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Debates on the Nature of Dark MatterSackler 2014
19-22 May 2014
Searching for Dark Matter in the Galactic Center with
Fermi LAT: Challenges
Simona MurgiaUniversity of California, Irvine
Gamma rays from DM Annihilation
arXiv:0908.0195
The Fermi Sky
Fermi LAT data 4 years, E > 1 GeV
Understanding the Gamma-ray Sky
= + +data sources galactic diffuse isotropic
+dark matter??
The diffuse gamma-ray emission from the Milky Way is produced by cosmic rays interacting with the interstellar gas and radiation field and carries important information on the acceleration, distribution, and propagation of cosmic rays.
Galactic Gamma-Ray Interstellar Emission
= + +data sources galactic diffuse isotropic
Inverse Compton Bremsstrahlung π0-decay
x-ray, gamma-rayx-ray, gamma-ray
proton
proton
synchotron radiation inverse Compton scattering
bremsstrahlung radiation
All of these mechanisms create also non γ-ray radiation
Cosmic ray origin, propagation, and properties of the interstellar medium can be constrained by comparing the data to predictions.
Generate models (in agreement with CR data) varying CR source distribution, CR halo size, gas distribution (GALPROP, http://galprop.stanford.edu) and compare with Fermi LAT data
Assume locally measured CR spectra and intensities are representative of the Galaxy
Galactic Gamma-ray Interstellar Emission
Cosmic ray origin, propagation, and properties of the interstellar medium can be constrained by comparing the data to predictions.
Generate models (in agreement with CR data) varying CR source distribution, CR halo size, gas distribution (GALPROP, http://galprop.stanford.edu) and compare with Fermi LAT data
Assume locally measured CR spectra and intensities are representative of the Galaxy
Gamma-ray emissivity of hydrogen gas from within ~ 1kpc from the Sun is in agreement with predictions based on directly measured CR spectra
Gamma Rays from Local HI
arXiv:0908.1171
Cosmic ray origin, propagation, and properties of the interstellar medium can be constrained by comparing the data to predictions.
Generate models (in agreement with CR data) varying CR source distribution, CR halo size, gas distribution (GALPROP, http://galprop.stanford.edu) and compare with Fermi LAT data
Example model:CR source distribution: SNRsCR confinement region: 20 kpc radius, 4 kpc height
– 88 –
Fig. 7.— Fractional residual maps, (model ! data)/data, in the energy range 200 MeV –
100 GeV. Shown are residuals for model SSZ4R20T150C5 (top) and model SLZ6R20T"C5
(bottom). The maps have been smoothed with an 0.5! hard edge kernel, see Figure 6.
(data - prediction)/prediction) for example model
All Sky
arXiv:1202.4039 Fermi LAT data 21 months, 200 MeV-100 GeV
On a large scale the agreement between data and prediction overall is good, however some extended excesses and deficits stand out.
Cosmic ray origin, propagation, and properties of the interstellar medium can be constrained by comparing the data to predictions.
Generate models (in agreement with CR data) varying CR source distribution, CR halo size, gas distribution (GALPROP, http://galprop.stanford.edu) and compare with Fermi LAT data
Inner galaxy
isotropic
IC
DGE Total
π0-decaybremsstrahlung
sources
Inner Galaxy
arXiv:1202.4039
Fermi LAT data 21 months, 200 MeV-100 GeV
☺ Steep DM profiles predicted by CDM ⇒ Large DM annihilation/decay signal from GC!
Galactic Center Region
☹ Good understanding of the conventional astrophysical background is crucial to extract a potential DM signal from this complex region of the sky:
‣ source confusion: many energetic sources near to or in the line of sight of the GC
‣ diffuse emission modeling: large uncertainties due to the overlap of structures along the line of sight, difficult to model
☺ Steep DM profiles predicted by CDM ⇒ Large DM annihilation/decay signal from GC!
☹ Good understanding of the conventional astrophysical background is crucial to extract a potential DM signal from this complex region of the sky:
‣ source confusion: many energetic sources near to or in the line of sight of the GC
‣ diffuse emission modeling: large uncertainties due to the overlap of structures along the line of sight, difficult to model
CR Source Distribution
– 82 –
Fig. 1.— CR source density at z = 0 in arbitrary units as a function of Galactocentric
radius. Solid black curve: SNRs (Case & Bhattacharya 1998). Dashed blue curve: Pulsars
(Lorimer et al. 2006). Dotted red curve: Pulsars (Yusifov & Kucuk 2004). Dash-dotted
green curve: OB stars (Bronfman et al. 2000). While the units are arbitrary, the relative
normalisations of the curves in the figure match those found in the GALPROP models used
in this analysis. The CR flux of the models is normalised to the observed CR flux at the solar
circle after propagation. The normalisation is done at 100 GeV and is therefore una!ected
by modulation.
