A Search for Dark Matter Annihilation in Newly Discovered Dwarf Galaxies

– 10 –

Table 1. Detection of new satellite galaxy candidates in DES Y1A1

Name ↵2000

�2000

m � M Map Sig TS Scan TS Fit rh ✏ � ⌃pi(deg) (deg) (�) (deg) (deg)

DES J0335.6-5403 (Ret II) 53.92 -54.05 17.5 24.6 1466 1713 0.10+0.01�0.01 0.6+0.1

�0.2 72+7

�7

338.1

DES J0344.3-4331 (Eri II) 56.09 -43.53 22.6 23.0 322 512 0.03+0.01�0.01 0.19+0.16

�0.16 90+30

�30

96.9

DES J2251.2-5836 (Tuc II) 343.06 -58.57 18.8 6.4 129 167 0.12+0.03�0.03 – – 114.9

DES J0255.4-5406 (Hor I) 43.87 -54.11 19.7 8.2 55 81 0.04+0.05�0.02 – – 30.6

DES J2108.8-5109 (Ind I) 317.20 -51.16 19.2 5.5 – 75 0.010+0.002�0.002 – – 26.6

DES J0443.8-5017 (Pic I) 70.95 -50.28 20.5 7.1 – 63 0.02+0.07�0.01 – – 19.1

DES J2339.9-5424 (Phe II) 354.99 -54.41 19.9 5.1 – 61 0.02+0.01�0.01 – – 19.4

DES J0222.7-5217 (Eri III) 35.69 -52.28 19.9 5.4 – 57 0.007+0.005�0.003 – – 8.9

Note. — Best-fit parameters from the maximum-likelihood fit assuming the composite isochrone described in Section 3.2. Uncertainties are

calculated from the the highest density interval containing 90% of the posterior distribution. “Map Sig” refers to detection significance of the

candidate from the stellar density map search method (Section 3.1). “TS Scan” refers to the significance (Equation 4) from the likelihood scan

using a Plummer model spatial kernel with half-light radius rh = 0.�1 (Section 3.2). “TS Fit” denotes the significance of the likelihood method

using the set of best-fit parameters. Ellipticities and position angles are not quoted for lower significance candidates where they are not well

constrained by the data. ⌃pi is the estimated number of satellite member stars with g < 23 in the stellar catalog.

Fig. 2.— Left : False color gri coadd image of the 0.

�3 ⇥ 0.

�3 region centered on DES J0335.6

�5403. Right : Stars in the same field of view with membership probability pi > 0.01 are marked

with colored circles. In this color map, red signifies high-confidence association with DES J0335.6

�5403 and blue indicates lower membership probability. The membership probabilities have been

evaluated using Equation (2) for the best-fit model parameters listed in Table 1.

In collaboration with Matt Walker (CMU)

Savvas Koushiappas (Brown) Sergey Koposov, Vasily Belokurov, Gabriel Torrealba, Wyn Evans (Cambridge IoA)

Vincent Bonnivard, Celine Combet, David Maurin (LPSC Grenoble)

RetII

arXiv:1503.02320 (PRL), arXiv:1410.2242 (PRD), arXiv:1504.03309 (ApJL)

DES

Alex Geringer-SamethCarnegie Mellon University

Cambridge IoA, Sep 23, 2015

Dark matter

Large scales — gravity

Microscopic physics — what is it?

Look for its particle interactions

Gamma-rays — Fermi satellite

NASA

Milky Way dwarf galaxies

Nearby

Lots of dark matter

Not much else: no astrophysical backgroundVery important! e.g. Galactic center

Num

ber o

f dw

arf g

alax

ies

SDSS

March 2015

Milky Way dwarf galaxies

3

Figure 3. False-colour map of the density of the main sequence turn-off (MSTO) stars with 0.2<g−r<0.6 as observed by the DES survey.The density in different magnitude bins corresponding to different distances is used to create different colour channels: blue 17<r<19(corresponding to distances of ∼ 4−10 kpc), green 19<r<21 (10−25 kpc), red 21<r<22.75 (25−56 kpc). The MW satellites discovered inthis paper are shown with white unfilled circles. Note that the declination axis has been broken to avoid showing large empty area between-35! δ !-5 without DES data

weight maps and masks in Rice compressed format was∼4.6 TB. Once uncompressed, the size of the images andweight maps increases by a factor of ∼ 10. For the anal-ysis reported below, only g,r and i band images wereanalysed (∼ 30TB of data).DES images are taken with 90s exposure and the DE-

Cam pixel scale is 0.26′′/pixel. InstCal products, de-livered by the DECam pipeline, are single-frame images(not stacks) that have been bias, dark and flat-field cal-ibrated as well as cross-talk corrected. Additionally, de-fects and cosmic rays have been masked and the WCSastrometry provided3.

