enhancing the sensitivity of searches for gravitational ... · ott1 cwb cwb+bw 108 107 106 105 104...

Kiranjyot Gill

Enhancing the Sensitivity of Searches for Gravitational Waves from Core-Collapse

Supernovae with a Bayesian classification of candidate events

Kiranjyot Gill

03/17/2017March LVC 2017

For LIGO folk: S5 data used

Collaborators: Wenhui Wang, Oscar Valdez, Marek Szczepanczyk, Michele Zanolin & Soma Mukherjee

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TALK TITLE DATENAME DATETALK TITLEKiranjyot Gill 03/17/2017March LVC 2017

The Need for BayesWaveGoal for LVC-SN Searches: reduction of the false alarm rate produced

by cWB in order to improve the ROC curve for GW detectionProcedure

1) cWB outputs a ‘ranking statistic’ that is used to separate the background noise from the injected triggers

2) All surviving triggers that are above the nominal value of the ranking statistic are then post-processed through BW

3) BW initially produces results using a scatterplot that differentiates between glitches, noise, and signals present in the data

4) This secondary classification is applied to the cWB ROC curve in hopes of improving the false alarm rate - and essentially the detection efficiency of each waveform family

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10�8 10�7 10�6 10�5 10�4 10�30.35

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0.55

FAR

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cWB ROC

If cWB+BW efficiency better than original cWB FAR = improvement!

old cWB FAR

new cWB+BW point with improved efficiency

The Need for BayesWave

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BayesWave Breakdown

SN source already known

LIGO-G1401157

catered to SN searches

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Seeing through the eyes of BW

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CCSNe “signals”

Successfully identified “background noise”


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O1/O2 Search Pool of Waveforms

Rotating Core-Collapse

Scheidegger+10 sch1: R1E1CA_L_thetaX.XXX_phiX.XXX sch2: R3E1AC_L_thetaX.XXX_phiX.XXX sch3: R4E1FC_L_thetaX.XXX_phiX.XXX

Dimmelmeier+08 dim1: signal_s15a2o05_ls dim2: signal_s15a2o09_ls dim3: signal_s15a3o15_ls

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Neutrino-driven Explosion Mueller+12

mul1: L153_thetaX.XXX_phiX.XXX mul2: N202_thetaX.XXX_phiX.XXX mul3: W154_thetaX.XXX_phiX.XXX

Ott+13 ott1: s27fheat1p05_thetaX.XXX_phiX.XXX

Yakunin+15 yak1: B12WH07 yak2: B15WH07 yak3: B20WH07 yak4: B25WH07

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BW Post-Processing Results

0.380.400.420.440.460.480.500.520.540.560.58

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ienc

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Dim1

0.42

0.44

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0.48

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0.54

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cWBcWB+BW

0.38

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0.48

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Sch1-c

cWBcWB+BW

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Ott1cWBcWB+BW

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MurphycWBcWB+BW

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Sch3

cWBcWB+BW

BW Post-Processing Results

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Waveform FAR cWB+BW

sch1-wf12 10-6 13.184% increase

sch2 10-6 10.243% increase

sch3 10-6 1.1643% increase

dim1 10-6 4.522% increase



murphy 10-6 12.412% increase

ott1 10-6 1.193% increase

cWB+BW ROC Improvement

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First paper is on the way!

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Linear polarization v Non-linear polarization


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Example: Mul1 & Mul3 (linear polarized BW code)[W. Wang runs]

Mishandled CCSNe Waveforms

injections are identified as

glitches instead of signals

The waveforms are initially produced at 10 kpc

(rescaled distances with scale factors)

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Yak1Yak2Yak3

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Ott

Framing the Problem with an SNR Outlook

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Ott

Framing the Problem with an SNR Outlook

Range of SNRs tested = problem is universal regardless of distance!

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Sch2 BW Waveform Reconstruction

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Let’s take a closer look…

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Let’s take a closer look…

BW does not reconstruct!

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Re-evaluate Waveform Reconstruction Efforts

Example studies:

Sch2

Yakunin+15

(ex: yak1)


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Re-evaluate Waveform Reconstruction Efforts

(ex: yak2)


A more worrisome reconstruction

example…

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Key Introduction to Existing BW Code


Original BW code was catered toward IMBH searches ✴ code assumed elliptical polarization

For the SN searches, we set ε = 0 for the linear polarized wf models (i.e., Dim)

✴ nice approximation for the initial stages of the rapidly-rotating (RR) wf models

✴ cannot make the same assumption for the later stages of the same RR models as we do not know the behavior of the waveform in its later stages (no simulation group has computed that far out yet that we know of) - via talks with Radice

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BW assumes that all signals are elliptically polarized i.e. h× = εh+eiπ/2

✴ where ε ∈ [0, 1] is the ellipticity parameter ✴ 0 - linearly polarized signals ✴ 1 - circularly polarized signals

LIGO-P1600181

For linearly polarized waveforms, with either the + or × component, would be detectable within a LIGO-only network, and therefore made the elliptical

constraint a fair approximation.

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LIGO-P1600181

it is not universally applicable in the case of SNe since the focus of our study is

more on realistic and phenomenological waveforms, which are not all linearly

polarized (such as Mueller 2012). Introduction of non-linear polarization capabilities

hardcoded into the BW pipeline

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Current CCSNe-focused BW Testing

List of Priors to be modified: ✴ Sky Location ✴ Glitch SNR ✴ Signal SNR ✴ Number of wavelets ✴ Waveform Type ✴ Clustering

(currently being tested with Tyson)

(currently being tested)

(currently being tested)(Done)

(Done)

(Done)

The quest to maximize the estimation of appropriate

parameters of the waveforms of

interest

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Extra Slides

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cWB ROC[1]

cWB+BW ROC Improvement

[2]

Estimate efficiency for cWB+BW ROC with thresholds set in cWB+BW fixed by [1] & [2]

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enhancing the sensitivity of searches for gravitational ... · ott1 cwb cwb+bw 108 107 106 105 104...

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