New gas - Old sources
Jean-Marc Casandjian
Isabelle Grenier
Régis Terrier
AIM, Service d’Astrophysique, CEA Saclay
APC
GANIL
~60% of g from MW diffuse emission
~30% from extragalactic
~10% g from sources
p0
Bremsstrahlung
Inverse Compton
N g _ diffus  qHI N ( HI )  qH 2W(CO )  qIC I IC  I bkg  SA T 
convolve with PSF
Modele HI+CO+IC
• CO: CfA, Dame et al.,2001
• HI: New LAB survey (Kalberla et al. astro-ph/0504140)
Instituto Argentino de Radioastronomia Survey (Bajaja et al. 2005)
TS=120K
p0
Bremsstrahlung
Inverse Compton
N g _ diffus  qHI N ( HI )  qH 2W(CO )  qIC I IC  I bkg  SA T 
convolve with PSF
N g _ diffus  qHI N ( HI )  qH 2W(CO )  qdust I dust  qIC I IC  I bkg  SA T 
" Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds",
Schlegel, Finkbeiner & Davis (SFD), 1998
model 1
model 2
data
Pij ( N  n | q ij ) 
Proba to get n counts when q predicted:
Likelihood:
Lq   Pij
ij
q ijn e
q ij
nij !
ln Lq   nij log( q ij )  q ij
ij
ij
TS  2(max ln( Lq )  max ln( Lqrest ))
Wilks theorem:
TS is distributed as a c2 with k degrees of freedom
PTS 9  0.001
TS=9
confidence interval = 99.7%
TS(with/without cold dust) = 1556 !!
P = 10-340
or
39s
HI+CO+EBV
39
HI+CO+I94GHz
EBV
I94GHz
~s
HI+CO+I100µ
HI+CO
116
I100µ
N g _ diffus  qHI N ( HI )  qH 2W(CO )  qdust I dust  qIC I IC  I bkg  SA T 
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Hydrogen ? HI, H2 ?
Log(NHdark) (atome cm-2)
How much ?
0.7:1:1
5:1:5
0.2:1:0.5
2:1:2.7
0.6:1:3
MH2 ~ 6 105 M
MHI ~ 7 105 M
Mdark ~ 2 105 M
CO:dark:HI
Mdark/MH2 ~ 30-35 %
Mdark/MHI ~ 26-30 %
0.7:1:3
6:1:6
0.4
M dark  M CO
If clumps
gas … …

-1.6
-1.8
-1.9
-2.0
Mdark/MH2
0.6
1.2
0.9
1.8
1.1
2.2
1.4
2.8
Heyer ‘01
dN

 M CO
 1.9    1.6
dM CO
Phase transition
Is there an effect on sources detection ?
First test:
use the sources catalog positions and just ajust
the sources flux: (“lm”-no position)
All the sources with sqrt(TS1234)>3, E>100MeV:
steady sources with sqrt(TS1234)>4-5
transient sources with sqrt(TS1234)>3
missing steady 3<sqrt(TS1234)<4-5
COSSC data (counts or exposure maps, 2001) probably differ
from the ones used for the catalog
18 regions
fit crab (2.1) , Geminga(1.5), Vela (1.7) by hand, for the rest SI=2.0
Loop till
~10% sources
with sqrt(TS)<3
• TS map ("ms").
• take max TS, likelihood ("le") with centroide at 50% .
• add this source to “other PSF map”.
• set ROI around the last source found (20o square).
• adjust position and flux for each source in ROI
("LPO“ and "lm"-noposition).
• Flux maximisation iteration on all sources("lm"-centroide at 50%).
• Remove sources with sqrt(TS)<3.
• Flux maximisation iteration on all sources ("lm"-centroide at 95%).
• Flux maximisation iteration on all sources ("lm"-centroide at 95%) again.
• Add together all the sources found in the regions.
• Flux maximisation iteration on all sources ("lm"-centroide at 95%).
• Flux maximisation iteration on all sources ("lm"-centroide at 95%).
• Check result with TS map ("ms") to see if still sqrt(TS)>3.
• Repeat for 3 energies: >100Mev, 300MeV-1GeV, >1GeV and use the more accurately
determined position and reoptimize the flux at 100MeV.
• Do the same in equatorial (one energy) and replace sources with b>60.
Catalog
EGRET diffuse emission
TS45
|b|>10, 4s
|b|<10, 5s
source significant but without a match
or with a non significant match
No match
with TS45
source significant without a match
No match
4.5s
5.5s
New LIKE results
EGRET diffuse emission
HI+CO+Dark diffuse emission
Conclusions:
• modele with dark gas fits data for |b|>5
• strong influence of dark gas on sources detection
Finish source detection and search for counterpart.
3d map of dark gaz / cold dust for the disk
influence of local electron density fluctuations (408 MHz), H+, new CO
J.R. Mattox, D.J. Macomb, D.L.Bertsch, J.A. Esposito