Searching for spectral features in the g -ray sky Alejandro Ibarra Technische Universität München Oslo 5 November 2014
Outline Motivation Indirect dark matter searches with gamma-rays. Overcoming backgrounds Gamma-ray spectral features A simple model generating spectral features. Conclusions
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance M87
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance Segue 1 (discovered by the SDSS in 2006)
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance Abell 1689
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance
There is evidence for particl cle dark matter in a wide range of distance scale les Clusters Observable Galaxies of galaxies Solar system Universe pc kpc Mpc Gpc distance The discovery of the dark matter was one (among the many) great discoveries in Physics of the 20 th century. In fact, it was one of the first particles for which there was evidence: Electron - Thomson, 1897 Proton - Rutherford, 1919 Neutron - Chadwick, 1932 Positron – Anderson, 1932 First evidence for dark matter - Zwicky, 1933
DARK MATTER ? ? ? ? ? ? ?
DARK MATTER ? ? ? ? ? ? ? Goal for the 21 st century: id identify the propert rties of the da dark matter partic icle le
Roszkowski
Roszkowski
WIMP dark matter production DM SM g n i r e t DM t a SM c s annihilation
WIMP dark matter production DM SM g n i r e t DM t a SM c s annihilation
WIMP dark matter Assuming that the dark matter particles were in thermal equilibrium with the SM in the production Early Universe, their relic abundance reads: DM SM g n i r e t DM t a SM c s annihilation
WIMP dark matter Assuming that the dark matter particles were in thermal equilibrium with the SM in the production Early Universe, their relic abundance reads: DM SM g n i r e t DM t a SM c s Correct dark matter abundance, DM h 2 0.1, if annihilation
WIMP dark matter Assuming that the dark matter particles were in thermal equilibrium with the SM in the production Early Universe, their relic abundance reads: DM SM g n i r e t DM t a SM c s Correct dark matter abundance, DM h 2 0.1, if annihilation ~ weak interaction
WIMP dark matter Assuming that the dark matter particles were in thermal equilibrium with the SM in the production Early Universe, their relic abundance reads: DM SM g n i r e t DM t a SM c s Correct dark matter abundance, DM h 2 0.1, if annihilation ~ weak interaction SM DM DM ) (provided SM
Dark matter searches with gamma-rays DM e n p g DM
Dark matter searches with gamma-rays DM e n p g DM Expected gamma-ray flux in a given direction: Source term Line-of-sight integral (particle physics) (astrophysics)
Dark matter searches with gamma-rays DM e n p g DM Expected gamma-ray flux in a given direction: Source term Line-of-sight integral (particle physics) (astrophysics) Which s v ? A well motivated choice: As required by thermal production. First milestone for exclusion.
Problem for discovery: for typical channels and typical masses, the expected flux lies well below the background. 10 5 E 2 GeV cm 2 s 1 sr 1 10 6 bb 10 7 m DM =500 GeV 10 8 10 9 E GeV 20 30 50 70 100 150 200 300 Do we understand backgrounds to the ~1% accuracy?
modelling of the diffuse emission Inverse Compton bremmstrahlung p 0 -decay
Great progress in understanding the diffuse gamma-ray emission, but unfortunately a detailed picture is still lacking. Always possible to use the gamma-ray data to set constraints on the dark matter properties (and should be done).
Great progress in understanding the diffuse gamma-ray emission, but unfortunately a detailed picture is still lacking. Always possible to use the gamma-ray data to set constraints on the dark matter properties (and should be done). However, to convincingly claim a dark matter signal it is necessary to convincingly subtract the astrophysical background.
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal Kuhlen, Diemand, Madau
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Segue 1: Optical image
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Segue 1: Optical image
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Segue 1: Optical image
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Mass-to-light ratio ~ 3400 M /L Most DM-dominated object known so far! Segue 1: Optical image
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Segue 1: Gamma-ray image (simulated!)
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Gamma-ray image taken with the MAGIC telescopes
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies MAGIC coll. arXiv:1312.1535
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies Fermi-LAT coll. arXiv:1310.0828
Overcoming backgrounds Strategy 1: Search for a gamma-ray excess with the spatial morphology expected from an annihilation signal A promising target for detection: dwarf galaxies B. Anderson Fermi Symposium 20-24 October 2014
Overcoming backgrounds Strategy 2: Search for a gamma-ray excess with an energy spectrum qualitatively different from the background. Idea: dN/dE Monochromatic signal at E=100 GeV E 10 15 20 30 50 70 100 150 200
Overcoming backgrounds Strategy 2: Search for a gamma-ray excess with an energy spectrum qualitatively different from the background. Idea: dN/dE Assume power-law background E 10 15 20 30 50 70 100 150 200
Overcoming backgrounds Strategy 2: Search for a gamma-ray excess with an energy spectrum qualitatively different from the background. Idea: dN/dE Total spectrum E 10 15 20 30 50 70 100 150 200 Fit data to
Overcoming backgrounds Strategy 2: Search for a gamma-ray excess with an energy spectrum qualitatively different from the background. Data don't really look like a power law...
Overcoming backgrounds Strategy 2: Search for a gamma-ray excess with an energy spectrum qualitatively different from the background. Data don't really look like a power law... Signal concentrated in a narrow energy range 10 15 20 30 50 70 100 150 200
Overcoming backgrounds Strategy 2: Search for a gamma-ray excess with an energy spectrum qualitatively different from the background. Data don't really look like a power law... In a narrow energy window, the background resembles a power-law ( Taylor's theorem) Signal concentrated in a narrow energy range 10 15 20 30 50 70 100 150 200
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