TAMA binary inspiral event search Hideyuki Tagoshi (Osaka Univ., Japan) 3rd TAMA symposium, ICRR,...
Transcript of TAMA binary inspiral event search Hideyuki Tagoshi (Osaka Univ., Japan) 3rd TAMA symposium, ICRR,...
TAMA binary inspiral event search
Hideyuki Tagoshi (Osaka Univ., Japan)
3rd TAMA symposium, ICRR, 2/6/2003
Coalescing compact binaries
Neutron starsBlack holes
Inspiral phase of coalescing compact binaries are main target because
Expected event rate of NS-NS merger: a few within 200Mpc /year
Well known waveform, etc.
Possibility of MACHO black holes
TAMA Binary inspiral search
1. Neutron star binary search
2. TAMA-LISM coincident event search for mass range (onestep search)
3. Lower mass
4. Higher mass
1 2M M
1 2M M
0.2M
10M
Matched filter• Detector outputs:
: known gravitational waveform (template)
: noise.
• Outputs of matched filter:
• noise spectrum density
• signal to noise ratio
• Matched filtering is the process to find optimal
parameters which realize
s t Ah t n t( ) ( ) ( ) h t( )n t( )
( , , ,...)~( )
~( )
( )
*
m m ts f h f
S fdfc
n1 2 2 z
max ( , , ,...), , ,...m m t
cc
m m t1 2
1 2FH IK
SNR = / 2
Post-Newtonian approximation
( )nS f
Matched filtering analysis
tRead data
FFT of dataApply transfer function
Conversion to stain equivalent data
Evaluate noise spectrum near the data( )nS f
( , , )ct M
max ( , , ) c
ct
t M
( 25 )ct ms
52 sec
Event list(only 7 events)
2( , , )ct M
( 7)if
,max ( , , )
c
Mt M
2 ( / )S N
TAMA events and Galactic event
Test signals
selection will produce loss of strong S/N events
2
2/ 16 T
AM
A e
vent
s
2
Search Result TAMA DT6
2/
Log
10[N
umbe
r of
eve
nts]
2/ 16
Upper limit to the Galactic event rate
N
T •N: Upper limit to the average number of events
over certain threshold
•T: Length of data [hours]
• : Detection efficiency
Galactic event simulationWe perform Galactic event simulation to estimate detection efficiency
Assume binary neutron stars distribution in our Galaxy
2 20/ 2 / zR R Z hdN e e RdRdZ
0 4.8 kpc
1 kpcz
R
h
•Give a time during DT6
•Determine mass, position, inclination angle, phase by random numbers
•Give a test signal into real data
•Search
•Make event lists and estimate detection efficiency
Mass : distribute uniformly between 1 2M
Galactic event detection efficiency
2/ 16 0.23
Upper limit to the event rate: Poisson statistics
•Threshold ( )
•Expected number of fake events over threshold : Nbg=0.1
•Observed number of events over threshold: Nobs=0
Assuming Poisson distribution for the number of real/fake events
over the threshold,
we obtain upper limit to the expected number of real events from( )
0
0
( )
!1
( )
!
obsbg
obsbg
nn Nx N bg
nnn N
N bg
n
x Ne
nCL
Ne
n
N=2.3 (C.L.=90%)
2/ 16
Upper limit to the Galactic event rate
threshold=16 ( ~ S/N=11)
(fake event rate=0.8/year)
Efficiency
•We also obtain upper limit to the average number of events over threshold by standard Poisson statistics analysis
N=2.3 (C.L.=90%)
•Observation time T = 1039 hours
0.23
0.0095 [1/ hour] ( . . 90%)N
C LT
c.f. Caltech 40m : 0.5/hour (C.L.=90%) Allen et al. Phys. Rev. Lett. 83, 1498 (1999).
TAMA DT7: 2002.8.31 ~ 2002.9.2
Best Sensitivity:
DT7 analysis
213.3 10 / Hz
DT7 event lists
These results will be used for TAMA-LIGO coincidence analysis.
23.7 hours data
2
Divide frequency region into bins.Test whether the contribution to from each bins agree with that expected from chirp signal
fminf1 f2 f3 f4 f5 fmax
1 2 3 4 5
FHG
IKJ z( , )
~( )~
( )
( )
*
s hs f h f
S fdf
n
2
22
2
2 2
1
i
i i
i i i i i
( )
( ) ,
chi square
[1.09minutes]
max
min
1/ 27 / 3
4( )
f
fn
fdf
S f
min max100Hz, f 2500Hzf TAMA DT6 all 8/1 ~ 9/20/2001
Variation of Noise power (1 minute average)
max
min
1/ 27 / 3
4( )
f
fn
fdf
S f
min max100Hz, f 2500Hzf LISM DT6 9/3 ~ 9/17/2001
Variation of Noise power (1 minute average)
[1.09minutes]
•Binary inspiral search : one step search (Tagoshi, Tatsumi,Takahashi)
TAMA-LISM coincidence
(Takahashi,Tagoshi,Tatsumi)
two step search (Tagoshi, Tanaka)
•Binary inspiral search using Wavelet: (Kanda)
•Continuous wave from known pulsar: (Soida, Ando)
•Burst wave search: (Ando)
•Noise veto analysis: (Kanda)
•Calibration: (Tatsumi, Telada,…)
•Interferometer online diagnostic: (Ando,…)
•BH ringdown search, Stochastic background search, etc. will be done.
•Two new post-docs (Tsunesasa(NAOJ),Nakano(Osaka))
TAMA data analysis activity