1. Introduction After the Higgs discovery in 2012, The Standard - PowerPoint PPT Presentation

In the study, we considered that the gamma rays from the extragalactic region is • Statistically isotropic • Integrated over the cosmological distances But due to the recent observational developments, • Anisotropies • Cosmological distances of the gamma rays can be used for the study

Important ingredients for our study: a). Inverse-Compton (IC) -rays in the γ b). Astrophysical sources in the c). Tomographic cross-correlation using local galaxy distribution

3. Part II: DM and local galaxy distributions

Ingredients for further analysis: • Anisotropies • Cosmological distances

c). Tomographic cross-correlation using local galaxy distribution Gamma rays are almost isotropic, but ..

c). Tomographic cross-correlation using local galaxy distribution There’re anisotropies Fermi-LAT ’12

Ingredients for further analysis: • Anisotropies • Cosmological distances Fermi-LAT ’12

Ingredients for further analysis: • Anisotropies • Cosmological distances

2MRS ’11 c). Tomographic cross-correlation using local galaxy distribution Galaxy distribution

c). Tomographic cross-correlation using local galaxy distribution

c). Tomographic cross-correlation using local galaxy distribution 6000<v<7000km/s 7000<v<8000km/s 8000<v<9000km/s We know the distance from each galaxy by its redshift

c). Tomographic cross-correlation using local galaxy distribution Ingredients for further analysis: • Anisotropies • Cosmological distances

c). Tomographic cross-correlation using local galaxy distribution Ingredients for further analysis: • Anisotropies • Cosmological distances

c). Tomographic cross-correlation using local galaxy distribution

c). Tomographic cross-correlation using local galaxy distribution Gamma rays are expected to trace galaxy distribution Cross correlation

c). Tomographic cross-correlation using local galaxy distribution ✖

2MASS,NVSS,MG,LRG c). Tomographic cross-correlation using local galaxy distribution galaxy catalog: 2MRS,QSO, ✖

c). Tomographic cross-correlation using local galaxy distribution ✖ Redshift distribution

c). Tomographic cross-correlation using local galaxy distribution ✖ Redshift distribution Selecting a galaxy catalog You can get cross-correlation for corresponding redshift region

c). Tomographic cross-correlation using local galaxy distribution Catalog A ✖

c). Tomographic cross-correlation using local galaxy distribution Tomographic cross-correlation Catalog C Catalog B Catalog A ✖ redshift

c). Tomographic cross-correlation using local galaxy distribution δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution ˆ n + θ ˆ n

c). Tomographic cross-correlation using local galaxy distribution Xia, Cuoco, Branchini, Viel ’15 Cross-correlation signal for < 1 �

Xia, Cuoco, Branchini, Viel ’15 Compare both, then exclude the theory which deviates from c). Tomographic cross-correlation using local galaxy distribution obs. obs. Catalog C Catalog B Catalog A ✖ ✖ ✖ obs. th. obs. ✖ obs.

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution [dimensionless] d χ W g ( z ) n g ( χ ˆ n , z ) Z Σ g = h n g i window function W g ( z ) = d log N g dz dz d χ h Σ g i = 1

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution = DM + astro. sources [ ] cm − 2 s − 1 str − 1 Decaying DM  ρ dm ( χ ˆ � Z n , z ) I dm d χ W dm = ( z ) h ρ dm i γ γ d Φ dm Z [ ] cm − 3 s − 1 str − 1 W dm γ ( z ) = d χ ( E γ , z ) dE γ γ d Φ dm d χ ( E γ , z ) = 1 1 [ ] Ω dm ρ c GeV − 1 cm − 3 s − 1 str − 1 γ , z ) e � τ ( E 0 1 + z Q dm γ ,z ) γ γ ( E 0 4 π m dm τ dm