2.1. From Images to Catalogues

For the subsequent catalogue creation, we haverelied heavily on the SExtractor/PSFEx rou-tines (see Bertin & Arnouts 1996; Bertin 2011;Annunziatella et al. 2013, for more details). Typi-cally, processing a single frame consisting of 60 CCDchips with SExtractor/PSFEx took ∼ 2.5 CPU-hours,leading to a total budget for the three DES filters of∼15000 CPU-hours. The image processing has beencarried out using the Darwin HPC computing facility4

as well as a local 8 node/96 core computer cluster. Themain catalogue assembly steps are as follows:

• Initial SExtractor pass. To provide the startingparameters for the PSFEx routine, the DES im-ages are analysed by SExtractor. The flag settingsare standard, albeit the PHOT_APERTURES flag is ad-justed to match the value of the G_SEEING keywordin the header (if it is available). Additionally, thedownloaded weight maps are provided to SExtrac-tor via the WEIGHT_MAP option.

• PSFEx run. The output of SExtractor is used tocalculate the PSFs for the subsequent photometry.PSFEx is run on each CCD chip separately withdefault PSFEx options, except the PSF_SIZE key-word which is set to (40,40) pixels.

3 Detailed information available through the DECam DataHandbook at http://bit.ly/1D7ZGDc

4 http://www.hpc.cam.ac.uk

• Final SExtractor pass. Using the PSF models com-puted in the previous step, SExtractor is run againto determine Model and PSF magnitudes. Thisstep is the longest in the entire sequence.

• Ingestion. For each filter, the resulting SExtrac-tor catalogues are ingested into a PostgreSQLdatabase as separate tables. Q3C spatial indices(Koposov & Bartunov 2006) are created to speedup further steps.

• Duplicate removal. Due to significant image over-laps, sources appearing more than once have tobe flagged in the catalogues. For each source weperform a search with 1′′ radius, and mark all ob-jects coming from different frames and HDUs assecondary.

• Photometric calibration. To convert instrumen-tal magnitudes into calibrated ones for each frame(including multiple HDUs) a cross-match betweenthe DES and the APASS DR7 survey data is per-formed. The zero-point is then measured as a me-dian offset with respect to the APASS photome-try on a per-field basis. The resulting photometricprecision as estimated using overlaps of differentframes is: 0.03 mag (Gaussian σ) in the g-band,0.025 mag in the r-band, and 0.033 mag in the i-band.

• Band-merging. The lists of primary sources in theg, r and i bands are combined into the final cat-alogue using the matching radius of 1 arcseconds.For the purpose of this paper, the catalogue wasbased on r-band, i.e. r-band detection was requiredin order for the object to be in the final catalogue.

• The final Q3C index is created on the band-mergedcatalogue to speed up spatial searches in thedataset.

2.2. Photometry and star-galaxy separation

5

Figure 4. Reticulum 2 satellite.Top row, 1st panel: Density of all stars centered on the satellite’s location, dark shades of grey correspondto density enhancement. Red circles show the size of the apertures used to create CMDs given in the 1st and the 3rd bottom panels.Note the prominent over-density in the centre.Top row, 2nd panel: Density of stars selected using the isochrone mask shown in the 1stbottom panel. The background/foreground density variations have now subsided further as compared to the left-most panel. Top row,

3rd panel: Density of galaxies in the vicinity of the satellite. No obvious over-density coincident with the object is visible. Top row, 4th

panel: Distribution of Galactic dust reddening E(B − V ) according to the measurement of Schlegel et al. (1998). The extinction valuescorresponding to black and white colors in the panel are given in the panel title. Bottom row, 1st panel: Colour-Magnitude distributionof stars inside the smaller of the two apertures shown in the 1st Top panel, centered on the object. Note the unmistakable overdensitycorresponding to the Main Sequence and Main Sequence Turn-Off stars. The Red Giant Branch stars are also visible, albeit more scarce.There appears to be at least one possible Blue Horizontal Branch star member, as indicated by the good match between with isochrone(red dashed line) and the M92 BHB ridge-line (blue solid line). Bottom row, 2nd panel: Comparison CMD built from random nearbystars outside the larger aperture, but covering the same on-sky area as in leftmost bottom panel. The comparison shows various stellarpile-ups, most prominently the disk dwarfs and objects near the detection limits, but features similar to that of the satellite’s populationsare not observed. Bottom row, 3rd panel: Satellite’s CMD for stars within the larger of the two apertures shown in the 1st top panel. Atleast 3 likely BHB members are visible. Bottom row, 4th panel: Hess difference for stars within and outside the aperture of r = 18′. Notethe satellite’s MS, MSTO and RGB populations standing out clearly. Bottom row, 5th panel: Density of nearby background stars in thecolour-magnitude space (Hess diagram).

