ams-02 antiprotons: implications for dark · pdf fileams-02 antiprotons: implications for dark...

AMS-02 antiprotons: implications for Dark Matter

Mathieu BoudaudLAPTh - Annecy, France

Topics in Astroparticle and Underground PhysicsTorino, Italy

September 9 2015

G. Giesen, M.B., Y. Genolini, V. Poulin, M. Cirelli, P. Salati and P.D. Serpico

Based on: JCAP09(2015)023

Mathieu Boudaud LAPTh - Annecy, France AMS-02 antiprotons: implications for Dark Matter

Preliminary p̄/p ratio from AMS-02

AMS-02 collaboration presented for the first time the measured p̄/p ratio from∼ 1GeV to ∼ 500GeV.

Preliminary p̄/p ratio from AMS-02

AMS-02 collaboration presented for the first time the measured p̄/p ratio from∼ 1GeV to ∼ 500GeV.

AMS-02 has suggested an antiproton excess with respect to the astrophysicalbackground!

Is this the discovery of dark matter?


Contents

1 Indirect detection of dark matter with antiprotons

2 CR’s propagation model

3 Astrophysical background

4 Dark matter

5 Conclusion


Indirect detection of dark matter with antiprotons Indirect detection of dark matter

p̄ astrophysical background relatively under control compared to other channels(e+, γ, ...).

No astrophysical primary componentPropagation uncertainty is rather small



Astrophysical background in good agreement with PAMELA data=⇒ bounds on DM annihilation cross-section (or decay life-time).

0.5 1.0 5.0 10.0 50.0 100.0

10-5

10-4

0.001

0.01

Energy @GeVD

AntiprotonFlux@1êm

2secsrGeVD

PAMELA 2012With ELDR, with SModWith ELDR, no SModNo ELDR, with SModNo ELDR, no SMod

MED

M. Cirelli and G. Giesen [arXiv:1301.7079]M.B., M. Cirelli, G. Giesen and P. Salati [arXiv:1412.5696]



What’s new with recent AMS-02 data?


Cosmic ray propagation in the Galaxy

CR’s propagation model Semi-analytical two-zone model

Two-zone model and semi-analytic method

1 < L < 15 kpc

K(E) = K0 β

(R

R0

)δ~Vc = Vc sign(z)~ez

KEE(E) =2

9Va

2 E2β2

K(E)

Cosmic rays transport equation

∂tψ −K(E)∇2ψ + ∂z [Vc sign(z)ψ] + ∂E [b(E, ~x)ψ −KEE(E, ~x)∂Eψ] = Q(E, t, ~x)

Q(E, t, ~x) = Qsource(E, t, ~x)−Qsink(E, ~x)

Maurin et al. (2001)Donato et al. (2003)

⇒




1 < L < 15 kpc

K(E) = K0 β

(R

R0


KEE(E) =2

9Va

2 E2β2

K(E)





⇒Bringmann et al.

(2012)Ackerman et al.

(2012)Lavalle et al. (2014)




1 < L < 15 kpc

K(E) = K0 β

(R

R0


KEE(E) =2

9Va

2 E2β2

K(E)




The transport equation is solved using Bessel expansions.

Donato et al. (2001)


Astrophysical background

Astrophysical background

Secondary astrophysical p̄ source term

p+H → p̄+X ∼ 70%

α+H → p̄+X ∼ 25%

p+He→ p̄+X ∼ 4%

α+He→ p̄+X ∼ 1%

Qsecp̄ (E,x) = 4π∑i=p,α

∑j=H,He

+∞∫E0

i

dEidσij→p̄X

dE(Ei → E)φi(Ei,x)nj(x)

Primary CR sources→ Supernova and pulsar distribution (Yusifov et al. 2004 )

Φ⊕p (E), Φ⊕α (E)→ AMS-02 preliminary data (AMS days 2015)

σpH→p̄X→ NA49 data parameterization/extrapolation (Di Mauro et al. 2014)


Astrophysical background Background uncertainties

What are the uncertainties?

1 p and α measured fluxes at Earth2 p̄ production X-sections3 propagation parameters4 solar environment effect (solar modulation)5 ...



Primary flux slope parametrization uncertainties

AMS-02 p and α fluxes presented during the AMS days.

Φ(R) ∼ Rγ[

1 +

(R

R0

)∆γ]



Φ(R) ∼ Rγ[

1 +

(R

R0

)∆γ]



Production X-sections uncertainties

NA49 data parametrization/extrapolation procedureIsospin asymmetry : σpH→n̄X ∼ [1, 1.5] × σpH→p̄X

Di Mauro et al. (2014)



Propagation uncertainties

5 parameters constrained using the B/C.




Solar modulation uncertainties

Force Field Approximation : ϕp̄F = [0.3, 1.0] GV ' ϕpF ± 50%Cirelli et al. (2014)



Astrophysical background uncertainties

AMS-02 data are consistent with the astrophysical background.