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution = DM + astro. sources [ ] cm − 2 s − 1 str − 1 Annihilating DM � 2  ρ dm ( χ ˆ Z n , z ) I dm d χ W dm = ( z ) h ρ dm i γ γ d Φ dm Z [ ] cm − 3 s − 1 str − 1 W dm γ ( z ) = d χ ( E γ , z ) dE γ γ ◆ 2 d Φ dm ✓ Ω dm ρ c d χ ( E γ , z ) = h σ v i [ ] γ , z ) e � τ ( E 0 (1 + z ) 3 Q dm γ ,z ) GeV − 1 cm − 3 s − 1 str − 1 γ γ ( E 0 8 π m dm

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution = DM + astro. sources Decaying/Annihilating DM (source term) [ ] Q dm γ , z ) = Q dm γ , z ) + Q dm γ , z ) + Q dm γ ( E 0 γ pr ( E 0 γ fsr ( E 0 γ ic ( E 0 GeV − 1 γ , z ) γ , z ) = (1 + z ) dN γ Q dm γ , z ) + Q dm γ pr ( E 0 γ fsr ( E 0 dE ( E 0 γ ) ( E γ BG , z ) Y e ( E e ) Z dE e dE γ BG (1 + z ) d σ IC Q dm γ , E e , E γ BG ) f BG γ ic ( E 0 ( E 0 γ , z ) = c γ b IC ( E e , z ) dE 0 γ [ ] f BG ( E γ BG , z ) = f CMB ( E γ BG , z ) + f EBL ( E γ BG , z ) GeV − 1 cm − 3 γ γ γ Z ∞ dE dN I X Y e ( E e ) = dE ( E ) E e I = e ± Z γ − E γ BG ) d σ IC [ ] GeV s − 1 γ , E e , E γ BG ) f BG dE 0 γ dE γ BG ( E 0 ( E 0 b IC ( E e , z ) = ( E γ BG , z ) γ dE 0 γ

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution = DM + astro. sources Astro. sources  n X ( χ ˆ � Z n , z ) X = blazar, SFG I X d χ W X γ = γ ( z ) h n X i dn X γ ( L γ , z ) Z [ ] Acero et al. ’15 W X γ ( z ) = χ 2 cm − 3 s − 1 str − 1 F γ ( L γ , z ) dL γ dL γ Ajello et al. ’15 Ackermann et al. ’12 Gruppioni et al. ’13 Tamborra, Ando, Murase ’14

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution = DM + astro. sources Astro. sources (window function) dn X γ ( L γ , z ) Z [ ] W X γ ( z ) = χ 2 F γ ( L γ , z ) dL γ cm − 3 s − 1 str − 1 dL γ [ ] dn X γ ( L γ , z ) : luminosity function erg − 1 s cm − 3 dL γ : number flux of photons from a source with luminosity and F γ ( L γ , z ) L γ [ ] redshift cm − 2 s − 1 str − 1 z [ ] erg s − 1 : luminosity L γ

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution Fornasa, Sánchez-Conde ’15 3 4 5 6 10 10 10 10 DGRB energy spectrum (Ackermann et al. 2014) -2 -2 10 Foreground system. error (Ackermann et al. (2014) 10 Blazars (Ajello et al. (2015) ] Misaligned AGNs (Di Mauro et al. 2014) -1 sr Star-forming galaxies (Tamborra et al. 2014) -3 -3 -1 10 10 Millisecond pulsars (Calore et al. 2014) s -2 [MeV cm -4 -4 10 10 Ω /dEd -5 -5 10 10 Φ d 2 E -6 -6 10 10 -7 -7 10 10 3 5 6 4 10 10 10 10 Energy [MeV]

クロス相関 暗黒物質は、 の領域からの寄与が相対 的に大きい の銀河とクロス相関をとることで、 の領域を選択的に取り出すことができる！ ガンマ線も銀河も宇宙の大規模構造を トレースしている つのマップはある程度似ているはず c). Tomographic cross-correlation using local galaxy distribution Advantages of tomography 2MRS Xia, Cuoco, Branchini, Viel ’15 Ando ’14