sity peak at the location of the satellite.We start by taking a catalogue of sources classified as

stars. A sub-set of these is then carved out with either aset of colour-magnitude cuts or with an isochrone maskoffset to a trial distance modulus. Then a 2D on-skydensity map of the selected stars is constructed, keepingthe spatial pixel sufficiently small, e.g. 1′ on a side. Atthe next step, the density map is convolved with a setof matched filters (described above) with different innerand outer kernels. Finally, these convolved maps areconverted into Gaussian significance maps and the mostsignificant over-densities are extracted.In the analysis presented here, we have used the mask

based on the PARSEC isochrone (Bressan et al. 2012)with an age of 12 Gyr and metallicity of [Fe/H] = −2 6,spread out by the characteristic DES photometric erroras a function of colour and magnitude. The trial distancemoduli explored in the search range from m−M=15 to

6 http://stev.oapd.inaf.it/cmd

m−M=24. The inner kernel size is allowed to vary from1′ to 10′. After extracting the most significant over-densities all detections are cross-matched with the listof positions of known dwarf galaxies from McConnachie(2012), nearby LEDA galaxies (Paturel et al. 2003) withradial velocities less than 2000km/s, globular clusters inthe catalogue of Harris (1996) as well as the globularclusters listed in Simbad.The list of over-densities produced is then cleaned for

duplicates, e.g. over-densities detected with more thanone distance modulus and/or kernel size. We have alsoremoved detections near the very edge of the survey’sfootprint. The remaining candidates are ranked by theirsignificance and eye-balled. Among the 9 objects pre-sented in this paper, 5 are at the very top of the rankedlist with significances well above 10σ, while a further 4are somewhat lower in the list (but with significancesof order of 10σ). We firmly believe that all objects pre-sented below are genuine new satellites of the Milky Way.Apart from the over-density significance, our inference

DES

Koposov et al 1503.02079 (ApJ)

Reticulum II

Gamma-rays 1-300 GeV Background model

�105 �100 �95 �90 �85 �80Galactic longitude [Deg]

�60

�55

�50

�45

�40

Gal

acti

cla

titu

de

[Deg

]

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

Rel

ativ

ein

tensi

ty

Uniform backgroundFar away from known sources

nearest of the new DES satellites (30 kpc)(Koposov+ 2015, Bechtol+ 2015)

100 101 102

Energy [GeV]

10�7

10�6

10�5

E2dF

/dE

[GeV

cm�

2s�

1sr

�1]

1339051 33 22

18 11

10 6

1

1

135.496.3

59.2 33.519.911.56.5 3.9 2.3 1.3

0.6 0.30.2 0.1 0.1

Events within 0.5° of RetII

Geringer-Sameth+ arXiv:1503.02320 (PRL)

A suggestive feature?

Need to quantify the significance of the signal (e.g. p-value)

Statistical procedure

Each photon gets a weight

sum over all observed events

Weight of photon is based on: !

• Energy • Angular separation from

location of dwarf

{

Qi

T =X

i2photons

w(Qi)

wQ = log

✓1 +

sQbQ

◆signal

background

AGS, Koushiappas, Walker arXiv:1410.2242 (PRD)

101 102 103

Mass [GeV]

0�

1�

2�

3�

4�

5�

Sig

nifi

cance

⌧+⌧�

Di↵use 1

Di↵use 2

Empirical 1

Empirical 2

101 102 103

Mass [GeV]

0�

1�

2�

3�

4�

5�

Sig

nifi

cance

µ+µ�

⌧+⌧�qq

bb

W+W �

hh

Results

pglobal < 9.8 ×10−5 Searching over dark matter masses = multiple hypothesis tests

Local p-value < 3 ⨉10-5 (4σ) in every channel

Robust to different background spectra

101 102 103

Mass [GeV]

