Supernova neutrinos and their implications for supernova physics

Transcription

1 Supernova neutrinos and their implications for supernova physics Ken ichiro Nakazato (Tokyo University of Science) in collaboration with H. Suzuki(Tokyo U of Sci.), T. Totani, H. Umeda(U of Tokyo), K. Sumiyoshi(Numazu CT) and S. Yamada(Waseda U) Fukuoka Univ., Dec. 4, 2013

2 Core-Collapse Supernovae evolution of density profile onset bounce accretion shock propagation proto-neutron star Nakazato+ (2013)

3 Supernova neutrinos Clue for puzzle in supernova physics. Burrows (1988) Kamiokande

4 Explosion mechanism SASI variability seen in neutrinos? Tamborra+ (2013)

5 Mass hierarchy Neutrino spectra for each time step sin 2 2θ 13 ~ 0.1 (T2K, Daya Bay, ) Kawagoe+ (2010) Normal Inverted θ 13 0 e excluded θ 13 0

6 Light curves and spectra Neutrino emission continues for 10 seconds. (diffusion time scale) x e e Nakazato+ (2013) Fischer+ (2012)

7 3 phases of neutrino emission x 1 neutronization burst ~ O (10 ms) e e 2 accretion phase ~ O (100 ms) 3 cooling phase ~ O (10 sec) Nakazato+ (2013)

8 Neutronization burst Shock dissociates nuclei. Protons capture electrons emitting e. deleptonization Shock A A A A A :electron

9 Accretion phase collapse Gravitational potential of accreted matter converts to thermal energy. accretion proto-neutron star shock Neutrinos of all flavors are emitted by thermal process.

10 Cooling phase Shock revives and propagates to outer layer. Heating by matter accretion stops. proto-neutron star Luminosity and mean energy of neutrinos drop.

11 When does shock revive? Possibly characterizing explosion mechanism. e.g. convection vs. SASI Whether the transition from accretion phase to cooling phase is early or late? Affecting the features of emitted neutrinos. More neutrinos would be emitted for later transition cases, because matter accretes more.

12 Supernova neutrino database A comprehensive dataset for the long term evolution of supernova neutrinos was made. It will be useful for simulations of future neutrino burst detection and predictions of relic supernova neutrino background. Parameterized by the shock revival time. Now On-line!

13 Supernova neutrino database A comprehensive dataset for the long term evolution of supernova neutrinos was made. It will be useful for simulations of future neutrino burst detection and predictions of relic supernova neutrino background. Parameterized by the shock revival time. Now On-line!

14 radiation hydrodynamics Spherically symmetric full GR hydrodynamics (Yamada 1997) Metric:Misner & Sharp (1964) Radial mesh:255 non uniform zones accretion + Neutrino transport (Boltzmann solver) phase (Yamada et al. 1999; Sumiyoshi et al. 2005) Species : e e μ ( = τ ) μ ( = τ ) Energy mesh : 20 zones (0 300 MeV) Reactions : e - + p n + e, e + + n p + e, + N + N, + e + e, e + A A + e -, + A + A, e - + e + +, γ* +, N + N N + N + +

15 Proto-neutron star cooling Multigroup Flux Limited Duffusion scheme (Suzuki 1994) cooling Species : e e μ ( = τ = μ = τ ) Energy mesh : 20 zones (same with rad-hydro.) phase Reactions : e - + p n + e, e + + n p + e, + N + N, + e + e, e + A A + e -, + A + A, e - + e + +, γ* +, N + N N + N + + (*) Equation of State by H. Shen is adopted for both computations.

16 Energy source of neutrinos collapse Gravitational potential accreted matter + proto-neutron star cooling. accretion proto-neutron star shock L ( ε, t) = + L acc. ( cool L ε (, t) ε, t)

17 Inequality of emission max acc.,max L ( ε, t) = L ( ε, t) + From 1D radiation hydro simulation. L > acc., t) cool The results of proto-neutron star simulation are the lower limit of neutrino emission. In 1D hydro simulation, amount of accretion is too much (thus fails to explode). The results correspond to the upper limit. ( ε L ( ε, t) From protoneutron star cooling simulation.

18 Modeling neutrino light curve Assuming shock revival time and fraction of accretion to the maximum f (t). e.g. shock revival time(t rev ): 100 ms after bounce acc.,max L ( ε, t) = L ( ε, t) f ( t) + f ( t) = 1 exp 0 t 150ms 30ms L cool ( ε, t) (t < 150 ms) (150 ms < t < 350 ms) (t > 350 ms)

19 Shock revival time Suggestions from observables. NS mass distribution ms explosion energy & 56 Ni yield ms We set t rev = 100, 200, 300 ms Belczynski et al. (2012) Yamamoto et al. (2013)

20 Progenitor models mass: M = 13-50M (4 cases) metallicity: Z = 0.02, (2 cases) among total 8 models 7 models: Supernovae 1 model: Black Hole (Failed supernova) 30M, Z = The maximum neutron star mass of adopted equation of state

21 Luminosity and mean energy 13M, Z = 0.02, t revive = 100 ms This work Totani+ (1998) x e e

22 Neutrino spectra Number luminosity This work Totani+ (1998)

23 Time integrated spectra They are similar to Fermi-Dirac distribution below 30 MeV. High energy tails are accretion phase origin.

24 Systematics early shock revival late If the shock revival time is late, the total energy of emitted neutrino gets high.

25 Core mass dependence Total emission energy increase with the core mass of progenitor. correlation with the amount of accretion

26 Implication from relic neutrino The flux of neutrinos and antineutrinos emitted by all corecollapse supernovae in the causallyreachable universe. Is it possible to study the shock revival time from supernova relic neutrinos? We are here! z = 0 z = 1 z = 2 time

27 Detection status The upper limit is near theoretical predictions. Malek+ (2003) Horiuchi+ (2009) largest allowed SRN invisible muon atmospheric

28 Agenda Estimation of the supernova relic neutrino flux dealing shock revival time dependence. Including a contribution of black-holeforming core-collapse. Failed supernovae Their fraction is indicated by GRB fraction, (1+z). Yüksel & Kistler (2012)

29 Setups df de = c dz dt dz dn de de de R SN (z) de de = 1+ z Cosmological parameters Star Formation rate: Hopkins & Beacom (2006) Initial mass function: Salpeter A Neutrino Oscillation Normal hierarchy and Inverted hierarchy

30 Event rate (SK, 1 year) If the shock revival is late, event rate increases. But average energy is not sensitive. If failed SNe are included, both event rate and average energy gets higher. 200ms 100ms 300ms without Failed SN with Failed SN

31 Shock revival vs. failed SNe Dividing into 2 bins: high and low energies. shock revival time N L, N H with failed SNe N L, N H N L N H

32 Event rate (HK,10 years) Different trends in N L + N H vs. N L N H plane. Key for shock revival time

33 Summary Neutrino detections will give clue for puzzle in supernova physics. We have constructed Supernova Neutrino Database, where the predictions for various cases are included. Using the dataset, estimation for the flux of supernova relic neutrino is done. The flux reflects shock revival time, which should depend on the still unknown explosion mechanism.