クロス相関 暗黒物質は、 の領域からの寄与が相対 的に大きい の銀河とクロス相関をとることで、 の領域を選択的に取り出すことができる！ ガンマ線も銀河も宇宙の大規模構造を トレースしている つのマップはある程度似ているはず c). Tomographic cross-correlation using local galaxy distribution Advantages of tomography 2MRS Xia, Cuoco, Branchini, Viel ’15 Ando ’14 Blazars and SFGs are dominant in z > 0 . 1

クロス相関 暗黒物質は、 の領域からの寄与が相対 的に大きい の銀河とクロス相関をとることで、 の領域を選択的に取り出すことができる！ ガンマ線も銀河も宇宙の大規模構造を トレースしている つのマップはある程度似ているはず c). Tomographic cross-correlation using local galaxy distribution Advantages of tomography 2MRS Xia, Cuoco, Branchini, Viel ’15 Ando ’14 Astro. BG can be reduced in z < 0 . 1

c). Tomographic cross-correlation using local galaxy distribution Theoretical calculation δ I γ = I γ � h I γ i δ Σ g = Σ g � h Σ g i C γ g ( θ ) = h δ I γ (ˆ n ) δ Σ g (ˆ n + θ ) i γ -ray flux galaxy distribution 2 ` + 1 C � g X = ` P ` (cos ✓ ) 4 ⇡ ` Z d � ✓ ◆ k = ` C � g = � 2 W � ( z ) W g ( z ) P � g � , z ` cross-power spectrum between -ray sources and galaxies γ

c). Tomographic cross-correlation using local galaxy distribution ◆ � , z k = ` ✓ Catalog C � 2 W � ( z ) W g ( z ) P � g Catalog B Catalog A ✖ Z d � = C � g `

c). Tomographic cross-correlation using local galaxy distribution ◆ � , z cross-correlation k = ` ✓ Catalog C � 2 W � ( z ) W g ( z ) P � g Catalog B Catalog A ✖ Z d � = C � g `

c). Tomographic cross-correlation using local galaxy distribution ◆ � , z k = ` tomography ✓ Catalog C � 2 W � ( z ) W g ( z ) P � g Catalog B Catalog A ✖ Z d � = C � g `

Xia, Cuoco, Branchini, Viel ’15 Compare both, then exclude the theory which deviates from c). Tomographic cross-correlation using local galaxy distribution obs. obs. Catalog C Catalog B Catalog A ✖ ✖ ✖ obs. th. obs. ✖ obs.

トモグラフィー 使用可能な情報 c). Tomographic cross-correlation using local galaxy distribution Galaxy catalogs より多くの赤方偏移の情報を使う → トモグラフィー Ando ’14 Catalog Redshift boundaries N g per bin 2MRS (0.003, 0.1) 43500 2MRS-N2 (0.003, 0.027, 0.1) 21750 2MRS-N3 (0.003, 0.021, 0.035, 0.1) 14500 2MXSC (0.003, 0.3) 770000 2MXSC-N2 (0.003, 0.083, 0.3) 385000 2MXSC-N3 (0.003, 0.066, 0.10, 0.3) 257000 2MXSC-N4 (0.003, 0.058, 0.083, 0.11, 0.3) 193000 2MXSC-N5 (0.003, 0.052, 0.073, 0.093, 0.12, 0.3) 154000 2MXSC-N10 (0.003, 0.039, 0.052, 0.063, 0.073, 77000 0.083, 0.093, 0.10, 0.12, 0.14, 0.3)

The reported anomalous cosmic rays: • Positron • Antiproton (over 100 GeV) • Antiproton (~ 80 GeV DM mass) (a) Φ / Φ ratio -4 AMS-02 10 PAMELA p Fermi AMS-02 p PAMELA -5 10 4 (b) 10 -1 10 + p e Φ / Φ Φ / Φ ratio Φ / Φ ratio -1 10 + + e e + p e Φ / Φ 3 10 p p -2 10 |Rigidity| [GV] 2 1 10 10 0 100 200 300 400 500

