Transcript Document

Dejan Urošević
Department of Astronomy, Faculty of Mathematics,
University of Belgrade
Supernova remnants: evolution, statistics,
spectra
Hydrodynamic Evolution of
SNRs
• First phase – free expansion phase (Ms < Me),
till 3/4Ek → U (Ms  3Me),
(for 1/2Ek → U, Ms  Me).
• Second phase – adiabatic phase (Ms >> Me )
till 1/2Ek → radiation
• Third phase – isothermal phase – formation
of thick shell
• Forth phase – dissipation into ISM
Radio Brightness Evolution in
the Adiabatic Phase
• synchrotron emissivity
 K H1+ -,
where K from N(E)=KE1+2 and spectral
index  from S -
• surface brightness
= S/ =Vshell/D22,
D is SNR diameter
where
• magnetic field H = f1(D) and K = f2(D);
both functions are power low functions
• surface brightness becomes:
  Dfk() DfH() Vshell/D2
• finally we obtain so-called  - D relation:
= AD-,
where =-(fk() +fH()+1) and A=const.
Trivial Theoretical  - D
Relation
• if the luminosity is constant
(or independent on D) during SNR
expansion we have:
 D-2
• this is trivial form of the theoretical  - D
relation
Short History of the Theoretical
 - D relation
• Shklovsky (1960)
- spherical model with: H  D-2, =0.5 
 D-6
• Lequeux (1962)
- shell model with: H  D-2, =0.5 
 D-5.8
• Poveda & Woltjer (1968)
- using van der Laan (1962) model with:
H = const., =0.5 
 D-3
• Kesteven (1968)
- shell of constant thickness:
H  D-1, =0.5 
 D-4.5
• Duric & Seaquist (1986)
- for H  D-2, =0.5 
 D-3.5 (D>>1pc),
 D-5 (D<<1pc)
- for =0.5 and 1.5  x  2 
-(2.75



3.5)
 D
(D>>1pc)
• Berezhko & Volk (2004)
 D-4.25 (time-dependent nonlinear
kinetic theory)
STATISTICS OF SNRs
Empirical -D Relation
• Necessary for determination of
distances to Galactic SNRs identified
only in radio continuum
• Necessary for confirmation of the
theory in order to define valid
evolutionary tracks
Empirical -D Relations
(Related Problems)
• Critical analyses: Green (1984, 1991, 2004)
• Galactic sample
- distances determination problem
- Malmquist Bias - volume selection
- other selection effects (sensitivity,
resolution, confusion)
effect
• Extragalactic samples
- sensitivity (surface brightness () limits)
- resolution (angular-size () limits)
- confusion
Updated Empirical  - D
Relations
• Galactic relation
(Milky Way (MW) 36 SNRs)
 D-2.4 (Case & Bhattacharya 1998)
• Extragalactic sample (11 galaxies)
LMC, SMC, M31, M33, IC1613, NGC300,
NGC6946, NGC7793, M82, NGC1569,
NGC2146 (148 SNRs)
- Monte Carlo simulations suggest that
the effect of survey sensitivity tending to
flatten the slopes toward the trivial
relation (opposite to effect of Malmquist
bias)
(Urošević et al. 2005)
- the only one valid empirical -D relation
is constructed for M82 (21 SNRs):

-3.4
D ,
the validity was checked by Monte Carlo
simulations and by L-D (luminositydiameter) dependences (Urošević et al.
2005, Arbutina et al. 2004)
- also, this relation is appropriate for
determination of distances to SNRs
(Arbutina et al. 2004)
Synchrotron spectra
Thermal Emission from SNRs
• Thermal Bremsstrahlung
 N2 T-1/2,
where N is particle concentration and T
is temperature
 There are two rare types of SNRs
with strong thermal emission
(Urošević and Pannuti 2005)
• the first type – the relatively young
SNRs in the adiabatic phase of
evolution that evolve in the dense
molecular cloud (MC)
– D  20 pc, 1GHz ~ 10-20 (SI)
– for N  300 cm-3 and T ~ 106 K 
1GHz, therm. 1GHz, synch.
• the second type – the extremely
evolved SNRs in the late adiabatic
phase expanded in denser warm
medium
– D  200 pc, 1GHz ~ 10-22 (SI)
– for N  1 - 10 cm-3 and T ~ 104 K 
1GHz, therm.
(0.1 - 10) 1GHz, synch.
HB3
Urošević et al. 2007
HB3 – observational data
•
•
•
S1GHz = 50 Jy
D= 70 pc (for distance of 2 kpc)
Shell thickness = 0.05 D
↓↓↓
•
Emissivity 1GHz=1.67 x 10-37
(ergs sec-1 cm-3 Hz-1)
HB3 - density of environment
We recall (cgs)= 7x10-38 N2 T-1/2
if we suppose 104 < T < 106 K
↓↓↓
10 < ne < 35 cm-3
SUMMARY
• Some updated results related to:
- evolution
- statistic
- spectra
of SNRs are given.
THANK YOU
VERY MUCH
ON YOUR
PATIENT!!!