Valentina De Romeri (IFIC Valencia - UV/CSIC) Realistic estimation for the detectability of dark matter subhalos using Fermi-LAT catalogs Credit: NASA/DOE/Fermi LAT Collaboration, using nine years of data collected from 2008 to 2017. Halo Substructure and Dark Matter Searches 27-29 June 2018, IFT (Madrid) Based on Phys.Rev. D96 (2017) no.6, 063009 with F. Calore, M. Di Mauro, F. Donato and F. Marinacci 1 Valentina De Romeri - IFIC UV/CSIC Valencia
There is overwhelming evidence for the existence of dark matter: CMB anisotropies, The content of the Universe in terms of paellas (after Planck) Clusters (X-rays, lensing), Large Scale Structures, Galaxies (rotation curves, fits…) 26.8% Cosmological and astrophysical observations 68.3% credit: R.A. Lineros 2 Valentina De Romeri - IFIC UV/CSIC Valencia
What do we know about DM? ‣ Non-baryonic (BBN, CMB) ‣ Collisionless (bullet cluster) ‣ Stable on cosmological scales (or lifetime >> tU ~13.8 Gyr) ‣ Neutral ‣ Massive ‣ Cold or Warm (structure formation) ‣ Not in conflict/excluded by DM experiments and cosmological data …....not included in the Standard Model → WIMPs, axions … Many candidates in Particle Physics Additional assumptions for this talk: Park, E.-K. DMSAG Report on the Direct Detection and Study of Dark Matter (2007) • dark matter is a WIMP (GeV - TeV mass scale) • WIMPs cluster in galaxies as dark halos (a main smooth halo and many subhalos) • can pair annihilate or decay to produce SM particles • accounts for the measured relic density 3 Valentina De Romeri - IFIC UV/CSIC Valencia
If DM is made of particles that interact among themselves and with SM particles we may hope to detect it. Two strategies: 1. DIRECT DETECTION (looks for energy { deposited within a detector by the DM- nuclei scattering) 2.1 Antimatter in the cosmic rays (antiprotons, antideuterons, positrons…) 2.2 Neutrinos (DM annihilation inside 2. INDIRECT DETECTION (looks for celestial bodies) WIMP annihilation (or decay) products) 2.3 Photons (DM annihilation in the galactic halo(s)) + complementary searches at colliders 4 Valentina De Romeri - IFIC UV/CSIC Valencia
Gamma-rays from WIMPs? - Annihilation processes DM 1. Prompt photons from DM annihilation: γ • Two-body annihilation into photons (gamma-ray lines) DM γ • Photon production in hard process (bremsstrahlung of charged particles) DM f γ DM f • Two-photon decay of neutral pions π 0 → γγ dumped by the hadronization chain of strongly interacting annihilation products (continuum) π 0 DM W - /Z/q γ π 0 γ π 0 γ γγ π 0 DM W + /Z/q π 0 γ π 0 2. Secondary photons from radiative processes associated with stable, charged particles produced by DM annihilation or decay (electrons and positrons): e.g. inverse-Compton and synchrotron emission. 5 Valentina De Romeri - IFIC UV/CSIC Valencia
The γ -ray flux from DM annihilation is defined as the number of photons collected by a detector per unit of time, area, energy and solid angle: ( E γ , ψ , θ , ∆Ω ) = d Φ P P d Φ γ γ ( E γ ) × J ( ψ , θ , ∆Ω ) dE γ dE γ 6 Valentina De Romeri - IFIC UV/CSIC Valencia
The γ -ray flux from DM annihilation is defined as the number of photons collected by a detector per unit of time, area, energy and solid angle: ( E γ , ψ , θ , ∆Ω ) = d Φ P P d Φ γ γ ( E γ ) × J ( ψ , θ , ∆Ω ) dE γ dE γ d Φ P P dN i h σ v i = 1 PARTICLE PHYSICS factor: X γ γ B i - bb, μ⁺μ⁻ , τ⁺τ⁻ final states 2 m 2 dE γ dE γ 4 π DM - B i = 1 (representative of larger class of models) i Velocity averaged annihilation cross-section Photon energy spectrum per annihilation Characteristic Energy Spectrum Important to: ● identify a DM signal ● determine the DM mass ● determine the annihilation process 7 Valentina De Romeri - IFIC UV/CSIC Valencia
The γ -ray flux from DM annihilation is defined as the number of photons collected by a detector per unit of time, area, energy and solid angle: ( E γ , ψ , θ , ∆Ω ) = d Φ P P d Φ γ γ ( E γ ) × J ( ψ , θ , ∆Ω ) dE γ dE γ d Φ P P dN i h σ v i = 1 PARTICLE PHYSICS factor: X γ γ B i - bb, μ⁺μ⁻ , τ⁺τ⁻ final states 2 m 2 dE γ dE γ 4 π DM - B i = 1 (representative of larger class of models) i Z ∆Ω ASTROPHYSICAL factor: Z ρ 2 (r(s , ψ , θ ))ds J ( ψ , θ , ∆Ω ) = d Ω • Sensitivity to different DM 0 los halo profiles Integration of the squared DM density at a distance s from the Earth in the direction along the l.o.s and in the observational cone of solid angle ΔΩ 8 Valentina De Romeri - IFIC UV/CSIC Valencia