Cosmic ray source density
SNRs
Pulsars (Lorimer 2006)
Pulsars (Yusifov&Kukuk 2004)
OB stars
arXiv:1202.4039
Fractional residual difference between models generated with two different CR source distributions
Diffuse TeV Emission
The gamma rays of the Galactic center ridge at TeV energies observed by HESS is hard (spectral index~2.3), suggesting spectrum of CRs is harder than measured locally
Aharonian et al 2006
HESS
Aharonian et al 2006
☺ Steep DM profiles predicted by CDM ⇒ Large DM annihilation/decay signal from GC!
☹ Good understanding of the conventional astrophysical background is crucial to extract a potential DM signal from this complex region of the sky:
‣ source confusion: many energetic sources near to or in the line of sight of the GC
‣ diffuse emission modeling: large uncertainties due to the overlap of structures along the line of sight, difficult to model
Interstellar Medium
Average gas density
z= 0 pc 100 pc 200 pc
Integrated line intensity of CO (traces H2)
☺ Steep DM profiles predicted by CDM ⇒ Large DM annihilation/decay signal from GC!
☹ Good understanding of the conventional astrophysical background is crucial to extract a potential DM signal from this complex region of the sky:
‣ source confusion: many energetic sources near to or in the line of sight of the GC
‣ diffuse emission modeling: large uncertainties due to the overlap of structures along the line of sight, difficult to model
Interstellar Radiation Field
Spatial variation of the radiation field in the Galaxy
☺ Steep DM profiles predicted by CDM ⇒ Large DM annihilation/decay signal from GC!
☹ Good understanding of the conventional astrophysical background is crucial to extract a potential DM signal from this complex region of the sky:
‣ source confusion: many energetic sources near to or in the line of sight of the GC
‣ diffuse emission modeling: large uncertainties due to the overlap of structures along the line of sight, difficult to model
‣ Also, unresolved source component likely
Unresolved Sources
Gregoire et al, arXiv:1305.1584
Models based on Story et al 2007, Faucher-Giguere & Loeb 2010
Predicted millisecond pulsar population undetectable by the LAT
Gamma-ray bubbles (Su et al 2010, ApJ 724, 1044):
‣ very extended (~ 50o from plane)
‣ hard spectrum (~E-2, 1-100 GeV)
‣ sharp edges
‣ possible counterparts in other wavelengths (ROSAT, WMAP, and Planck)
Outflow from the center of the Milky Way: jets from the supermassive black hole? starburst?
Su et al 2010, ApJ 724, 1044
Fermi BubblesFermi LAT data, E>10 GeV
Spectrum
A. Franckowiak and D. Malyshev 15
PRELIMINARY
Shift in normalization can be explained by: • Different
foreground modeling
• Different definition of the bubble template resulting in different area of the template
Fermi LAT Collaboration, ICRC 2013
Dark Matter Distribution
NFW profile
�0 = 0.3 GeV/cm3
a0 = 20 kpc, r0 = 8.5 kpc
The dark matter annihilation (or decay) signal strongly depends on the dark matter distribution.Cuspier profiles can provide large boost factors
Bertone et al., arXiv:0811.3744
✓ Via Lactea II (Diemand et al 2008) predicts a cuspier profile, ρ(r)∝r-1.2
✓ Aquarius (Springel et al 2008) predicts a shallower than r-1
innermost profile
Navarro, Frenk, and White 1997
17
⇢(r) = ⇢0r0r
(1 + r0/a0)2
(1 + r/a0)2
DATA DATA-MODEL (diffuse)
Fermi’s View of the Inner Galaxy (15ox15o region)
Fermi LAT preliminary results with 32 months of data, E>1 GeV (P7CLEAN_V6, FRONT):
W28
LAT PSR J1809-2332
LAT PSR J1732-3131
2FGL J1745.6-2858
➡ Bright excesses after subtracting diffuse emission model are consistent with known sources.
Galactic diffuse emission model: all sky GALPROP model tuned to the inner galaxy
DATADATA DATA-MODEL (diffuse+sources)
Fermi’s View of the Inner Galaxy (15ox15o region)
Fermi LAT preliminary results with 32 months of data, E>1 GeV (P7CLEAN_V6, FRONT):
➡ Diffuse emission and point sources account for most of the emission observed in the region.
