K., et al. 2016, ApJ, 816, L5Trentham, N. & Tully, R. B. 2002, MNRAS, 335, 712Tully, R. B., Courtois, H. M., Dolphin, A. E., et al. 2013, AJ, 146, 86Valdes, F., Gruendl, R., & DES Project. 2014, in Astronomical Society of thePacific Conference Series, Vol. 485, Astronomical Data Analysis Softwareand Systems XXIII, ed. N. Manset & P. Forshay, 379van der Marel, R. P. & Kallivayalil, N. 2014, ApJ, 781, 121Venhola, A., Peletier, R., Laurikainen, E., et al. 2017, A&A, 608, A142Willmer, C. N. A. 2018, ApJS, 236, 47Wittmann, C., Kotulla, R., Lisker, T., et al. 2019, ApJS, 245, 10