�3�

�2�

�1�

0�

1�

2�

3�

Sig

nifi

cance

⌧+⌧�

RetIISeg1

�105 �100 �95 �90 �85 �80Galactic longitude [Deg]

�60

�55

�50

�45

�40

Gal

acti

cla

titu

de

[Deg

]

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

Rel

ativ

ein

tensi

tyLocal p-value of 8/3306 = 0.0024 (2.8σ)

Global p-value of 32/3306 = 0.0097 (2.3σ)

Empirical background sampling

Geringer-Sameth+ arXiv:1503.02320 (PRL)

101 102 103

Mass [GeV]

10�1

100

101

102

103

J19

h�vi �

26

bb

⌧+⌧�hh

µ+µ�

<σv> upper limits from other dwarfs gives a prediction for Ret2’s J value

22

101 102 103

Mass [GeV]

27

26

25

24

23

�+��

FIG. 11: Annihilation cross section limits from the joint analysis of 20 dwarf galaxies. The shaded band is the systematic 1�

uncertainty in the limit derived from many realizations of halo J-profiles of the dwarfs consistent with kinematic data. Thesolid line depicts the median of this distribution of limits over the halo realizations. The thin dashed line corresponds to thebenchmark value of the required relic abundance cross section (3 ⇥ 10�26cm3

/s), while the solid horizontal line correspondsto the detailed calculation of this quantity derived by Steigman et al. [18]. The observed limits are below this latter curvefor masses less than [0, 26, 54] GeV (for annihilation into bb), [18, 29, 62] GeV (⌧+

⌧

�), [21, 35, 64] GeV (uu, dd, ss, cc, and gg),[87, 114, 146] GeV (��), and [5, 6, 10] GeV (e+

e

�), where the quantities in brackets are for the �1�, median, and +1� levels ofthe systematic uncertainty band. A machine-readable file tabulating these limits is available as Supplemental Material.

observed test statistic. The signal significance is shownassuming the two di↵erent background PDFs. An as-sumption of a Poisson background does not describe theactual background in many cases and can lead to a mis-takenly large detection significance.

The di�culty in fitting a multi-component Poissonbackground model is illustrated in Fig. 4 of [92]. There,“blank sky locations” are used to test whether the like-lihood ratio test statistic is accurately described by an“asymptotic” �2 distribution. This sampling of blank skylocations is analogous to the empirical background sam-pling developed in [48] and employed in the present work.Ackermann et al. [92] found that the blank sky PDF ofthe test statistic deviated from the �2 distribution at

large values of the test statistic. One of the reasons forthe deviation could be that the background model is notflexible enough to describe the true background. Carl-son et al. [56] present evidence that unresolved blazarsand radio sources are at least partly responsible for theinsu�ciency of the background treatment used in [92].

The blank sky location sampling of Ackermann et al.[92, Fig. 4] reduces the tail probability of a TS = 8.7observation to a local p-value of 0.13. This correspondsto a significance of 2.2� which can be directly comparedto the values shown in our Figs. 8, 9, and 10. Thus,when calibrating the detection significance using an em-pirical sampling of the background, the results of Acker-mann et al. [92] are closer in line with what we find. We

h�vi

allowed

ruled out

Reticulum 2 Other dwarfs

log10 J & 19.6± 0.3

AGS, Koushiappas, Walker arXiv:1410.2242 (PRD) Geringer-Sameth+ arXiv:1503.02320 (PRL)

If signal is due to dark matter annihilation what can we say about the dark matter particle?

Jh�vi

Bonnivard et. al. arXiv:1504.03309 (ApJL)

Measured J values

4 Bonnivard et al.

[deg]intα-210 -110 1 10

]-5

cm

2) [

GeV

int

αJ(

1710

1910

2110

2310

Median68% CIs95% CIs

Reticulum II

J-factor

[deg]intα-210 -110 1 10

]-2

) [G

eV c

min

tα

D(

1610

1710

1810

1910

2010

2110

2210

Median68% CIs95% CIs

Reticulum II

D-factor

Figure 3. Median (solid), 68 % (dashed), and 95% (dash-dot) CIsof the J- (top) and D-factors (bottom) of Ret II, as a function ofintegration angle, reconstructed from our Jeans/MCMC analysis.