γ -ray experiments relevant for DM searches (GeV to TeV) Ground based: MAGIC (2003), VERITAS Space based: Fermi-LAT (2008) (2006), H.E.S.S. (2002) (Pair conversion detector) (Atmospheric Cherenkov Telescopes) Effective area: O(1m 2 ) Observation times: O(yr) Energies: 20 MeV - 1 TeV HAWC (2015) (Water Cherenkov Telescope) Effective area: O(10 5 m 2 ) Effective area: O(10 4 m 2 ) Observation times: O(100hr) Observation times: O(100hr) Energies: ~50 GeV - 10 TeV Energies: 100 GeV - 10 TeV 9 Valentina De Romeri - IFIC UV/CSIC Valencia
Detectability of dark matter subhalos with Fermi-LAT ‣ Two Fermi-LAT catalogs: • 3FGL (Acero et al. 2015) : 4 years, 0.1 – 300 GeV, Pass 7 data, 3000 sources (at a latitude |b| > 20 ◦ mainly AGN) • 2FHL (Ackermann et al. 2015) : 80 months, 50 – 2000 GeV, Pass 8 data, 360 sources ‣ In both catalogues, a large fraction of sources remain unassociated: about 15% in the 2FHL and 30% in the 3FGL. ‣ Unassociated sources are point-like gamma-ray emitters detected as such by the LAT, but lacking association with astrophysical objects known in other wavelengths. ‣ The sample of unassociated sources in the Fermi-LAT catalogues might already contain gamma-ray emitting DM SHs. 10 Valentina De Romeri - IFIC UV/CSIC Valencia
Modelling the DM distribution in the Galaxy ‣ We want to predict the detectability of galactic DM subhalos by the Fermi-LAT. ‣ Numerical simulations predict a large amount of subhalos in a galaxy-size Milky Way halo (of which dSphs are a manifestation). ‣ Estimates for the numbers of SHs detectable by Fermi-LAT strongly depend on the assumptions made about the local distribution of DM SHs and the shapes of the density profiles. ‣ For modelling the SH population in the Galaxy, we use one of the most recent cosmological numerical simulations that includes baryonic physics, Hydro Aquarius (Marinacci et al. 2015) ‣ We use two runs, DMO and Hydro Springel et al. (2008) Marinacci et al. (MNRAS 2013) Q. Zhu et al. (MNRAS, 2016) 11 Valentina De Romeri - IFIC UV/CSIC Valencia
Cosmological simulations: DM-only vs HYDRO Effects of baryons: ‣ increasing the density in the center of the Galaxy ‣ removing both DM and luminous matter and redistribute them in the SHs ‣ evaporating the gas and preventing gas accretion from the intergalactic medium Differences: ‣ Fewer SHs in the Hydro simulation ‣ Low-mass SHs depleted in the Hydro simulation ‣ Depletion mostly near the center. Springel et al. (2008) Marinacci et al. (MNRAS 2013) 12 Q. Zhu et al. (MNRAS, 2016) Valentina De Romeri - IFIC UV/CSIC Valencia
Cosmological simulations: DM-only vs HYDRO The gamma-ray emissivity from DM annihilation in SHs is determined by the internal spatial profile of the DM subhalos. ‣ SH spatial distribution: Einasto profile • n − 2 = 0.66±0.06 (0.50±0.03) • α = 1.17 ± 0.15 (2.20 ± 0.29) • r − 2 = 0.64 ± 0.02 (0.65 ± 0.02) Rvir ‣ SH mass distribution: dN/dM ∼ M − 1.9 Calore, VDR et al. Phys.Rev. D96 (2017) no.6, 063009 ‣ Radial abundance lower for Hydro simulation, mostly in the central region. ‣ Vmax (MSH) dependence of radial distribution — stronger for Hydro simulation. 13 Valentina De Romeri - IFIC UV/CSIC Valencia
DM distribution and density profile of the SH ‣ DM distribution and density profile of the SHs: Einasto α = 0.16 Z ∆Ω Z ρ 2 (r(s , ψ , θ ))ds J ( ψ , θ , ∆Ω ) = d Ω r max = r s x 2.189 0 los Calore, VDR et al. Phys.Rev. D96 (2017) no.6, 063009 14 Valentina De Romeri - IFIC UV/CSIC Valencia
Realistic estimation of the flux sensitivity ‣ We assume that gamma rays are produced from DM annihilations via the prompt mechanism ‣ We take into account two channels: b bar and τ + τ - which give the largest fluxes ‣ We take the gamma-ray spectra from DM annihilation from Cirelli et al. 2011 (Pythia 8) . F [ Integrated photon flux: MDM = 10, 100, 800, 5000 GeV bb Spectral energy distribution of the signal: Super-exponential cutoff parametrisation E peak = mDM/20 (bbar) Calore, VDR et al. Phys.Rev. D96 (2017) no.6, 063009 15 Valentina De Romeri - IFIC UV/CSIC Valencia
Estimation of the flux sensitivity (3FGL) ‣ The sensitivity flux is the flux for which TS=25. ‣ For each DM mass we simulate DM SHs with different channels and at different latitudes. ‣ We simulate also the IEM and isotropic components taking the reference models for the 3FGL and 2FHL catalogs. ‣ The data analysis details (exposure time, energy range,...) are the same as in the 3FGL and 2FHL catalogs. Calore, VDR et al. Phys.Rev. D96 (2017) no.6, 063009 MDM = 8 GeV bb MDM = 30 GeV MDM = 80 GeV MDM = 300 GeV MDM = 600 GeV Sensitivity flux threshold MDM = 1200 GeV as a function of DM mass 3FGL 16 Valentina De Romeri - IFIC UV/CSIC Valencia
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