The reported anomalous cosmic rays: • Positron • Antiproton (over 100 GeV) • Antiproton (~ 80 GeV DM mass) (a) Φ / Φ ratio -4 AMS-02 10 PAMELA p Fermi AMS-02 p PAMELA -5 10 4 (b) 10 -1 10 + p e Φ / Φ Φ / Φ ratio Φ / Φ ratio -1 10 + + e e + p e Φ / Φ 3 10 p p -2 10 |Rigidity| [GV] 2 1 10 10 0 100 200 300 400 500 Decaying DM Decaying DM Annihilating DM Annihilating DM

Decaying DM (for the anomalous ) e + Here we focus on three-body leptonic decay: DM → ν l ± l ⌥ (a). ν µ ± e ⌥ & ν e ± e ⌥ (mainly ) e ± (mainly ) µ ± (b). ν µ ± µ ⌥ & ν e ± µ ⌥

Decaying DM (for the anomalous ) e + Ando, KI ’16 (a). (b).

Decaying DM (for the anomalous ) e + Ando, KI ’16 (a). (b). Including astrophysical sources give ~10 times stronger constraints

Decaying DM (for the anomalous ) e + Ando, KI ’16 (a). (b). Best fit regions taken from Ibe et al.’14 The preferred regions are excluded

Ando, KI ’16 Impacts of IC gamma rays (Results without astro. comp.) (a). (b). Results without IC (consistent with Regis et al. ’15)

Ando, KI ’16 Impacts of IC gamma rays (Results without astro. comp.) (a). (b). IC gamma gives 1-2 orders of magnitude stronger constraints over TeV region

Ando, KI ’16 Impacts of IC gamma rays (Results without astro. comp.) (a). (b). IC gamma gives 1-2 orders of magnitude stronger constraints over TeV region IC gamma rays are crucial to constrain over TeV DM

Decaying DM (for the anomalous ) Ando, KI ’16 O (100) GeV ¯ p DM → W ± µ ⌥ preferred region The preferred regions are excluded (only by DM component)

Annihilating DM (for the anomalous ) Ando, KI ’16 O (100) GeV ¯ p DM DM → W + W − preferred region The preferred regions are excluded (by including astro components)

Annihilating DM (for the anomalous ) O (1) GeV ¯ p DM DM → b ¯ Ando, KI ’16 b Obtained constraints are similar to those given by dwarf galaxy (consistent with Cuoco et al. ’15 )

Annihilating DM (for the anomalous ) O (1) GeV ¯ p DM DM → b ¯ Ando, KI ’16 b Best fit regions given by Cuoco et al. ’17 The motivated region is partly excluded

4. Ultra high energy cosmic rays and DM

Although we’ve shown the constraints on DM models, Our goal is to find the DM! For the goal, a naive step to take next would be to consider • Lower DM mass • Higher DM mass

Although we’ve shown the constraints on DM models, Our goal is to find the DM! For the goal, a naive step to take next would be to consider • Lower DM mass • Higher DM mass DM signal might be in PeV neutrino data IceCube ’15

Although we’ve shown the constraints on DM models, Our goal is to find the DM! For the goal, a naive step to take next would be to consider • Lower DM mass • Higher DM mass People are getting Cohen, Murase, Rodd, Safdi, Soreq ’17 interested in heavier Kalashev, Kuznetsov ’16 DM Kachelriess, Kalashev, Kuznetsov ’18 Dudas, Gherghetta, Kaneta, Mambrini, Olive ’18

Beyond High Energy Cosmic Rays Fonseca ’03 Very Ultra Extremely High Energy High Energy High Energy High Energy Cosmic Rays Cosmic Rays Cosmic Rays Cosmic Rays (HECRs) (VHECRs) (UHECRs) (EHECRs) TeV PeV EeV ZeV

Beyond High Energy Cosmic Rays Fonseca ’03 Very Ultra Extremely High Energy High Energy High Energy High Energy Cosmic Rays Cosmic Rays Cosmic Rays Cosmic Rays (HECRs) (VHECRs) (UHECRs) (EHECRs) TeV PeV EeV ZeV IceCube ’15