0.1 < Pi < 0.95, we obtain very similar results. Thesetwo tests confirm that the reconstruction of the astro-physical factors of Ret II is not significantly a↵ected byoutliers. This is not always the case, notably for Segue I(Bonnivard, Maurin & Walker, in prep.).We note that Simon et al. (2015) independently per-

formed an analysis of the M2FS Ret II spectroscopic dataand found a slightly smaller J-factor. This can be tracedto their choice of priors and light profile (L. Strigari,private communication). A detailed comparison will bepresented in Geringer-Sameth at al. (in prep.).

4. COMPARISON TO OTHER DSPHS

The same Jeans analysis has been applied to twenty-one other dSphs in Bonnivard et al. (2015b). In Figure 4,we compare the J-factors (for ↵

int

= 0.5�) of Ret II to thebrightest objects identified in Bonnivard et al. (2015b)11.Ret II is comparable to Wilman I in terms of its medianJ-factor, but slightly below Coma Berenices and UrsaMajor II. Its CIs are typical of an ‘ultrafaint’ dSph, andsignificantly larger than the uncertainties of ‘classical’dSphs.Interpreting the possible �-ray signal in Ret II in

terms of DM annihilation (Geringer-Sameth et al. 2015b;Hooper & Linden 2015), one would expect similar emis-sions from the dSphs with comparable J-factors, such asUMa II, Coma, and Wil I. However, no excess was re-ported from these latter objects (Geringer-Sameth et al.2014; Fermi-LAT Collaboration 2015). This could beexplained by the large statistical and systematic12 un-

11 Segue I may have a highly uncertain J-factor (Bonnivard,Maurin & Walker, in prep.). We show it only for illustration pur-poses.

12 The latter comes from a possible triaxiality of the dSph (0.4and 0.3 dex for annihilation and decay respectively, see Bonnivardet al. 2015a), and depends on the l.o.s. orientation with respect to

Ret II UMa II Coma Wil I Dra UMi Seg I

)-5

cm

2)/G

eV°

= 0

.5in

tα

(J(

10Lo

g

15

16

17

18

19

20

21

Ret II:Optimised setupPi-weightedBinned analysisBootstrap68% CIs (+ triaxiality systematics [ ] )

d [kpc]30 30 44 38 82 66 23

Bonnivard et al. (2015b)ClassicalUltrafaint

Figure 4. Comparison of the J-factors at ↵int = 0.5� obtainedfor Ret II (red circle) and for the potentially brightest objectsfrom Bonnivard et al. (2015b) (blue squares), with the sameJeans/MCMC analysis. Ret II is comparable to Wil I in termsof J-factors, but slightly below Coma and UMa II. A 0.4 dex sys-tematic uncertainty was added in quadrature to the 68% CIs toaccount for possible triaxiality of the DM halo (Bonnivard et al.2015a). Also shown are the J-factors obtained for Ret II by varyingdi↵erent ingredients of the analysis - see Section 3.

certainties in the J-factors. Moreover, the Jeans analysisassumes all of these objects to be in dynamical equilib-rium, but tidal interactions with the Milky Way couldartificially inflate the velocity dispersion and thereforethe astrophysical factors. UMa II, and to a lesser extentComa, appear to be experiencing tidal disturbance (Si-mon & Geha 2007; Fellhauer et al. 2007; Munoz et al.2010; Smith et al. 2013), while Wil I may show non-equilibrium kinematics (Willman et al. 2011). Cautionis therefore always advised when interpreting the astro-physical factors of these objects. The dynamical statusof Ret II is not yet clear. Its flattened morphology maysignal ongoing tidal disruption. However, the availablekinematic data do not exhibit a significant velocity gra-dient that might be associated with tidal streaming mo-tions (Walker et al. 2015).

5. CONCLUSION

We have applied a spherical Jeans analysis to the newlydiscovered dSph Ret II, using sixteen likely membersfrom the kinematic data set of Walker et al. (2015).We employed the optimized setup of Bonnivard et al.(2015a,b), which was found to mitigate several biasesof the analysis, and checked that our results are robustagainst several of its ingredients. We find that Ret IIpresents one of the largest annihilation J-factors amongthe Milky Way’s dSphs, possibly making it one of thebest targets to constrain DM particle properties. How-ever, it is important to obtain follow-up photometric andspectroscopic data in order to test the assumptions of dy-namical equilibrium as well as to constrain the fraction ofbinary stars in the kinematic sample. Nevertheless, theproximity of Ret II and its apparently large dark mattercontent place it among the most attractive targets fordark matter particle searches.