AMS-02 data are consistent with the astrophysical background.

Similar conclusion from independent analysis:Evoli, Gaggero and Grasso, arXiv:1504.05175 Kappl, Reinert and Winkler, arXiv:1506.04145

(M.W. Winkler’s talk)


Dark matter constraints

Dark matter

DM source term

QDMp̄ (E, ~x) =1

2〈σv〉

(ρ(~x)

mχ

)2

g(E)

ρ(~x) : DM density. Depends on DM density profile adopted.

g(E) =dNp̄(E)

dE(PYTHIA)


Dark matter

DM annihilation cross-section bounds

10 100 1000 1000010-28

10-26

10-24

10-22

DM mass mDM @GeVD

crosssectionXsv\@cm

3 êsecD

Annihilation constraints from p ê p

ccÆ m+ m-ccÆ ggccÆ W+W-ccÆ bb

Einasto MED

10 100 1000 1000010-27

10-26

10-25

10-24

10-23

10-22

10-21

DM mass mDM @GeVDcrosssectionXsv\@cm

3 êsecD

Astrophysical uncertainties on the constraints

Varying propagation parametersVarying halo profilesEinasto MED

EinMIN

EinMAXBu

r MED

ccÆ bb


Conclusions

Conclusion

1- There is no clear antiproton excess.


Conclusion

2- Stronger bounds on DM annihilation X-section or decay life-time.


Conclusion

3- Data seem to prefer a relatively mild energy dependence of thediffusion coefficient at high energies (such as MAX model).


Conclusion

Thanks for your attention!


Conclusion

Backup


Conclusion

Energy losses

Ionization of neutral interstellar matter (mostly H and He)Coulomb interactions (mostly scattering on thermal electrons)Adiabatic energy losses induced by convective processesInelastic and non-annihilating interactions of antiprotons on ISM (so-calledtertiary component) p̄+ p(ISM)→ p̄+ {∆→ p+ π}

1e-08

1e-07

1e-06

1e-05

1e-04

1e-03

1e-02

0.1 1 10 100

φ- p

[m-2

GeV

-1 s

-1 s

r-1]

T-p [GeV]

Primary Antiproton Spectrum, Channel b, m = 200GeV

MIN Without Tert/Diff ReacMED Without Tert/Diff ReacMAX Without Tert/Diff ReacMIN Without Reac Just LossesMED Without Reac Just LossesMAX Without Reac Just Losses

τloss(E) ≡ −T

b(T )'

3h

Vc

b(T ) ≡ 〈dT

dt〉


Conclusion

Diffusive reacceleration

Diffusion in energy space whose coefficient may be expressed as :

KEE(E) =2

9Va

2 E2β2

K(E)

1e-08

1e-07

1e-06

1e-05

1e-04

1e-03

1e-02

0.1 1 10 100

φ- p [m

-2 G

eV

-1 s

-1 s

r-1]

T-p [GeV]


MIN Without Tert/Diff Reac

MED Without Tert/Diff Reac

MAX Without Tert/Diff Reac

MIN Just Reac Without Losses

MED Just Reac Without Losses

MAX Just Reac Without Losses

τreac(E) ≡T 2

KEE(T )'

9K(E)

2Va2


Conclusion

Energy losses vs diffusive reacceleration

10-1 1 10 102 103 10410-2

10-1

1

10

102

103

104

105

106

Energy @GeVD

rati

oof

tim

esca

les

MIN

MED

MAX

Τloss�Τdisk

Τreac�Τdisk

1e-08

1e-07

1e-06

1e-05

1e-04

1e-03

1e-02

0.1 1 10 100

φ- p

[m-2

GeV

-1 s

-1 s

r-1]

T-p [GeV]


MIN With Tert/Diff ReacMED With Tert/Diff ReacMAX With Tert/Diff ReacMIN Without Tert/Diff ReacMED Without Tert/Diff ReacMAX Without Tert/Diff Reac

ELDR is more efficient at low energyDR is dominant at low energyEL is dominant at high energyDifferences between MIN, MED and MAX


Conclusion

AMS-02 proton spectrum


Conclusion

AMS-02 alpha spectrum


Astrophysical spectrum

Fit on AMS-02 data for MIN, MED and MAX propagation models with 2 freeparameters taking into account :

X-sections uncertainties: A(Tp̄)

SMod uncertainties: ϕF

1 5 10 50 100 5000.01

0.05

0.10

0.50

1.00

5.00

10.00

Kinetic energy T @GeVD

FpêF p

¥104

PAMELA 2012AMS-02 2015Bestfit SMod

MIN

1 5 10 50 100 5000.01

0.05

0.10

0.50

1.00

5.00

10.00


FpêF p

¥104


MED

1 5 10 50 100 5000.01

0.05

0.10

0.50

1.00

5.00

10.00


FpêF p

¥104


MAX

ams-02 antiprotons: implications for dark · pdf fileams-02 antiprotons: implications for dark...

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