Dark Matter ConstraintsUse LAT data from the inner Galaxy to constrain DM by requiring that the DM contribution doesn’t exceed observed dataConstraints are not competitive unless background is (at least partially) subtracted or for contracted DM profiles
Fermi LAT Collaboration, arXiv:1308.3515
Optimized region for NFWNFW
NFWc
Einasto
Burkert
cc Æ bbPromptPrompt + ICS
5 10 20 50 100 200 500 1000200010-28
10-27
10-26
10-25
10-24
10-23
10-22
m DM @GeVD
<sv>@cm
3 êsD NFW
NFWc
Einasto
Burkert
cc Æ m + m -PromptPrompt + ICS
5 10 20 50 100 200 500 1000200010-28
10-27
10-26
10-25
10-24
10-23
10-22
m DM @GeVD
<sv>@cm
3 êsD
NFW
NFWc
Einasto
Burkert
cc Æ t + t -PromptPrompt + ICS
5 10 20 50 100 200 500 1000200010-28
10-27
10-26
10-25
10-24
10-23
10-22
m DM @GeVD
<sv>@cm
3 êsD
NFW
NFWc
Einasto
Burkert
cc ÆW +W -
W+W-threshold
PromptPrompt + ICS
5 10 20 50 100 200 500 1000200010-28
10-27
10-26
10-25
10-24
10-23
10-22
m DM @GeVD
<sv>@cm
3 êsD
Figure 5: 3� upper limits on the annihilation cross-section of models in which DM annihilates intob¯b, µ+µ� (upper panel), ⌧+⌧� or W+W� (lower panel), for the four DM density profiles discussedin the text. Upper limits set without including the ICS component in the computation are alsogiven as dashed curves (prompt) for comparison. The uncertainty in the diffusion model is shownas the thickness of the solid curves (from top to bottom: MIN, MED, MAX) while the lightershaded regions represent the impact of the different strengths of the Galactic magnetic field withlower(higher) values of the cross-section corresponding to B
0
= 1 µG(B0
= 10 µG). The horizontalline corresponds to the expected value of the thermal cross-section for a generic WIMP candidate.
contribution from prompt gamma rays and the total contribution from prompt plus ICS gammarays.
First, it is worth noting that if the DM density follows an Einasto, NFW or Burkert profile,the upper limits on the annihilation cross section are above the value of the thermal cross-sectionfor any annihilation channel. Nevertheless, the situation is drastically different when we considerthe DM compression due to baryonic infall in the inner region of the Galaxy. Indeed, by adopting
14
3σ
Hooper and Linden, arXiv: 1110.0006
Use LAT data from the inner Galaxy to constrain DM by requiring that the DM contribution doesn’t exceed observed dataConstraints are not competitive unless background is (at least partially) subtracted or for contracted DM profiles
10�22
10�23
10�24
10�25
10�26
h�vi
(cm
3s�
1)
e+e�
Observed Limit
Median Expected
68% Containment
95% Containment
10�22
10�23
10�24
10�25
10�26
h�vi
(cm
3s�
1)
µ+µ�
101 102 103
Mass (GeV/c2)
10�22
10�23
10�24
10�25
10�26
h�vi
(cm
3s�
1)
⌧+⌧�
uu
bb
101 102 103
Mass (GeV/c2)
W+W�
FIG. 5. Constraints on the dark matter annihilation cross section at 95% CL derived from acombined analysis of 15 dwarf spheroidal galaxies assuming an NFW dark matter distribution(solid line). In each panel bands represent the expected sensitivity as calculated by repeatingthe combined analysis on 300 randomly-selected sets of blank fields at high Galactic latitudes inthe LAT data. The dashed line shows the median expected sensitivity while the bands representthe 68% and 95% quantiles. For each set of random locations, nominal J-factors are randomizedin accord with their measurement uncertainties. Thus, the positions and widths of the expectedsensitivity bands reflect the range of statistical fluctuations expected both from the LAT data andfrom the stellar kinematics of the dwarf galaxies. The most significant excess in the observed limitsoccurs for the bb channel between 10 GeV and 25 GeV with TS=8.7 (global p-value of p ⇡ 0.08).
36
Hooper and Linden, arXiv: 1110.0006
Fermi LAT Collaboration, arXiv:1310.0828
Dark Matter Constraints
Sgr A*
Image (width~0.5o) combines a near-infrared view from the Hubble Space Telescope (yellow), an infrared view from the Spitzer Space Telescope (red) and an X-ray view from the Chandra X-ray Observatory blue and violet) into one multi-wavelength picture.
Our knowledge of the conventional astrophysical background is uncertain. This is currently the big limitation for the search of dark matter in the Galactic center with gamma rays.
In addition, better understanding of the dark matter density distribution in the Galactic center is essential in interpreting observations.
Difficult analysis, but the rewards are big!
Conclusions
Thank you!