This work has been supported by the “Investissementsd’avenir, Labex ENIGMASS”, and by the French ANR,Project DMAstro-LHC, ANR-12-BS05-0006. MGW

the principle axes of the halo.

19.6

Use line of sight velocities + Jeans equation to infer dark matter density profile

see also Simon et. al. arXiv:1504.02889 (ApJ)

Bonnivard et. al. arXiv:1504.03309 (ApJL)

Measured J values

4 Bonnivard et al.

[deg]intα-210 -110 1 10

]-5

cm

2) [

GeV

int

αJ(

1710

1910

2110

2310

Median68% CIs95% CIs

Reticulum II

J-factor

[deg]intα-210 -110 1 10

]-2

) [G

eV c

min

tα

D(

1610

1710

1810

1910

2010

2110

2210

Median68% CIs95% CIs

Reticulum II

D-factor

Figure 3. Median (solid), 68 % (dashed), and 95% (dash-dot) CIsof the J- (top) and D-factors (bottom) of Ret II, as a function ofintegration angle, reconstructed from our Jeans/MCMC analysis.

0.1 < Pi < 0.95, we obtain very similar results. Thesetwo tests confirm that the reconstruction of the astro-physical factors of Ret II is not significantly a↵ected byoutliers. This is not always the case, notably for Segue I(Bonnivard, Maurin & Walker, in prep.).We note that Simon et al. (2015) independently per-

formed an analysis of the M2FS Ret II spectroscopic dataand found a slightly smaller J-factor. This can be tracedto their choice of priors and light profile (L. Strigari,private communication). A detailed comparison will bepresented in Geringer-Sameth at al. (in prep.).

4. COMPARISON TO OTHER DSPHS

The same Jeans analysis has been applied to twenty-one other dSphs in Bonnivard et al. (2015b). In Figure 4,we compare the J-factors (for ↵

int

= 0.5�) of Ret II to thebrightest objects identified in Bonnivard et al. (2015b)11.Ret II is comparable to Wilman I in terms of its medianJ-factor, but slightly below Coma Berenices and UrsaMajor II. Its CIs are typical of an ‘ultrafaint’ dSph, andsignificantly larger than the uncertainties of ‘classical’dSphs.Interpreting the possible �-ray signal in Ret II in

terms of DM annihilation (Geringer-Sameth et al. 2015b;Hooper & Linden 2015), one would expect similar emis-sions from the dSphs with comparable J-factors, such asUMa II, Coma, and Wil I. However, no excess was re-ported from these latter objects (Geringer-Sameth et al.2014; Fermi-LAT Collaboration 2015). This could beexplained by the large statistical and systematic12 un-

11 Segue I may have a highly uncertain J-factor (Bonnivard,Maurin & Walker, in prep.). We show it only for illustration pur-poses.

12 The latter comes from a possible triaxiality of the dSph (0.4and 0.3 dex for annihilation and decay respectively, see Bonnivardet al. 2015a), and depends on the l.o.s. orientation with respect to

Ret II UMa II Coma Wil I Dra UMi Seg I

)-5

cm

2)/G

eV°

= 0

.5in

tα

(J(

10Lo

g

15

16

17

18

19

20

21

Ret II:Optimised setupPi-weightedBinned analysisBootstrap68% CIs (+ triaxiality systematics [ ] )

d [kpc]30 30 44 38 82 66 23

Bonnivard et al. (2015b)ClassicalUltrafaint

Figure 4. Comparison of the J-factors at ↵int = 0.5� obtainedfor Ret II (red circle) and for the potentially brightest objectsfrom Bonnivard et al. (2015b) (blue squares), with the sameJeans/MCMC analysis. Ret II is comparable to Wil I in termsof J-factors, but slightly below Coma and UMa II. A 0.4 dex sys-tematic uncertainty was added in quadrature to the 68% CIs toaccount for possible triaxiality of the DM halo (Bonnivard et al.2015a). Also shown are the J-factors obtained for Ret II by varyingdi↵erent ingredients of the analysis - see Section 3.

certainties in the J-factors. Moreover, the Jeans analysisassumes all of these objects to be in dynamical equilib-rium, but tidal interactions with the Milky Way couldartificially inflate the velocity dispersion and thereforethe astrophysical factors. UMa II, and to a lesser extentComa, appear to be experiencing tidal disturbance (Si-mon & Geha 2007; Fellhauer et al. 2007; Munoz et al.2010; Smith et al. 2013), while Wil I may show non-equilibrium kinematics (Willman et al. 2011). Cautionis therefore always advised when interpreting the astro-physical factors of these objects. The dynamical statusof Ret II is not yet clear. Its flattened morphology maysignal ongoing tidal disruption. However, the availablekinematic data do not exhibit a significant velocity gra-dient that might be associated with tidal streaming mo-tions (Walker et al. 2015).

5. CONCLUSION

We have applied a spherical Jeans analysis to the newlydiscovered dSph Ret II, using sixteen likely membersfrom the kinematic data set of Walker et al. (2015).We employed the optimized setup of Bonnivard et al.(2015a,b), which was found to mitigate several biasesof the analysis, and checked that our results are robustagainst several of its ingredients. We find that Ret IIpresents one of the largest annihilation J-factors amongthe Milky Way’s dSphs, possibly making it one of thebest targets to constrain DM particle properties. How-ever, it is important to obtain follow-up photometric andspectroscopic data in order to test the assumptions of dy-namical equilibrium as well as to constrain the fraction ofbinary stars in the kinematic sample. Nevertheless, theproximity of Ret II and its apparently large dark mattercontent place it among the most attractive targets fordark matter particle searches.

This work has been supported by the “Investissementsd’avenir, Labex ENIGMASS”, and by the French ANR,Project DMAstro-LHC, ANR-12-BS05-0006. MGW

the principle axes of the halo.

19.6

10 Bonnivard, Maurin, Walker

Seg I UMa II Ret II Wil I Coma UMi Dra

)-5

cm

2)

/ G

eV

° =

0.5

int

α (

J(

10

Lo

g

12

14

16

18

20

22

Membership prob. (P)

EM P-weighted MCMC

Bayesian Cut-95% Bootstrap

d [kpc]23 30 30 38 44 66 82

Bootstrapσ68% CIs/

No P available

P analysis Stat. analysis

Figure 8. Comparison of the J-factors of Seg I, obtained with the severaltests of this paper, to the values for the closest dSphs galaxies from Bon-nivard et al. (2015a,b). The J-factor can vary from ⇠ 10

16 to ⇠ 10

21

GeV2 cm�5 from one analysis to another. On the other hand, Ret II’s J-factor was found to be robust against the different tests.

for other dSph galaxies10. Depending on choice of procedure, forSeg I we can recover estimates of J-factors spanning ⇠ 3 orders ofmagnitude, covering the range of previously published values. Weconclude that estimates of J-factors for Seg I should be regardedwith extreme caution when planning and interpreting indirect de-tection experiments.

ACKNOWLEDGEMENTS

We thank Celine Combet and Alex Geringer-Sameth for useful dis-cussions, and Manoj Kaplinghat for comments that have helpedus improve the paper. This work has been supported by the “In-vestissements d’avenir, Labex ENIGMASS” and by the FrenchANR, Project DMAstro-LHC, ANR-12-BS05-0006. MGW is sup-ported by National Science Foundation grants AST-1313045, AST-1412999. This study used the CC-IN2P3 computation center ofLyon.

REFERENCES

Aaronson M., 1983, ApJ, 266, L11Ackermann, Fermi-LAT Collaboration, 2011, Physical Review

Letters, 107, 241302Ackermann M. et al., 2014, Phys. Rev. D, 89, 042001Aleksic J. et al., 2014, J. Cosmology Astropart. Phys., 2, 8Aliu E. et al., 2012, Phys. Rev. D, 85, 062001Baes M., van Hese E., 2007, A&A, 471, 419Belokurov V. et al., 2009, MNRAS, 397, 1748Belokurov V., et al., 2007, ApJ, 654, 897Binney J., Tremaine S., 2008, Galactic Dynamics: Second Edi-

tion. Princeton University PressBonnivard V. et al., 2015a, ArXiv e-printsBonnivard V. et al., 2015b, ArXiv e-printsBonnivard V., Combet C., Maurin D., Walker M. G., 2015c, MN-

RAS, 446, 3002

10 For Ursa Major II (UMa II), Willman I (Wil I) and Coma, we could notrepeat our tests for sensitivity to choice of procedure for handling member-ship probabilities, as the relevant stellar-kinematic samples are not publiclyavailable.

Bonnivard V., Hutten M., Nezri E., Charbonnier A., Combet C.,Maurin D., 2015d, ArXiv e-prints

Brooks A. M., Zolotov A., 2014, ApJ, 786, 87Charbonnier A. et al., 2011, MNRAS, 418, 1526Charbonnier A., Combet C., Maurin D., 2012, Computer Physics

Communications, 183, 656Cholis I., Salucci P., 2012, Phys. Rev. D, 86, 023528Efron B., 1982, The Jackknife, the Bootstrap and other resampling

plansEssig R., Sehgal N., Strigari L. E., Geha M., Simon J. D., 2010,

Phys. Rev. D, 82, 123503Evans N. W., Ferrer F., Sarkar S., 2004, Phys. Rev. D, 69, 123501Fermi-LAT Collaboration et al., 2015, ArXiv e-printsGeringer-Sameth A., Koushiappas S. M., 2011, Physical Review

Letters, 107, 241303Geringer-Sameth A., Koushiappas S. M., Walker M., 2015, ApJ,

801, 74Geringer-Sameth A., Koushiappas S. M., Walker M. G., 2014,

ArXiv e-printsGeringer-Sameth A., Walker M. G., Koushiappas S. M., Koposov

S. E., Belokurov V., Torrealba G., Wyn Evans N., 2015, ArXive-prints, 1503.02320

Hooper D., Linden T., 2015, ArXiv e-prints, 1503.06209Kirby E. N. et al., 2010, ApJS, 191, 352Klimentowski J., Łokas E. L., Kazantzidis S., Prada F., Mayer L.,

Mamon G. A., 2007, MNRAS, 378, 353Koposov S. E., Belokurov V., Torrealba G., Wyn Evans N., 2015a,

ArXiv e-prints, 1503.02079Koposov S. E. et al., 2015b, ArXiv e-printsLake G., 1990, Nature, 346, 39Martin N. F., Ibata R. A., Chapman S. C., Irwin M., Lewis G. F.,

2007, MNRAS, 380, 281Martinez G. D., Bullock J. S., Kaplinghat M., Strigari L. E., Trotta

R., 2009, Journal of Cosmology and Astro-Particle Physics, 6, 14Martinez G. D., Minor Q. E., Bullock J., Kaplinghat M., Simon

J. D., Geha M., 2011, ApJ, 738, 55Mateo M. L., 1998, ARA&A, 36, 435McConnachie A. W., 2012, AJ, 144, 4Putze A., Derome L., 2014, Physics of the Dark Universe, 5, 29Robin A. C., Reyle C., Derriere S., Picaud S., 2003, A&A, 409,

523Simon J. D. et al., 2015, ArXiv e-printsSimon J. D., Geha M., 2007, ApJ, 670, 313Simon J. D. et al., 2011, ApJ, 733, 46Springel V. et al., 2008, MNRAS, 391, 1685Strigari L. E., 2013, Phys. Rep., 531, 1Strigari L. E., Bullock J. S., Kaplinghat M., Simon J. D., Geha M.,

Willman B., Walker M. G., 2008a, Nature, 454, 1096Strigari L. E., Koushiappas S. M., Bullock J. S., Kaplinghat M.,

2007, Phys. Rev. D, 75, 083526Strigari L. E., Koushiappas S. M., Bullock J. S., Kaplinghat M.,

Simon J. D., Geha M., Willman B., 2008b, ApJ, 678, 614The DES Collaboration et al., 2015, ArXiv e-printsWalker M. G., Combet C., Hinton J. A., Maurin D., Wilkinson

M. I., 2011, ApJ, 733, L46Walker M. G., Mateo M., Olszewski E. W., 2009, AJ, 137, 3100Walker M. G., Mateo M., Olszewski E. W., Bailey, III

J. I., Koposov S. E., Belokurov V., Wyn Evans N., 2015,ArXiv:1504.03060

Walker M. G., Mateo M., Olszewski E. W., Penarrubia J., WynEvans N., Gilmore G., 2009a, ApJ, 704, 1274

c� Xxxx RAS, MNRAS 000, 1–10

Use line of sight velocities + Jeans equation to infer dark matter density profile

Bonnivard et. al. arXiv:1506.08209

see also Simon et. al. arXiv:1504.02889 (ApJ)

Seg1

1. Gamma-ray data is inconsistent with background

2. Consistent with dark matter annihilation

3. Inconsistent with any other possible source

Dark matter halo of RetII !Energy spectrum of signal

Population of sources inside RetII (pulsars?) !Distant source coincidentally in same direction !Instrument/data, Pass 8 !

— related to (1)

Drlica-Wagner+ (Fermi,DES) 1503.02632 (ApJL) Hooper & Linden 1503.06209

Hurdles for any dark matter interpretation